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      EGFR G796D mutation mediates resistance to osimertinib

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          Abstract

          Osimertinib is an effective third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) approved in multiple countries and regions for patients with EGFR T790M mutation-positive non-small cell lung cancer (NSCLC). Despite impressive initial tumor responses, development of drug resistance ultimately limits the benefit of this compound. Mechanisms of resistance to osimertinib are just beginning to emerge, such as EGFR C797S and L718Q mutations, BRAF V600E and PIK3CA E545K mutations, as well as ERBB2 and MET amplification. However, a comprehensive view is still missing. In this study, we presented the first case of Chinese NSCLC patient who developed resistance to osimertinib, and discovered de novo EGFR G796D mutation as a potential mechanism. Our findings provided insights into mechanisms of resistance to osimertinib and highlighted tumor heterogeneity and clonal evolution during the development of drug resistance.

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          SAMBLASTER: fast duplicate marking and structural variant read extraction

          Gregory Faust, Ira Hall (2014)
          Motivation: Illumina DNA sequencing is now the predominant source of raw genomic data, and data volumes are growing rapidly. Bioinformatic analysis pipelines are having trouble keeping pace. A common bottleneck in such pipelines is the requirement to read, write, sort and compress large BAM files multiple times. Results: We present SAMBLASTER, a tool that reduces the number of times such costly operations are performed. SAMBLASTER is designed to mark duplicates in read-sorted SAM files as a piped post-pass on DNA aligner output before it is compressed to BAM. In addition, it can simultaneously output into separate files the discordant read-pairs and/or split-read mappings used for structural variant calling. As an alignment post-pass, its own runtime overhead is negligible, while dramatically reducing overall pipeline complexity and runtime. As a stand-alone duplicate marking tool, it performs significantly better than PICARD or SAMBAMBA in terms of both speed and memory usage, while achieving nearly identical results. Availability and implementation: SAMBLASTER is open-source C++ code and freely available for download from https://github.com/GregoryFaust/samblaster. Contact: imh4y@virginia.edu
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            Acquired resistance to TKIs in solid tumours: learning from lung cancer.

            D. Ross Camidge, William Pao, Lecia V. Sequist (2014)
            The use of advanced molecular profiling to direct the use of targeted therapy, such as tyrosine kinase inhibitors (TKIs) for patients with advanced-stage non-small-cell lung cancer (NSCLC), has revolutionized the treatment of this disease. However, acquired resistance, defined as progression after initial benefit, to targeted therapies inevitably occurs. This Review explores breakthroughs in the understanding and treatment of acquired resistance in NSCLC, focusing on EGFR mutant and ALK rearrangement-positive disease, which may be relevant across multiple different solid malignancies with oncogene-addicted subtypes. Mechanisms of acquired resistance may be pharmacological (that is, failure of delivery of the drug to its target) or biological, resulting from evolutionary selection on molecularly diverse tumours. A number of clinical approaches can maintain control of the disease in the acquired resistance setting, including the use of radiation to treat isolated areas of progression and adding or switching to cytotoxic chemotherapy. Furthermore, novel approaches that have already proven successful include the development of second-generation and third-generation inhibitors and the combination of some of these inhibitors with antibodies directed against the same target. With our increased understanding of the spectrum of acquired resistance, major changes in how we conduct clinical research in this setting are now underway.
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              Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients

              Jacob Chabon, Andrew D. Simmons, Alexander Lovejoy … (2016)
              Circulating tumour DNA (ctDNA) analysis facilitates studies of tumour heterogeneity. Here we employ CAPP-Seq ctDNA analysis to study resistance mechanisms in 43 non-small cell lung cancer (NSCLC) patients treated with the third-generation epidermal growth factor receptor (EGFR) inhibitor rociletinib. We observe multiple resistance mechanisms in 46% of patients after treatment with first-line inhibitors, indicating frequent intra-patient heterogeneity. Rociletinib resistance recurrently involves MET, EGFR, PIK3CA, ERRB2, KRAS and RB1. We describe a novel EGFR L798I mutation and find that EGFR C797S, which arises in ∼33% of patients after osimertinib treatment, occurs in <3% after rociletinib. Increased MET copy number is the most frequent rociletinib resistance mechanism in this cohort and patients with multiple pre-existing mechanisms (T790M and MET) experience inferior responses. Similarly, rociletinib-resistant xenografts develop MET amplification that can be overcome with the MET inhibitor crizotinib. These results underscore the importance of tumour heterogeneity in NSCLC and the utility of ctDNA-based resistance mechanism assessment.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Oncotarget
                Journal ID (iso-abbrev): Oncotarget
                Journal ID (publisher-id): Oncotarget
                Journal ID (publisher-id): ImpactJ
                Title: Oncotarget
                Publisher: Impact Journals LLC
                ISSN (Electronic): 1949-2553
                Publication date Collection: 25 July 2017
                Publication date (Electronic): 16 May 2017
                Volume: 8
                Issue: 30
                Pages: 49671-49679
                Affiliations
                1 Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School, Shanghai, China
                2 IMED Asia, AstraZeneca, Shanghai, China
                3 Research and Development Information, AstraZeneca, Shanghai, China
                4 Department of Pathology, Shanghai Pulmonary Hospital, Tongji University Medical School, Shanghai, China
                Author notes
                Correspondence to: Jianfang Xu, xujianfang63@ 123456aliyun.com
                Article
                Publisher ID: 17913
                DOI: 10.18632/oncotarget.17913
                PMC ID: 5564797
                PubMed ID: 28572531
                SO-VID: 99494b36-a9b3-4a9e-baf5-8ee05d4b0d86
                Copyright © Copyright: © 2017 Zheng et al.
                License:

                This article is distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                Date received : 8 March 2017
                Date accepted : 4 May 2017
                Categories
                Subject: Research Paper

                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: egfr,nsclc,osimertinib,drug resistance,g796d
                Data availability:
                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: egfr, nsclc, osimertinib, drug resistance, g796d

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