Clinical significance and biological mechanisms of glutathione S-transferase mu gene family in colon adenocarcinoma

Abstract Background Colon adenocarcinoma (COAD) is the most common form of colon cancer. The glutathione S-transferase Mu (GSTM) gene belongs to the GST gene family, which functions in cell metabolism and detoxification. The relationship between GSTM and COAD and the underlying mechanism remain unknown. Methods Data extracted from The Cancer Genome Atlas included mRNA expression and clinical information such as gender, age, and tumor stage. Prognostic values of GSTM genes were identified by survival analysis. Function and mechanism of prognostic GSTM genes were identified by gene set enrichment analysis. A nomogram was used to predict the contribution of risk factors to the outcome of COAD patients. Results Low expression of GSTM1 and GSTM2 was related to favorable OS (adjusted P = 0.006, adjusted HR = 0.559, 95% CI = 0.367–0.849 and adjusted P = 0.002, adjusted HR = 0.519, 95% CI = 0.342–0.790, respectively) after adjusting for tumor stage. Enrichment analysis also showed that genes involved were related to cell cycle, metabolism, and detoxification processes, as well as the Wnt signaling and NF-κB pathways. Conclusions In conclusion, low expression of GSTM1 and GSTM2 were significantly associated with favorable prognosis in COAD. These two genes may serve as potential biomarkers of COAD prognosis.

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Downregulated ARID1A by miR-185 Is Associated With Poor Prognosis and Adverse Outcomes in Colon Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.679334 ◽

2021 ◽

Vol 11 ◽

Author(s):

Salem Baldi ◽

Hassan Khamgan ◽

Yuanyuan Qian ◽

Han Wu ◽

Zhenyu Zhang ◽

...

Keyword(s):

Cell Line ◽

Survival Curve ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Adverse Outcomes ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Interaction Domain ◽

Molecular Features ◽

Low Expression

AT-rich interaction domain 1A (ARID1A) is a tumor suppressor gene that mutates in several cancer types, including breast cancer, ovarian cancer, and colorectal cancer (CRC). In colon adenocarcinoma (COAD), the low expression of ARID1A was reported but the molecular reason is unclear. We noticed that ARID1A low expression was associated with increased levels of miR-185 in the COAD. Therefore, this study aims to explore ncRNA-dependent mechanism that regulates ARID1A expression in COAD regarding miR-185. The expression of ARID1A was tested in COAD cell line under the effect of miR-185 mimics compared with inhibitor. The molecular features associated with loss of ARID1A and its association with tumor prognosis were analyzed using multi-platform data from The Cancer Genome Atlas (TCGA), and gene set enrichment analysis (GSEA) to identify potential signaling pathways associated with ARID1A alterations in colon cancer. Kaplan-Meier survival curve showed that a low level of ARID1A was closely related to low survival rate in patients with COAD. Results showed that inhibiting miR-185 expression in the COAD cell line significantly restored the expression of ARID1A. Further, the increased expression of ARID1A significantly improved the prolonged overall survival of COAD. We noticed that there is a possible relationship between ARID1A high expression and tumor microenvironment infiltrating immune cells. Furthermore, the increase of ARID1A in tumor cells enhanced the response of inflammatory chemokines. In conclusion, this study demonstrates that ARID1A is a direct target of miR-185 in COAD that regulates the immune modulations in the microenvironment of COAD.

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Immunoglobulin superfamily member 10 is a novel prognostic biomarker for breast cancer

PeerJ ◽

10.7717/peerj.10128 ◽

2020 ◽

Vol 8 ◽

pp. e10128

Author(s):

Mengxue Wang ◽

Meng Dai ◽

Yu-shen Wu ◽

Ziying Yi ◽

Yunhai Li ◽

...

Keyword(s):

Breast Cancer ◽

Quantitative Polymerase Chain Reaction ◽

Enrichment Analysis ◽

Clinical Information ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Immunoglobulin Superfamily ◽

Qrt Pcr ◽

Mtorc1 Signaling

Background Immunoglobulin superfamily member 10 (IGSF10) is a member of the immunoglobulin superfamily that is expressed at high levels in both the gallbladder and ovary. Currently, the role and possible mechanism of IGSF10 in breast cancer remain unclear. Method By applying real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), the expression of IGSF10 in breast cancer cells and tissues was detected. We collected the clinical information from 700 patients with breast cancer in The Cancer Genome Atlas (TCGA), and analyzed the relationship between IGSF10 expression and the clinicopathological features and survival outcomes of these patients. The potential mechanisms and pathways associated with IGSF10 in breast cancer were explored by performing a gene set enrichment analysis (GSEA). Results According to TCGA data, qRT-PCR and IHC experiments, levels of the IGSF10 mRNA and protein were significantly decreased in breast cancer tissues. IGSF10 expression was significantly correlated with age, tumor size, and tumor stage. Moreover, shorter overall survival (OS) and relapse-free survival (RFS) correlated with lower IGSF10 expression, according to the survival analysis. The multivariate analysis identified that IGSF10 as an independent prognostic factor for the OS (hazard ratio (HR) = 1.793, 95% confidence interval (CI) [1.141–2.815], P = 0.011) and RFS (HR = 2.298, 95% CI [1.317–4.010], P = 0.003) of patients with breast cancer. Based on the GSEA, IGSF10 was involved in DNA repair, cell cycle, and glycolysis. IGSF10 was also associated with the PI3K/Akt/mTOR and mTORC1 signaling pathways. Conclusions This study revealed a clear relationship between IGSF10 expression and the tumorigenesis of breast cancer for the first time. Therefore, further studies are needed to understand the mechanism of IGSF10 in breast cancer.

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Integrative Analysis of Pinin as A Prognostic Factor in Digestive Tract Cancers

10.21203/rs.3.rs-705965/v1 ◽

2021 ◽

Author(s):

Hui Zhang ◽

Ming Jin ◽

Meng Ye ◽

Yanping Bei ◽

Shaohui Yang ◽

...

Keyword(s):

Prognostic Factor ◽

Digestive Tract ◽

Methylation Status ◽

Rectal Adenocarcinoma ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Clinical Information ◽

Independent Prognostic Factor ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas

Abstract Background: Pinin (PNN) was originally identified for acting an essential role in epithelial cell-cell adhesion. We aim to illuminate the expression profile, mutation feature, methylation status of PNN and its prognostic value in digestive tract cancers. Methods: Expression and methylation data of PNN, as well as clinical information on esophagus cancer (ESCA), gastric adenocarcinoma (STAD), colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) were acquired from The Cancer Genome Atlas database. The value of PNN expression, mutation feature and methylation status in prognosis were assessed. GO enrichment and Gene set enrichment analysis were performed to investigate the enriched biological functions and pathways of PNN in COAD. Tumor Immune Estimation Resource and CIBERSORT were applied for evaluating the effects of PNN on tumor immune infiltrating cells. Results: PNN was significantly overexpressed in digestive tract cancers and was remarkably related to tumor stage. Highly expressed of PNN was positively related to poor free survival (PFS) and overall survival (OS) in COAD. Additionally, 10 CpG sites methylation in PNN had significant effects on survival. PNN expression was confirmed as an independent prognostic factor for predicting the OS in COAD. GO and GSEA analyses revealed that PNN participates in multiple biological processes underlying carcinogenicity in COAD. PNN was significantly associated with TIICs. Moreover, a promising prognostic nomogram incorporating the PNN expression and clinicopathological characteristics was established for predicting OS probability in COAD. Conclusions: Our comprehensive bioinformatics study demonstrated that PNN was highly expressed in digestive tract cancers, which could act as an independent prognostic factor for COAD.

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Mining novel cell glycolysis related gene markers that can predict the survival of colon adenocarcinoma patients

Bioscience Reports ◽

10.1042/bsr20201427 ◽

2020 ◽

Vol 40 (8) ◽

Author(s):

Sihan Chen ◽

Guodong Cao ◽

Wei Wu ◽

Yida Lu ◽

Xiaobo He ◽

...

Keyword(s):

Cox Regression ◽

Mechanistic Model ◽

Single Gene ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Risk Scores ◽

Gene Markers ◽

Cox Regression Analysis

Abstract Colon adenocarcinoma (COAD) is a malignant gastrointestinal tumor, often occurring in the left colon, which is regulated by glycolysis-related processes. In past studies, multiple genes that influence the prognosis for survival have been discovered through bioinformatics analysis. However, the prediction of disease prognosis using a single gene is not an accurate method. In the present study, a mechanistic model was established to achieve better prediction for the prognosis of COAD. COAD-related data downloaded from The Cancer Genome Atlas (TCGA) were correlated with the glycolysis process using gene set enrichment analysis (GSEA) to determine the glycolysis-related genes that regulate COAD. Using COX regression analysis, glycolysis-related genes associated with the prognosis of COAD were identified, and the genes screened to establish a predictive model. The risk scores of this model were correlated with relevant clinical data to obtain a connection diagram between the model and survival rate, tumor characteristic data, etc. Finally, genes in the model were correlated with cells in the tumor microenvironment, finding that they affected specific immune cells in the model. Seven genes related to glycolysis were identified (PPARGC1A, DLAT, 6PC2, P4HA1, STC2, ANKZF1, and GPC1), which affect the prognosis of patients with COAD and constitute the model for prediction of survival of COAD patients.

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Enolase 1 Correlated With Cancer Progression and Immune-Infiltrating in Multiple Cancer Types: A Pan-Cancer Analysis

Frontiers in Oncology ◽

10.3389/fonc.2020.593706 ◽

2021 ◽

Vol 10 ◽

Author(s):

Wenhua Xu ◽

Wenna Yang ◽

Chunfeng Wu ◽

Xiaocong Ma ◽

Haoyu Li ◽

...

Keyword(s):

Cancer Progression ◽

Stress Protein ◽

Enrichment Analysis ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Clinical Prognosis ◽

Multiple Tumor ◽

Normal Tissues

Enolase 1 (ENO1) is an oxidative stress protein expressed in endothelial cells. This study aimed to investigate the correlation of ENO1 with prognosis, tumor stage, and levels of tumor-infiltrating immune cells in multiple cancers. ENO1 expression and its influence on tumor stage and clinical prognosis were analyzed by UCSC Xena browser, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and GTEx Portal. The ENO1 mutation analysis was performed by cBio Portal, and demonstrated ENO1 mutation (1.8%) did not impact on tumor prognosis. The relationship between ENO1 expression and tumor immunity was analyzed by Tumor Immune Estimation Resource (TIMER) and GEPIA. The potential functions of ENO1 in pathways were investigated by Gene Set Enrichment Analysis. ENO1 expression was significantly different in tumor and corresponding normal tissues. ENO1 expression in multiple tumor tissues correlated with prognosis and stage. ENO1 showed correlation with immune infiltrates including B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells, and tumor purity. ENO1 was proved to be involved in DNA replication, cell cycle, apoptosis, glycolysis process, and other processes. These findings indicate that ENO1 is a potential prognostic biomarker that correlates with cancer progression immune infiltration.

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Expression Profile and Prognostic Values of SMC Family Members in HCC

10.21203/rs.3.rs-635749/v1 ◽

2021 ◽

Author(s):

Wei Yan ◽

Dan-dan Wang ◽

He-da Zhang ◽

Jinny Huang ◽

Jun-Chen Hou ◽

...

Keyword(s):

Gene Family ◽

Expression Profile ◽

Proportional Hazards ◽

Wide Spectrum ◽

Clinical Stage ◽

Family Members ◽

Enrichment Analysis ◽

Cox Proportional Hazards ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas

Abstract Background: The structural maintenance of chromosome (SMC) gene family, comprising 6 members, is involved in a wide spectrum of biological functions in many types of human cancers. However, there is little research on the expression profile and prognostic values of SMC genes in hepatocellular carcinoma (HCC). Based on updated public resources and integrative bioinformatics analysis, we tried to determine the value of SMC gene expression in predicting the risk of developing HCC. Methods and materials: The expression data of SMC family members were obtained from The Cancer Genome Atlas (TCGA). The prognostic values of SMC members and clinical features were identified. A gene set enrichment analysis (GSEA) was conducted to explore the mechanism underlying the involvement of SMC members in liver cancer. The associations between tumor immune infiltrating cells (TIICs) and the SMC family members were evaluated using the Tumor Immune Estimation Resource (TIMER) database. Results: Our analysis demonstrated that mRNA downregulation of SMC genes was common alteration in HCC patients. SMC1A, SMC2, SMC3, SMC4, SMC6 were upregulated in HCC. Upregulation of SMC2, SMC3 and SMC4, along with clinical stage, were associated with a poor HCC prognosis based on the results of univariate and multivariate Cox proportional hazards regression analyses. SMC2, SMC3 and SMC4 are also related to tumor purity and immune infiltration levels of HCC. The GSEA results indicated that SMC members participate in multiple biological processes underlying tumorigenesis. Conclusion: This study comprehensively analyzed the expression of SMC gene family members in patients with HCC. This can provide insights for further investigation of the SMC family members as potential targets in HCC and suggest that the use of SMC inhibitor targeting SMC2, SMC3 and SMC4 may be an effective strategy for HCC therapy.

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An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

Bioscience Reports ◽

10.1042/bsr20204442 ◽

2021 ◽

Vol 41 (4) ◽

Author(s):

Dengliang Lei ◽

Yue Chen ◽

Yang Zhou ◽

Gangli Hu ◽

Fang Luo

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Cancer ◽

Long Noncoding Rna ◽

Noncoding Rna ◽

Enrichment Analysis ◽

Clinical Information ◽

Roc Curves ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Highly Correlated

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers worldwide. Neovascularization is closely related to the malignancy of tumors. We constructed a signature of angiogenesis-related long noncoding RNA (lncRNA) to predict the prognosis of patients with HCC. The lncRNA expression matrix of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA). First, gene set enrichment analysis (GSEA) was used to distinguish the differentially expressed genes of the angiogenesis genes in liver cancer and adjacent tissues. Next, a signature of angiogenesis-related lncRNAs was constructed using univariate and multivariate analyses, and receiver operating characteristic (ROC) curves were used to assess the accuracy. The signature and relevant clinical information were used to construct the nomogram. A 5-lncRNA signature was highly correlated with overall survival (OS) in HCC patients and performed well in evaluations using the C-index, areas under the curve, and calibration curves. In summary, the 5-lncRNA model can serve as an accurate signature to predict the prognosis of patients with liver cancer, but its mechanism of action must be further elucidated by experiments.

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TRPV4 is a Prognostic Biomarker That Correlates With the Immunosuppressive Microenvironment and Chemoresistance of Anti-Cancer Drugs

10.21203/rs.3.rs-383566/v1 ◽

2021 ◽

Author(s):

kai wang ◽

Jun xing Feng ◽

Zhi ling Zheng ◽

Ying ze Chai ◽

Hui jun Yu ◽

...

Keyword(s):

Ovarian Cancer ◽

Transient Receptor Potential ◽

Immune Cell ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Receptor Potential ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Free Interval ◽

Pan Cancer

Abstract Background: Transient receptor potential cation channel subfamily V member 4 (TRPV4) has been reported to regulate tumor progression in many tumor types. However, its association with the tumor immune microenvironment remains unclear.Methods: TRPV4 expression was assessed using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. The clinical features and prognostic roles of TRPV4 were assessed using TCGA cohort. Gene set enrichment analysis (GSEA) of TRPV4 was conducted using the R package clusterProfiler. We analyzed the association between TRPV4 and immune cell infiltration scores of TCGA samples downloaded from published articles and the TIMER2 database.Results: TRPV4 was highly expressed and associated with worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in colon adenocarcinoma (COAD) and ovarian cancer. Furthermore, TRPV4 expression was closely associated with immune regulation-related pathways. Moreover, tumor-associated macrophage (TAM) infiltration levels were positively correlated with TRPV4 expression in TCGA pan-cancer samples. Immunosuppressive genes such as PD-L1, PD-1, CTLA4, LAG3, TIGIT, TGFB1, and TGFBR1 were positively correlated with TRPV4 expression in most tumors.Conclusions: Our results suggest that TRPV4 is an oncogene and a prognostic marker in COAD and ovarian cancer. High TRPV4 expression is associated with tumor immunosuppressive status and may contribute to TAM infiltration based on TCGA data from pan-cancer samples.

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Evaluation of FGFR1 as a diagnostic biomarker for ovarian cancer using TCGA and GEO datasets

PeerJ ◽

10.7717/peerj.10817 ◽

2021 ◽

Vol 9 ◽

pp. e10817

Author(s):

Huiting Xiao ◽

Kun Wang ◽

Dan Li ◽

Ke Wang ◽

Min Yu

Keyword(s):

Ovarian Cancer ◽

Expression Patterns ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Clinical Information ◽

Residual Tumor ◽

Diagnostic Value ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Diagnostic Biomarker

Background Malignant ovarian cancer is associated with the highest mortality of all gynecological tumors. Designing therapeutic targets that are specific to OC tissue is important for optimizing OC therapies. This study aims to identify different expression patterns of genes related to FGFR1 and the usefulness of FGFR1 as diagnostic biomarker for OC. Methods We collected data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. In the TCGA cohort we analyzed clinical information according to patient characteristics, including age, stage, grade, longest dimension of the tumor and the presence of a residual tumor. GEO data served as a validation set. We obtained data on differentially expressed genes (DEGs) from the two microarray datasets. We then used gene set enrichment analysis (GSEA) to analyze the DEG data in order to identify enriched pathways related to FGFR1. Results Differential expression analysis revealed that FGFR1 was significantly downregulated in OC specimens. 303 patients were included in the TCGA cohort. The GEO dataset confirmed these findings using information on 75 Asian patients. The GSE105437 and GSE12470 database highlighted the significant diagnostic value of FGFR1 in identifying OC (AUC = 1, p = 0.0009 and AUC = 0.8256, p = 0.0015 respectively). Conclusions Our study examined existing TCGA and GEO datasets for novel factors associated with OC and identified FGFR1 as a potential diagnostic factor. Further investigation is warranted to characterize the role played by FGFR1 in OC.

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Down-regulation of DLG2 predicts an unfavorable prognosis and promotes the proliferation and migration of Hepatocellular Carcinoma.

10.21203/rs.3.rs-22758/v1 ◽

2020 ◽

Author(s):

Jiawei Gu ◽

Runqi Hong ◽

Gengming Niu ◽

Zhiqing Hu ◽

Tao Song ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Enrichment Analysis ◽

Underlying Mechanism ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Down Regulation ◽

Normal Tissues ◽

And Migration ◽

Proliferation And Migration

Abstract Background Discs large MAGUK scaffold protein 2 (DLG2), a member of the MAGUK family, has been associated with certain tumor suppressing processes. In this study, we aim to identify the prognosis value and specific function of DLG2 in hepatocellular carcinomas (HCCs). Methods Expression of DLG2 in HCCs and adjacent normal tissues (NTs) was analyzed with transcriptomic datasets from the Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB) and immunohistochemical (IHC) staining of a tissue microarray (TMA). Prognostic roles of DLG2 in HCCs were investigated in the TMA cohort and validated in two cohorts from HCCDB. The in vitro activities of DLG2 were investigated in cultured HCC cells with lentiviruses. The underlying mechanism was explored using Gene Set Enrichment Analysis (GSEA) and gene-gene correlation analyses with The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Results The expression of DLG2 was significantly decreased in HCCs compared to that in NTs. Down-regulation of DLG2 in HCCs was associated with unfavorable prognosis. Overexpression of DLG2 inhibited, while knockdown of DLG2 prompted proliferation and migration of cultured HCCs. Mechanistically, DLG2 may inhibited cell growth of HCCs by interacting with key molecules that regulate cell cycles. Conclusion DLG2 inhibited HCC progression and may be a novel prognosis biomarker and therapeutic target for HCC.

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