Dataset Information

Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.

ABSTRACT:

Background

Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and transcription factors (DETFs) were screened using the following databases: Cistrome, The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and InnateDB. We constructed a network showing the regulation of DEIGs by DETFs. Using weighted gene co-expression network analysis, we prepared 5 co-expressed gene modules; 6 hub genes (CD1A, CD1B, FGF9, GRP, SERPINE1, and F2RL2) obtained using univariate and multivariate regression analysis were used to construct a risk model. Patients from TCGA database were divided into high- and low-risk groups based on whether their risk score was greater or less than the mean; the public dataset GSE40967, which contains gene expression profiles of 566 colon cancer patients, was used for validation.

Results

Survival analysis, somatic gene mutations, and tumor-infiltrating immune cells differed significantly between the high- and low-risk groups.

Conclusions

This immune-related gene signature could play an important role in guiding treatment, making prognoses, and potentially developing future clinical applications.

SUBMITTER: Zhou R

PROVIDER: S-EPMC9552517 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.

Zhou Rui R Gao Zhuowei Z Ju Yongle Y

BMC bioinformatics 20221011 1

<h4>Background</h4>Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and ...[more]

PMID: 36221049

Similar Datasets

Project description:Background: Fatty acid metabolism (FAM), as a hallmark of caner, plays important roles in tumor initiation and carcinogenesis. However, the significance of fatty acid metabolism-related genes in colon adenocarcinoma (COAD) are largely unknown. Methods: RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas (TCGA) cohort. Univariate and multivariate Cox regression analyses were utilized to construct a fatty acid metabolism-related gene signature. Kaplan-Meier survival and receiver operating characteristic (ROC) analyses were used to verify the performance of this signature. GEO datasets were applied to validate the signature. Maftools package was utilized to analyze the mutation profiles of this signature. Correlation between the risk signature and stemness scores was compared by RNA stemness score (RNAss). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set variation analysis (GSVA) were performed to explore the potential functions and signaling pathways. Immune landscape of the signature was explored by analyzing different immune cells infiltration, immune functions and microsatellite instability. A nomogram was constructed by combining the risk signature and multiple clinical factors. Expression levels and prognostic values of the risk genes were revealed in the cancer genome atlas and GEO databases. Moreover, the expression the risk genes were measured in cell lines using real time quantitative PCR (qRT-PCR). Results: Eight fatty acid metabolism-related genes (CD36, ENO3, MORC2, PTGR1, SUCLG2, ELOVL3, ELOVL6 and CPT2) were used to construct a risk signature. This signature demonstrated better prognostic value than other clinicopathological parameters, with AUC value was 0.734 according to the cancer genome atlas database. There was negative correlation between the riskscore and RNA stemness score. The patients in the high-risk group demonstrated higher infiltration of M0 macrophages, and less infiltration of activated CD4 memory T cells and Eosinophils. There were more MSI patients in the high-risk group than those in the low-risk group (38% vs. 30%). The risk scores of patients in the MSI group were slightly higher than those in the microsatellite stability group. Gene ontology, kyoto encyclopedia of genes and genomes and gene set variation analysis enrichment analyses showed that several metabolism-related functions and signaling pathways were enriched. A nomogram showed good predictive capability of the signature. Moreover, qRT-PCR revealed upregulated expression of ENO3, MORC2, SUCLG2 and ELOVL6, and downregulated expression of CPT2 in all examined colon adenocarcinoma cell lines. Conclusion: This study provided novel insights into a fatty acid metabolism-related signature in the prognosis an immune landscape of colon adenocarcinoma patients.

Project description:BackgroundDisruptions in calcium homeostasis are associated with a wide range of diseases, and play a pivotal role in the development of cancer. However, the construction of prognostic models using calcium extrusion-related genes in colon adenocarcinoma (COAD) has not been well studied. We aimed to identify whether calcium extrusion-related genes serve as a potential prognostic biomarker in the COAD progression.MethodsWe constructed a prognostic model based on the expression of calcium extrusion-related genes (SLC8A1, SLC8A2, SLC8A3, SLC8B1, SLC24A2, SLC24A3 and SLC24A4) in COAD. Subsequently, we evaluated the associations between the risk score calculated by calcium extrusion-related genes and mutation signature, immune cell infiltration, and immune checkpoint molecules. Then we calculated the immune score, stromal score, tumor purity and estimate score using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm. The response to immunotherapy was assessed using tumor immune dysfunction and exclusion (TIDE). Finally, colorectal cancer cells migration, growth and colony formation assays were performed in RKO cells with the overexpression or knockdown SLC8A3, SLC24A2, SLC24A3, or SLC24A4.ResultsWe found that patients with high risk score of calcium extrusion-related genes tend to have a poorer prognosis than those in the low-risk group. Additionally, patients in high-risk group had higher rates of KRAS mutations and lower MUC16 mutations, implying a strong correlation between KRAS and MUC16 mutations and calcium homeostasis in COAD. Moreover, the high-risk group showed a higher infiltration of regulatory T cells (Tregs) in the tumor microenvironment. Finally, our study identified two previously unreported model genes (SLC8A3 and SLC24A4) that contribute to the growth and migration of colorectal cancer RKO cells.ConclusionsAltogether, we developed a prognostic risk model for predicting the prognosis of COAD patients based on the expression profiles of calcium extrusion-related genes, Furthermore, we validated two previously unreported tumor suppressor genes (SLC8A3 and SLC24A4) involved in colorectal cancer progression.

Project description:Background: Immune-related genes (IRGs) are critically involved in the tumor microenvironment (TME) of colon adenocarcinoma (COAD). Here, the study was mainly designed to establish a prognostic model of IRGs to predict the survival of COAD patients. Methods: The Cancer Genome Atlas (TCGA), Immunology Database and Analysis Portal (ImmPort) database, and Cistrome database were utilized for extracting data regarding the expression of immune gene- and tumor-related transcription factors (TFs), aimed at the identification of differentially expressed genes (DEGs), differentially expressed IRGs (DEIRGs), and differentially expressed TFs (DETFs). Univariate Cox regression analysis was subsequently performed for the acquisition of prognosis-related IRGs, followed by establishment of TF regulatory network for uncovering the possible molecular regulatory association in COAD. Subsequently, multivariate Cox regression analysis was conducted to further determine the role of prognosis-related IRGs for prognostic prediction in COAD. Finally, the feasibility of a prognostic model with immunocytes was explored by immunocyte infiltration analysis. Results: A total of 2450 DEGs, 8 DETFs, and 79 DEIRGs were extracted from the corresponding databases. Univariate Cox regression analysis revealed 11 prognosis-related IRGs, followed by establishment of a regulatory network on prognosis-related IRGs at transcriptional levels. Functionally, IRG GLP2R was negatively modulated by TF MYH11, whereas IRG TDGF1 was positively modulated by TF TFAP2A. Multivariate Cox regression analysis was subsequently performed to establish a prognostic model on the basis of seven prognosis-related IRGs (GLP2R, ESM1, TDGF1, SLC10A2, INHBA, STC2, and CXCL1). Moreover, correlation analysis of immunocyte infiltration also revealed that the seven-IRG prognostic model was positively associated with five types of immunocytes (dendritic cell, macrophage, CD4 T cell, CD8 T cell, and neutrophil), which may directly reflect tumor immune state in COAD. Conclusions: Our present findings indicate that the prognostic model based on prognosis-related IRGs plays a crucial role in the clinical supervision and prognostic prediction of COAD patients at both molecular and cellular levels.

Project description:BackgroundLung cancer has been the focus of attention for many researchers in recent years due to its leading contribution to cancer-related death worldwide, with lung adenocarcinoma (LUAD) being the most common histological type. Ferroptosis, a novel iron-dependent form of regulated cell death, can be induced by sorafenib. Emerging evidence shows that triggering ferroptosis has potential as a cancer therapy. This work aimed to build a ferroptosis-related gene signature for predicting the outcome of LUAD.MethodsThe TCGA-LUAD dataset was set as the training cohort, and the GSE72094 and GSE68465 datasets were set as the validation cohorts. Sixty-two ferroptosis-related genes were retrieved from the literature. A univariate Cox regression model was constructed for the training cohort to preliminarily screen for potential prognostic ferroptosis-related genes. A gene signature was generated from a LASSO Cox regression model and assessed with the training and validation cohorts through Kaplan-Meier, Cox, and ROC analyses. In addition, the correlation between the risk score and autophagy-related genes was determined by the Pearson test. Finally, GSEA and immune infiltrating analyses were performed to better study the functional annotation of the signature and the role of each kind of immune cell.ResultsA ten-gene signature was constructed from the training cohort and validated in three cohorts by Kaplan-Meier and Cox regression analyses, revealing its independent prognostic value in LUAD. Moreover, a ROC analysis conducted with all cohort data confirmed the predictive ability of the ten-gene signature for LUAD prognosis. A total of 62.85% (308/490) of autophagy-related genes were found to be significantly correlated with risk scores. GSEA detailed the exact pathways related to the gene signature, and immune-infiltrating analyses identified crucial roles for resting mast cells and resting dendritic cells in the prognosis of LUAD.ConclusionsWe identified a novel ferroptosis-related ten-gene signature (PHKG2, PGD, PEBP1, NCOA4, GLS2, CISD1, ATP5G3, ALOX15, ALOX12B, and ACSL3) that can accurately predict LUAD prognosis and is closely linked to resting mast cells and resting dendritic cells.

Dataset Information

Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.

Background

Results

Conclusions

Publications

Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets