Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer

Li Wang, John A. Wrobel, Ling Xie, Dong Xu Li, Giada Zurlo, Huali Shen, Pengyuan Yang, Zefeng Wang, Yibing Peng, Harsha P. Gunawardena, Qing Zhang, Xian Chen

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

To discriminate the patient subpopulations with different clinical outcomes within each breast cancer (BC) subtype, we introduce a robust, clinical-practical, activity-based proteogenomic method that identifies, in their oncogenically active states, candidate biomarker genes bearing patient-specific transcriptomic/genomic alterations of prognostic value. First, we used the intronic splicing enhancer (ISE) probes to sort ISE-interacting trans-acting protein factors (trans-interactome) directly from a tumor tissue for subsequent mass spectrometry characterization. In the retrospective, proteogenomic analysis of patient datasets, we identified those ISE trans-factor-encoding genes showing interaction-correlated expression patterns (iCEPs) as new BC-subtypic genes. Further, patient-specific co-alterations in mRNA expression of select iCEP genes distinguished high-risk patient subsets/subpopulations from other patients within a single BC subtype. Function analysis further validated a tumor-phenotypic trans-interactome contained the drivers of oncogenic splicing switches, representing the predominant tumor cells in a tissue, from which novel personalized biomarkers were clinically characterized/validated for precise prognostic prediction and subsequent individualized alignment of optimal therapy. The interpatient tumor-phenotypic heterogeneity hinders discovery of biomarkers for individualized prognosis. Wang and colleagues introduce an alternative splicing activity-based proteogenomic method that dissects tumor heterogeneity for de novo discovery of individualized prognostic biomarkers. The resulting biomarkers distinguish high-risk patient subpopulations from other patients within each single breast cancer subtype.

Original languageEnglish (US)
Pages (from-to)619-633.e5
JournalCell Chemical Biology
Volume25
Issue number5
DOIs
StatePublished - May 17 2018
Externally publishedYes

Fingerprint

Biomarkers
Tumors
RNA
Genes
Neoplasms
Breast Neoplasms
Bearings (structural)
Tissue
Gene encoding
Alternative Splicing
Set theory
Trans-Splicing
Mass spectrometry
Trans-Activators
Cells
Switches
Proteomics
Proteogenomics
Neoplasm Genes
Messenger RNA

Keywords

  • affinity proteomics
  • breast cancer
  • dissection of tumor heterogeneity
  • patient-specific prognostic markers
  • proteogenomics
  • quantitative proteomics
  • RNA-protein interactions

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Pharmacology
  • Drug Discovery
  • Clinical Biochemistry

Cite this

Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer. / Wang, Li; Wrobel, John A.; Xie, Ling; Li, Dong Xu; Zurlo, Giada; Shen, Huali; Yang, Pengyuan; Wang, Zefeng; Peng, Yibing; Gunawardena, Harsha P.; Zhang, Qing; Chen, Xian.

In: Cell Chemical Biology, Vol. 25, No. 5, 17.05.2018, p. 619-633.e5.

Research output: Contribution to journalArticle

Wang, L, Wrobel, JA, Xie, L, Li, DX, Zurlo, G, Shen, H, Yang, P, Wang, Z, Peng, Y, Gunawardena, HP, Zhang, Q & Chen, X 2018, 'Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer', Cell Chemical Biology, vol. 25, no. 5, pp. 619-633.e5. https://doi.org/10.1016/j.chembiol.2018.01.016
Wang, Li ; Wrobel, John A. ; Xie, Ling ; Li, Dong Xu ; Zurlo, Giada ; Shen, Huali ; Yang, Pengyuan ; Wang, Zefeng ; Peng, Yibing ; Gunawardena, Harsha P. ; Zhang, Qing ; Chen, Xian. / Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer. In: Cell Chemical Biology. 2018 ; Vol. 25, No. 5. pp. 619-633.e5.
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