Clinical Proteomics of Breast Cancer Reveals a Novel Layer of Breast Cancer Classification.

Cancer Research
Gali YanovichTamar Geiger

Abstract

Breast cancer classification has been the focus of numerous worldwide efforts, analyzing the molecular basis of breast cancer subtypes and aiming to associate them with clinical outcome and to improve the current diagnostic routine. Genomic and transcriptomic profiles of breast cancer have been well established, however the proteomic contribution to these profiles has yet to be elucidated. In this work, we utilized mass spectrometry-based proteomic analysis on more than 130 clinical breast samples to demonstrate intertumor heterogeneity across three breast cancer subtypes and healthy tissue. Unsupervised analysis identified four proteomic clusters, among them, one that represents a novel luminal subtype characterized by increased PI3K signaling. This subtype was further validated using an independent protein-based dataset, but not in two independent transcriptome cohorts. These results demonstrate the importance of deep proteomic analysis, which may affect cancer treatment decision making.Significance: These findings utilize extensive proteomics to identify a novel luminal breast cancer subtype, highlighting the added value of clinical proteomics in breast cancer to identify unique features not observable by genomic approaches....Continue Reading

Citations

Apr 21, 2020·Expert Review of Proteomics·Aurora S BlucherYiu Huen Tsang
Sep 23, 2020·Molecular Systems Biology·Anjana ShenoyTamar Geiger
Oct 31, 2018·High-throughput·Maria Eugenia Gallo CantafioMaria Teresa Di Martino
Feb 11, 2020·Frontiers in Cell and Developmental Biology·Joseph Parsons, Chiara Francavilla
Feb 6, 2020·Journal of Lasers in Medical Sciences·Shabnam ShahrokhMohammadreza Razzaghi
Sep 29, 2019·International Journal of Molecular Sciences·Michael OlivierLaura A Cox
Jan 28, 2021·Cancer Research·Georgina D BarnabasTamar Geiger
Mar 18, 2020·Journal of Proteome Research·Marketa LastovickovaJanette Bobalova
Oct 1, 2021·Pathology Oncology Research : POR·Muhammad Ihtisham UmarXianju Huang

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