Dataset Information

In silico development and in vitro validation of a novel five-gene signature for prognostic prediction in colon cancer.

ABSTRACT: Colon cancer is one of the most common cancers in digestive system, and its prognosis remains unsatisfactory. Therefore, this study aimed to identify gene signatures that could effectively predict the prognosis of colon cancer patients by examining the data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO-Cox regression analysis generated a five-gene signature (DCBLD2, RAB11FIP1, CTLA4, HOXC6 and KRT6A) that was associated with patient survival in the TCGA cohort. The prognostic value of this gene signature was further validated in two independent GEO datasets. GO enrichment revealed that the function of this gene signature was mainly associated with extracellular matrix organization, collagen-containing extracellular matrix, and extracellular matrix structural constituent. Moreover, a nomogram was established to facilitate the clinical application of this signature. The relationships among the gene signature, mutational landscape and immune infiltration cells were also investigated. Importantly, this gene signature also reliably predicted the overall survival in IMvigor210 anti-PD-L1 cohort. In addition to the bioinformatics study, we also conducted a series of in vitro experiments to demonstrate the effect of the signature genes on the proliferation, migration, and invasion of colon cancer cells. Collectively, our data demonstrated that this five-gene signature might serve as a promising prognostic biomarker and shed light on the development of personalized treatment in colon cancer patients.

SUBMITTER: Zhu Q

PROVIDER: S-EPMC9906087 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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In silico development and in vitro validation of a novel five-gene signature for prognostic prediction in colon cancer.

Zhu Qiankun Q Rao Benqiang B Chen Yongbing Y Jia Pingping P Wang Xin X Zhang Bingdong B Wang Lin L Zhao Wanni W Hu Chunlei C Tang Meng M Yu Kaiying K Chen Wei W Pan Lei L Xu Yu Y Luo Huayou H Wang Kunhua K Li Bo B Shi Hanping H

American journal of cancer research 20230115 1

Colon cancer is one of the most common cancers in digestive system, and its prognosis remains unsatisfactory. Therefore, this study aimed to identify gene signatures that could effectively predict the prognosis of colon cancer patients by examining the data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO-Cox regression analysis generated a five-gene signature (<i>DCBLD2, RAB11FIP1, CTLA4, HOXC6</i> and <i>KRT6A</i>) that was associated with patient survival ...[more]

PMID: 36777511

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Project description:Aberrant expression of chromatin regulators (CRs) could lead to the development of various diseases including cancer. However, the biological function and prognosis role of CRs in colon adenocarcinoma (COAD) remains unclear. We performed the clustering analyses for expression profiling of COAD downloaded from The Cancer Genome Atlas. We developed a chromatin regulator prognostic model, which was validated in an independent cohort data. Time-intendent receiver operating characteristics curve was used to evaluate predict ability of model. Univariate and multivariate cox regression were used to assess independence of risk score. Nomogram was established to assess individual risk. Gene ontology, and Kyoto Encyclopedia of genes and genomes, gene set variation analysis and gene set enrichment analysis were performed to explore the function of CRs. Immune infiltration and drug sensitivity were also performed to assess effect of CRs on treatment in COAD. COAD can be separated into two subtypes with different clinical characteristics and prognosis. The C2 had elevated immune infiltration levels and low tumor purity. Using 12 chromatin regulators, we developed and validated a prognostic model that can predict the overall survival of COAD patients. We built a risk score that can be an independent prognosis predictor of COAD. The nomogram score system achieved the best predict ability and were also confirmed by decision curve analysis. There were significantly different function and pathway enrichment, immune infiltration levels, and tumor mutation burden between high-risk and low-risk group. The external validation data also indicated that high-risk group had higher stable disease/progressive disease response rate and poorer prognosis than low-risk group. Besides, the signature genes included in the model could cause chemotherapy sensitivity to some small molecular compounds. Our integrative analyses for chromatin regulators could provide new insights for the risk management and individualized treatment in COAD.

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Dataset Information

In silico development and in vitro validation of a novel five-gene signature for prognostic prediction in colon cancer.

Publications

In silico development and in vitro validation of a novel five-gene signature for prognostic prediction in colon cancer.

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