Potential biomarkers and immune characteristics of small bowel adenocarcinoma

Abstract Small bowel adenocarcinoma (SBA) is a gastrointestinal malignancy with low incidence but poor prognosis, and its pathogenesis is still unclear. This study aimed to explore potential disease-causing biomarkers of SBA. The gene expression datasets of SBA and normal samples were downloaded fro...

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Main Authors: Jinggao Feng, Xiayu Tang, Liusong Song, Zhipeng Zhou, Yuan Jiang, Yao Huang
Format: Article
Language:English
Published: Nature Portfolio 2022-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-20599-5
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author Jinggao Feng
Xiayu Tang
Liusong Song
Zhipeng Zhou
Yuan Jiang
Yao Huang
author_facet Jinggao Feng
Xiayu Tang
Liusong Song
Zhipeng Zhou
Yuan Jiang
Yao Huang
author_sort Jinggao Feng
collection DOAJ
description Abstract Small bowel adenocarcinoma (SBA) is a gastrointestinal malignancy with low incidence but poor prognosis, and its pathogenesis is still unclear. This study aimed to explore potential disease-causing biomarkers of SBA. The gene expression datasets of SBA and normal samples were downloaded from the Gene Expression Omnibus database. First, differential gene expression analysis and weighted gene coexpression network analysis (WGCNA) were performed. Common genes (CGs) were obtained by intersection of differentially expressed genes (DEGs) and optimal modal genes of WGCNA. Subsequently, a protein‒protein interaction network was established to screen hub genes, and target genes were obtained by Lasso regression analysis of hub genes. An SBA risk prediction model was established based on target genes. The prediction accuracy of the model was evaluated by the area under the receiver operating characteristic curve (AUC). The levels of immune cell infiltration and activation of immune pathways were compared between SBA and normal samples using the "ggpubr" and "reshape2" packages. A total of 1058 DEGs were identified. WGCNA showed that the signature gene in the brown module was significantly associated with SBA (p = 7E−17), and 469 CGs were obtained. Four target genes (APOA4, APOB, COL1A2, FN1) were identified and showed excellent prediction of SBA risk (AUC = 0.965). In addition, active dendritic cells and macrophages showed higher infiltration levels in SBA. Meanwhile, the APC_co_stimulation pathway and parainflammation pathway were strongly active in SBA. Four target genes (APOA4, APOB, COL1A2, FN1) may be involved in the pathogenesis of small bowel adenocarcinoma.
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spelling doaj.art-6d51ce17e82d41db9ea6287eea3f267e2022-12-22T03:33:38ZengNature PortfolioScientific Reports2045-23222022-09-011211910.1038/s41598-022-20599-5Potential biomarkers and immune characteristics of small bowel adenocarcinomaJinggao Feng0Xiayu Tang1Liusong Song2Zhipeng Zhou3Yuan Jiang4Yao Huang5Department of Gastrointestinal and Anorectal Surgery, The Central Hospital of YongzhouDepartment of Gastrointestinal and Anorectal Surgery, The Central Hospital of YongzhouDepartment of Gastrointestinal and Anorectal Surgery, The Central Hospital of YongzhouDepartment of Gastrointestinal and Anorectal Surgery, The Central Hospital of YongzhouDepartment of Gastrointestinal and Anorectal Surgery, The Central Hospital of YongzhouDepartment of Gastrointestinal and Anorectal Surgery, The Central Hospital of YongzhouAbstract Small bowel adenocarcinoma (SBA) is a gastrointestinal malignancy with low incidence but poor prognosis, and its pathogenesis is still unclear. This study aimed to explore potential disease-causing biomarkers of SBA. The gene expression datasets of SBA and normal samples were downloaded from the Gene Expression Omnibus database. First, differential gene expression analysis and weighted gene coexpression network analysis (WGCNA) were performed. Common genes (CGs) were obtained by intersection of differentially expressed genes (DEGs) and optimal modal genes of WGCNA. Subsequently, a protein‒protein interaction network was established to screen hub genes, and target genes were obtained by Lasso regression analysis of hub genes. An SBA risk prediction model was established based on target genes. The prediction accuracy of the model was evaluated by the area under the receiver operating characteristic curve (AUC). The levels of immune cell infiltration and activation of immune pathways were compared between SBA and normal samples using the "ggpubr" and "reshape2" packages. A total of 1058 DEGs were identified. WGCNA showed that the signature gene in the brown module was significantly associated with SBA (p = 7E−17), and 469 CGs were obtained. Four target genes (APOA4, APOB, COL1A2, FN1) were identified and showed excellent prediction of SBA risk (AUC = 0.965). In addition, active dendritic cells and macrophages showed higher infiltration levels in SBA. Meanwhile, the APC_co_stimulation pathway and parainflammation pathway were strongly active in SBA. Four target genes (APOA4, APOB, COL1A2, FN1) may be involved in the pathogenesis of small bowel adenocarcinoma.https://doi.org/10.1038/s41598-022-20599-5
spellingShingle Jinggao Feng
Xiayu Tang
Liusong Song
Zhipeng Zhou
Yuan Jiang
Yao Huang
Potential biomarkers and immune characteristics of small bowel adenocarcinoma
Scientific Reports
title Potential biomarkers and immune characteristics of small bowel adenocarcinoma
title_full Potential biomarkers and immune characteristics of small bowel adenocarcinoma
title_fullStr Potential biomarkers and immune characteristics of small bowel adenocarcinoma
title_full_unstemmed Potential biomarkers and immune characteristics of small bowel adenocarcinoma
title_short Potential biomarkers and immune characteristics of small bowel adenocarcinoma
title_sort potential biomarkers and immune characteristics of small bowel adenocarcinoma
url https://doi.org/10.1038/s41598-022-20599-5
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