Transcriptional response profiles of paired tumor-normal samples offer novel perspectives in pan-cancer analysis
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Shuofeng Hu1, Hanyu Yuan1, Zongcheng Li1,2, Jian Zhang1, Jiaqi Wu1, Yaowen Chen1,3, Qiang Shi1, Wu Ren1,4, Ningsheng Shao1 and Xiaomin Ying1
1Beijing Institute of Basic Medical Sciences, Beijing 100850, China
2Translational Medicine Center of Stem Cells, 307-Ivy Translational Medicine Center, Laboratory of Oncology, Affiliated Hospital, Academy of Military Medical Sciences, Beijing 100071, China
3Department of Obstetrics and Gynecology, Fuzhou General Hospital of Nanjing Military Command, Fujian 350025, China
4Department of Gastrointestinal Surgery, The First Affiliated Hospital of Jilin University, Changchun 130021, China
Keywords: transcriptional response profiles, paired tumor-normal sample, pan-cancer, comparison, biomarker
Received: October 15, 2016 Accepted: April 03, 2017 Published: April 20, 2017
Both tumor and adjacent normal tissues are valuable in cancer research. Transcriptional response profiles represent the changes of gene expression levels between paired tumor and adjacent normal tissues. In this study, we performed a pan-cancer analysis based on the transcriptional response profiles from 633 samples across 13 cancer types. We obtained two interesting results. Using consensus clustering method, we characterized ten clusters with distinct transcriptional response patterns and enriched pathways. Notably, head and neck squamous cell carcinoma was divided in two subtypes, enriched in cell cycle-related pathways and cell adhesion-related pathways respectively. The other interesting result is that we identified 92 potential pan-cancer genes that were consistently upregulated across multiple cancer types. Knockdown of FAM64A or TROAP inhibited the growth of cancer cells, suggesting that these genes may promote tumor development and are worthy of further validations. Our results suggest that transcriptional response profiles of paired tumor-normal tissues can provide novel perspectives in pan-cancer analysis.
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