Landscape of clinically actionable mutations in breast cancer ‘A cohort study’

• Main Authors: Mithua Ghosh, Radheshyam Naik, Sheela Mysore Lingaraju, Sridhar Papaiah Susheela, Shekar Patil, Gopinath Kodaganur Srinivasachar, Satheesh Chiradoni Thungappa, Krithika Murugan, Srinivas Belagutty Jayappa, Somorat Bhattacharjee, Nalini Rao, Mahesh Bandimegal, Roopesh Krishnappa, Shashidhara Haragadde Poppareddy, Krishna Chennagiri Raghavendrachar, Yogesh Shivakumar, Sunitha Nagesh, Ramya Kodandapani, Ashwini Rajan, Urvashi Bahadur, Pooja Agrawal, Veena Ramaswamy, Tejaswini Bangalore Nanjaiah, Sateesh Kunigal, Shanmukh Katragadda, Ashwini Manjunath, Amritanshu Ram, Basavalinga S. Ajaikumar
• Format: Article
• Language: English
• Published: Elsevier 2021-01-01
• Series: Translational Oncology
• Subjects: Breast cancer; Next generation sequencing; NGS; Genetic profiling; Somatic mutations: PIK3CA; Signalling pathway
• Online Access: http://www.sciencedirect.com/science/article/pii/S1936523320303697

Breast cancer (BC) is a heterogeneous disease. Numerous chemotherapeutic agents are available for early stage or advanced/metastatic breast cancer to provide maximum benefit with minimum side effects. However, the clinical outcome of patients with the same clinical and pathological characteristics and treated with similar treatments may show major differences and a vast majority of patients still develop treatment resistance and eventually succumb to disease. It remains an unmet need to identify specific molecular defects, new biomarkers to enable clinicians to adopt individualized treatment for every patient in terms of endocrine, chemotherapy or targeted therapy which will improve clinical outcomes in BC. Our study aimed to identify frequent hotspot mutation profile in BC by targeted deep sequencing in cancer-related genes using Illumina Truseq amplicon/Swift Accel-Amplicon panel and MiSeq technology in an IRB-approved prospective study in a CLIA compliant laboratory. All the cases had pathology review for stage, histological type, hormonal status and Ki-67. Data was processed using Strand NGS™. Mutations identified in the tumor were assessed for ‘actionability’ i.e. response to therapy and impact on prognosis.