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Updated: Feb 27, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Discovery of putative breast cancer antigens using an integrative platform of genomics-driven immunoproteomics
Veneta Qendro1, Deborah H Lundgren1, Samuel Palczewski1
1Center for Vascular Biology, Department of Cell Biology, University of Connecticut School of Medicine, Farmington, CT, USA.
Abstract:
Recent advances in cancer immuno-therapeutics such as checkpoint inhibitors, chimeric antigen-receptor T cells, and tumor infiltrating T cells (TIL) are now significantly impacting cancer patients in a positive manner. Although very promising, reports indicate no more than 25% of cases result in complete remission. One of the limitations of these treatments is the identity of putative cancer antigens in each patient, as it is technically challenging to identify cancer antigens in a rapid fashion. Thus, identification of cancer antigens followed by targeted treatment will increase the efficacy of cancer immunotherapies. To achieve this goal, a combined technologies platform of deep genomic sequencing and personalized immune assessment was devised, termed Genomics Driven Immunoproteomics (GDI). Using this technological platform, we report the discovery of 149 tumor antigens from human breast cancer patients. Significant number of these putative cancer antigens arise from single nucleotide variants (SNVs), as well as insertions and deletions that results into frame-shift mutations. We propose a general model of anti-cancer immunity and suggest that the GDI platform may help identify patient-specific tumor antigens in a timely fashion for precision immunotherapies.
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