Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients.

Affiliation

Department of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. [Email]

Abstract

Presently, a 50-gene expression model (PAM50) serves as a breast cancer (BC) subtype classifier that is insufficient to distinguish, within each single PAM50-classified subtype, patient subpopulations having different prognosis. There is a pressing need for inexpensive and minimally invasive biomarker tests to easily and accurately predict individuals' clinical outcomes and response to treatments. Although quantitative proteomic approaches have been developed to identify/profile proteins secreted (secretome) from various cancer cell lines in vitro, missing are the clinicopathological relevance and the associated prognostic value of these secretomic identifications.

Keywords

Label-free quantitative proteomics,Multi-omics correlations,Patient survival analysis,Protein secretion,Secretion-correlated expression pattern,TCGA,

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