Integrated Proteogenomic Analysis Reveals Distinct Potentially Actionable Therapeutic Vulnerabilities in Triple-Negative Breast Cancer Subtypes

Pushpinder Kaur; Alexander Ring; Tania B Porras; Guang Zhou; Janice Lu; Irene Kang; Julie E Lang

doi:10.3390/cancers16030516

Integrated Proteogenomic Analysis Reveals Distinct Potentially Actionable Therapeutic Vulnerabilities in Triple-Negative Breast Cancer Subtypes

Cancers (Basel). 2024 Jan 25;16(3):516. doi: 10.3390/cancers16030516.

Authors

Pushpinder Kaur^{1

2}, Alexander Ring³, Tania B Porras⁴, Guang Zhou⁵, Janice Lu^{2

6}, Irene Kang^{2

6}, Julie E Lang^{1

2

5}

Affiliations

¹ Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
² Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.
³ Department of Medical Oncology and Hematology, University Hospital Zürich, 8091 Zurich, Switzerland.
⁴ Cancer and Blood Disease Institute, Children Hospital Los Angeles, University of Southern California, Los Angeles, CA 90027, USA.
⁵ Division of Breast Services, Department of General Surgery, Digestive Disease and Surgery Institute, Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
⁶ Division of Medical Oncology, Department of Medicine, University of Southern California Norris Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.

Abstract

Triple-negative breast cancer (TNBC) is characterized by an aggressive clinical presentation and a paucity of clinically actionable genomic alterations. Here, we utilized the Cancer Genome Atlas (TCGA) to explore the proteogenomic landscape of TNBC subtypes to see whether genomic alterations can be inferred from proteomic data. We found only 4% of the protein level changes are explained by mutations, while 21% of the protein and 35% of the transcriptomics changes were determined by copy number alterations (CNAs). We found tighter coupling between proteome and genome in some genes that are predicted to be the targets of drug inhibitors, including CDKs, PI3K, tyrosine kinase (TKI), and mTOR. The validation of our proteogenomic workflow using mass spectrometry Clinical Proteomic Tumor Analysis Consortium (MS-CPTAC) data also demonstrated the highest correlation between protein-RNA-CNA. The integrated proteogenomic approach helps to prioritize potentially actionable targets and may enable the acceleration of personalized cancer treatment.

Keywords: TNBC; breast cancer; genomic; proteomic; transcriptomic.

Grants and funding

The project was supported in part by award number P30CA014089 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institute of Health. The project was also supported by the Woodbury Foundation.