Coagulation-related Genes Research Articles

Machine Learning-based Framework Develops a Tumor Thrombus Coagulation Signature in Multicenter Cohorts for Renal Cancer.

Background: Renal cell carcinoma (RCC) is frequently accompanied by tumor thrombus in the venous system with an extremely dismal prognosis. The current Tumor Node Metastasis (TNM) stage and Mayo clinical classification do not appropriately identify preference-sensitive treatment. Therefore, there is an urgent need to develop a better ideal model for precision medicine. Methods: In this study, we developed a coagulation tumor thrombus signature for RCC with 10 machine-learning algorithms (101 combinations) based on a novel computational framework using multiple independent cohorts. Results: The established tumor thrombus coagulation-related risk stratification (TTCRRS) signature comprises 10 prognostic coagulation-related genes (CRGs). This signature could predict survival outcomes in public and in-house protein cohorts and showed high performance compared to 129 published signatures. Additionally, the TTCRRS signature was significantly related to some immune landscapes, immunotherapy response, and chemotherapy. Furthermore, we also screened out hub genes, transcription factors, and small compounds based on the TTCRRS signature. Meanwhile, CYP51A1 can regulate the proliferation and migration properties of RCC. Conclusions: The TTCRRS signature can complement the traditional anatomic TNM staging system and Mayo clinical stratification and provide clinicians with more therapeutic options.

Identification of key biomarkers and therapeutic targets in sepsis through coagulation-related gene expression and immune pathway analysis.

Sepsis, characterized by a widespread and dysregulated immune response to infection leading to organ dysfunction, presents significant challenges in diagnosis and treatment. In this study, we investigated 203 coagulation-related genes in sepsis patients to explore their roles in the disease. Through differential gene expression analysis, we identified 20 genes with altered expression patterns. Subsequent correlation analysis, visualized through circos plots and heatmaps, revealed significant relationships among these genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that these genes are involved in immune response activation, coagulation, and immune receptor activity. Disease Ontology (DO) enrichment analysis further linked these genes to autoimmune hemolytic anemia and tumor-related signaling pathways. Additionally, the CIBERSORT analysis highlighted differences in immune cell composition in sepsis patients, revealing an increase in neutrophils and monocytes and a decrease in inactive NK cells, CD8 T cells, and B cells. We employed machine learning techniques, including random forest and SVM, to construct a diagnostic model, identifying FCER1G and FYN as key biomarkers. These biomarkers were validated through their expression levels and ROC curve analysis in an independent validation cohort, demonstrating strong diagnostic potential. Single-cell analysis from the GSE167363 dataset further confirmed the distinct expression profiles of these genes across various cell types, with FCER1G predominantly expressed in monocytes, NK cells, and platelets, and FYN in CD4+ T cells and NK cells. Enrichment analysis via GSEA and ssGSEA revealed that these genes are involved in critical pathways, including intestinal immune networks, fatty acid synthesis, and antigen processing. In conclusion, our comprehensive analysis identifies FCER1G and FYN as promising biomarkers for sepsis, providing valuable insights into the molecular mechanisms of this complex condition. These findings offer new avenues for the development of targeted diagnostic and therapeutic strategies in sepsis management.

Identification of prognostic coagulation-related signatures in clear cell renal cell carcinoma through integrated multi-omics analysis and machine learning

Clear cell renal cell carcinoma is a threat to public health with high morbidity and mortality. Clinical evidence has shown that cancer-associated thrombosis poses significant challenges to treatments, including drug resistance and difficulties in surgical decision-making in ccRCC. However, the coagulation pathway, one of the core mechanisms of cancer-associated thrombosis, recently found closely related to the tumor microenvironment and immune-related pathway, is rarely researched in ccRCC. Therefore, we integrated bulk RNA-seq data, DNA mutation and methylation data, single-cell data, and proteomic data to perform a comprehensive analysis of coagulation-related genes in ccRCC. First, we demonstrated the importance of the coagulation-related gene set by consensus clustering. Based on machine learning, we identified 5 coagulation signature genes and verified their clinical value in TCGA, ICGC, and E-MTAB-1980 databases. It's also demonstrated that the specific expression patterns of coagulation signature genes driven by CNV and methylation were closely correlated with pathways including apoptosis, immune infiltration, angiogenesis, and the construction of extracellular matrix. Moreover, we identified two types of tumor cells in single-cell data by machine learning, and the coagulation signature genes were differentially expressed in two types of tumor cells. Besides, the signature genes were proven to influence immune cells especially the differentiation of T cells. And their protein level was also validated.

Classification and immunotherapy assessment of lung adenocarcinoma based on coagulation-related genes.

Introduction: This study on lung adenocarcinoma (LUAD), a common lung cancer subtype with high mortality. Aims: This study focuses on how tumor cell interactions affect immunotherapy responsiveness. Methods: Using public databases, we used non-negative matrix factorization clustering method, ssGSEA, CIBERSORT algorithm, immunophenotype score, survival analysis, protein-protein interaction network method to analyze gene expression data and coagulation-related genes. Results: We dividedLUAD patients into three coagulation-related subgroups with varying immune characteristics and survival rates. A cluster ofthreepatients, having the highest immune infiltration and survival rate, also showed the most potential for immunotherapy. We identified fivekey genes influencing patient survival using a protein-protein interaction network. Conclusion: This research offers valuable insights for forecasting prognosis and immunotherapy responsiveness in LUAD patients, helping to inform clinical treatment strategies.

Clinical Consequences of Rare Germline Variation in Genes Associated with Coagulation across 451,958 Individuals

Introduction Despite deep biological insights over the preceding decades, our ability to assess for inherited hypercoagulable states remains limited. In light of these challenges and the increasing relevance of precision medicine and next-generation sequencing (NGS) to clinical practice, the identification of rare germline variants in coagulation-focused NGS panels is increasingly becoming accepted practice. However, the discovery of variants of unknown significance (VUS) remains a common clinical conundrum in molecular testing, particularly because evidence for the thrombosis risk associated with many genes derives from small, uncontrolled studies, case reports, and pedigree analysis. Large-scale evaluation of the clinical consequences associated with loss of function in individual coagulation-related genes would contribute to the clinical assessment of patients presenting with heterozygous VUS in poorly characterized genes. Objectives Determine the risk of four thrombosis phenotypes associated with rare, germline loss-of-function variants in a major clinical coagulation-focused NGS panel. Methods The UK Biobank (UKBB) contains paired clinical and whole exome sequencing data for over 450,000 participants. We identified rare (minor allele frequency <0.1%) germline variants that were predicted in silico to alter protein activity (functional impact score ≥0.8) within the 54 evaluable genes of the Yale NGS coagulation panel. For each gene, parallel multivariable Firth's logistic regression models were generated to assess the association between rare qualifying variants and four thrombotic phenotypes as well as coagulopathic bleeding in a gene-level collapsing analysis (N=270 independent models). We adjusted for age, sex, ancestry, and sequencing batch. Phenotypes of interest included venous thromboembolism (VTE), myocardial infarction (MI), stroke (CVA), peripheral artery disease (PAD), and coagulopathic bleeding. The Bonferroni corrected p-value for each phenotype was 0.001. We validated functional impact score predictions in seven secreted proteins measured in a subset of 47,923 UKBB participants who underwent plasma proteomic assessment (Olink Explore 1536 panel). Results A total of 451,958 individuals in the UKBB with whole exome sequencing data were evaluated. Among the 54 genes in the Yale NGS coagulation panel, there were 18,975 qualifying variants (98.4% heterozygous). Function-altering variants in 4 of 54 genes were associated with a statistically significant increased risk of thrombosis after adjusting for multiple comparisons: PROC (OR = 5.7, 95% CI: 3.2 - 9.6, p = 1.6x10 -7), SERPINC1 (OR = 5.0, 95% CI: 2.7 - 8.7, p = 4.0x10 -6), PROS1 (OR = 3.2, 95% CI: 2.0 - 4.8, p = 6.0x10 -6), and STAB2 (OR = 1.4, 95% CI: 1.2 - 1.7, p = 5.3x10 -4) (Figure 1). Nominal significance was achieved for 7 genes in the VTE phenotype, 1 gene in CVA, 3 genes in MI, 5 genes in PAD, and 0 genes in coagulopathic bleeding. Variants in a total of 37 genes did not appear to be significantly associated with any of the evaluated phenotypes. To assess the reliability of variant functional impact scores derived in silico, plasma levels for 13 of the 53 coagulation genes were analyzed. Of these, 8 were identified as secreted proteins amenable to assessment by plasma levels, including ADAMTS13 ( ADAMTS13), factor IX ( F9), factor VII ( F7), tissue plasminogen activator ( PLAT), urokinase ( PLAU), protein C ( PROC), plasminogen activator inhibitor 1 ( SERPINE1), and von Willebrand factor ( VWF). For these proteins, average plasma levels consistently demonstrated a negative correlation with functional impact score (Pearson r = -0.98, P=0.0009), indicating that our in silico assessments in this context are broadly reliable (Figure 2). Conclusion Within the commonly encountered clinical context of heterozygous loss of function, most genes contained in coagulation-focused NGS panels likely have fairly weak effects on disease risk that are limited to venous thrombosis. However, our findings do not rule out the possibility of more profound effects from homozygous or compound heterozygous loss of function in these same genes. By defining the clinical consequence of heterozygous loss of function in specific coagulation-related genes across a large population, our findings may help inform the interpretation of molecular testing results in which patients are found to have a VUS.

Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer

Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn’t been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.

Identification of a coagulation-related signature correlated with immune infiltration and their prognostic implications in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a fatal form of lung cancer with a poor prognosis. Coagulation system had been confirmed closely related to tumor progression and the hypercoagulable state encouraged the immune infiltration and development of tumor cells, leading to a poor prognosis in cancer patients. However, the use of the coagulation-related genes (CRGs) for prognosis in LUAD has yet to be determined. In this study, we constructed an immune-related signature (CRRS) and identified a potential coagulation-related biomarker (P2RX1). We obtained a total of 209 CRGs based on two coagulation-related KEGG pathways, then developed the CRRS signature by using the TCGA-LUAD RNA-seq data via the procedure of LASSO-Cox regression, stepwise-Cox regression, univariate and multivariate Cox regression. Grouped by the CRRS, Kaplan-Meier survival curves and receiver operating characteristic curves were drawn for the training and validation sets, respectively. In addition, single-sample gene set enrichment analysis was exploited to explore immune infiltration level. Moreover, immunophenotypes and immunotherapy grouped by CRRS were further analyzed. We developed an immune-related signature (CRRS) composed of COL1A2, F2, PLAUR, C4BPA, and P2RX1 in LUAD. CRRS was an independent risk factor for overall survival and displayed stable and powerful performance. Additionally, CRRS possessed distinctly superior accuracy than traditional clinical variables and molecular features. Functional analysis indicated that the differentially high expressed genes in the low-risk group significantly enriched in T cell and B cell receptor signaling pathways. The low-risk group was sensitive to anti-PD-1/PD-L1 immunotherapy and displayed abundant immune infiltration and immune checkpoint gene expression. Finally, we identified an independent prognostic gene P2RX1. Low expression of P2RX1 associated with poor overall survival and decreased immune infiltration. Our study revealed a significant correlation between CRRS and immune infiltration. CRRS could serve as a promising tool to improve the clinical outcomes for individual LUAD patients.

A new prognostic model for glioblastoma multiforme based on coagulation-related genes

A new prognostic model for glioblastoma multiforme based on coagulation-related genes

A novel coagulation-related lncRNA predicts the prognosis and immune of clear cell renal cell carcinoma

Renal cell cancer is associated with the coagulation system. Long non-coding RNA (lncRNA) expression is closely associated with the development of clear cell renal cell carcinoma (ccRCC). The aim of this study was to build a novel lncRNA model to predict the prognosis and immunological state of ccRCC. The transcriptomic data and clinical data of ccRCC were retrieved from TCGA database, subsequently, the lasso regression and lambda spectra were used to filter prognostic lncRNAs. ROC curves and the C-index were used to confirm the predictive effectiveness of this model. We also explored the difference in immune infiltration, immune checkpoints, tumor mutation burden (TMB) and drug sensitivity between the high- and low-risk groups. We created an 8 lncRNA model for predicting the outcome of ccRCC. Multivariate Cox regression analysis showed that age, tumor grade, and risk score are independent prognostic factors for ccRCC patients. ROC curve and C-index revealed the model had a good performance in predicting prognosis of ccRCC. GO and KEGG analysis showed that coagulation related genes were related to immune response. In addition, high risk group had greater TMB level and higher immune checkpoints expression. Sorafenib, Imatinib, Pazopanib, and etoposide had higher half maximal inhibitory concentration (IC50) in the high risk group whereas Sunitinib and Bosutinib had lower IC50. This novel coagulation-related long noncoding RNAs model could predict the prognosis of patients with ccRCC, and coagulation-related lncRNA may be connected to the tumor microenvironment and gene mutation of ccRCC.

Docking Complexes of Active Phytochemicals with VK-deficient Genes

Background:: Vitamin K (VK) deficiency occurs when the body does not have enough vitamin K to produce proteins that are essential for blood clotting and bone health. Vitamin K is a cofactor that plays a major role in various comorbidities. Over the years, efforts have been made to identify the interaction between natural compounds, such as K vitamers, that could play a sig-nificant role in regulation of the blood coagulation. We intended to obtain insights into the poten-tial therapeutic implications of phytochemicals for treating VK deficiency-related diseases by in-vestigating the interactions between phytochemicals and VK-deficient genes. Methods:: On active phytochemical docking complexes with VK-deficient genes, there is no spe-cific information available as of yet. In this computationally aided docking study, we were inter-ested in finding the pathogenic blood coagulation-related genes that are linked to VK deficiency. Based on literature reviews and databases, bioactive phytochemicals and other ligands were con-sidered. To provide precise predictions of ligand-protein interactions, docking parameters and scoring algorithms were thoroughly optimized. We have performed molecular docking studies and observed the way the complexes interact. Results:: Specific binding interactions between active phytochemicals and VK pathogenic muta-tions have been identified by the docking study. Hydrogen bonds, van der Waals interactions, and hydrophobic contacts, which are indications of high binding affinities, have been observed in the ligand-protein complexes. Few phytochemicals have demonstrated the ability to interact with the targets of VK-deficient genes, indicating their capacity to modify pathways relevant to VK defi-ciency. The results of the docking study have explained the three pathogenic genes, viz. VWF, F8, and CFTR, wherein VWF and F8 play important roles in blood coagulation and people with cyst-ic fibrosis, to have a deficiency in vitamin K. Thirty-five compounds from different plant and natural sources were screened through molecular docking, out of which two compounds have been considered as controls, including curcumin and warfarin (R-warfarin and S-warfarin), which are the most common anticoagulants readily available in the market. They act by inhibiting vita-min K epoxide reductase (VKOR), which is needed for the gamma-carboxylation of vitamin K-dependent factors. Conclusion:: A focus on other compounds, like theaflavin, ellagic acid, myricetin, and catechin was also made in this study as they show more binding affinity with the three pathogenic proteins. Based on the results, the complexes have been found to possess great potential and thus may be considered for further interaction studies. The potential for active phytochemicals to generate docking complexes with VK-deficient genes is highlighted in this computational analysis. Health disorders related to VK insufficiency may be significantly impacted by these interactions. To val-idate the expected interactions and determine the therapeutic potential of the identified phyto-chemicals, more experimental research, including in vitro and in vivo experiments, is needed.

The coagulation-related genes for prognosis and tumor microenvironment in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a malignancy characterized by challenging early diagnosis and poor prognosis. It is believed that coagulation has an impact on the tumor microenvironment of PDAC. The aim of this study is to further distinguish coagulation-related genes and investigate immune infiltration in PDAC.MethodsWe gathered two subtypes of coagulation-related genes from the KEGG database, and acquired transcriptome sequencing data and clinical information on PDAC from The Cancer Genome Atlas (TCGA) database. Using an unsupervised clustering method, we categorized patients into distinct clusters. We investigated the mutation frequency to explore genomic features and performed enrichment analysis, utilizing Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) to explore pathways. CIBERSORT was used to analyze the relationship between tumor immune infiltration and the two clusters. A prognostic model was created for risk stratification, and a nomogram was established to assist in determining the risk score. The response to immunotherapy was assessed using the IMvigor210 cohort. Finally, PDAC patients were recruited, and experimental samples were collected to validate the infiltration of neutrophils using immunohistochemistry. In addition, and identify the ITGA2 expression and function were identified by analyzing single cell sequencing data.ResultsTwo coagulation-related clusters were established based on the coagulation pathways present in PDAC patients. Functional enrichment analysis revealed different pathways in the two clusters. Approximately 49.4% of PDAC patients experienced DNA mutation in coagulation-related genes. Patients in the two clusters displayed significant differences in terms of immune cell infiltration, immune checkpoint, tumor microenvironment and TMB. We developed a 4-gene prognostic stratified model through LASSO analysis. Based on the risk score, the nomogram can accurately predict the prognosis in PDAC patients. We identified ITGA2 as a hub gene, which linked to poor overall survival (OS) and short disease-free survival (DFS). Single-cell sequencing analysis demonstrated that ITGA2 was expressed by ductal cells in PDAC.ConclusionsOur study demonstrated the correlation between coagulation-related genes and the tumor immune microenvironment. The stratified model can predict the prognosis and calculate the benefits of drug therapy, thus providing the recommendations for clinical personalized treatment.

Integrated analysis to identify the prognostic and immunotherapeutic roles of coagulation-associated gene signature in clear cell renal cell carcinoma.

The coagulation system is closely related to the physiological status and immune response of the body. Recent years, studies focusing on the association between coagulation system abnormalities and tumor progression have been widely reported. In clear cell renal cell carcinoma (ccRCC), poor prognosis often occurs in patients with venous tumor thrombosis and coagulation system abnormalities, and there is a lack of research in related fields. Significant differences in coagulation function were also demonstrated in our clinical sample of patients with high ccRCC stage or grade. Therefore, in this study, we analyzed the biological functions of coagulation-related genes (CRGs) in ccRCC patients using single-cell sequencing and TCGA data to establish the 5-CRGs based diagnostic signature and predictive signature for ccRCC. Univariate and multivariate Cox analyses suggested that prognostic signature could be an independent risk factor. Meanwhile, we applied CRGs for consistent clustering of ccRCC patients, and the two classes showed significant survival and genotype differences. The differences in individualized treatment between the two different subtypes were revealed by pathway enrichment analysis and immune cell infiltration analysis. In summary, we present the first systematic analysis of the significance of CRGs in the diagnosis, prognosis, and individualized treatment of ccRCC patients.

Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated.MethodsFirstly, we identified differentially expressed coagulation-related genes of HCC and control samples in the datasets GSE54236, GSE102079, TCGA-LIHC, and Genecards database. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to determine the key CRGs and establish the coagulation-related risk score (CRRS) prognostic model in the TCGA-LIHC dataset. The predictive capability of the CRRS model was evaluated by Kaplan–Meier survival analysis and ROC analysis. External validation was performed in the ICGC-LIRI-JP dataset. Besides, combining risk score and age, gender, grade, and stage, a nomogram was constructed to quantify the survival probability. We further analyzed the correlation between risk score and functional enrichment, pathway, and tumor immune microenvironment.ResultsWe identified 5 key CRGs (FLVCR1, CENPE, LCAT, CYP2C9, and NQO1) and constructed the CRRS prognostic model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group. The AUC values for 1 -, 3 -, and 5-year OS in the TCGA dataset were 0.769, 0.691, and 0.674, respectively. The Cox analysis showed that CRRS was an independent prognostic factor for HCC. A nomogram established with risk score, age, gender, grade, and stage, has a better prognostic value for HCC patients. In the high-risk group, CD4+T cells memory resting, NK cells activated, and B cells naive were significantly lower. The expression levels of immune checkpoint genes in the high-risk group were generally higher than that in the low-risk group.ConclusionsThe CRRS model has reliable predictive value for the prognosis of HCC patients.

Evaluating the Predictive Value of a Coagulation-Related Gene Model in Glioma.

To evaluate coagulation related gene model as a biomarker for predicting prognosis of gliomas. The mRNA expression and clinical data of glioma were downloaded from the TCGA and CGGA databases. Coagulation-related genes were downloaded from the KEGG database. The expression model was constructed using LASSO regression. The GBM data were divided into high and low-risk expression groups based on the median risk score, and the differences in overall survival and progression-free survival between them were calculated. The prognostic model was further validated using the TCGA-LGG and CGGA glioma databases, respectively. The accuracy of the risk score was calculated by ROC analysis for 1 year and 3 years. Four model genes, namely the SERPINA5, PLAUR, BDKRB1, and PTGIR, were identified, and the risk score was calculated as follows: risk score= SERPINA5*0.126264111304559 + PLAUR*0.288587629696211 + BDKRB1*0.349215422945011 + PTGIR*0.17334527969703, respectively. Based on glioma data from three groups, patients were divided into high and low-risk groups according to the median risk score. The overall survival, progression-free survival, and risk scores of the high-risk score group were worse than the low-risk group. The ROC curve analysis showed that the AUC values of the coagulation-related gene model at 1 year, 3 years, and 5 years were more than 0.65, validating the reliability of the prognostic model. This study established the correlation between the coagulation-related gene model and glioma prognosis, providing deeper insight into the mechanism and treatment of glioma.

Peripheral blood mononuclear cell tissue factor (F3 gene) transcript levels and circulating extracellular vesicles are elevated in severe coronavirus 2019 (COVID-19) disease

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with excessive coagulation, thrombosis, and mortality. ObjectiveTo provide insight into mechanisms that contribute to excessive coagulation in coronavirus 2019 (COVID-19) disease. Patients/MethodsBlood from COVID-19 patients was investigated for coagulation–related gene expression and functional activities. ResultsSingle-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells from severe COVID-19 patients revealed a 5.2-fold increase in tissue factor (TF [F3 gene]) transcript expression levels (P < .05), the trigger of extrinsic coagulation; a 7.7-fold increase in C1-inhibitor (SERPING1 gene; P < .01) transcript expression levels, an inhibitor of intrinsic coagulation; and a 4.4-fold increase in anticoagulant thrombomodulin (TM [THBD gene]) transcript expression levels (P < .001). Bulk RNA-seq analysis of sorted CD14+ monocytes on an independent cohort of COVID-19 patients confirmed these findings (P < .05). Indicative of excessive coagulation, 41% of COVID-19 patients’ plasma samples contained high D-dimer levels (P < .0001); of these, 19% demonstrated extracellular vesicle TF activity (P = .109). COVID-19 patients’ ex vivo plasma–based thrombin generation correlated positively with D-dimer levels (P < .01). Plasma procoagulant extracellular vesicles were elevated ∼9-fold in COVID-19 patients (P < .01). Public scRNA-seq data sets from bronchoalveolar lung fluid and our peripheral blood mononuclear cell scRNA-seq data show CD14+ monocytes/macrophages TF transcript expression levels are elevated in severe but not mild or moderate COVID-19 patients. ConclusionsBeyond local lung injury, SARS-CoV-2 infection increases systemic TF (F3) transcript levels and elevates circulating extracellular vesicles that likely contribute to disease-associated coagulation, thrombosis, and related mortality.

Children with Acute Lymphoblastic Leukemia and Early Thrombosis Have Dysregulated Coagulation-Related Genes and Pathways

Introduction Thrombo-embolic events (TE) are a frequent complication of childhood acute lymphoblastic leukemia (ALL). Disease-specific mechanistic insights governing the development of TE in this disease remain unclear. Overexpression of coagulation-related genes (coagulome) and pathways have been identified in cancer-induced TE. We investigate whether coagulome dysregulation in newly-diagnosed children with ALL is associated with TE development. Methods We included patients aged 1-21 years old with newly-diagnosed ALL from September 3, 2015, to June 30, 2021, with available RNA-sequencing (RNAseq) data at diagnosis, either enrolled on the Dana-Farber Cancer Institute (DFCI) ALL Consortium Protocol 16-001 or treated following the DFCI 11-001 protocol. RNAseq was performed through an optional study performed as part of the DFCI 16-001 clinical trial for patients who consented to it, or through the research oncogenomic program of the province of Quebec. The primary outcome was the occurrence of TE during ALL therapy requiring medical intervention (grade ≥2 as per the CTCAE version 5). TE were classified as early thrombosis (ET) if they occurred within 6 weeks from treatment start. Patients' characteristics were compared using Chi-Square or Fisher's exact test. Differential gene expression (DE) was performed to compare children with and without TE, adjusted for ALL phenotype (B- or T-cell lineage). The dysregulated genes were compared to a customized panel of 174 genes known to be implicated in cancer-related TE (coagulome and podoplanin) and in coagulation pathways. A secondary analysis, determined a priori, stratified children between ET and no TE, based on the hypothesis that the leukemia environment might predominantly affect early complications. Gene set enrichment analyses (GSEA) were performed on KEGG and gene ontology (GO) databases from the molecular signatures database (MSigDB). DE was considered for absolute fold change (FC) ≥2, and benjamini-Hochberg adjusted p-values (adj p) <0.05. Results We included 274 ALL patients (median age: 6.7 years [interquartile range, IQR: 3.7-12.0 years], 54% male, 81% B-ALL) of whom 49 (17.9%) experienced a TE (including 21 ET) at a median of 76 days (IQR: 27-155 days) following ALL diagnosis. Patients with TE were more likely to be ≥10 years old (57.1% vs. 31.6%, p<0.001) compared to those without TE. Sex, immunophenotype, mediastinal mass, central nervous system disease (CNS) involvement at diagnosis and risk status were otherwise not significantly different among the two groups. Three coagulation pathway-related genes were dysregulated in children with TE compared to those without TE. Glycoprotein 9 (GP9) and platelet factor 4 (PF4), implicated in von Willebrand-dependent platelet adhesion and platelet aggregation, were upregulated (log2FC = 2.1 and 1.5, respectively). Metalloproteinase-2 (MMP2), involved in collagenolysis and thrombus degradation, was downregulated (log2FC = -1.9). The KEGG olfactory transduction pathway was downregulated in the group with TE (normalized enrichment score (NES) = 1.55, adj p<0.001). In the secondary analysis stratified by timing of TE, patients with early TE were more likely to be ≥10 years (80.9% vs. 31.6%, p<0.001), have T-ALL (38.1% vs. 16.9%, p=0.002) and be CNS-positive at diagnosis (52.4% vs. 22.7%, p=0.004). Patients with ET showed overexpression of the GP9, PF4, integrin subunit beta 3 (ITGB3) and clusterin (CLU) genes involved in platelet aggregation and adhesion (log2FC = 3.3, 3.7, 2.7 and 1.6, respectively). The following GO pathways were significantly upregulated: blood coagulation (NES=1.73, adj p<0.001), platelet activation (NES=2.21, adj p<0.01), and platelet alpha granules (NES=2.48, adj p<0.001) while the KEGG olfactory transduction pathway was downregulated (NES=-1.70, adj p<0.001). Dysregulation of the olfactory transduction pathway has previously been described in cancer-associated TE in adults. Conclusion Our study identified coagulation-related genes and pathways that might be drivers of leukemia-induced thrombosis. Early TEs in childhood ALL were associated with significant upregulation of coagulation and platelet activation pathways, suggesting a role of the leukemia microenvironment in TE development. Additional studies are required to validate these observations that could be incorporated in future algorithms to predict TE risk in children with ALL. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Construction and validation of a novel coagulation-related 7-gene prognostic signature for gastric cancer.

Background: Gastric cancer (GC) is the most common malignant tumor. Due to the lack of practical molecular markers, the prognosis of patients with advanced gastric cancer is still poor. A number of studies have confirmed that the coagulation system is closely related to tumor progression. Therefore, the purpose of this study was to construct a coagulation-related gene signature and prognostic model for GC by bioinformatics methods. Methods: We downloaded the gene expression and clinical data of GC patients from the TCGA and GEO databases. In total, 216 coagulation-related genes (CRGs) were obtained from AmiGO 2. Weighted gene co-expression network analysis (WGCNA) was used to identify coagulation-related genes associated with the clinical features of GC. Last absolute shrinkage and selection operator (LASSO) Cox regression was utilized to shrink the relevant predictors of the coagulation system, and a Coag-Score prognostic model was constructed based on the coefficients. According to this risk model, GC patients were divided into high-risk and low-risk groups, and overall survival (OS) curves and receiver operating characteristic (ROC) curves were drawn in the training and validation sets, respectively. We also constructed nomograms for predicting 1-, 2-, and 3-year survival in GC patients. Single-sample gene set enrichment analysis (ssGSEA) was exploited to explore immune cells’ underlying mechanisms and correlations. The expression levels of coagulation-related genes were verified by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). Results: We identified seven CRGs employed to construct a Coag-Score risk model using WGCNA combined with LASSO regression. In both training and validation sets, GC patients in the high-risk group had worse OS than those in the low-risk group, and Coag-Score was identified as an independent predictor of OS, and the nomogram provided a quantitative method to predict the 1-, 2-, and 3-year survival rates of GC patients. Functional analysis showed that Coag-Score was mainly related to the MAPK signaling pathway, complement and coagulation cascades, angiogenesis, epithelial–mesenchymal transition (EMT), and KRAS signaling pathway. In addition, the high-risk group had a significantly higher infiltration enrichment score and was positively associated with immune checkpoint gene expression. Conclusion: Coagulation-related gene models provide new insights and targets for the diagnosis, prognosis prediction, and treatment management of GC patients.

Characterization of coagulation-related gene signature to predict prognosis and tumor immune microenvironment in skin cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is an extremely metastatic form of skin cancer. However, there are few valuable molecular biomarkers, and accurate diagnosis is still a challenge. Hypercoagulable state encourages the infiltration and development of tumor cells and is significantly associated with poor prognosis in cancer patients. However, the use of a coagulation-related gene (CRG) signature for prognosis in SKCM, on the other hand, has yet to be determined. We used data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases to identify differentially expressed CRGs, then designed a prognostic model by using the LASSO algorithm, univariate and multivariate Cox regression analysis, and constructed a nomogram which was evaluated by calibrationcurves. Moreover, the Gene Expression Omnibus (GEO), GSE54467 was used as an independent validation. The correlation between risk score and clinicopathological characteristics, tumor microenvironment (TME), and immunotherapy was further analyzed. To develop a prognostic model, seven CRGs in SKCM patients related to overall survival (OS) were selected: ANG, C1QA, CFB, DUSP6, KLKB1, MMP7, and RABIF. According to the Kaplan-Meier survival analysis, an increased OS was observed in the low-risk group than in the high-risk group (P<0.05). Immunotherapy was much more beneficial in the low-risk group, as per immune infiltration, functional enrichment, and immunotherapy analysis. The prognosis of SKCM patients may now be predicted with the use of a CRG prognostic model, thus guiding the development of treatment plans for SKCM patients and promoting OS rates.

Suppression of Inflammatory Cytokine Genes Expression in Vascular Endothelial Cells by Super-low Dose Lipopolysaccharide-activated Macrophages.

Vascular endothelial cells play an important role in regulating immune responses and in keeping the balance between blood coagulation and fibrinolysis. Inflammatory cytokines produced by activated macrophages and vascular endothelial cells excessively activate vascular endothelial cells, leading to an imbalance in the expression of blood coagulation- and fibrinolysis-related factors. The dysfunction of vascular endothelial cells can lead to development of various diseases. In a previous study the increased expression of inflammatory cytokines in adipocytes was shown to be suppressed by the culture medium of macrophages activated by low-dose lipopolysaccharide (LPS). Suppressing inflammatory cytokine gene expression of low-dose LPS-activated macrophages may allow for the regulation of the dysfunction in vascular endothelial cells. Human monocytes THP-1 cells were differentiated into macrophages with phorbol 12-myristate 13-acetate (PMA) and were activated with LPS. The culture medium of the LPS-activated THP-1 was added to human aortic endothelial cells (HAoEC). After five days, the expression of inflammatory cytokine genes interleukin (IL)1B, IL6, IL8, and tumor necrosis factor (TNF)A, blood coagulation-related genes SERPINE1, tissue factor (TF), and thrombopoietin (TM), and fibrinolysis-related gene tissue-type plasminogen activator (t-PA) was analyzed using quantitative real-time PCR. IL1B, IL8, SERPINE1, TF, and TM expression in HAoEC was significantly reduced in the culture medium of super-low dose (0.1 ng/ml) LPS-activated macrophages. Super-low dose LPS-activated macrophages can suppress vascular endothelial cell inflammation and may be useful in preventing various diseases caused by the dysfunction of activated vascular endothelial cells.

Immune infiltration and clinical significance analyses of the coagulation-related genes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common types of cancers and a global health challenge with a low early diagnosis rate and high mortality. The coagulation cascade plays an important role in the tumor immune microenvironment (TME) of HCC. In this study, based on the coagulation pathways collected from the KEGG database, two coagulation-related subtypes were distinguished in HCC patients. We demonstrated the distinct differences in immune characteristics and prognostic stratification between two coagulation-related subtypes. A coagulation-related risk score prognostic model was developed in the Cancer Genome Atlas (TCGA) cohort for risk stratification and prognosis prediction. The predictive values of the coagulation-related risk score in prognosis and immunotherapy were also verified in the TCGA and International Cancer Genome Consortium cohorts. A nomogram was also established to facilitate the clinical use of this risk score and verified its effectiveness using different approaches. Based on these results, we can conclude that there is an obvious correlation between the coagulation and the TME in HCC, and the risk score could serve as a robust prognostic biomarker, provide therapeutic benefits for chemotherapy and immunotherapy and may be helpful for clinical decision making in HCC patients.