Abstract

Abstract Breast cancer has a high annual incidence among females in India, with an age adjusted rate of 25.8 cases per 100,000 women and a mortality rate of 12.7 per 100,000 women1. Approximately 75% of breast cancers are estrogen receptor positive (ER+), and unfortunately, a significant number will develop resistance to first line hormonal therapy. Although several mechanisms have been linked to hormonal therapy resistance, no biomarker in clinical use currently exists to predict hormonal therapy resistance in a reliable manner. Comprehensive genomic profiling (CGP) is not routinely performed for metastatic breast carcinoma (MBC) in a relapsed setting in India. This research highlights utility of CGP on a MBC sample combined with interpretation by Watson™ for Genomics (WfG), an artificial-intelligence (AI)-based decision-support system (DSS), when a patient in a middle-income country developed resistance to endocrine therapy. A 33-year-old Indian female was diagnosed with ER+, progesterone-receptor-negative (PR-), human-epidermal-receptor-2-negative (HER2-) breast cancer. Two years later, she noted an axillary mass which was biopsied and revealed an ER+, PR-, HER2- MBC metastasis. CGP was performed with a panel from Illumina designed to detect genomic alterations in 170 genes, including 148 genes for substitutions and indels, 55 genes for fusion and splice variants, and 59 genes for copy number variation detection. Variant annotation and interpretation performed using WfG revealed co-existing ESR1 D538G mutation and ESR1-CCDC170 fusion. In addition, alterations in CCND1 resulting in activation of the CDK signaling pathway, an oncogenic mutation in MTOR resulting in activation of the MTOR/PI3K signaling pathway, and amplification of FGFR1, a poor prognostic factor in MBC, were also identified. While ESR1 D538 and ESR1-CCDC170 fusion individually have been reported to confer resistance to endocrine therapy, to the best of our knowledge, our report is the first HR+ MBC case with these two oncogenic alterations co-occurring in a metastatic tumor suggesting a synergistic role. CGP in this patient revealed a possible mechanism of resistance to endocrine therapy informing the physician to change treatment to a generic mTOR inhibitor based on the oncogenic MTOR mutation. In conclusion, assessment of DNA/RNA tumor variants in one assay along with a robust AI-based DSS can provide relevant information for consideration by the clinician when developing a treatment plan, may create efficiencies in tumor sample usage, time, and cost of treatment. Further research is needed to explore the functional synergy of the oncogenic ESR1 mutation and fusion detected in this patient's tumor and the role of identifying these pathogenic variants through circulating tumor cell or cell-free DNA assays to detect minimal residual disease. Citation Format: Ravindra Kolhe, Ashis Mondal, Nikhil Sahajpal, Meenakshi Ahluwalia, Yull Arriaga, Allan Njau, David Brotman, Jane Snowdon, Gretchen Jackson, Dilhan Weeraratne. Co-existing ESR1 D538G mutation and ESR1-CCDC170 fusion in a patient with metastatic hormone receptor positive breast cancer with progression after hormonal therapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4105.

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