Decreasing Tumor Growth and Angiogenesis by Inhibition of Coagulation

Nadir, Yona

doi:10.1055/s-0039-1693473

Cited by 13 publications

(10 citation statements)

References 64 publications

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“…Thrombin regulates multiple processes of cancer spread such as: invasion, migration, access to blood vessels, survival in the lymphatic system and promoting tumor growth [63]. By using a heparin derivative and heparanase inhibitor prothrombin inhibitory mechanism, tumor growth and neovascularization can be inhibited [64]. In our research center, the higher expression of the F2 low expression group was signi cantly improved.…”

Section: Discussionmentioning

confidence: 80%

Uncovering the Mechanism of Shenlian Capsules in the Treatment of Non-small Cell Lung Cancer by System Pharmacology

Gong

Wei

et al. 2020

Preprint

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Background: Shenlian Capsule is a Chinese medicine compound approved by the China Food and Drug Administration (CFDA) for the treatment of advanced non-small cell lung cancer(NSCLC). However, due to its complex constituents, cause its effective active compounds and main action mechanisms for treating diseases are still not fully clear. The purpose of this work is to explore the active ingredients and mechanisms of Shenlian Capsule treatment NSCLC through a system pharmacological approach. Methods: First, a database of Shenlian Capsule chemical composition was constructed by retrieving Chinese herbal medicine data. Absorption, distribution, metabolism and excretion (ADME) methods were used to screen potential active compounds. Predict active compound targets with a large-scale molecular network target prediction technology. Clustering of active compounds obtained through cluster analysis by MECODE plug-in, each cluster obtains the main pathways through enrichment analysis method. To get all targets related to survival in NSCLC, the survival related targets were intersected with the compounds target (C-T) network to get the survival related targets for Shenlian Capsule. Finally, a batch molecular docking technique was used to verify the effect of active compounds of Shenlian Capsule on survival-related targets.Results: The Shenlian Capsule C-T network was constructed with 117 potential compounds and 47 targets. Treatment of NSCLC with Shenlian Capsule through enrichment analysis may involve multiple pathways such as anti-inflammatory, immune regulation, regulation of cell cycle, apoptosis, antiviral, cell hypoxia, angiogenesis and so on. Shenlian Capsule has eight survival-related genes in non-small cell lung adenocarcinoma (LUAD) and two survival-related genes in non-small cell squamous cell lung carcinoma (LUSC). It is known through molecular docking that the active compound has lower energy after conformation with survival-related genes, and has lower binding energy and stable binding.Conclusion: In this study, the potential compounds of active compounds in Shenlian Capsule were first predicted using network pharmacology technology. Through the enrichment analysis, the main pathways of the role of Shenlian Capsule were outcropped. Secondly, by combining bioinformatics and network pharmacology, Shenlian Capsule can be regulated to target survival-related targets. Finally, the molecular docking technique shows the relationship between active compounds and survival-related targets after docking. This work provided a scientific basis for the clinical role of Shenlian Capsule in the treatment of NSCLC, provided a research basis for further clarifying the active ingredients and mechanism of Shenlian Capsule in the treatment of NSCLC.

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Section: Discussionmentioning

confidence: 80%

Uncovering the Mechanism of Shenlian Capsules in the Treatment of Non-small Cell Lung Cancer by System Pharmacology

Gong

Wei

et al. 2020

Preprint

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“…In skin diseases, the promoted angiogenesis and lymphatic vessel enlargement were a response to ultraviolet (UV; Okazaki et al, 2012 ). Moreover, angiogenesis was decreased by inhibiting coagulation ( Nadir, 2019 ). EMT also promotes basal mammary stem cell and tumor-initiating cell stemness by inducing hedgehog signaling ( Guen et al, 2017 ).…”

Section: Resultsmentioning

confidence: 99%

A Coagulation-Related Gene-Based Prognostic Model for Invasive Ductal Carcinoma

Wang

et al. 2021

Front. Genet.

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Background: Invasive ductal carcinoma (IDC) is the most common type of metastatic breast cancer. Due to the lack of valuable molecular biomarkers, the diagnosis and prognosis of IDC remain a challenge. A large number of studies have confirmed that coagulation is positively correlated with angiogenesis-related factors in metastatic breast cancer. Therefore, the purpose of this study was to construct a COAGULATION-related genes signature for IDC using the bioinformatics approaches.Methods: The 50 hallmark gene sets were obtained from the molecular signature database (MsigDB) to conduct Gene Set Variation Analysis (GSVA). Gene Set Enrichment Analysis (GSEA) was applied to analyze the enrichment of HALLMARK_COAGULATION. The COAGULATION-related genes were extracted from the gene set. Then, Limma Package was used to identify the differentially expressed COAGULATION-related genes (DECGs) between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) samples in GSE26340 data set. A total of 740 IDC samples from The Cancer Genome Atlas (TCGA) database were divided into a training set and a validation set (7:3). The univariate and multivariate Cox regression analyses were performed to construct a risk signature, which divided the IDC samples into the high- and low-risk groups. The overall survival (OS) curve and receiver operating characteristic (ROC) curve were drawn in both training set and validation set. Finally, a nomogram was constructed to predict the 1-, 2-, 3-, 4-, and 5-year survival rates of IDC patients. Quantitative real-time fluorescence PCR (qRT-PCR) was performed to verify the expression levels of the prognostic genes.Results: The “HALLMARK_COAGULATION” was significantly activated in IDC. There was a significant difference in the clinicopathological parameters between the DCIS and IDC patients. Twenty-four DECGs were identified, of which five genes (SERPINA1, CAPN2, HMGCS2, MMP7, and PLAT) were screened to construct the prognostic model. The high-risk group showed a significantly lower survival rate than the low-risk group both in the training set and validation set (p=3.5943e-06 and p=0.014243). The risk score was demonstrated to be an independent predictor of IDC prognosis. A nomogram including risk score, pathological_stage, and pathological_N provided a quantitative method to predict the survival probability of 1-, 2-, 3-, 4-, and 5-year in IDC patients. The results of decision curve analysis (DCA) further demonstrated that the nomogram had a high potential for clinical utility.Conclusion: This study established a COAGULATION-related gene signature and showed its prognostic value in IDC through a comprehensive bioinformatics analysis, which may provide a potential new prognostic mean for patients with IDC.

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“…The change in coagulation function plays a vital role in the invasion and metastasis of tumor cells [14]. The research on inhibiting the coagulation system to reduce tumor growth and metastasis has attracted much attention [15]. However, little attention has been paid to the relationship between coagulation and prognosis, immune microenvironment of HCC.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2023

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Background Hepatocellular 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. Methods Firstly, 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. Results We 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. Conclusions The CRRS model has reliable predictive value for the prognosis of HCC patients.

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Decreasing Tumor Growth and Angiogenesis by Inhibition of Coagulation

Cited by 13 publications

References 64 publications

Uncovering the Mechanism of Shenlian Capsules in the Treatment of Non-small Cell Lung Cancer by System Pharmacology

Uncovering the Mechanism of Shenlian Capsules in the Treatment of Non-small Cell Lung Cancer by System Pharmacology

A Coagulation-Related Gene-Based Prognostic Model for Invasive Ductal Carcinoma

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

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