2. Academic Validation
  3. Systematic characterization of cancer transcriptome at transcript resolution

Systematic characterization of cancer transcriptome at transcript resolution

  • Nat Commun. 2022 Nov 10;13(1):6803. doi: 10.1038/s41467-022-34568-z.
Wei Hu # 1,  Yangjun Wu # 2,  Qili Shi # 3,  Jingni Wu 1,  Deping Kong 1,  Xiaohua Wu 2,  Xianghuo He 4,  Teng Liu 5 6,  Shengli Li 7
Affiliations

Affiliations

  • 1 Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China.
  • 2 Department of Gynecological Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
  • 3 Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
  • 4 Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China. xhhe@fudan.edu.cn.
  • 5 Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China. liuteng@alumni.hust.edu.cn.
  • 6 Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, 318000, China. liuteng@alumni.hust.edu.cn.
  • 7 Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China. shengli.li@sjtu.edu.cn.
  • # Contributed equally.
PMID: 36357395 DOI: 10.1038/s41467-022-34568-z
Abstract

Transcribed RNAs undergo various regulation and modification to become functional transcripts. Notably, Cancer transcriptome has not been fully characterized at transcript resolution. Herein, we carry out a reference-based transcript assembly across >1000 Cancer cell lines. We identify 498,255 transcripts, approximately half of which are unannotated. Unannotated transcripts are closely associated with cancer-related hallmarks and show clinical significance. We build a high-confidence RNA binding protein (RBP)-transcript regulatory network, wherein most RBPs tend to regulate transcripts involved in cell proliferation. We identify numerous transcripts that are highly associated with anti-cancer drug sensitivity. Furthermore, we establish RBP-transcript-drug axes, wherein PTBP1 is experimentally validated to affect the sensitivity to decitabine by regulating KIAA1522-a6 transcript. Finally, we establish a user-friendly data portal to serve as a valuable resource for understanding Cancer transcriptome diversity and its potential clinical utility at transcript level. Our study substantially extends Cancer RNA repository and will facilitate anti-cancer drug discovery.

Figures
Products