Dataset Information

Clinical Proteomics of Breast Cancer Unravels a Novel Layer of Breast Cancer Classification

ABSTRACT: Breast cancer classification has been in the focus of numerous large worldwide efforts, analyzing the molecular basis of breast cancer subtypes, aiming to associate them with clinical outcome and improve the current diagnostic routine. Genomic and transcriptomic profiles of breast cancer have been well established, however the proteomic contribution to these profiles is yet to be elucidated. In this work, we examined inter-tumor heterogeneity by performing a mass-spectrometry (MS)-based proteomic analysis of more than 130 clinical breast samples originating from 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 cancer signaling. This subtype was further validated using an independent protein-based dataset, but not in two independent transcriptome cohorts. Altogether, our results demonstrate the importance of deep proteomic analysis, which may affect cancer treatment decision making.

INSTRUMENT(S): Q Exactive Plus, Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Breast Cancer Cell

DISEASE(S): Breast Cancer

SUBMITTER: Tamar Geiger

LAB HEAD: Tamar Geiger

PROVIDER: PXD009766 | Pride | 2019-07-29

REPOSITORIES: Pride

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Publications

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

Yanovich Gali G Agmon Hadar H Harel Michal M Sonnenblick Amir A Peretz Tamar T Geiger Tamar T

Cancer research 20180828 20

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 sampl ...[more]

PMID: 30154156

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Project description:A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. In this study, we have conducted a prospective sample collection and retrospective blinded validation (PRoBE design) to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatants respectively. Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven transcriptomic biomarker candidates and two proteomic biomarker candidates were selected for a preclinical validation using an independent sample set. Transcriptomic biomarkers were validated by RT-qPCR and proteomic biomarkers were validated by quantitative protein immunoblot. Eight mRNA biomarkers and one protein biomarker have been validated for breast cancer detection, yielding ROC-plot AUC values between 0.665 and 0.959. This report provides proof of concept of salivary biomarkers for the non-invasive detection of breast cancer. The salivary biomarkersâ discriminatory power paves the way for a PRoBE-design definitive validation study. Keywords: Salivary biomarker, Breast cancer, Early detection, Salivary transcriptome, Salivary proteome This study, which was approved by the UCLA and Cedars-Sinai Medical Center Institutional Review Boards (#06-07-043 and #3870, respectively), started sample collection in February 2007. The sample collection followed the PRoBE principle (prospective specimen collection). The saliva bank for breast cancer project at the UCLA Dental Research Institute in collaboration with Cedars Sinai Medical Center has collected 200 saliva samples since 2007 with all subjects recruited from the Saul and Joyce Brandman Breast Cancer Center. Of these, 113 samples, including 41 breast cancer patients and 72 healthy control individuals, were selected for the discovery and validation phase of this study. Inclusion criteria of cancer patients consisted of a confirmed diagnosis of breast cancer. Exclusion criteria of cancer patients included therapy/surgery and/or a diagnosis of other malignancies within 5 years prior to saliva collection. Exclusion criteria of control patients included a diagnosis of any malignancies within 5 years prior to saliva collection. Written informed consents and questionnaire data sheets were obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were consistently collected, stabilized, and preserved as previously described. The sample supernatants were reserved at -80 C prior to assay. This study consisted of a discovery phase, followed by an independent preclinical validation phase. Of the 113 samples, 10 breast cancer samples and 10 healthy control samples were chosen for the discovery phase. All breast cancer cases are invasive ductal carcinoma (IDC), the most common type of breast cancer. Biomarkers identified from the discovery studies were first verified using the discovery sample set. An independent sample set, including 31 breast cancer patients and 62 healthy control subjects, was used for the biomarker validation phase.

Dataset Information

Clinical Proteomics of Breast Cancer Unravels a Novel Layer of Breast Cancer Classification

Publications

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

Similar Datasets

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