Abstract
Esophageal carcinoma (ESCA) is a common and lethal malignant tumor worldwide. The mitochondrial biomarkers were useful in finding significant prognostic gene modules associated with ESCA owing to the role of mitochondria in tumorigenesis and progression. In the present work, we obtained the transcriptome expression profiles and corresponding clinical information of ESCA from The Cancer Genome Atlas (TCGA) database. Differential expressed genes (DEGs) were overlapped with 2030 mitochondria-related genes to get mitochondria-related DEGs. The univariate cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate cox regression were sequentially used to define the risk scoring model for mitochondria-related DEGs, and its prognostic value was verified in the external datasets GSE53624. Based on the risk score, ESCA patients were divided into high- and low-risk groups. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to further investigate the difference between low- and high-risk groups at the gene pathway level. CIBERSORT was used to evaluate immune cell infiltration. The mutation difference between high- and low-risk groups was compared by using the R package “Maftools”. Cellminer was used to assess the association between the risk scoring model and drug sensitivity. As the most important outcome of the study, a 6-gene risk scoring model (APOOL, HIGD1A, MAOB, BCAP31, SLC44A2, and CHPT1) was constructed from 306 mitochondria-related DEGs. Pathways including the “hippo signaling pathway” and “cell–cell junction” were enriched in the DEGs between high and low groups. According to CIBERSORT, samples with high-risk scores demonstrated a higher abundance of CD4+ T cells, NK cells, M0 and M2 macrophages, and a lower abundance of M1 macrophages. The immune cell marker genes were correlated with the risk score. In mutation analysis, the mutation rate of TP53 was significantly different between the high- and low-risk groups. Drugs with a strong correlation with the risk model were selected. In conclusion, we focused on the role of mitochondria-related genes in cancer development and proposed a prognostic signature for individualized integrative assessment.
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Data availability
Gene expression RNAseq (HTseq) and somatic mutation profiles were downloaded from The Cancer Genome Atlas database (TCGA: https://portal.gdc.cancer.gov/). Phenotype and survival data were downloaded from the University of California SANTA CRUZ (UCSC: https://xenabrowser.net/datapages/). GEO datasets are all downloadable from the National Center for Biotechnology Information (NCBI) online Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo). Human mitochondrial-related genes were retrieved from Gene Set Enrichment Analysis (http://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Pathway-related genes were downloaded from GSEA (https://www.gsea-misgdb.org/gsea/index.jsp). Gene lists encoding immunomodulators and chemokines were downloaded from translation initiation site database (TISDB) website (http://cis.hku.hk/TISIDB/download.php). The same sample of gene expression and drug sensitivity data was downloaded from the cellminer website (https://discover.nci.nih.gov/cellminer/).
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Funding
This work was supported by the National Natural Science Foundation of China (No. 81902513), the Applied Basic Research Project of Shanxi Province (No. 202103021224228 and No. 20210302124376) and the Science/Technology Project of Sichuan Province (No. 2021YFS0161).
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X.Z., H.W., J.Z., and M.L. designed the experiments. X.Z. and H.W. completed the experiments. X.Z., H.W., J.N., Y.H., W.Z., and J.C. analyzed the data. X.Z. and M.L. drafted the manuscript. J.N., L.L., J.Z., C.Z., and M.L. edited the manuscript. All authors reviewed the manuscript.
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Zhang, X., Wu, H., Niu, J. et al. A novel mitochondria-related gene signature in esophageal carcinoma: prognostic, immune, and therapeutic features. Funct Integr Genomics 23, 109 (2023). https://doi.org/10.1007/s10142-023-01030-2
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DOI: https://doi.org/10.1007/s10142-023-01030-2