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01 January 2020 : Clinical Research  

Integrative Gene Expression Profiling Analysis to Investigate Potential Prognostic Biomarkers for Colorectal Cancer

Xinkui Liu1ABCDEF, Zhitong Bing234C, Jiarui Wu1AG*, Jingyuan Zhang1C, Wei Zhou1C, Mengwei Ni1C, Ziqi Meng1C, Shuyu Liu1C, Jinhui Tian23C, Xiaomeng Zhang1C, Yingfei Li5C, Shanshan Jia1C, Siyu Guo1C

DOI: 10.12659/MSM.918906

Med Sci Monit 2020; 26:e918906

Abstract

BACKGROUND: Despite noteworthy advancements in the multidisciplinary treatment of colorectal cancer (CRC) and deeper understanding in the molecular mechanisms of CRC, many of CRC patients with histologically identical tumors present different treatment response and prognosis. Thus, more evidence on novel predictive and prognostic biomarkers for CRC remains urgently needed. This study aims to identify potential prognostic biomarkers for CRC with integrative gene expression profiling analysis.

MATERIAL AND METHODS: Differential expression analysis of paired CRC and adjacent normal tissue samples in 6 microarray datasets was independently performed, and the 6 datasets were integrated by the robust rank aggregation method to detect consistent differentially expressed genes (DEGs). Aberrant expression patterns of these genes were further validated in RNA sequencing data. Then, gene set enrichment analysis (GSEA) was performed to investigate significantly dysregulated biological functions in CRC. Finally, univariate, LASSO and multivariate Cox regression models were built to identify key prognostic genes in CRC patients.

RESULTS: A total of 990 DEGs (495 downregulated and 495 upregulated genes) were acquired after integratedly analyzing the 6 microarray datasets, and 4131 DEGs (2050 downregulated and 2081 upregulated genes) were obtained from the RNA sequencing dataset. Subsequently, these DEGs were intersected and 885 consistent DEGs were finally identified, including 458 downregulated and 427 upregulated genes. Two risky prognostic genes (TIMP1 and LZTS3) and 5 protective prognostic genes (AXIN2, CXCL1, ITLN1, CPT2 and CLDN23) were identified, which were significantly associated with the prognosis of CRC.

CONCLUSIONS: The 7 genes that we identified would provide more evidence for further applying novel diagnostic and prognostic biomarkers in clinical practice to facilitate personalized treatment of CRC.

Keywords: Biological Markers, Colorectal Neoplasms, Gene Expression Profiling, Biomarkers, Tumor, Computational Biology, Databases, Genetic, gene ontology, Gene Regulatory Networks, Microarray Analysis, Protein Interaction Maps

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Med Sci Monit 2024; 30:e945315

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750