多癌种肿瘤相关静脉血栓风险识别课题分解方案

Cancer patients are at increased risk of deep vein thrombosis and pulmonary embolism. The incidence among different groups of cancer patients varies considerably depending on clinical factors, the most important being tumor entity and stage. Biomarkers have been specifically investigated for their capacity of predicting venous thromboembolism (VTE) during the course of disease. Parameters of blood count analysis (elevated leukocyte and platelet count and decreased hemoglobin) have turned out to be useful in risk prediction. Associations between elevated levels and future VTE have been found for d-dimer, prothrombin fragment 1+2, and soluble P-selectin and also for clotting factor VIII and the thrombin generation potential. The results for tissue factor–bearing microparticles are heterogeneous: an association with occurrence of VTE in pancreatic cancer might be present, whereas in other cancer entities, such as glioblastoma, colorectal, or gastric carcinoma, this could not be confirmed. Risk assessment models were developed that include clinical and laboratory markers. In the high-risk categories, patient groups with up to a >20% VTE rate within 6 months can be identified. A further improvement in risk stratification would allow better identification of patients for primary VTE prevention using indirect or novel direct anticoagulants.

Cancer patients have an increased risk of venous thromboembolism (VTE). In this review, we summarize common and cancer type–specific pathways of VTE in cancer patients. Increased levels of leukocytes, platelets, and tissue factor–positive (TF+) microvesicles (MVs) are all potential factors that alone or in combination increase cancer-associated thrombosis. Patients with lung or colorectal cancer often exhibit leukocytosis. Neutrophils could increase VTE in cancer patients by releasing neutrophil extracellular traps whereas monocytes may express TF. Thrombocytosis is often observed in gastrointestinal, lung, breast, and ovarian cancer and this could decrease the threshold required for VTE. Soluble P-selectin has been identified as a biomarker of cancer-associated thrombosis in a general cancer population and may reflect activation of the endothelium. P-selectin expression by the endothelium may enhance VTE by increasing the recruitment of leukocytes. Studies in patients with pancreatic or brain cancer suggest that elevated levels of PAI-1 may contribute to VTE. Although elevated levels of TF+ MVs have been observed in patients with different types of cancer, an association between TF+ MVs and VTE has been observed only in pancreatic cancer. Podoplanin expression is associated with VTE in patients with brain cancer and may activate platelets. Future studies should measure multiple biomarkers in each cancer type to determine whether combinations of biomarkers can be used as predictors of VTE. A better understanding of the pathways that increase VTE in cancer patients may lead to the development of new therapies to reduce the morbidity and mortality associated with thrombosis.

… There are very few studies assessing the longitudinal changes in cancer-associated VTE biomarkers in cancer patients. A recent longitudinal study over six months in patients with …

Abstract Venous thromboembolism (VTE) is a main contributor to morbidity and mortality in cancer patients. Biomarkers with the potential to predict cancer-associated VTE are continually sought. Of these, markers of thrombin generation present a likely option. The present systematic review examines the ability of three widely used biomarkers of thrombin generation: prothrombin fragment 1.2 (F1.2), thrombin-antithrombin complex (TAT), and ex vivo thrombin generation, to predict VTE in both solid and hematologic adult cancer patients. Relevant studies were identified in the PubMed and Embase databases, and the review conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Each study was evaluated using the quality assessment tool from the National Heart, Lung, and Blood Institute. The review protocol was published on PROSPERO with identifier CRD42022362339. In total, 24 papers were included in the review: 11 reporting data on F1.2, 9 on TAT, and 12 on ex vivo thrombin generation. The quality ratings of the included studies varied from good ( n  = 13), fair ( n  = 8), to poor ( n  = 3) with a high heterogenicity. However, F1.2, TAT complex, and ex vivo thrombin generation were all found to be associated with the development of VTE. This association was most pronounced for F1.2. Furthermore, the determination of F1.2 was able to improve the precision of several established risk assessment scores. In conclusion, markers of thrombin generation were found to be elevated in cancer patients with VTE, and particularly, F1.2 was found to be a promising predictor of cancer-associated VTE.

MicroRNAs (miRNAs) are small noncoding RNAs with gene regulatory functions and are commonly dysregulated in disease states. As miRNAs are relatively stable, easily measured, and accessible from plasma or other body fluids, they are promising biomarkers for the diagnosis and prediction of cancer and cardiovascular diseases. Venous thromboembolism (VTE) is the third most common cardiovascular disease worldwide with high morbidity and mortality. The suggested roles of miRNAs in regulating the pathophysiology of VTE and as VTE biomarkers are nowadays more evidenced. Patients with cancer are at increased risk of developing VTE compared to the general population. However, current risk prediction models for cancer-associated thrombosis (CAT) perform suboptimally, and novel biomarkers are therefore urgently needed to identify which patients may benefit the most from thromboprophylaxis. This review will first discuss how miRNAs mechanistically contribute to the pathophysiology of VTE. Next, the potential use of miRNAs as predictive biomarkers for VTE in subjects without cancer is reviewed, followed by an in-depth focus on CAT. Several of the identified miRNAs in CAT were found to be differentially regulated in VTE as well, giving clues on the pathophysiology of CAT. We propose that subsequent studies should be adequately sized to determine which panel of miRNAs best predicts VTE and CAT. Thereafter, validation studies using comparable patient populations are required to ultimately unveil whether miRNAs-as standalone or incorporated into existing risk models-are promising valuable VTE and CAT biomarkers.

Abstract Background and Aims Patients with cancer have increased risk of venous thromboembolism (VTE) and bleeding. Inflammatory and cardiac biomarkers may predict these complications, but their role remains unclear. This study examined associations between two inflammatory-related markers (C-reactive protein and growth differentiation factor-15) and two cardiac markers [N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T (hs-TnT)] with VTE and clinically relevant bleeding in cancer patients. Methods A post hoc analysis of the AVERT trial, which evaluated apixaban for VTE prevention in ambulatory cancer patients with a Khorana score of ≥2, was performed. Biomarkers were measured at baseline and 1 month, with C-reactive protein also at 3 months. Fine and Gray regression, accounting for competing risk of death and adjusted for age and advanced cancer, estimated subdistribution hazard ratios (SHRs) for VTE and clinically relevant bleeding. Results Of 574 patients, 514 provided baseline samples. One- and 3-month samples were available from 454 and 447, and 378 and 364, patients without prior VTE and bleeding events, respectively. Elevated baseline growth differentiation factor-15 was associated with increased VTE risk [SHR 1.36, 95% confidence interval (CI) 1.01–1.84]. N-terminal pro-B-type natriuretic peptide (SHR 1.44, 95% CI 1.08–1.92) and C-reactive protein (SHR 1.38, 95% CI 1.07–1.76) were linked to bleeding risk. Increasing high-sensitivity troponin T from baseline to 1 month was associated with higher VTE risk (SHR 1.89, 95% CI 1.14–3.16). Nomograms were developed to estimate VTE and clinically relevant bleeding risks. Conclusions Select inflammatory-related and cardiac markers were associated with VTE and bleeding risks in cancer patients, which can be determined using developed nomograms. Prospective research is needed to confirm these findings.

Abstract Background  Cancer patients have an increased risk of venous thromboembolism (VTE). Currently, the availability of highly discriminatory prediction models for VTE in cancer patients is limited. The implementation of biomarkers in prediction models might lead to refined VTE risk prediction. In this systematic review and meta-analysis, we aimed to evaluate candidate biomarkers and their association with cancer-associated VTE. Methods  We searched Medline, EMBASE, and Cochrane Central for studies that evaluated biomarkers in adult cancer patients from inception to September 2022. We included studies reporting on VTE after a cancer diagnosis with biomarker measurements performed at a defined time point. Median/mean differences (for continuous measures) and odds ratios (for dichotomous measures) with 95% confidence intervals were estimated and pooled using random-effects models. Results  We included 113 studies in the systematic review. Of these, 50 studies were included in the meta-analysis. We identified two biomarkers at cancer diagnosis (factor VIII and time to peak thrombin), three biomarkers pre-chemotherapy (D-dimer, fibrinogen, and mean platelet volume), and one biomarker preoperatively (platelet count) that had significant median or mean differences. Additionally, we found that hemoglobin <100 g/L and white blood count >11 × 10 9 /L were significantly associated with future VTE risk only when measured at cancer diagnosis. Pre-chemotherapy neutrophil-to-lymphocyte ratio ≥3 and preoperative platelet count ≥400 × 10 9 /L were also found to be associated with future VTE risk. Conclusion  In conclusion, this study identified nine candidate blood biomarkers that may help in optimizing VTE prediction in cancer patients that should be further explored in future studies.

Venous thromboembolism (VTE; deep venous thrombosis and pulmonary embolism) is associated with a poor prognosis in most malignancies and is a major cause of death among cancer patients. Universal anticoagulation for primary thromboprophylaxis in the outpatient setting is precluded by potential bleeding complications, especially without sufficient evidence that all patients would benefit from such prophylaxis. Therefore, appropriately targeting cancer patients for thromboprophylaxis is key to reducing morbidity and perhaps mortality. Predictive biomarkers could aid in identifying patients at high risk for VTE. Possible biomarkers for VTE include C-reactive protein, platelet and leukocyte counts, D-dimer and prothrombin fragment 1+2, procoagulant factor VIII, tissue factor, and soluble P-selectin. Evidence is emerging to support the use of risk assessment models in selecting appropriate candidates for primary thromboprophylaxis in the cancer setting. Further studies are needed to optimize these models and determine utility in reducing morbidity and mortality from cancer-associated thromboembolism.

Cancer-associated thrombosis (including venous thromboembolism (VTE) and arterial events) is highly consequential for patients with cancer and is associated with worsened survival. …

Abstract Venous thromboembolism (VTE) is a frequent complication in cancer patients. Platelet activation is thought to be involved in cancer-associated VTE. Here, we determined the association between evolving markers of platelet activation (soluble P-selectin [sP-selectin], soluble CD40 ligand [sCD40L], thrombospondin-1 [TSP-1] and platelet factor-4 [PF-4]) and the development of cancer-associated VTE. A nested matched case–control study was applied within a cohort of 1779 patients with different types of cancer that had been included in the Vienna Cancer and Thrombosis Study (CATS), a prospective, observational study on patients with newly diagnosed or progressive cancer after remission. Primary endpoint is symptomatic VTE during a maximum follow-up of 2 years. Cases (patients who developed VTE during follow-up) were matched in a 1:2 ratio to controls without VTE during follow-up with respect to tumor type, stage and time of observation in the study. In total, 131 VTE cases were compared to 262 controls. In logistic regression analysis, only sP-selectin was associated with risk of VTE. The odds ratios (OR) per double increase of sP-selectin, sCD40L, TSP-1 and PF-4 were 1.66 (95% confidence interval: 1.17–2.35, p = 0.005), 1.04 (0.89–1.21, p = 0.635), 1.09 (0.90–1.32, p = 0.360) and 1.03 (0.87–1.21, p = 0.737), respectively. In conclusion, sP-selectin, but not sCD40L, TSP-1 or PF-4 were associated with risk of VTE in cancer patients in this nested case–control study.

Introduction Venous thromboembolism (VTE) is the second leading cause of mortality among cancer patients and is potentially preventable through the use of anticoagulation therapy. Risk models exist to guide use of prophylactic therapy but have low positive predictive value. New biomarkers are needed, particularly in intermediate-risk cancer types. Extracellular small RNAs, such as miRNAs, are promising biomarkers that have been implicated in tumor-dependent modification of platelets, a key component of thrombus formation. In this pilot study, we explore miRNAs as potential biomarkers for VTE risk in patients with colorectal cancer. Methods We conducted a case-control study utilizing specimens from a population enrolled in a prospective colorectal cancer biorepository at the Cleveland Clinic. Cases were defined as patients who developed VTE, including deep vein thrombosis and pulmonary embolism, within 6 months after cancer diagnosis and had their blood drawn prior to VTE. Cases were matched to controls (who did not have VTE and had a minimum of 6 months survival after cancer diagnosis) on a 1:2 ratio based on age, sex, cancer stage at diagnosis, and cancer treatment received prior to blood collection for a total of 21 patients. Total RNA from plasma specimens were sequenced on a Ion Proton platform (Thermo Fisher). Sequencing data were analyzed using the limma-voom R package. As this study was meant to be exploratory, miRNA were determined to be differentially expressed at a corrected Benjamini-Hochberg false detection rate (FDR) < 0.2. Target genes of differentially expressed miRNAs were predicted using mirDB and target gene pathways constructed with PANTHER. Results The study population had a median age of 65 (IQR 51-72). Of these patients, 85.7% were male; 42.9% had stage I/II cancer, 42.9% stage III cancer, 14.3% stage IV cancer; 71.4% had received no treatment prior to blood collection, 14.3% received chemo/chemoradiation therapy, and 14.3% received surgery. A total of 2426 unique miRNAs (median 1524, IQR 1371-1665) were expressed in the study group. Of these, 9 miRNAs were significantly differentially expressed (FDR < 0.2) and downregulated in cases compared to controls: hsa-miR-4451, 942-3p, 8063, 3132, 3118, 105-5p, 891a-5p, 200a-5p, and 6832-3p. From these miRNAs, 609 target genes were predicted and classified into 75 pathways, including angiogenesis, G-protein coupled receptors (GPCRs), inflammation mediated by chemo/cytokines, and integrin signaling. Target genes within these notable pathways included EPHA3, PDGFA, PTK2/FAK1, and IL15. Conclusions We identified 9 significantly downregulated miRNAs in the blood of colorectal cancer patients who developed VTE compared to controls in this pilot study. These data suggest that colorectal cancer patients may express unique miRNA profiles prior to VTE development which may be useful as biomarkers in future predictive models. In addition, this study identified potential new mechanistic targets for understanding cancer-associated thrombosis. While the role of GPCRs, integrins, and inflammation in platelet activation and function is widely known, this study also identified factors within the angiogenesis pathway that have been linked to increased platelet aggregation and tissue factor activation. Thus, downregulation of inhibitory miRNAs may cause disinhibition of pathways important for platelet and vascular function and other prothrombotic factors. Khorana: Janssen: Consultancy; Bayer: Consultancy; Pfizer: Consultancy; Sanofi: Consultancy. McCrae:Pfizer Pharmaceutical: Membership on an entity's Board of Directors or advisory committees; Dova Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Rigel Pharmaceutical: Membership on an entity's Board of Directors or advisory committees; Sanofi Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees.

… As such, additional and better predictive biomarkers of cancer-associated VTE are mandatory for a paradigm shift [7]. In recent years, the implications of several SNPs primarily …

Cancer-associated thrombosis (CAT) is a major cause of morbidity and mortality in patients with malignancy. Biomarkers of hypercoagulability and thromboinflammation may improve risk stratification and support personalised thromboprophylaxis, but evidence remains heterogeneous, particularly in cervical cancer. A systematic review was conducted according to PRISMA 2020. PubMed/MEDLINE, Scopus, Embase, and Web of Science were searched for studies published between January 2009 and March 2025 evaluating biological, molecular, genetic, and imaging biomarkers associated with hypercoagulability and thromboinflammation in women withcervical cancer. Evidence from breast cancer and broader CAT studies was incorporated to provide translational context. Owing to substantial methodological heterogeneity, findings were synthesised qualitatively. Twenty-five cervical cancer studies met eligibility criteria. D-dimer was the most extensively investigated biomarker and was consistently associated with VTE risk, although specificity was limited. Biomarkers of thrombin generation and fibrinolytic activation, including thrombin–antithrombin complexes, prothrombin fragment 1+2, and plasmin–α2-antiplasmin complex, demonstrated greater mechanistic specificity. Multimarker panels integrating coagulation, fibrinolysis, endothelial injury, platelet activation, and inflammation showed superior predictive performance compared with single biomarkers. Emerging biomarkers, including circulating tumour DNA, extracellular vesicles, and microRNAs, further supported tumour-driven thromboinflammation. SERPINE1 and F2 gene variants were associated with thrombotic risk and adverse prognosis. Current evidence supports further evaluation of integrated multimodal biomarker strategies for CAT risk assessment, but prospective, standardised, tumour-specific studies are required before biomarker-guided approaches can be implemented in clinical practice.

Venous thromboembolism (VTE) represents a significant health concern because of its high morbidity and mortality and is moreover characterized by high rates of recurrence. It would be useful to know biomarkers that enable early identification of patients at high or low risk of primary and recurrent VTE. Various established and novel biomarkers associated with VTE have been investigated with regard to their potential for predicting primary or recurrent VTE, for facilitating the diagnosis and for optimizing the clinical management of VTE. In this review, data on selected biomarkers (D-Dimer, soluble P-selectin, coagulation factor VIII, inflammatory markers and thrombin generation) having procoagulant properties or reflecting a prothrombotic state are summarized, and their role in clinical application is discussed.

The relationship between inflammation and venous thrombosis is not well understood. An inflammatory response may be both the cause and consequence of venous thromboembolism (VTE). In fact, several risk factors of VTE modulate thrombosis through inflammatory markers. Acute pulmonary embolism (PE) is burdened by a remarkable mortality rate, up to 34% in severely ill patients presenting with hemodynamic instability. Initial mortality risk stratification is based on hemodynamic instability. Patients with a situation of hemodynamic stability require immediate further risk assessment based on clinical, imaging, and circulating biomarkers, as well as the presence of comorbidities. Some inflammatory biomarkers have shown potential usefulness in the risk stratification of patients with VTE, especially acute PE. C-reactive protein on admission is associated with 30-day mortality and bleeding in VTE patients. P-selectin is associated with right ventricle dysfunction in PE patients and might be associated with VTE recurrences and the extension of thrombosis. Tissue factor microparticles are associated with VTE recurrence in cancer-associated thrombosis. Other inflammatory biomarkers present scarce evidence (inflammatory cytokines, erythrocyte sedimentation rate, fibrinogen, leukocyte count). In this manuscript, we will review the prognostic role of different inflammatory biomarkers available both for clinical practice and research in VTE patients.

Venous thrombosis is a common and potentially fatal disease, because of its high morbidity and mortality, especially in hospitalized patients. To establish the diagnosis of venous thrombosis, in the last years, a multi-modality approach that involves not only imaging modalities but also serology has been evolving. Multiple studies have demonstrated the use of some biomarkers, such as D-dimer, selectins, microparticles or inflammatory cytokines, for the diagnosis and treatment of venous thrombosis, but there is no single biomarker available to exclusively confirm the diagnosis of venous thrombosis. Considering the fact that there are some issues surrounding the management of patients with venous thrombosis and the duration of treatment, recent studies support the idea that these biomarkers may help guide the length of appropriate anticoagulation treatment, by identifying patients at high risk of recurrence. At the same time, biomarkers may help predict thrombus evolution, potentially identifying patients that would benefit from more aggressive therapies. This review focuses on classic and novel biomarkers currently under investigation, discussing their diagnostic performance and potential benefit in guiding the therapy for venous thrombosis.

Background Venous thromboembolism (VTE) is a common thrombotic vascular disease that has a significant impact on people’s well-being and quality of life. A plethora of clinical studies explore the relationship between inflammatory biomarkers and VTE but yield conflicting results. This article proposed to pool these studies to draw a more convincing conclusion. Methods We searched several databases for studies before April 2023. Available data was processed using Stata software (version 15.0 SE) and R (version 4.1.2). This meta-analysis has been registered in PROSPERO (CRD42022321815). The VTE in this review encompassed pulmonary embolism, deep vein thrombosis, and cerebral venous thrombosis. Results A total of 25 articles were finally involved in this study. Our results revealed that higher levels of high-sensitivity C-reactive protein (hs-CRP, MD, 0.63, 95%CI, 0.21—1.05) and C-reactive protein (CRP)> 3ug/ml (OR, 1.52, 95%CI, 1.18—1.96) might be regarded as risk factors for future VTE occurrence. The elevated levels of monocyte (MD, 0.03, 95%CI, 0.00—0.05), hs-CRP (0.85, 0.61—1.08), CRP (0.66, 0.20—1.13) and IL-6 (0.47, 0.25—0.70) might represent the previous VTE; a series of markers such as white blood cell (1.43, 0.88—1.98), neutrophil (1.79, 1.02—2.56), monocyte (0.17, 0.14—0.21), hs-CRP (3.72, 1.45—5.99), IL−6 (5.99, 4.52—7.46), platelet-lymphocyte ratio (33.1, 24.45—41.78) and neutrophil-lymphocyte ratio (1.34, 0.95—1.73) increased during the acute phase of VTE. Conclusions In general, activated inflammatory biomarkers might not only be correlated with an increased risk of VTE, but may also give a hint of the occurrence of VTE in clinical settings.

Thrombosis remains a major cause of morbidity and mortality in cancer patients. Existing risk models fail to reliably predict venous thromboembolism (VTE), underscoring the need for more accurate predictive models. In this study, we conducted a high-throughput proteomic analysis of 1,105 plasma proteins from newly diagnosed lung and gastric cancer patients prospectively monitored for VTE development. Utilizing a Bayesian probabilistic machine learning approach, we developed a predictive model incorporating 11 protein biomarkers and five clinical parameters (age, sex, history of VTE, body mass index, and hemoglobin), which significantly outperformed the Khorana prediction model. Orthogonal validation in an external placebo cohort from a phase III trial confirmed the model’s predictive power. Further investigation into the mechanistic role of CD200 receptor 1 (CD200R1), a checkpoint receptor limiting leukocyte inflammatory response that contributed strongly to the model, showed that reduced concentrations in plasma correlated with higher D-dimer and thrombosis risk. In CD200R1-deficient mice, elevated thrombin-antithrombin complexes confirmed a prothrombotic state characterized by increased interleukin-17A (IL-17A) and endothelial inflammation. Administration of anti-IL-17A antibodies to CD200R1 deficient mice normalized thrombin generation in vivo, and a meta-analysis of human clinical IL-17A inhibitory antibody studies confirmed antithrombotic activity. These findings improve the prediction of thrombosis in cancer and highlight the utility of plasma proteomics to identify unanticipated mechanistic insights and therapeutic targets in thrombo-inflammatory disease.

Simple Summary The risk of venous thromboembolism in cancer is nine times higher than in the general population and the second leading cause of death in these patients. Tissue factor and downstream plasmatic coagulation cascade are largely responsible for the risk of thrombosis in cancer. In recent years, it has been increasingly recognised that platelets also play a central role in tumour growth and cancer-associated thrombosis. The underlying molecular mechanisms are largely unknown. In order to comprehensively investigate the biochemical changes in platelets from cancers with high risk of thrombosis, we examined the platelet proteome of brain and lung cancer patients in comparison to sex and age-matched healthy controls. However, we only found alterations in lung cancer, where some of these platelet proteins directly promote thrombosis. One example is the increased amount of the enzyme protein disulfide isomerase, which is clinically investigated as an antithrombotic drug target of the plant-based flavonol quercetin. Abstract In order to comprehensively expose cancer-related biochemical changes, we compared the platelet proteome of two types of cancer with a high risk of thrombosis (22 patients with brain cancer, 19 with lung cancer) to 41 matched healthy controls using unbiased two-dimensional differential in-gel electrophoresis. The examined platelet proteome was unchanged in patients with brain cancer, but considerably affected in lung cancer with 15 significantly altered proteins. Amongst these, the endoplasmic reticulum (ER) proteins calreticulin (CALR), endoplasmic reticulum chaperone BiP (HSPA5) and protein disulfide-isomerase (P4HB) were significantly elevated. Accelerated conversion of the fibrin stabilising factor XIII was detected in platelets of patients with lung cancer by elevated levels of a coagulation factor XIII (F13A1) 55 kDa fragment. A significant correlation of this F13A1 cleavage product with plasma levels of the plasmin–α-2-antiplasmin complex and D-dimer suggests its enhanced degradation by the fibrinolytic system. Protein association network analysis showed that lung cancer-related proteins were involved in platelet degranulation and upregulated ER protein processing. As a possible outcome, plasma FVIII, an immediate end product for ER-mediated glycosylation, correlated significantly with the ER-executing chaperones CALR and HSPA5. These new data on the differential behaviour of platelets in various cancers revealed F13A1 and ER chaperones as potential novel diagnostic and therapeutic targets in lung cancer patients.

Introduction Clinical risk assessment scores can help risk-stratify patients for cancer-associated thrombosis (CAT); however, their performance in individual cancer subtype remains suboptimal. While previous studies have explored the utility of single plasma biomarkers such as D-dimer or P-selectin, we lack a validated, non-invasive biomarker signature panel. Our current study evaluates a plasma proteomic assay and machine learning model for predicting CAT. Methods We performed a nested case control study from 1,694 patients with newly diagnosed solid tumor malignancy who had plasma sample collection from 2011-2023 at the Harris Health System. Patients with early-stage disease, samples taken before cancer diagnosis or after chemotherapy initiation, or inadequate follow-up were excluded. Five common cancer types were selected (breast, colorectal, lung, pancreatic, gastroesophageal) to form an eligible cohort of 312 patients. Incidence density sampling was used with 1:2 matching on cancer type, stage, and treatment to form a final analytic cohort of 170 patients (57 CAT vs 113 controls). We performed proteomic profiling using the Olink Explore HT, which uses the proximity extension assay to measure plasma proteins as normalized protein expression (NPX) values. Random Survival Forest (RSF) model was used to predict time to CAT, where NPX values (5,416 proteins) and clinical variables (age, sex, race, ethnicity, cancer type, stage, diagnosis year) were trained in 100 bootstrapped iterations with resample. Internal validation with time dependent receiver operating characteristic (TD-ROC) was assessed at days 30, 90, and 180, using out-of-bag (OOB) test samples. Top proteins identified by nonparametric permutation variable importance (VIMP) and stably present in multiple iterations were retained for pathway enrichment analysis using the Reactome Over-Representation Analysis with p-value <0.05 and FDR q-value <0.1. Results Among 170 patients, the median age was 54 (IQR 47-60), 64% were female. Race and ethnicity included 62% Hispanic, 12% Non-Hispanic (NH) White, 18% NH Black, and 7% NH Asian. There were 42 breast, 51 colorectal, 35 lung, 22 pancreatic, and 20 gastroesophageal cancers; 53% were metastatic; and all received chemotherapy after sample collection. The 57 CAT events included 23 pulmonary embolism, 12 lower extremity deep vein thrombosis (DVT), 18 upper extremity DVT, and 4 splanchnic vein thrombosis. Median time to CAT was 154 days (IQR 70-262). There were 7, 19, and 31 events by 30, 90, and 180 days, respectively. Among 5,416 proteins, the NPX values ranged from -11.43 to +12.40 (IQR -0.50 to +0.52). There were no significant differences by batch or storage time. For internal validation, the RSF model achieved a bootstrapped mean TD-ROC of 0.82 (95% CI 0.54-0.98), 0.71 (95% CI 0.57-0.88), and 0.67 (95% CI 0.56-0.79) at 30, 90, and 180 days, respectively. Approximately 35% were classified as high-risk. In the OOB test sets, the observed average VTE incidence in the high-risk group were 13%, 21%, and 26% at 30d, 90d, and 180d, respectively. In comparison, the observed average VTE incidence in the low-risk group was 1%, 8%, and 15% at the same time points. Top important proteins included KANK1, F9, CABP4, PRND, and GFPT2, among others. In pathway enrichment analyses, the top 20% proteomic features were over-represented in neutrophil degranulation, extracellular matrix organization, platelet cytosolic calcium and degranulation, integrin cell surface interactions, regulation of complement cascade, and formation of fibrin clot. Conclusion Individual cancer patients have unique prothrombotic expression profiles in the plasma that are prognostic for future CAT occurrence. As demonstrated in the pathway enrichment analyses from the top RSF features, the relationship between coagulation cascade, neutrophil, platelet, complement, and extracellular matrix is complex and non-linear. A survival tree-based machine learning model incorporating all plasma proteomic signatures can predict short-term CAT occurrence with higher accuracy than long-term (0.82 vs 0.67). Instead of single target assays, panel-based plasma proteomic assays may complement existing clinical risk scores and further differentiate the thrombotic risk profiles among individual cancer subtypes. External and prospective cohort validations are needed to ensure reproducibility and generalizability.

… plasma protein profiles in cancer patients, potentially 3 providing insight into treatment-specific prothrombotic … Distinct proteomic profiles after 1 remission of Cushing syndrome, but …

Comprehensive protein analyses of plasma are made possible by high-throughput proteomic screens, which may help find new therapeutic targets and diagnostic biomarkers. Patients with cancer are frequently affected by venous thromboembolism (VTE). The limited predictive accuracy of current VTE risk assessment tools highlights the need for new, more targeted biomarkers. Although coagulation biomarkers for the diagnosis, prognosis, and treatment of VTE have been investigated, none of them have the necessary clinical validation or diagnostic accuracy. Proteomics holds the potential to uncover new biomarkers and thrombotic pathways that impact the risk of thrombosis. This review explores the fundamental methods used in proteomics and focuses on particular biomarkers found in VTE and cancer-associated thrombosis.

Simple Summary The most life-threatening events in colorectal cancer (CRC) are metastasis and thrombosis. Platelets can play a role in these outcomes via the release of medium-sized extracellular vesicles (mEVs). Thus, we aimed to study the EVs released from activated platelets of CRC patients and healthy controls (HS) for their size composition, protein content, and the capacity to influence the expression of genes involved in malignancy and the synthesis of a prothrombotic lipid mediator such as thromboxane (TX)A2. Our findings show that the protein content of thrombin-stimulated mEVs is modulated in CRC. Its evaluation may represent a noninvasive tool to discriminate patients from healthy subjects. Moreover, our findings show that characterizing the regulation of the expression of promalignant genes and prothrombotic phenotypes in cancer cells by the crosstalk with platelet mEVs could provide prognostic information on cancer patients, which could help in developing an appropriate anticancer strategy. Abstract Background: Platelet–cancer cell interactions modulate tumor metastasis and thrombosis in cancer. Platelet-derived extracellular vesicles (EVs) can contribute to these outcomes. Methods: We characterized the medium-sized EVs (mEVs) released by thrombin-stimulated platelets of colorectal cancer (CRC) patients and healthy subjects (HS) on the capacity to induce epithelial-mesenchymal transition (EMT)-related genes and cyclooxygenase (COX)-2(PTGS2), and thromboxane (TX)B2 production in cocultures with four colorectal cancer cell lines. Platelet-derived mEVs were assessed for their size distribution and proteomics signature. Results: The mEV population released from thrombin-activated platelets of CRC patients had a different size distribution vs. HS. Platelet-derived mEVs from CRC patients, but not from HS, upregulated EMT marker genes, such as TWIST1 and VIM, and downregulated CDH1. PTGS2 was also upregulated. In cocultures of platelet-derived mEVs with cancer cells, TXB2 generation was enhanced. The proteomics profile of mEVs released from activated platelets of CRC patients revealed that 119 proteins were downregulated and 89 upregulated vs. HS. Conclusions: We show that mEVs released from thrombin-activated platelets of CRC patients have distinct features (size distribution and proteomics cargo) vs. HS and promote prometastatic and prothrombotic phenotypes in cancer cells. The analysis of platelet-derived mEVs from CRC patients could provide valuable information for developing an appropriate treatment plan.

ABSTRACT Introduction Advances in various proteomics technologies, especially high-throughput and reproducibility, have enabled the systematic exploration of the circulating thrombosis proteome. This includes dissecting biological systems and pathways imperative to thrombosis, such as platelet activation, coagulation cascade, complement system, and endothelial cells. These insights strengthen our understanding of the cause and effect of thrombosis and improve precision medicine by identifying better biomarkers and biomarker panels, which may aid clinicians in decision-making in venous thromboembolism (VTE) and other thrombotic patients. This progress has the potential to reduce thrombosis-related morbidity and mortality, ultimately improving patient quality of life. Areas covered This review highlights recent advances and applications of mass spectrometry and affinity-based proteomics in thrombosis over the past three years (2022–2024), focusing on the thrombotic proteome signature related to VTE. Expert opinion Plasma proteomics, predominantly driven by mass spectrometry and affinity-based proteomics, has shown promise in identifying novel disease biomarkers and pathways. With the recent advances in the field, proteomics holds the potential to revolutionize precision medicine. As thrombosis is an intravascular disease, analysis of the blood proteome can capture environmental, genetic, and epigenetic contributors to risk variation in thrombosis, revealing novel protein biomarkers for diagnosis and risk prediction and new biological pathways.

Cancer patients have an eleven-fold increased risk of venous thromboembolism (VTE) compared to the general population. In this hypothesis-generating study we investigated plasma protein levels in colorectal cancer patients with and without thrombosis using targeted absolute quantification of 269 plasma proteins. We included samples from 142 patients with stage III/IV colorectal cancer from MICA - a multinational prospective cohort study, and from 98 patients from CATS - a prospective cohort study with stage III/IV colorectal cancer. The primary outcome was objectively confirmed symptomatic or incidental deep vein thrombosis or pulmonary embolism during a 6-month follow-up period. In MICA, 11 (7.7%) developed VTE; in CATS 6 patients (6.1%) developed VTE within 6 months, and 10 (10.2%) within 2 years. Six differentially abundant proteins (DAPs) were identified in MICA: APOB100, CD5L, IGHG1, IGHM, PRG4, and TF. A model using these six proteins achieved a c-statistic of 0.687 (95% CI: 0.658-0.717) by internal cross-validation with 100 repeats and random 80% training sets. The optimism-corrected c-statistics was 0.675 (95% CI: 0.648-0.701). Using any subset of the DAPs yielded a c-statistics >0.67, with the best model reaching 0.768 (95% CI: 0.746-0.790). This outperformed the Khorana, modified-Vienna, PROTECHT, and CONKO models. The six DAPs had also predictive value in CATS with c-statistics at 0.70 (95% CI:0.671-0.728) for the 6-month, and 0.73 (95% CI:0.702-0.728) for 2-year follow-up. Two proteins showed inverted patterns between cohorts, likely due to chemotherapy. Our findings call for further investigation into the proteins identified, warranting further validation in larger, standardized studies.

Simple Summary The interactions between circulating tumor cells (CTCs) and plasma proteins are critical for hematogenous metastasis, and understanding the molecular mechanisms behind these interactions can improve liquid-biopsy-based diagnostics and cancer therapies. This review summarizes recent literature on the surface molecules of CTCs that interact with coagulation proteins and their biological and clinical relevance. It also discusses future research directions to expand our knowledge of the CTC interactome, which can lead to the discovery of new molecular markers for diagnostics and additional targets for cancer therapies. Abstract Cancer metastasis is a complex process. After their intravasation into the circulation, the cancer cells are exposed to a harsh environment of physical and biochemical hazards. Whether circulating tumor cells (CTCs) survive and escape from blood flow defines their ability to metastasize. CTCs sense their environment with surface-exposed receptors. The recognition of corresponding ligands, e.g., fibrinogen, by integrins can induce intracellular signaling processes driving CTCs’ survival. Other receptors, such as tissue factor (TF), enable CTCs to induce coagulation. Cancer-associated thrombosis (CAT) is adversely connected to patients’ outcome. However, cancer cells have also the ability to inhibit coagulation, e.g., through expressing thrombomodulin (TM) or heparan sulfate (HS), an activator of antithrombin (AT). To that extent, individual CTCs can interact with plasma proteins, and whether these interactions are connected to metastasis or clinical symptoms such as CAT is largely unknown. In the present review, we discuss the biological and clinical relevance of cancer-cell-expressed surface molecules and their interaction with plasma proteins. We aim to encourage future research to expand our knowledge of the CTC interactome, as this may not only yield new molecular markers improving liquid-biopsy-based diagnostics but also additional targets for better cancer therapies.

Cancer patients have a four- to sevenfold increased risk of developing cancer-associated thrombosis (CAT), which is associated with a strong increase in morbidity and mortality. Not all cancer patients receive thromboprophylaxis as this may lead to adverse events in a cancer population that is already at increased risk for major bleedings. Different risk prediction models have been developed to identify cancer patients at high risk of developing CAT that may be selected for thromboprophylaxis. However, risk models using the currently established biomarkers and clinical parameters perform poorly, particularly when validated in independent cohorts. Discovery of new and better biomarkers are therefore urgently needed. This review describes how aberrations in the genetic profile of the tumor and host influence a hypercoagulable state, and explores how these can be used as novel biomarker to improve CAT risk prediction.

Background This study aimed to identify novel plasma proteins associated with first-lifetime venous thromboembolism (VTE) and molecular pathways involved in VTE pathogenesis. Methods A case–cohort comprising incident VTE cases ( n  = 294) and a randomly sampled age- and sex-weighted subcohort ( n  = 1,066) was derived from the Trøndelag Health Study (HUNT3, n = 50,800). Blood samples were collected and stored at cohort inclusion (2006–2008), and participants were followed up to 5 years. Proteome-wide analyses was performed using the 7k SomaScan® proteomics platform, and weighted Cox-regression models adjusted for age, sex, and sample batch were conducted, with the Bonferroni method applied to account for multiple testing. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied on the top-ranked 200 proteins associated with VTE. Results Out of 7,288 human proteins, 7 proteins were significantly associated with higher VTE risk with p -value <6.9 × 10 −6 (hazard ratios per 1 standard deviation increase in protein levels ranging from 1.39 to 1.86). Except for coagulation factor VIII and tumor necrosis factor soluble receptor II, these proteins were novel associations and included collagen alpha-3(VI):BPTI/Kunitz inhibitor, histo-blood group ABO system transferase, peroxidasin, human epididymis protein 4, and regulator of G protein signaling 3. KEGG analyses of the top-ranked 200 proteins revealed significant pathway enrichment of nine proteins in the complement (mainly lectin pathway) and coagulation (mainly intrinsic pathway) cascades. Conclusion Our proteome-wide analysis led to discovery of five novel protein candidates associated with 5-year risk of future VTE. KEGG analyses supported an interplay between the complement and coagulation pathways in the pathogenesis of VTE.

Platelets play an important role in tumor growth and, at the same time, platelet characteristics are affected by cancer presence. Therefore, we investigated whether the platelet proteome harbors differentially expressed proteins associated with early-stage cancer. For this proof-of-concept study, patients with early-stage lung (n = 8) or head of pancreas cancer (n = 4) were included, as were healthy sex- and age-matched controls for both subgroups. Blood samples were collected from controls and from patients before surgery. Furthermore, from six of the patients, a second sample was collected two months after surgery. NanoLC-MS/MS-based proteomics of gel-fractionated platelet proteins was used for comparative spectral count analyses of patients to controls and before to after surgery samples. The total platelet proteome dataset included 4384 unique proteins of which 85 were significantly (criteria Fc > 1.5 and p < 0.05) changed in early-stage cancer compared to controls. In addition, the levels of 81 platelet proteins normalized after tumor resection. When filtering for the most discriminatory proteins, we identified seven promising platelet proteins associated with early-stage cancer. In conclusion, this pioneering study on the platelet proteome in cancer patients clearly identifies platelets as a new source of candidate protein biomarkers of early-stage cancer. BIOLOGICAL SIGNIFICANCE Currently, most blood-based diagnostics/biomarker research is performed in serum or plasma, while the content of blood cells is usually neglected. It is known that especially blood platelets, which are the main circulating pool of many bioactive proteins, such as growth factors, chemokines, and cytokines, are a potentially rich source of biomarkers. The current study is the first to measure the effect of early-stage cancer on the platelet proteome of patients. Our study demonstrates that the platelet proteome of patients with early-stage lung or head of pancreas cancer differs considerably compared to that of healthy individuals of matched sex and age. In addition, the platelet proteome of cancer patients normalized after surgical resection of the tumor. Exploiting platelet proteome differences linked to both tumor presence and disease status, we were able to demonstrate that the platelet proteome can be mined for potential biomarkers of cancer.

Key Points • We applied proteomic profiling to patients with suspected HIT, thus analyzing a large number of potential proteins.• Our analysis provided evidence supporting the potential of soluble P-selectin as a promising new biomarker in HIT.

Highlights • Complement activation is upregulated in JAK2V617F MPN with splanchnic thrombosis.• Proteomics reveals downregulation of natural anticoagulants in MPN patients.• Endothelial adhesion markers VCAM1 and ICAM1 are elevated in SVT patients.• Platelet and immune dysregulation contribute to thrombosis in MPN-related SVT.

It is well known that fibrin network binds a large variety of proteins, including inhibitors and activators of fibrinolysis, which may affect clot properties, such as stability and susceptibility to fibrinolysis. Specific plasma clot composition differs between individuals and may change in disease states. However, the plasma clot proteome has not yet been in-depth analyzed, mainly due to technical difficulty related to the presence of a highly abundant protein—fibrinogen and fibrin that forms a plasma clot. The aim of our study was to optimize quantitative proteomic analysis of fibrin clots prepared ex vivo from citrated plasma of the peripheral blood drawn from patients with prior venous thromboembolism (VTE). We used a multiple enzyme digestion filter aided sample preparation, a multienzyme digestion (MED) FASP method combined with LC–MS/MS analysis performed on a Proxeon Easy-nLC System coupled to the Q Exactive HF mass spectrometer. We also evaluated the impact of peptide fractionation with pipet-tip strong anion exchange (SAX) method on the obtained results. Our proteomic approach revealed 476 proteins repeatedly identified in the plasma fibrin clots from patients with VTE including extracellular vesicle-derived proteins, lipoproteins, fibrinolysis inhibitors, and proteins involved in immune responses. The MED FASP method using three different enzymes: LysC, trypsin and chymotrypsin increased the number of identified peptides and proteins and their sequence coverage as compared to a single step digestion. Peptide fractionation with a pipet-tip strong anion exchange (SAX) protocol increased the depth of proteomic analyses, but also extended the time needed for sample analysis with LC–MS/MS. The MED FASP method combined with a label-free quantification is an excellent proteomic approach for the analysis of fibrin clots prepared ex vivo from citrated plasma of patients with prior VTE.

It has been reported that 476 proteins can be detected in plasma fibrin clots from patients with venous thromboembolism. Plasma fibrin clots proteomic composition in relation to their properties has not been studied in acute pulmonary embolism (PE). Clots generated from plasma of 20 PE patients and 20 healthy controls were assessed using mass spectrometry, clot permeability (Ks), and clot lysis time (CLT). The proteomic composition of plasma fibrin clots from acute PE patients differed from that of control subjects in regard to 198 clot-bound proteins. In the acute PE group, we observed increased clot-bound fibrinogen, apolipoprotein B-100, platelet glycoprotein Ib, lipopolysaccharide-binding protein, and histones H3 + 4 and reduced fibronectin, α2-antiplasmin, α2-macroglobulin, factor (F)XIII, histidine-rich glycoprotein, antithrombin, von Willebrand Factor, plasminogen, and prothrombin. Among PE patients, low Ks (≤3.83 × 10-9 cm2) was associated with increased clot-bound C-reactive protein, kininogen-1, protein S, β-2-microglobulin, and thromboxane-A synthase when compared with patients having Ks > 3.83 × 10-9 cm2. Ks correlated inversely with FIX and FV, thrombin-activatable fibrinolysis inhibitor, complement C1s, C7, C8, and apolipoprotein A-I. The specific protein composition in plasma fibrin clots from acute PE patients is associated with denser clot formation. Several proteins unrelated to the coagulation system can modulate fibrin phenotype in acute thrombotic states. SIGNIFICANCE: Our study significantly advances the field of thrombosis and hemostasis. The plasma fibrin clot proteomics findings fill the gap of knowledge about the presence and the role of other proteins to the plasma fibrin clot in the acute phase of pulmonary embolism, aside fibrinogen, which is the main component of fibrin. The reported methodology, which involves the sample preparation using Multienzyme Digestion-Filter Aided Sample Preparation (MED FASP), data acquisition with the Quadrupole-Orbitrap mass spectrometer, and data analysis using the advanced tools such as MaxQuant, Total Protein Approach and Perseus, allows to gain not only the qualitative, but also the quantitative insights into the microworld of proteins entangled among the fibrin network. By comparing the clots formed from plasma of patients with acute pulmonary embolism with the clots from healthy control, we provide the specific protein composition associated with unfavorable clot properties observed in this disease. Moreover, our findings emphasize that several proteins unrelated to the coagulation system, can modulate fibrin phenotype in acute thrombotic states.

Background: Venous thromboembolism (VTE) remains a leading cause of global morbidity and mortality. The pathophysiological mechanisms leading to VTE are still not fully elucidated. Diagnostic biomarkers for VTE lack specificity, and biomarkers to guide the duration of anticoagulation therapy have not yet entered routine clinical practice. Proteomics has emerged as a high-throughput approach for novel biomarker discovery, offering insights into the complex biological processes across the VTE continuum. This review explores current VTE proteomic research and discusses the challenges and gaps hindering clinical translation. Methods: We performed a narrative review based on a search of Scopus and PubMed for original human proteomic studies published between 1995 and July 2025. Results were limited to whole-blood, plasma or serum-based studies. Results: A total of 1190 studies were retrieved, of which 27 studies were included in this review. Studies were mainly plasma-based. Studies compared VTE patients to non-VTE controls, different VTE subtypes, and various provoked VTE cohorts. Broad themes identified proteomic signatures involving dysregulated coagulation, complement activation, inflammation, and platelet activation. Conclusions: Current proteomic evidence supports VTE as a systemic immunothrombotic disorder that shows key differences even years before developing VTE. Proteomic research in VTE holds the promise to identify biomarkers that may aid in the diagnosis and guide management of VTE. However, most proteomic findings remain exploratory to date and methodologies are varied across studies. Future studies should prioritise the workflow standardisation and validate promising biomarker panels in large-scale, prospective, longitudinal cohorts.

Venous thromboembolism (VTE) involves complex genetic and molecular interactions not fully captured by current prediction tools. This study integrated a polygenic risk score (PRS) with plasma proteomics data from 44,138 UK Biobank participants to explore the molecular mechanisms underlying VTE. Associations between PRSVTE and 2,911 plasma proteins were analyzed, identifying 265 significant proteins linked to extracellular matrix organization and transmembrane signaling activity. Cox regressions further identified 354 proteins that significantly associated with incident VTE. Mendelian randomization supported causal relationships for 13 proteins, indicating their potential as therapeutic targets. To improve clinical risk prediction, we developed a protein-based risk score (ProteinRS) using LASSO regression. Here we show that the ProteinRS significantly improves VTE discrimination beyond traditional clinical factors and revealed a three-fold gradient in cumulative VTE risk (Hazard Ratio 0.52 vs 1.49). Our findings demonstrate that integrating plasma proteomics with genetic risk scores provides valuable biological insights and improves prediction of VTE.

Platelets may be pivotal mediators of the thrombotic and coagulopathic complications of preeclampsia (PE), linking inflammation and thrombosis with endothelial and vascular dysfunction. Both PE and gestational hypertension (GH) fall within the spectrum of hypertensive complications of pregnancy, with GH being a risk factor for preeclampsia. However, it is unclear what biomarkers distinguish PE from GH. Using a discovery size cohort, we aimed to characterize specific plasma and platelet thrombo-inflammatory drivers indicative of PE and differentiate PE from GH. We performed multiplex immunoassays, platelet and plasma quantitative proteomics and metabolomics of PE patients, comparing with non-pregnant (NP), healthy pregnant controls (PC) and GH participants. The expression pattern of plasma proteins and metabolites in PE/GH platelets was distinct from that of NP and PC. Whilst procoagulation in PC may be fibrinogen driven, inter-alpha-trypsin inhibitors ITIH2 and ITIH3 are likely mediators of thrombo-inflammation in GH and PE, and fibronectin and S100A8/9 may be major procoagulant agonists in PE only. Also enriched in PE were CCL1 and CCL27 plasma cytokines, and the platelet leucine-rich repeat-containing protein 27 and 42 (LRRC27/42), whose effects on platelets were explored using STRING analysis. Through protein-protein interactions analysis, we generated a new hypothesis for platelets’ contribution to the thrombo-inflammatory states of preeclampsia.

Deep vein thrombosis (DVT) is a serious health issue that often leads to considerable morbidity and mortality. Diagnosis of DVT in a clinical setting, however, presents considerable challenges. The fusion of metabolomics techniques and machine learning methods has led to high diagnostic and prognostic accuracy for various pathological conditions. This study explored the synergistic potential of dual-platform metabolomics (specifically, gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–mass spectrometry (LC-MS)) to expand the detection of metabolites and improve the precision of DVT diagnosis. Sixty-one differential metabolites were identified in serum from DVT patients: 22 from GC-MS and 39 from LC-MS. Among these, five key metabolites were highlighted by SHapley Additive exPlanations (SHAP)-guided feature engineering and then used to develop a stacking diagnostic model. Additionally, a user-friendly interface application system was developed to streamline and automate the application of the diagnostic model, enhancing its practicality and accessibility for clinical use. This work showed that the integration of dual-platform metabolomics with a stacking machine learning model enables faster and more accurate diagnosis of DVT in clinical environments.

Background Venous thromboembolism (VTE) is a complex thrombotic disorder that constitutes a major source of mortality and morbidity. To improve understanding of the cause of VTE, we conducted a metabolomic analysis in a case‐control study including 240 incident VTE cases and 6963 controls nested within 3 large prospective population‐based cohorts, the Nurses’ Health Study, the Nurses’ Health Study II, and the Health Professionals Follow‐Up Study. Methods and Results For each individual, we measured 211 metabolites and collected detailed information on lifestyle factors. We performed logistic regression and enrichment analysis to identify metabolites and biological categories associated with incident VTE risk, accounting for key confounders, such as age, sex, smoking, alcohol consumption, body mass index, and comorbid diseases (eg, cancers). We performed analyses of all VTEs and separate analyses of pulmonary embolism. Using the basic model controlling for age, sex, and primary disease, we identified 60 nominally significant VTE‐ or pulmonary embolism–associated metabolites (P<0.05). These metabolites were enriched for diacylglycerols (P permutation<0.05). However, after controlling for multiple testing, only 1 metabolite (C5 carnitine; odds ratio, 1.25; 95% confidence interval, 1.10–1.41; P corrected=0.03) remained significantly associated with VTE. After further adjustment for body mass index, no metabolites were significantly associated with disease after accounting for multiple testing, and no metabolite classes were enriched for nominally significant associations. Conclusions Although our findings suggest that circulating metabolites may influence the risk of incident VTE, the associations we observed were confounded by body mass index. Larger studies involving additional individuals and with broader metabolomics coverage are needed to confirm our findings.

Deep vein thrombosis (DVT) of the lower extremities is one of the most common peripheral vascular diseases, with significant complications and sequelae. Metabolomics aims to identify small molecules in biological samples. It can serve as a promising method for screening compounds that can be used for early disease detection, diagnosis, treatment response prediction, and prognosis. In addition, high-throughput metabolomics screening can yield significant insights into the pathophysiological pathways of DVT. Currently, the metabolomic profiles of DVT have yielded inconsistent expression patterns. This article examines the recent advancements in metabolomic studies of DVT and analyzes the factors that may influence the results.

In recent years, the field of venous thromboembolism has undergone numerous innovations, starting from the recent discoveries on the role of biomarkers, passing through the role of metabolomics in expanding our knowledge on pathogenic mechanisms, which have opened up new therapeutic targets. A variety of studies have contributed to characterizing the metabolic phenotype that occurs in venous thromboembolism, identifying numerous pathways that are altered in this setting. Among these pathways are the metabolism of carnitine, tryptophan, purine, and fatty acids. Furthermore, new evidence has emerged with the recent COVID-19 pandemic. Hypercoagulability phenomena induced by this viral infection appear to be related to altered von Willebrand factor activity, alteration of the renin–angiotensin–aldosterone system, and dysregulation of both innate and adaptive immunity. This is the first literature review that brings together the most recent evidence regarding biomarkers, metabolomics, and COVID-19 in the field of venous thromboembolism, while also mentioning current therapeutic protocols.

Supplemental Digital Content is available in the text. Objective: Deep vein thrombosis and pulmonary embolism referred as venous thromboembolism (VTE) are a common cause of morbidity and mortality. Plasma from healthy controls or individuals who have experienced a VTE were analyzed using metabolomics to characterize biomarkers and metabolic systems of patients with VTE. Approach and Results: Polar metabolite and lipidomic profiles from plasma collected 3 months after an incident VTE were obtained using liquid chromatography mass spectrometry. Fasting-state plasma samples from 42 patients with VTE and 42 healthy controls were measured. Plasma metabolomic profiling identified 512 metabolites forming 62 biological clusters. Multivariate analysis revealed a panel of 21 metabolites altogether capable of predicting VTE status with an area under the curve of 0.92 (P=0.00174, selectivity=0.857, sensitivity=0.971). Multiblock systems analysis revealed 25 of the 62 functional biological groups as significantly affected in the VTE group (P<0.05 to control). Complementary correlation network analysis of the dysregulated functions highlighted a subset of the lipidome composed mainly of n-3 long-chain polyunsaturated fatty acids within the predominant triglycerides as a potential regulator of the post-VTE event biological response, possibly controlling oxidative and inflammatory defence systems, and metabolic disorder associated dysregulations. Of interest was microbiota metabolites including trimethylamine N-oxide that remained associated to post incident VTE patients, highlighting a possible involvement of gut microbiota on VTE risk and relapse. Conclusions: These findings show promise for the elucidation of underlying mechanisms and the design of a diagnostic test to assess the likely efficacy of clinical care in patients with VTE.

Deep vein thrombosis (DVT) is a significant contributor to cardiovascular morbidity and mortality, which can be classified as muscular calf vein thrombosis (MCVT) or popliteal vein thrombosis (PVTE). This study aimed to evaluate the differential metabolites of DVT using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Metabolic profiles were analyzed, and binary logistic regression was used to build a diagnostic model to identify possible potential biomarkers for distinguishing DVT and its subtypes. The area under the curve (AUC) of the receiver operating characteristic (ROC) curves was employed to evaluate the diagnostic performance of these possible potential biomarkers. In this study, eight, three, and six differential metabolites associated with DVT, MCVT, and PVTE were identified. Enrichment analysis of differential metabolites revealed that DVT was mainly associated with energy metabolism, purine metabolism, and amino acid metabolism. Diagnostic models were developed based on differential metabolites; the diagnostic performance of DVT, MCVT, and PVTE was excellent. Our findings revealed distinct metabolic profiles for DVT, MCVT, and PVTE. Despite the small sample size and the inclusion of only Asian populations, this study paves the way for future large-sample multicenter follow-up studies.

Essentials Risk‐stratification often fails to predict clinical deterioration in pulmonary embolism (PE). First‐ever high‐throughput metabolomics analysis of risk‐stratified PE patients. Changes in circulating metabolites reflect a compromised energy metabolism in PE. Metabolites play a key role in the pathophysiology and risk stratification of PE.

Abstract Thrombosis is a relatively common human disease, being the third cause of mortality worldwide. Alterations in hemostasis, endothelial processes and blood flow are the major features involved in the pathophysiology of the disease, whose molecular basis is not yet fully understood due to the complexity and numerous influences that might lead to blood clotting. The activity and the role of blood metabolites in thrombosis are attracting great attention in the quest of understanding the triggering off uncontrolled clotting. Metabolomics can bring insights into metabolic fingerprints of any biological sample, quantify, and measure the metabolic responses to the pathophysiological stimuli or genetic modifications, and lead to an integrated comprehension of metabolites function in health and disease. Furthermore, the identification of biomarkers can reveal metabolic pathways associated with the pathogenesis and progression of the disease. In this review, we summarized the current state of knowledge of metabolomics in arterial and venous thrombosis research by nuclear magnetic resonance spectroscopy and mass spectrometry approaches and cited and discussed the altered metabolites that have been cited in both conditions. It is worth stating that the contribution of the metabolomics in this field or research is modest and being introduced in some case studies, and expected to grow in the near future.

BACKGROUND Venous thromboembolism (VTE) is an important complication in elderly patients with cancer, yet traditional clinical scoring systems insufficiently capture its molecular heterogeneity. This study aimed to construct a VTE-related molecular risk stratification framework for elderly cancer patients, identify molecular features that remain stable across datasets, and clarify the potential inflammation-coagulation interaction mechanisms underlying high-risk states. METHODS The peripheral-blood discovery cohort GSE19151 and the validation cohort GSE48000 from the Gene Expression Omnibus (GEO) database were integrated to identify stably differentially expressed genes (SDEGs). In The Cancer Genome Atlas (TCGA) elderly pan-cancer cohort, SDEGs and related pathway features were then used to construct a VTE-related molecular risk stratification framework. LASSO and random forest recursive feature elimination were applied for feature selection, multiple machine-learning models were compared, and SHAP analysis was used to evaluate feature contributions. GO/KEGG enrichment analysis, GSVA and weighted gene co-expression network analysis (WGCNA) were performed to characterize the biological basis of the high molecular-risk state. Kaplan-Meier analysis, time-dependent ROC curves and Cox regression were used to assess associations between the molecular risk score and prognosis. RESULTS A total of 427 VTE-related differentially expressed genes were identified in the GSE19151 discovery cohort, and 38 SDEGs were retained after cross-cohort validation in GSE48000. Machine-learning analysis further identified 11 robust core features. Among them, LY96, CCNT1 and IFI44L showed dominant contributions in feature importance ranking, SHAP analysis and interaction analysis. Model comparison indicated that XGBoost and random forest achieved favorable classification performance. Functional enrichment analysis showed that SDEGs were mainly enriched in innate immunity, inflammatory responses, cytokine signaling and complement-coagulation-related processes. GSVA and WGCNA further revealed significant activation of complement-coagulation cascades, IL-6/JAK/STAT signaling and immune-inflammatory networks in the high VTE molecular-risk group. Survival analysis showed that the high-risk group had significantly poorer overall survival and progression-free interval, and the VTE molecular risk score retained independent prognostic value in multivariable Cox models. CONCLUSIONS This study identified elderly cancer VTE-related core molecular features represented by LY96-CCNT1-IFI44L and established an interpretable molecular risk stratification framework. The framework highlights the coordinated activation of immune inflammation and coagulation pathways in high-risk states and provides a basis for evaluating VTE-related molecular heterogeneity and prognosis in elderly cancer patients.

… Citrullinated histone H3, a biomarker of neutrophil extracellular 736 trap forma on, predicts the risk of venous thromboembolism in … Risk assessment models of cancer-associated 949 …

Pulmonary embolism (PE) is defined as the obstruction of the pulmonary artery or one of its branches by a blood clot, tumor, air, or fat emboli originating elsewhere in the body. A saddle PE occurs when the obstruction affects the bifurcation of the main pulmonary artery trunk. We present a case of a 46-year-old man who presented to our hospital due to an episode of syncope. Computed tomography angiography (CTA) of the chest showed extensive PE and abdominal CT scan showed a large 8 cm left renal mass with inferior vena cava (IVC) thrombus. Emergent embolectomy, left total nephrectomy, and IVC tumor removal were performed yielding the diagnosis of clear cell renal cell carcinoma (RCC). Interestingly, our patient did not experience any symptoms related to his RCC until the diagnosis of PE due to syncope, and the asymptomatic tumor was found out to be the possible cause of this PE due to the presence of tumor cells constituting the tumor embolus. It is thus recommended to improve the early screening process for RCC. Besides, clinicians should pay attention to patients presenting with uncharacteristic symptoms of RCC who might present with symptoms of saddle PE.

… Khorana score have been proposed. The Vienna CATS group expanded the score by adding two biomarkers: … Currently, neither modification of the Khorana score has been validated or …

BackgroundAlthough patients with acute myeloid leukemia (AML) were shown to have an increased risk of thrombosis, no thrombosis risk assessment scoring system has been developed for AML patients. The Khorana Risk Score (KRS), which has been widely used for thrombosis risk assessment in the clinical setting, was developed on the basis of solid tumor data and has not been validated among AML patients. This study aims to validate the use of the KRS as a thrombosis risk-scoring system among patients with AML.MethodsUsing data from H. Lee Moffitt Cancer Center and Research Institution’s Total Cancer Care Research Study, we retrospectively identified patients who were histologically confirmed with AML from 2000 to 2018. Clinical and laboratory variables at the time of AML diagnosis were characterized and analyzed. The thrombotic event rate was estimated with the Kaplan-Meier method and compared using the log-rank test.ResultsA total of 867 AML patients were included in the analysis. The median age at AML diagnosis was 75 years (range, 51–96), and the majority were male (65%, n = 565). A total of 22% (n = 191), 51% (n = 445), 24% (n = 207), and 3% (n = 24) of patients had a KRS of 0, 1, 2, and 3, respectively. A total of 42 thrombotic events (3% [n = 6/191] with a KRS of 1; 5% [n = 23/445] with a KRS of 2; 6.3% [n = 13/207] with a KRS of 3) were observed, with a median follow-up of 3 months (range, 0.1–307). There was no statistical difference in the risk of thrombosis between these groups (P = .1949).ConclusionsAlthough there was an increased risk of thrombosis associated with a higher KRS among AML patients with a KRS of 1 to 3, the difference was not statistically significant. Furthermore, only a few patients were found to have a KRS > 3, and this was largely due to pancytopenia, which is commonly associated with AML. These results indicate the need for a better thrombotic risk-scoring system for AML patients.

… and biomarkers as well as the validation of a risk score that helps … Little is known about predictive biomarkers or clinical risk … the Ottawa score—has been proposed but validation studies …

Abstract Ovarian cancer (OC) remains one of the most lethal gynaecological malignancies worldwide, largely due to the absence of effective screening strategies, which frequently results in diagnosis at advanced stages of disease, together with the development of chemoresistance. Moreover, clinical outcomes are significantly compromised by cancer-associated thrombosis (CAT), particularly venous thromboembolism (VTE), which is a major cause of morbidity and mortality in this population. Despite the well-established association between OC and VTE, evidence on thromboprophylaxis remains fragmented. This comprehensive narrative review focuses on the prevention of VTE in OC patients, examining the epidemiology, risk factors, underlying pathophysiological mechanisms, emerging biomarkers, current thromboprophylaxis strategies and further clinical implications. The available evidence indicates a consistently high incidence of VTE across all disease stages, with particularly elevated risk during chemotherapy and among specific histological subtypes, notably clear cell tumours. Established clinical risk factors are supported by consistent evidence across studies, while coagulation abnormalities appear to reflect tumour aggressiveness, highlighting the close interplay between thrombosis and OC biology. Among the biomarkers investigated, D-dimer is the most consistently validated marker for VTE prediction and diagnosis, whereas the clinical utility of emerging biomarkers and currently available risk assessment models, including the Khorana score, remains limited by inconsistent performance and insufficient external validation. Although thromboprophylaxis may offer benefit in selected high-risk groups, uncertainties remain regarding optimal patient selection, timing, and therapeutic approaches. The predominance of retrospective, single-centre studies and heterogeneous patient cohorts further constrains the current evidence base. Future research should prioritise large, prospective, multicentre investigations, the development and external validation of OC-specific risk prediction models, and well-designed clinical trials evaluating personalised thromboprophylaxis strategies to reduce the burden of VTE and improve clinical outcomes in OC patients.

Background Although the Khorana venous thromboembolism (VTE) risk score (KRS) is well recognized as a simple VTE risk assessment method in patients with cancer, whether it is suitable for Asian populations is unclear. Objectives This study validated KRS for the prediction of VTE and investigated the value of the KRS in predicting mortality in Japanese patients with cancer. Methods A body mass index value of 25 kg/m2 or more was defined as obesity according to World Health Organization consensus. A total of 27,687 patients with cancer were subdivided into low- (0), intermediate- (1-2), and high-score (3) groups by the KRS. The primary and secondary endpoints were VTE and all-cause mortality, respectively. Results The prevalence of VTE was 1.7%, 7.3%, and 11.0% for low-, intermediate-, and high-score patients, respectively. Receiver operating characteristic (ROC) analysis showed that the KRS significantly predicted VTE (area under the curve, 0.679; 95% confidence interval [CI] 0.666-0.692; P < 0.001). The cutoff value for the KRS was 1.0. Logistic regression analysis demonstrated that the KRS was an independent predictor of VTE (odds ratio 1.766; 95% CI 1.673-1.865; P < 0.01). The cutoff value of the KRS for all-cause mortality determined by ROC analysis was 2.0. Kaplan–Meier analysis demonstrated a significantly higher incidence of mortality in the KRS ≥2 group than in the KRS 0-1 group (log-rank: P < 0.01). Conclusions The KRS was useful in Japanese patients with cancer and might be a potentially useful marker for the prediction of mortality. Establishing optimal scores for Japanese subjects is mandatory because of its low diagnostic ability. (KUMAMON Cancer registry; UMIN000047554)

Background: Existing risk models for cancer-associated thrombosis (CAT) show suboptimal performance in selective high-risk populations with cancer. Affinity-based plasma proteomics offer a novel approach for detecting CAT risk. Objectives: To identify plasma biomarkers for CAT using proximity extension assays in an advanced cancer cohort. Patients/Methods: We performed a nested case-control study using the Olink Explore HT panel. The final cohort included 57 patients with CAT and 113 matched control patients from five selected cancer types who had samples collected between cancer diagnosis and chemotherapy initiation. Random survival forest model was used to assess non-linear associations with CAT in 5,416 normalized protein expressions and 8 clinical variables. Evaluation metrics averaged across bootstrapped out-of-bag test sets included time-dependent receiver operation characteristic curve (TD-ROC), calibration plot, and cumulative incidence in high- versus low-risk predicted groups. We used SHapley Additive exPlanation (SHAP) for feature interpretability. We performed overrepresentation analysis (ORA) and gene set enrichment analysis (GSEA) to assess biological pathway plausibility. Results: Our internally validated model predicted early thrombotic events well (TD-ROC 0.83 at 30 days and 0.73 at 90 days), but the discrimination waned with follow-up time (0.67 at 180 days). Calibration followed a similar pattern. In ORA and GSEA, important proteins were observed in hemostatic pathways including platelet activation, fibrin clot formation, and complement cascade regulation. Conclusion: Affinity-based plasma proteomics can be used as a novel strategy to identify biomarkers of CAT. External validation with larger sample size in a cohort setting is required for risk prediction models.

Purpose Venous thromboembolism (VTE), including deep vein thrombosis and pulmonary embolism, is a leading cause of morbidity and mortality in cancer patients. Prostate cancer is associated with an elevated risk of VTE, yet the molecular drivers remain poorly defined. Methods In this study, we employed high-throughput proteomic profiling using the SomaLogic platform to analyze plasma from 85 prostate cancer patients, including 43 with and 42 without VTE. Samples were collected at cancer diagnosis, with VTE diagnosed at a mean of 96.8 months later. Results Principal component analysis showed modest proteomic separation between groups. Differential expression analysis identified enriched pathways in VTE patients, including hemostasis (TIMP1, JAM2, TMX3, F3, and ESAM), cell adhesion (CXCL12, CCL11, CCN5, COL18A1, and ADGRB1) and cell proliferation (TIMP1, REG1B, REG1A, CRLF2, and ALDH1A2). Receiver Operating Characteristic analysis using top fifteen proteins achieved an area under the curve of 0.859, indicating strong predictive value for VTE in this cohort. Conclusions We identified a specific cluster of circulating proteins associated with development of VTE in patients with prostate cancer. This work deepens understanding of systemic mediators of cancer-associated VTE and, pending validation in other cohorts, paves the way for improved risk stratification and long-term monitoring in this population.

Background About 5% of patients with unprovoked venous thromboembolism (VTE) have occult cancer. Despite standard cancer screening, 50% of cancers remain undetected. Objectives We used quantitative targeted proteomics to identify novel cancer biomarkers among patients with unprovoked VTE. Methods Patients aged ≥40 years with a first unprovoked VTE and without a malignancy in the preceding 5 years were invited to an international prospective cohort study. Plasma samples were collected within 10 days after VTE. The primary outcome was an adjudicated cancer diagnosis during 12-month follow-up. Concentrations of 269 plasma proteins covering coagulation, complement, and cancer-associated pathways were measured using quantitative mass spectrometry-based targeted proteomics. In a nested case-control study, protein profiles of patients with cancer were compared with those of randomly sampled unique control patients (ratio 3:1). Proteins with an unadjusted P value < .05 and fold change ≥15% were combined in a multivariable logistic regression model. To address the variability in the obtained model, the protein selection and model-building approach were replicated in 250 bootstrap samples, and an optimism-adjusted c-statistic was calculated. Results Of the 476 included participants, 28 (5.9%) were newly diagnosed with cancer. Plasma samples were available for 24 cases, which were compared with those of 75 control patients. Concentrations of P-selectin, β-2 microglobulin, complement component 7, intracellular adhesion molecule 1, and lumican were higher in cases than in controls, whereas coagulation factor (F)VII, FX, and FXII, β-Ala-His dipeptidase, and kalistatin were lower. The optimism-adjusted c-statistic of the multivariable logistic regression model including these proteins was 0.78 (95% CI, 0.70-0.87). Conclusion Ten differentially abundant proteins were identified in patients with occult cancer, suggesting potential of plasma proteomic tests as novel biomarker for occult cancer in patients with unprovoked VTE.

A State of the Art lecture titled “Proteomics in Thrombosis Research” was presented at the ISTH Congress in 2021. In clinical practice, there is a need for improved plasma biomarker‐based tools for diagnosis and risk prediction of venous thromboembolism (VTE). Analysis of blood, to identify plasma proteins with potential utility for such tools, could enable an individualized approach to treatment and prevention. Technological advances to study the plasma proteome on a large scale allows broad screening for the identification of novel plasma biomarkers, both by targeted and nontargeted proteomics methods. However, assay limitations need to be considered when interpreting results, with orthogonal validation required before conclusions are drawn. Here, we review and provide perspectives on the application of affinity‐ and mass spectrometry‐based methods for the identification and analysis of plasma protein biomarkers, with potential application in the field of VTE. We also provide a future perspective on discovery strategies and emerging technologies for targeted proteomics in thrombosis research. Finally, we summarize relevant new data on this topic, presented during the 2021 ISTH Congress.

Venous thromboembolism (VTE) is a significant global health issue, yet effective therapeutic targets for its prevention and treatment remain elusive. This study aimed to identify plasma proteins causally associated with VTE risk using proteome-wide Mendelian randomization (MR) and colocalization analyses. We utilized genome-wide association study (GWAS) data from the UK Biobank and FinnGen cohorts, encompassing 38,573 VTE cases and 946,373 controls. Plasma protein levels were quantified using Olink technology in the UK Biobank Pharma Proteomics Project (UKB-PPP) and SomaScan in the deCODE Health study. MR analysis was performed to assess causal relationships, followed by colocalization analysis to evaluate shared genetic variants. Functional enrichment analyses and molecular docking were conducted to explore biological mechanisms and predict potential therapeutic compounds. Eight proteins showed significant associations with VTE risk after Bonferroni correction (p < 3.19 × 10−5). Odds ratios ranged from 0.98 (95% CI: 0.98–0.99) for PLEK to 1.03 (95% CI: 1.02–1.04) for LRP12. Strong colocalization evidence (PH4 ≥ 0.8) was found for LRP12, F11, PLCG2, and ABO. Molecular docking identified promising drug candidates including valine, folic acid, ibrutinib, and simvastatin, with valine showing the strongest binding energy (-32.057 kcal/mol). This study highlights novel therapeutic targets for VTE and provides insights into potential drug candidates. These findings offer a foundation for future research and drug development aimed at reducing VTE risk.

Patients with lower‐leg cast immobilization and patients undergoing knee arthroscopy have an increased risk of venous thrombosis (VT). Guidelines are ambiguous about thromboprophylaxis use, and individual risk factors for developing VT are often ignored. To assist in VT risk stratification and guide thromboprophylaxis use, various prediction models have been developed. These models depend largely on clinical factors and provide reasonably good C‐statistics of around 70%. We explored using protein levels in blood plasma measured by multiplexed quantitative targeted proteomics to predict VT. Our aim was to assess whether a VT risk prediction model based on absolute plasma protein quantification is possible.

BACKGROUND: Venous thromboembolism (VTE) is a leading cardiovascular disease, yet its etiology is incompletely understood. This study used large-scale, high-throughput aptamer-based proteomics to identify new circulating protein biomarkers and biological pathways for incident VTE. METHODS: We included 4 longitudinal cohorts (the ARIC study [Atherosclerosis Risk in Communities], CHS [Cardiovascular Health Study], MESA [Multi-Ethnic Study of Atherosclerosis], and the HUNT study [Trøndelag Health]) that identified 1371 incident noncancer VTEs among 20 737 participants followed for a maximum of 10 to 29 years. We used the SomaScan to measure baseline plasma levels of ≈5000 to 7000 proteins and examined the prospective relationships between the protein biomarkers and noncancer VTE. We then conducted an external replication of top VTE proteins in 783 incident noncancer VTEs among 39 097 participants in the UKB study (UK Biobank) based on the Olink proteomics platform. We used Cox proportional hazards regression to estimate the association between each protein biomarker and VTE risk. Mendelian randomization (MR) analysis was used to assess the possible causal associations between identified proteins and VTE risk. RESULTS: There were 23 proteins that exceeded a false discovery rate–adjusted P<0.05 (unadjusted P<6.5×10-4) in the discovery meta-analysis of ARIC, CHS, and MESA and were replicated in HUNT at (unadjusted) P<0.05. Of these, 15 are new to VTE, and 3 of the 15 (transgelin, sushi, von Willebrand factor type A, EGF and pentraxin domain-containing protein 1, and TIMP4 [metalloproteinase inhibitor 4]) exceeded the Bonferroni corrected significance threshold in HUNT. Sixteen of the 23 top VTE proteins were available on the UKB Olink panel, of which 11 were replicated in the UKB study after Bonferroni correction. MR analysis of the 15 new proteins provided significant evidence for a possible causal role of TIMD4 (T-cell immunoglobulin and mucin domain-containing protein 4) (Bonferroni-corrected P<0.05) and suggestive evidence for TIMP4 and CST3 (cystatin-c) (unadjusted P<0.05) in VTE risk. The direction of association from the MR analyses was opposite of that from the VTE proteomics analysis for TIMP4 and TIMD4 but was consistent for CST3. CONCLUSIONS: We identified several novel plasma proteins for VTE that reflect biological processes outside established VTE pathophysiology, including extracellular matrix regulation, immunity, immune–vascular endothelium interactions, and vascular senescence. Results may provide new modifiable targets to improve VTE risk stratification, prevention, or treatment.

The obesity paradox, the controversial finding that obesity promotes disease development but protects against sequelae in patients, has been observed in venous thromboembolism (VTE). The aim of this investigation was to identify a body mass-related proteomic signature in VTE patients and to evaluate whether this signature mediates the obesity paradox in VTE patients. Data from the Genotyping and Molecular Phenotyping in Venous ThromboEmbolism Project, a prospective cohort study of 693 VTE patients, were analyzed. A combined end point of recurrent VTE or all-cause death was used. Relative quantification of 444 proteins was performed using high-throughput targeted proteomics technology. Measurements were performed in samples collected during the acute VTE event and at 12-month follow-up. An 11-protein signature (CLEC4C, FABP4, FLT3LG, IL-17C, LEP, LYVE1, MASP1, ST2, THBS2, THBS4, TSLP) for body mass in VTE patients was identified. The signature did not significantly mediate the obesity paradox (change in hazard ratio [HR]: 0.04; likelihood ratio test of nested models = 7.7; P = .74), but its main constituent protein, leptin, was inversely associated with recurrent VTE or death (adjusted HR [95% confidence interval] per standard deviation increase: 0.66 [0.46-0.94]). This relationship was significantly (P = .007) modified by markers of leptin resistance (ie, high body mass index and high circulating matrix metalloproteinase-2 levels). Although the signature did not substantially explain the obesity paradox, leptin appears to be protective against disease recurrence and death in VTE patients. This protective effect was abrogated under conditions of leptin resistance and hence was unrelated to the obesity paradox.

Background Risk stratification is crucial to improve tailored therapy in patients with suspected coronary artery disease (CAD). This study investigated the ability of targeted proteomics to predict presence of high-risk plaque or absence of coronary atherosclerosis in patients with suspected CAD, defined by coronary computed tomography angiography (CCTA). Methods Patients with suspected CAD (n = 203) underwent CCTA. Plasma levels of 358 proteins were used to generate machine learning models for the presence of CCTA-defined high-risk plaques or complete absence of coronary atherosclerosis. Performance was tested against a clinical model containing generally available clinical characteristics and conventional biomarkers. Findings A total of 196 patients with analyzable protein levels (n = 332) was included for analysis. A subset of 35 proteins was identified predicting the presence of high-risk plaques. The developed machine learning model had fair diagnostic performance with an area under the curve (AUC) of 0·79 ± 0·01, outperforming prediction with generally available clinical characteristics (AUC = 0·65 ± 0·04, p < 0·05). Conversely, a different subset of 34 proteins was predictive for the absence of CAD (AUC = 0·85 ± 0·05), again outperforming prediction with generally available characteristics (AUC = 0·70 ± 0·04, p < 0·05). Interpretation Using machine learning models, trained on targeted proteomics, we defined two complementary protein signatures: one for identification of patients with high-risk plaques and one for identification of patients with absence of CAD. Both biomarker subsets were superior to generally available clinical characteristics and conventional biomarkers in predicting presence of high-risk plaque or absence of coronary atherosclerosis. These promising findings warrant external validation of the value of targeted proteomics to identify cardiovascular risk in outcome studies. Fund This study was supported by an unrestricted research grant from HeartFlow Inc. and partly supported by a European Research Area Network on Cardiovascular Diseases (ERA-CVD) grant (ERA CVD JTC2017, OPERATION). Funders had no influence on trial design, data evaluation, and interpretation.

Summary Cancer-associated thrombosis (CAT) is a major cause of morbidity and mortality in patients with cancer, but the immune landscape of the thrombus itself is poorly mapped. We combined high-parameter mass cytometry of paired peripheral blood and venous thrombi from non-cancer deep vein thrombosis (DVT) and CAT with an integrated single-cell RNA-sequencing atlas to profile immune remodeling at single-cell resolution. Relative to non-cancer DVT, CAT thrombi showed expansion of CXCR3+CD11b+ myeloid subsets, loss of conventional CD4+ and CD8+ T cells, and accumulation of unconventional double-negative T cells, alongside systemic depletion of T-bet+EOMES+ natural killer (NK) cells. We also detected PD-L1 on the CD45− non-immune compartment of CAT thrombi and found a positive association between hemoglobin and FOXP3+CD8+ T cells. These exploratory findings nominate chemokine- and checkpoint-related pathways for future study and provide an open single-cell resource for thrombo-immunology research.

… were significant predictors of postoperative deep vein thrombosis (DVT) [5]. … biomarkers that may be helpful in identifying cancer patients who are at high risk of developing thrombosis …

… development of cancer-associated thrombosis formation. … recurrent or metastatic squamous cell carcinoma of the head … present an attractive source of candidate biomarkers for cancer …

Tissue factor (TF) is a protein that plays a critical role in blood clotting, but recent research has also shown its involvement in cancer development and progression. Herein, we provide an overview of the structure of TF and its involvement in signaling pathways that promote cancer cell proliferation and survival, such as the PI3K/AKT and MAPK pathways. TF overexpression is associated with increased tumor aggressiveness and poor prognosis in various cancers. The review also explores TF's role in promoting cancer cell metastasis, angiogenesis, and venous thromboembolism (VTE). Of note, various TF-targeted therapies, including monoclonal antibodies, small molecule inhibitors, and immunotherapies have been developed, and preclinical and clinical studies demonstrating the efficacy of these therapies in various cancer types are now being evaluated. The potential for re-targeting TF toward cancer cells using TF-conjugated nanoparticles, which have shown promising results in preclinical studies is another intriguing approach in the path of cancer treatment. Although there are still many challenges, TF could possibly be a potential molecule to be used for further cancer therapy as some TF-targeted therapies like Seagen and Genmab’s tisotumab vedotin have gained FDA approval for treatment of cervical cancer. Overall, based on the overviewed studies, this review article provides an in-depth overview of the crucial role that TF plays in cancer development and progression, and emphasizes the potential of TF-targeted and re-targeted therapies as potential approaches for the treatment of cancer.

Platelets rapidly undergo responsive transitions in form and function to repair vascular endothelium and mediate hemostasis. In contrast, heterogeneous platelet subpopulations with a range of primed or refractory phenotypes gradually arise in chronic inflammatory and other conditions in a manner that may indicate or support disease. Qualitatively distinguishable platelet phenotypes are increasingly associated with a variety of physiological and pathological circumstances; however, the origins and significance of platelet phenotypic variation remain unclear and conceptually vague. As changes in platelet function in disease exhibit many similarities to platelets following the activation of platelet agonist receptors, the intracellular responses of platelets common to hemostasis and inflammation may provide insights to the molecular basis of platelet phenotype. Here, we review concepts around how protein-level relations-from platelet receptors through intracellular signaling events-may help to define platelet phenotypes in inflammation, immune responses, aging, and other conditions. We further discuss how representing systems-wide platelet proteomics data profiles as circuit-like networks of causally related intracellular events, or, pathway maps, may inform molecular definitions of platelet phenotype. In addition to offering insights into platelets as druggable targets, maps of causally arranged intracellular relations underlying platelet function can also advance precision and interceptive medicine efforts by leveraging platelets as accessible, dynamic, endogenous, circulating biomarkers of vascular wellness and disease. Graphic Abstract: A graphic abstract is available for this article.

Liquid biopsies represent a potential revolution in cancer diagnostics as a noninvasive method for detecting and monitoring diseases, complementary to or even replacing current tissue biopsy approaches. Several blood-based biosources and biomolecules, such as cell-free DNA and RNA, proteins, circulating tumor cells, and extracellular vesicles, have been explored for molecular test development. We recently discovered the potential of tumor-educated blood platelets (TEP) as a noninvasive biomarker trove for RNA biomarker panels. TEPs are involved in the progression and spread of several solid tumors, and spliced TEP RNA surrogate signatures can provide specific information on the presence, location, and molecular characteristics of cancers. So far, TEP samples from patients with different tumor types, including lung, brain, and breast cancers, have been tested, and it has been shown that TEPs from patients with cancer are distinct from those with inflammatory and other noncancerous diseases. It remains to be investigated how platelets are "educated," which mechanisms cause intraplatelet RNA splicing, and whether the relative contribution of specific platelet subpopulations changes in patients with cancer. Ultimately, TEP RNA may complement currently used biosources and biomolecules employed for liquid biopsy diagnosis, potentially enhancing the detection of cancer in an early stage and facilitating noninvasive disease monitoring. Cancer Res; 78(13); 3407-12. ©2018 AACR.

… biomarkers to predict patient responses or alternative angiogenic targets to VEGFA to avoid resistance warrants more research into TECs in brain cancer… clear cell renal cell carcinoma (…

… RNAs and proteins released by cancer cells. Thus, platelets … , predictive, or monitoring biomarkers. In this review, we cover … potential application of platelet RNA as disease biomarkers. …

Summary A characteristic clinical complication in cancer patients is the frequent incidence of thrombotic events. Numerous studies have shown hyperactive/activated platelets to be a critical earlier trigger for cancer-associated thrombus formation. However, there currently is no viable approach to monitor specific changes in tumor-associated platelet activity. Here, we describe a chromatograph-like microfluidic device that is highly sensitive to the activity status of peripheral circulating platelets in both tumor-bearing mice and clinical cancer patients. Our results show a strongly positive correlation between platelet activation status and tumor progression. Six-month follow-up data from advanced cancer patients reveal positive links between platelet activity level and thrombus occurrence rate, with a high predictive capacity of thrombotic events (AUC = 0.842). Our findings suggest that circulating platelet activity status determined by this microfluidic device exhibits sensitive, predictive potential for thrombotic events in cancer patients for directing well-timed antithrombosis treatment.

Simple Summary Blood clots in veins, known as venous thromboembolism (VTE), can be very dangerous and even fatal if not detected early. Current methods to diagnose these clots, like special ultrasounds and scans, can be time-consuming, expensive, and sometimes expose patients to harmful radiation. Our review looks at various biological markers in the blood that could help detect these clots more quickly and safely. We studied both the markers that are already in use and the new ones being researched. We found that while these markers show promise, they also have limitations, like not being specific enough to VTE. By combining different markers and using new technologies, we hope to develop better diagnostic tools. These improvements could lead to earlier detection of blood clots, better treatment decisions, and ultimately save lives by reducing the burden of this serious condition on patients and healthcare systems.

Biomarker-driven individualized treatment in oncology has made tremendous progress through technological developments, new therapeutic modalities and a deeper understanding of the molecular biology for tumors, cancer stem cells and tumor-infiltrating immune cells. Recent technical developments have led to the establishment of a variety of cancer-related diagnostic, prognostic and predictive biomarkers. In this regard, different modern OMICs approaches were assessed in order to categorize and classify prognostically different forms of neoplasia. Despite those technical advancements, the extent of molecular heterogeneity at the individual cell level in human tumors remains largely uncharacterized. Each tumor consists of a mixture of heterogeneous cell types. Therefore, it is important to quantify the dynamic cellular variations in order to predict clinical parameters, such as a response to treatment and or potential for disease recurrence. Recently, single-cell based methods have been developed to characterize the heterogeneity in seemingly homogenous cancer cell populations prior to and during treatment. In this review, we highlight the recent advances for single-cell analysis and discuss the challenges and prospects for molecular characterization of cancer cells, cancer stem cells and tumor-infiltrating immune cells.

… thrombosis are still not fully understood. In this review we will discuss several coagulation factors and their contribution on cancer … tumor-specific production and secretion of coagulation …

Abstract It has been long-established that cancer and thrombosis are linked, but the exact underlying pathological mechanism remains to be unraveled. As the initiator of the coagulation cascade, the transmembrane glycoprotein tissue factor (TF) has been intensely investigated for its role in cancer-associated thrombosis and cancer progression. TF expression is regulated by both specific oncogenes and environmental factors, and it is shown to regulate primary growth and metastasis formation in a variety of cancer models. In clinical studies, TF has been shown to be overexpressed in most cancer types and is strongly associated with disease progression. While TF clearly associates with cancer progression, a prominent role for TF in the development of cancer-associated thrombosis is less clear. The current concept is that cancer-associated thrombosis is associated with the secretion of tumor-derived TF-positive extracellular vesicles in certain tumor types. To date, many therapeutic strategies to target TF—both in preclinical and clinical phase—are being pursued, including targeting TF or the TF:FVIIa complex by itself or by exploiting TF as a docking molecule to deliver cytotoxic compounds to the tumor. In this review, the authors summarize the current understanding of the role of TF in both cancer progression and cancer-associated thrombosis, and discuss novel insights on TF as a therapeutic target as well as a biomarker for cancer progression and VTE.

Simple Summary The tissue factor (TF)-factor VIIa complex is the major physiological initiator of blood coagulation. Tumors express TF and release TF-positive extracellular vesicles (EVs) into the circulation, and this is associated with the activation of coagulation. Circulating levels of EVTF activity may be a useful biomarker to identify patients at risk for thrombosis. Tumor TF and TF-positive EVs are also associated with reduced survival. Abstract Tissue factor (TF) is a transmembrane glycoprotein that functions as a receptor for FVII/FVIIa and initiates the extrinsic coagulation pathway. Tumors and cancer cells express TF that can be released in the form of TF positive (TF+) extracellular vesicles (EVs). In this review, we summarize the studies of tumor TF and TF + EVs, and their association with activation of coagulation and survival in cancer patients. We also summarize the role of tumor-derived TF + EVs in venous thrombosis in mouse models. Levels of tumor TF and TF + EVs are associated with venous thromboembolism in pancreatic cancer patients. In addition, levels of EVTF activity are associated with disseminated intravascular coagulation in cancer patients. Furthermore, tumor-derived TF + EVs enhance venous thrombosis in mice. Tumor TF and TF + EVs are also associated with worse survival in cancer patients, particularly in pancreatic cancer patients. These studies indicate that EVTF activity could be used as a biomarker to identify pancreatic cancer patients at risk for venous thrombosis and cancer patients at risk for disseminated intravascular coagulation. EVTF activity may also be a useful prognostic biomarker in cancer patients.

… Soluble vascular endothelial growth factor (sVEGF) and the risk of venous thromboembolism in patients with cancer: results from the Vienna Cancer and Thrombosis Study (CATS). …

… In the most serious cases, clinical signs of vascular thrombosis or disseminated intravascular coagulation complicate the evolution of the malignant disease (1). Activation of the …

… As a result, a microenvironment promoting tumor growth is … cancer-thrombosis connection exists, by which cancer cells support clot formation, and clotting proteins support cancer …

Several studies have suggested a role for blood coagulation proteins in tumour progression. Herein, we discuss (1) the activation of the blood clotting cascade in the tumour microenvironment and its impact on primary tumour growth; (2) the intravascular activation of blood coagulation and its impact on tumour metastasis and cancer-associated thrombosis; and (3) antitumour therapies that target blood-coagulation-associated proteins. Expression levels of the clotting initiator protein TF (tissue factor) have been correlated with tumour cell aggressiveness. Simultaneous TF expression and PS (phosphatidylserine) exposure by tumour cells promote the extravascular activation of blood coagulation. The generation of blood coagulation enzymes in the tumour microenvironment may trigger the activation of PARs (protease-activated receptors). In particular, PAR1 and PAR2 have been associated with many aspects of tumour biology. The procoagulant activity of circulating tumour cells favours metastasis, whereas the release of TF-bearing MVs (microvesicles) into the circulation has been correlated with cancer-associated thrombosis. Given the role of coagulation proteins in tumour progression, it has been proposed that they could be targets for the development of new antitumour therapies.

Simple Summary Microparticles (MPs) play a key role in intercellular communication and mediate many features of cancers by delivering their various biomolecular cargos (including phospholipids). Increased release of phosphatidylserine-rich MPs from cancer and blood cells promotes tumor development and progression. Cancer cell signaling contributes to the formation of hypercoagulability, which in turn facilitates tumor progression. This review links coagulation activation with the process of metastatic tumor spread, including angiogenesis and matrix degradation. Therefore, anticoagulation can not only reduce thrombus formation but also slow tumor progression, which is of great significance for patient treatment. We provide promising cancer treatment strategies targeting the phosphatidylserine-mediated coagulation cascade and fill current knowledge gaps. Abstract Tumor progression and cancer metastasis has been linked to the release of microparticles (MPs), which are shed upon cell activation or apoptosis and display parental cell antigens, phospholipids such as phosphatidylserine (PS), and nucleic acids on their external surfaces. In this review, we highlight the biogenesis of MPs as well as the pathophysiological processes of PS externalization and its involvement in coagulation activation. We review the available evidence, suggesting that coagulation factors (mainly tissue factor, thrombin, and fibrin) assist in multiple steps of tumor dissemination, including epithelial–mesenchymal transition, extracellular matrix remodeling, immune escape, and tumor angiogenesis to support the formation of the pre-metastatic niche. Platelets are not just bystander cells in circulation but are functional players in primary tumor growth and metastasis. Tumor-induced platelet aggregation protects circulating tumor cells (CTCs) from the blood flow shear forces and immune cell attack while also promoting the binding of CTCs to endothelial cells and extravasation, which activates tumor invasion and sustains metastasis. Finally, in terms of therapy, lactadherin can inhibit coagulation by competing effectively with coagulation factors for PS binding sites and may similarly delay tumor progression. Furthermore, we also investigate the therapeutic potential of coagulation factor inhibitors within the context of cancer treatment. The development of multiple therapies targeting platelet activation and platelet–tumor cell interactions may not only reduce the lethal consequences of thrombosis but also impede tumor growth and spread.

Blood coagulation appears to play an important role in the occurrence of cancer and its effects may be twofold. First, in patients with cancer, blood coagulation is activated in the direction of a prothrombotic state. Second, a procoagulant environment may promote cancer in different ways. In this chapter we discuss some of the mechanisms that may be involved in this interplay between coagulation and cancer. Blood coagulation proteins interact with cells in the vasculature to maintain hemostasis. However, many proteins that are involved in coagulation and anticoagulation, as well as fibrinolysis, are also found in extravascular tissues. In different organs, these proteins may be involved in cell-signaling mechanisms, through interaction with cell receptors like protease-activated receptors (PARs). Such interactions may drive inflammation, angiogenesis and cell proliferation. The potential procarcinogenic actions of proteases like thrombin may be counteracted by the anticoagulant and anti-inflammatory actions of the protein C-thrombomodulin mechanism. In the blood of cancer patients, the balance is usually shifted towards a procoagulant direction. The resulting excess thrombin- and fibrin-forming activity promotes venous thrombosis and may in the extravascular compartment stimulate cancer progression. The activation of platelets and their interaction with leukocytes may propagate this process. In addition to the therapeutic modulation of the prothrombotic environment, the induction of specific anticoagulant proteins including thrombomodulin may have effects on tumor growth or dissemination, but the nature of these effects still remains hard to predict. The interplay between cancer and blood coagulation merits further experimental and clinical research.

… different human pancreatic cancer cell lines using a one stage clotting assay. These results … many tumors associated with thrombotic complications were mucin-secreting carcinomas …

… thrombosis, tumor growth, tumor angiogenesis, and metastasis. Tissue factor is expressed in two naturally occurring protein … drives coagulation in prostate cancer-associated thrombosis…

… in cancer may accomplish two goals: prevention of thrombosis, and prevention of … to tumor angiogenesis via both clotting-dependent and -independent mechanisms. 41 Clotting-…

Summary.  The close link between coagulation activation and clinical cancer is well established and recent progress has defined underlying molecular pathways by which tumour cells interact with the haemostatic system to promote cancer progression. Tumour type‐specific oncogenic transformations cause constitutive and hypoxia‐dependent upregulation of tissue factor (TF) in cancer cells, but TF expressed by vascular, stromal and inflammatory cells also contributes to the procoagulant character of the tumour microenvironment. A growing body of genetic and pharmacological evidence implicates signalling by protease activated receptors (PARs) and specifically by tumour cell‐expressed TF‐VIIa‐PAR2 in the induction of an array of proangiogenic and immune modulating cytokines, chemokines and growth factors. Specific inhibition of this pathway results in attenuated tumour growth and angiogenesis. PARs are increasingly recognised as targets for proteases outside the coagulation system and emerging evidence indicates that alternative protease signalling pathways synergise with the coagulation system to promote tumour growth, angiogenesis and metastasis. The elucidation of new therapeutic targets in tumour‐promoting protease signalling pathways requires new diagnostic approaches to identify patients that will benefit from tailored therapy targeting procoagulant or signalling aspects of the TF pathway.

… coagulation cascade leading to an increased risk of cancer-associated thrombosis and venous thrombosis in cancer … their role in cancer metastasis as they bind to tumor cells once they …

The activation of blood coagulation and the thrombotic diathesis of patients with cancer is multifactorial, and the mechanisms include nonspecific factors, tumor-specific activities, and anticancer therapies (that is, chemo-and radiotherapy, and surgery). General mechanisms for clotting activation in malignancy are related to the host response to the tumor and include the acute-phase reactants and necrosis (that is, inflammation), abnormal protein metabolism (that is, paraproteinemia), and hemodynamic disorders (that is, venous stasis). However, a prominent role in the hemostatic system activation in this disease is attributed to tumor-specific, clot-promoting mechanisms, which include a series of prothrombotic properties of tumor cells. Of particular interest are also a number of procoagulant effects triggered by chemotherapy.

Emerging evidence shows a broad spectrum of biological functions of tissue factor (TF). TF classical role in initiating the extrinsic blood coagulation and its direct thrombotic action in close relation to cardiovascular risks have long been established. TF overexpression/hypercoagulability often observed in many clinical conditions certainly expands its role in proinflammation, diabetes, obesity, cardiovascular diseases, angiogenesis, tumor metastasis, wound repairs, embryonic development, cell adhesion/migration, innate immunity, infection, pregnancy loss, and many others. This paper broadly covers seminal observations to discuss TF pathogenic roles in relation to diverse disease development or manifestation. Biochemically, extracellular TF signaling interfaced through protease-activated receptors (PARs) elicits cellular activation and inflammatory responses. TF diverse biological roles are associated with either coagulation-dependent or noncoagulation-mediated actions. Apparently, TF hypercoagulability refuels a coagulation-inflammation-thrombosis circuit in “autocrine” or “paracrine” fashions, which triggers a wide spectrum of pathophysiology. Accordingly, TF suppression, anticoagulation, PAR blockade, or general anti-inflammation offers an array of therapeutical benefits for easing diverse pathological conditions.

… the coagulation impairment. On the other hand, the management of thrombosis and hemorrhages in cancer … This review provides an overview of the hemostatic complications in cancer, …