Dataset Information

Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis.

ABSTRACT: BACKGROUND:Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD. METHODS:The gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis. RESULTS:Among 1647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P<0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group. CONCLUSION:We successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.

SUBMITTER: Luo J

PROVIDER: S-EPMC7654612 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis.

Luo Jihang J Liu Puyu P Wang Leibo L Huang Yi Y Wang Yuanyan Y Geng Wenjing W Chen Duo D Bai Yuju Y Yang Ze Z

BMC cancer 20201109 1

<h4>Background</h4>Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD.<h4>Methods</h4>The gene expression profiles and clinic ...[more]

PMID: 33167940

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Project description:The outcome of colon adenocarcinoma (COAD) patients remains dismal, and lactate metabolism has been characterized to promote tumor development and immune evasion. Based on the above background, it is worthwhile to explore novel prognostic and therapeutic biomarkers for COAD patients from the aspect of lactate metabolism. Above all, 228 available lactate-metabolism-related genes (LMRGs) were acquired, and the landscape of copy number variation and the expression difference of mRNA levels between colon normal and tumor samples were investigated among these LMRGs. Importantly, eight overall survival (OS)-involved LMRGs were then distinguished by means of univariate Cox regression analysis in both GSE40967 and TCGA-COAD data sets. Subsequently, prognostic risk scores were established, integrating seven OS-related LMRGs by LASSO Cox regression analysis in the GSE40967 set, and then verified in the TCGA-COAD cohort. From the comprehensive analyses, COAD patients with high risk had comparatively more inferior survival probability in all populations of the study, and they tended to have more severe clinicopathological features with the risk score increasing. Moreover, by integrating age, AJCC T and pathological stage, and risk score, we constructed a prognostic nomogram that demonstrated great prediction effectiveness for OS of COAD patients. Furthermore, the potential effect of various risk score on tumor immune was assessed from enrichment of immune-related pathways, tumor-infiltrating immune cells, and expression levels of immune checkpoints separately. We could draw a conclusion that COAD patients with higher lactate-metabolism-related risk scores may acquire an immunosuppressive tumor microenvironment, which subsequently led to immune escapes and poor prognoses. Conclusively, all findings in the present study illustrate a great prognostic value of the lactate-metabolism-related risk signature, providing more in-depth insights into the indispensable function of lactate metabolism in prognosis and tumor immunity of COAD.

Project description:A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher's exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with lower 12-gene scores in GSE39582, the subgroup receiving ACT showed significantly longer OS time compared with those who received no ACT (Log Rank p = 0.021), while there is no obvious difference between counterparts among patients with higher 12-gene scores (Log Rank p = 0.12). Besides COAD, our 12-gene signature is multifunctional in several other cancer types including kidney cancer, lung cancer, uveal and skin melanoma, brain cancer, and pancreatic cancer. Functional classification showed that seven of the twelve genes are involved in immune system function and regulation, so our 12-gene signature could potentially be used to guide decisions about adjuvant therapy for patients with stage II/III and pMMR COAD.

Dataset Information

Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis.

Publications

Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis.

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