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Updated: Aug 22, 2025

Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies
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Systematic characterization of cancer transcriptome at transcript resolution.

Wei Hu1, Yangjun Wu2, Qili Shi3

  • 1Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China.

Nature Communications
|November 10, 2022
PubMed
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This summary is machine-generated.

This study characterizes cancer transcriptomes at high resolution, discovering numerous unannotated transcripts linked to cancer hallmarks and drug sensitivity. A novel RNA binding protein-transcript network aids anti-cancer drug discovery.

Area of Science:

  • Genomics
  • Molecular Biology
  • Cancer Research

Background:

  • Cancer transcriptomes remain incompletely characterized at the transcript level.
  • Understanding transcript diversity is crucial for cancer research and drug development.

Purpose of the Study:

  • To comprehensively assemble and analyze cancer transcriptomes at high resolution.
  • To identify novel transcripts, regulatory networks, and their association with cancer hallmarks and drug sensitivity.
  • To establish a valuable resource for cancer transcriptomics research and anti-cancer drug discovery.

Main Methods:

  • Reference-based transcript assembly across over 1000 cancer cell lines.
  • Construction of a high-confidence RNA binding protein (RBP)-transcript regulatory network.

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  • Analysis of transcript associations with cancer hallmarks, clinical significance, and anti-cancer drug sensitivity.

    • Main Results:

    • Identification of 498,255 transcripts, with approximately half being unannotated.
    • Unannotated transcripts correlate with cancer hallmarks and clinical significance.
    • Discovery of numerous transcripts associated with anti-cancer drug sensitivity, including PTBP1-KIAA1522-a6 axis affecting decitabine sensitivity.
    • Establishment of a user-friendly data portal for cancer transcriptome exploration.

    Conclusions:

    • The study significantly expands the cancer RNA repository, providing transcript-level insights.
    • Identified unannotated transcripts and regulatory networks offer new avenues for understanding cancer biology.
    • The findings facilitate anti-cancer drug discovery and personalized medicine approaches.