Xin Li1, Cuiyan Ma2,3,4. 1. Department of Rehabilitation Medicine, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine Tsinghua University Beijing China. 2. Department of Computer Science and Technology, BNRist, RIIT, Institute of Internet Industry Tsinghua University Beijing China. 3. Integrative Medicine Center, School of Life Sciences Beijing University of Chinese Medicine Beijing China. 4. Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua-Peking Center for Life Sciences Tsinghua University Beijing China.
Abstract
Background and Aims: Chromophobe renal cell carcinoma (chRCC) is the third common pathological subtype in renal cancers. However, the underlying mechanisms of specific genetic characteristics of chRCC are currently unclear. In this study, protein expression profiles, gene ontology (GO), and survival plots were provided by integrated bioinformatics analysis to investigate key genes associated with the mechanism of tumorigenesis and prognosis of chRCC. Methods: The chRCC data set of gene expression profiles and clinical data were obtained from the gdc-client (https://portal.gdc.cancer.gov) deposited on The Cancer Genome Atlas (TCGA) data portal. Differentially expressed genes (DEGs) in chRCC, compared with normal samples, were analyzed by R packages "DESeq2," "edgeR," and "limma." Heat maps, volcano plots, and principal component analysis (PCA) were performed for integrated analyses. GUniGO, mutant analysis, and survival plots were performed by R packages. A protein-protein interaction (PPI) network was generated and analyzed by R packages, online String software, and Cytoscape software. Survival analysis and gene expressing comparison in tumor and normal samples were used to detect the core genes of chRCC. Furthermore, the top interacting proteins were reanalyzed. Results: A total of 306 upregulated genes and 678 downregulated genes were identified by a Venn diagram. Ten hub genes were extracted from PPI network. Furthermore, Alpha-2-Heremans-Schmid-glycoprotein (AHSG), one of 10 hub genes, was found to be associated with chRCC, and had a big difference in expression between survival and dead events. AHSG could predict potential prognostic and may be a diagnostic biomarker in chRCC. Conclusion: This study illustrated that AHSG may be a potential therapeutic target and prognostic genetic marker for chRCC.
Background and Aims: Chromophobe renal cell carcinoma (chRCC) is the third common pathological subtype in renal cancers. However, the underlying mechanisms of specific genetic characteristics of chRCC are currently unclear. In this study, protein expression profiles, gene ontology (GO), and survival plots were provided by integrated bioinformatics analysis to investigate key genes associated with the mechanism of tumorigenesis and prognosis of chRCC. Methods: The chRCC data set of gene expression profiles and clinical data were obtained from the gdc-client (https://portal.gdc.cancer.gov) deposited on The Cancer Genome Atlas (TCGA) data portal. Differentially expressed genes (DEGs) in chRCC, compared with normal samples, were analyzed by R packages "DESeq2," "edgeR," and "limma." Heat maps, volcano plots, and principal component analysis (PCA) were performed for integrated analyses. GUniGO, mutant analysis, and survival plots were performed by R packages. A protein-protein interaction (PPI) network was generated and analyzed by R packages, online String software, and Cytoscape software. Survival analysis and gene expressing comparison in tumor and normal samples were used to detect the core genes of chRCC. Furthermore, the top interacting proteins were reanalyzed. Results: A total of 306 upregulated genes and 678 downregulated genes were identified by a Venn diagram. Ten hub genes were extracted from PPI network. Furthermore, Alpha-2-Heremans-Schmid-glycoprotein (AHSG), one of 10 hub genes, was found to be associated with chRCC, and had a big difference in expression between survival and dead events. AHSG could predict potential prognostic and may be a diagnostic biomarker in chRCC. Conclusion: This study illustrated that AHSG may be a potential therapeutic target and prognostic genetic marker for chRCC.
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