Student Thesis Defense: Astor Ankney

Thesis title: Secretotranscriptomics: A Novel Approach to the Discovery of Liquid Biopsy Biomarkers for Breast Cancer Prognosis

Seminar is based upon the doctoral dissertation of Astor Ankney under the direction of Dr. Xian Chen

ABSTRACT

Presently, a 50-gene expression model (PAM50) serves as a breast cancer 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. To discover biomarkers to predict individualized prognosis we introduce a new multi-omics (secreto-transcriptomics) method that identifies, in their oncogenically secreted states, candidate markers of BC subtypes whose genes bear patient-specific mRNA expression alterations of prognostic significance. By combining LFQ secretome screening with proteo-transcriptomic retrospective analysis of patient data, our integrated multi-omics approach bypasses costly, tedious, genome-wide fishing and predictive modeling that are commonly required to distinguish a few prognostically altered genes from hundreds thousands of other non-BC related genes in a genome.