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Development of a prognostic index of colon adenocarcinoma based on immunogenomic landscape analysis.

ABSTRACT: Background:Colon adenocarcinoma (COAD) is one of the most commonly diagnosed cancers, and it is closely related to the immune microenvironment. Considering that immunotherapy is not effective for all COAD patients, it is necessary to identify the effective population before administering treatment. In this study, we established an independent prognostic index based on immune-related genes (IRGs), in order to evaluate the clinical outcome of COAD. Methods:The gene expression profiles and IRGs taken from The Cancer Genome Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort), respectively, were integrated in order to identify the differentially expressed IRGs. Functional enrichment analysis was conducted and the prognostic value of survival-related IRGs was determined. Based on Cox regression analysis, the IRG-based prognostic index (IRGPI) was established, and the model was evaluated and applied. Results:A total of 51 differentially expressed survival-related IRGs were identified. The most significant signaling pathway was "cytokine-cytokine receptor interaction". The index established herein was based on 12 survival-related IRGs, and it was highly accurate in monitoring prognosis. Moreover, the IRGPI was significantly correlated with multiple clinicopathologic factors, as well as with the infiltration of immune cells. Conclusions:An independent IRGPI was established in order to assess the immune status and tumor prognosis in COAD patients. This index can serve as a robust biomarker in clinical prognosis applications, including cancer immunotherapy.

SUBMITTER: Qiang W

PROVIDER: S-EPMC7186653 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Development of a prognostic index of colon adenocarcinoma based on immunogenomic landscape analysis.

Qiang Weijie W Dai Yifei Y Sun Guibo G Xing Xiaoyan X Sun Xiaobo X

Annals of translational medicine 20200301 6

<h4>Background</h4>Colon adenocarcinoma (COAD) is one of the most commonly diagnosed cancers, and it is closely related to the immune microenvironment. Considering that immunotherapy is not effective for all COAD patients, it is necessary to identify the effective population before administering treatment. In this study, we established an independent prognostic index based on immune-related genes (IRGs), in order to evaluate the clinical outcome of COAD.<h4>Methods</h4>The gene expression profil ...[more]

PMID: 32355728

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Project description:Background: Lysosomes are essential for the development and recurrence of cancer. The relationship between a single lysosome-related gene and cancer has previously been studied, but the relationship between the lysosome-related genes (LRGs) and colon adenocarcinoma (COAD) remains unknown. This research examined the role of lysosome-related genes in colon adenocarcinoma. Methods: 28 lysosome-related genes associated with prognosis (PLRGs) were found by fusing the gene set that is differently expressed between tumor and non-tumor in colon adenocarcinoma with the gene set that is related to lysosomes. Using consensus unsupervised clustering of PLRGs, the colon adenocarcinoma cohort was divided into two subtypes. Prognostic and tumor microenvironment (TME) comparisons between the two subtypes were then made. The PLRGs_score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify each patient's prognosis and provide advice for treatment. Lastly, Western Blot and immunohistochemistry (IHC) were used to identify MOGS expression at the protein level in colon adenocarcinoma tissues. Results: PLRGs had more somatic mutations and changes in genetic level, and the outcomes of the two subtypes differed significantly in terms of prognosis, tumor microenvironment, and enrichment pathways. Then, PLRGs_score was established based on two clusters of differential genes in the cancer genome atlas (TCGA) database, and external verification was performed using the gene expression omnibus (GEO) database. Then, we developed a highly accurate nomogram to enhance the clinical applicability of the PLRGs_score. Finally, a higher PLRGs_score was associated with a poorer overall survival (OS), a lower tumor mutation burden (TMB), a lower cancer stem cell (CSC) index, more microsatellite stability (MSS), and a higher clinical stage. MOGS was substantially elevated at the protein level in colon adenocarcinoma as additional confirmation. Conclusion: Overall, based on PLRGs, we identified two subtypes that varied significantly in terms of prognosis and tumor microenvironment. Then, in order to forecast patient prognosis and make treatment suggestions, we developed a diagnostic model with major significance for prognosis, clinical relevance, and immunotherapy. Moreover, we were the first to demonstrate that MOGS is highly expressed in colon adenocarcinoma.

Dataset Information

Development of a prognostic index of colon adenocarcinoma based on immunogenomic landscape analysis.

Publications

Development of a prognostic index of colon adenocarcinoma based on immunogenomic landscape analysis.

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