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Identification of Candidate Biomarkers and Prognostic Analysis in Colorectal Cancer Liver Metastases

BACKGROUND: Colorectal cancer (CRC), one of the most common malignant tumors worldwide, has a high mortality rate, especially for patients with CRC liver metastasis (CLM). However, CLM pathogenesis remains unclear. METHODS: We integrated multiple cohort datasets and databases to clarify and verify p...

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Detalles Bibliográficos
Autores principales: Zhang, Tianhao, Yuan, Kaitao, Wang, Yingzhao, Xu, Mingze, Cai, Shirong, Chen, Chuangqi, Ma, Jinping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371911/
https://www.ncbi.nlm.nih.gov/pubmed/34422629
http://dx.doi.org/10.3389/fonc.2021.652354
Descripción
Sumario:BACKGROUND: Colorectal cancer (CRC), one of the most common malignant tumors worldwide, has a high mortality rate, especially for patients with CRC liver metastasis (CLM). However, CLM pathogenesis remains unclear. METHODS: We integrated multiple cohort datasets and databases to clarify and verify potential key candidate biomarkers and signal transduction pathways in CLM. GEO2R, DAVID 6.8, ImageGP, STRING, UALCAN, ONCOMINE, THE HUMAN PROTEIN ATLAS, GEPIA 2.0, cBioPortal, TIMER 2.0, DRUGSURV, CRN, GSEA 4.0.3, FUNRICH 3.1.3 and R 4.0.3 were utilized in this study. RESULTS: Sixty-three pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened from three gene expression profiles (GSE6988, GSE14297 and GSE81558). Thirty-one up-regulated genes and four down-regulated genes were identified from these three gene expression profiles and verified by another gene expression profiles (GSE 49355) and TCGA database. Two pathways (IGFBP-IGF signaling pathway and complement-coagulation cascade), eighteen key differentially expressed genes (DEGs), six hub genes (SPARCL1, CDH2, CP, HP, TF and SERPINA5) and two biomarkers (CDH2 and SPARCL1) with significantly prognostic values were screened by multi-omics data analysis and verified by Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) cohort. CONCLUSIONS: In this study, we identified a robust set of potential candidate biomarkers in CLM, which would provide potential value for early diagnosis and prognosis, and would promote molecular targeting therapy for CRC and CLM.