JCO global oncology · 2024
Deep Diving Into the Fusion Across Cancer Types in the Indian Population From Formalin-Fixed Paraffin-Embedded RNA-Exome Data: A Road to Discovering Novel Rearrangements With Clinical Relevance.
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Khuntia Satya Prakash, Mukherjee Nilesh, Javle Vyomesh, Tanwar Nishtha AjitSingh, Sreekanthreddy Peddagangannagari, Varghese Linu, Gowda Pooja, Kottlahouse Anju, Chandrani Pratik, Choughule Anuradha, Pange Priyanka, Gupta Vinod, Noronha Vanita, Patil Vijay Maruti, Pramanik Raja, Kumar Sunil, Nayak Sandeep Peraje, Babu Suresh, Shetty Rohan, Kantharaju Madan, Chinder Pramod Shekarappa, Korlimarla Aruna, Srinath B S, Prabhash Kumar, Periyasamy Giridharan, Rishi Kshitij Datta, Goswami Hitesh Madan, Veldore Vidya Harini
Аннотация
PURPOSE: Gene fusions are critical oncogenic mutations that drive cancer development and serve as diagnostic and prognostic biomarkers. Despite the increasing cancer burden in India, large-scale analyses of molecular landscapes, particularly gene fusions, have been relatively scarce.
MATERIALS AND METHODS: This retrospective study used RNA-exome data from 1,392 Indian patients with cancer across 15 major cancer types to explore gene fusions. The study used a comprehensive framework that integrated open-source and proprietary tools to detect gene fusions from formalin-fixed paraffin-embedded tumor samples. The process involved RNA extraction, RNA-exome library preparation, and analysis using tools such as FastQC, DRAGEN RNA Pipeline, STAR-Fusion, and FusionInspector. We validated and filtered potential false-positive fusion calls using AGFusion and FusionAnnotator to annotate fusion breakpoints and their functional impact through various in silico tools.
RESULTS: The study found a notable prevalence of FGFR fusions across cancer types, especially FGFR3, with FGFR3::TACC3 as the most recurrent. Kinase fusions were prevalent in the cohort accounting for 37% of incidence in the patients. We also identified 91 novel potential driver fusions, including those involving FGFR2, MET, ESR1, and PDGFRA.
CONCLUSION: This study underscores the critical role of gene fusions as biomarkers in cancer, extending beyond fusion-driven malignancies to encompass all cancer types. Gene fusions serve as both diagnostic markers and tumor-agnostic therapeutic targets within the current cancer treatment paradigm. Our insights into the prevalence of oncogenic drivers and novel targets expand the understanding of gene fusions, shedding new light on their mechanisms and clinical implications.
MATERIALS AND METHODS: This retrospective study used RNA-exome data from 1,392 Indian patients with cancer across 15 major cancer types to explore gene fusions. The study used a comprehensive framework that integrated open-source and proprietary tools to detect gene fusions from formalin-fixed paraffin-embedded tumor samples. The process involved RNA extraction, RNA-exome library preparation, and analysis using tools such as FastQC, DRAGEN RNA Pipeline, STAR-Fusion, and FusionInspector. We validated and filtered potential false-positive fusion calls using AGFusion and FusionAnnotator to annotate fusion breakpoints and their functional impact through various in silico tools.
RESULTS: The study found a notable prevalence of FGFR fusions across cancer types, especially FGFR3, with FGFR3::TACC3 as the most recurrent. Kinase fusions were prevalent in the cohort accounting for 37% of incidence in the patients. We also identified 91 novel potential driver fusions, including those involving FGFR2, MET, ESR1, and PDGFRA.
CONCLUSION: This study underscores the critical role of gene fusions as biomarkers in cancer, extending beyond fusion-driven malignancies to encompass all cancer types. Gene fusions serve as both diagnostic markers and tumor-agnostic therapeutic targets within the current cancer treatment paradigm. Our insights into the prevalence of oncogenic drivers and novel targets expand the understanding of gene fusions, shedding new light on their mechanisms and clinical implications.