Dataset Information

CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma.

ABSTRACT: Pancreatic adenocarcinoma (PAAD) is the 10th most common cancer worldwide and the outcomes for patients with the disease remain extremely poor. Precision biomarkers are urgently needed to increase the efficiency of early diagnosis and to improve the prognosis of patients. The tumor microenvironment (TME) and tumor immune infiltration are thought to impact the occurrence, progression, and prognosis of PAAD. Novel biomarkers excavated originating from the TME and immune infiltration may be effective in predicting the prognosis of PAAD patients. In the current study, the ESTIMATE and CIBERSORT algorithms were applied to estimate the division of immune and stromal components and the proportion of tumor-infiltrating immune cells in 182 PAAD cases downloaded from The Cancer Genome Atlas database. Intersection analyses of the Protein-Protein Interaction networks and Cox regression analysis identified the chemokine (CXC-motif) ligand 10 (CXCL10) as a predictive biomarker. We verified that CXCL10 in the TME negatively correlates with prognosis in PAAD and positively correlates with tumor cell differentiation. GSE62452 from the GEO database and cumulative survival analysis were performed to validate CXCL10 expression as an independent prognostic indicator. We also found that memory B cells, regulatory T cells, and macrophages M0 and M1 were correlated with the expression of CXCL10 indicating that expression of CXCL10 influenced the immune activity of the TME. Our data suggest that CXCL10 is beneficial as a prognostic indicator in PAAD patients and highlights the potential for immune targeted therapy in the treatment of PAAD.

SUBMITTER: Huang H

PROVIDER: S-EPMC7930611 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma.

Huang Huimin H Zhou Wangxiao W Chen Renpin R Xiang Bingfeng B Zhou Shipeng S Lan Linhua L

Frontiers in molecular biosciences 20210218

Pancreatic adenocarcinoma (PAAD) is the 10th most common cancer worldwide and the outcomes for patients with the disease remain extremely poor. Precision biomarkers are urgently needed to increase the efficiency of early diagnosis and to improve the prognosis of patients. The tumor microenvironment (TME) and tumor immune infiltration are thought to impact the occurrence, progression, and prognosis of PAAD. Novel biomarkers excavated originating from the TME and immune infiltration may be effecti ...[more]

PMID: 33681290

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Project description:BackgroundTUBA1C is a microtubule component that is involved in a variety of cancers. Our main objective was to investigate TUBA1C expression, its prognostic value, its potential biological functions, and its impact on the immune system of patients with lung adenocarcinoma (LUAD).MethodsThe Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA) and Immunohistochemistry Analysis were used to analyze TUBA1C expression, its clinicopathology, overall survival (OS), and disease-free survival (DFS) in LUAD patients. We also determined the correlation between TUBA1C and tumor-infiltrating immune cells (TIICs) by using CIBERSORT and GEPIA databases. To determine the expression of TUBA1C in LUAD, we analyzed a collection of immune infiltration levels and cumulative survival of LUAD tissues in TIMER database. By using UALCAN, STRING, and GeneMANIA databases, we investigated the protein-coding genes related to TUBA1C and its co-expression genes in LUAD tissues. Gene set enrichment analysis (GSEA) was performed by using the TCGA dataset.ResultsThe mRNA and the protein expression of TUBA1C were found to be up-regulated in LUAD tissues. The univariate analysis indicated that an increased expression of TUBA1C was significantly correlated to the following parameters: age, stage, and lymph node metastasis. An over-expression of TUBA1C was associated with a poor prognosis of LUAD. In TIMER and CIBERSORT databases, we found that TUBA1C is correlated with 13 types of TIICs: activated B cell, activated CD4 T cell, central memory CD4 T cell, effector memory CD8 T cell, eosinophils, immature B cell, gamma-delta T cell, immature dendritic cell, mast cell, memory B cell, natural killer T cell, regulatory T cell, and type 2T helper cell. By performing GSEA, we found that TUBA1C is closely correlated to cell cycle, p53 signaling pathway, glycolysis, and gluconeogenesis.ConclusionsOur findings indicate that TUBA1C is associated with TIICs in tumor microenvironment. Therefore, it serves as a novel prognostic biomarker and a target for future treatment methods of LUAD.

Project description:PurposePancreatic adenocarcinoma (PAAD) is one of the most lethal malignancies, with less than 10% of patients surviving more than 5 years. Existing biomarkers for reliable survival rate prediction need to be enhanced. As a result, the objective of this study was to create a novel immune-related gene prognostic index (IRGPI) for estimating overall survival (OS) and to analyze the molecular subtypes based on this index. Materials and procedures: RNA sequencing and clinical data were retrieved from publicly available sources and analyzed using several R software packages. A unique IRGPI and optimum risk model were developed using a machine learning algorithm. The prediction capability of our model was then compared to that of previously proposed models. A correlation study was also conducted between the immunological tumor microenvironment, risk groups, and IRGPI genes. Furthermore, we classified PAAD into different molecular subtypes based on the expression of IRGPI genes and investigated their features in tumor immunology using the K-means clustering technique.ResultsA 12-gene IRGPI (FYN, MET, LRSAM1, PSPN, ERAP2, S100A1, IL20RB, MAP3K14, SEMA6C, PRKCG, CXCL11, and GH1) was established, and verified along with a risk model. OS prediction by our model outperformed previous gene signatures. According to the findings of our correlation studies, different risk groups and IRGPI genes were found to be tightly related to tumor microenvironments, and PAAD could be further subdivided into immunologically distinct molecular subtypes based on the expression of IRGPI genes.ConclusionThe current study constructed and verified a unique IRGPI. Furthermore, our findings revealed a connection between the IRGPI and the immunological microenvironment of tumors. PAAD was differentiated into several molecular subtypes that might react differently to immunotherapy. These findings could provide new insights for precision and translational medicine for more innovative immunotherapy strategies.

Dataset Information

CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma.

Publications

CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma.

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