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      Genomic and Transcriptomic Determinants of Therapy Resistance and Immune Landscape Evolution during Anti-EGFR Treatment in Colorectal Cancer

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      1 , 11 , 2 , 11 , 1 , 11 , 1 , 11 , 1 , 1 , 1 , 3 , 3 , 1 , 1 , 1 , 5 , 2 , 2 , 1 , 2 , 6 , 2 , 2 , 2 , 2 , 5 , 2 , 7 , 7 , 8 , 9 , 3 , 6 , 10 , 1 , 2 , 2 , 2 , 2 , 4 , 2 , 12 , 1 , 2 , 12 , 13 ,
      Cancer Cell
      Cell Press
      cancer evolution, EGFR, drug resistance mechanisms, molecular subtype, colorectal cancer, cetuximab, predictive biomarker, immunotherapy, cancer genomics, cancer-associated fibroblasts

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          Summary

          Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRCs). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF1 and non-canonical RAS/RAF aberrations with primary resistance and validated transcriptomic CRC subtypes as non-genetic predictors of benefit. Sixty-four percent of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype at baseline to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PD-L1 and LAG3 immune checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy.

          Highlights

          • NF1 and non-canonical KRAS and BRAF aberrations associate with cetuximab resistance

          • Genetic resistance drivers are absent in most biopsies that acquired resistance

          • Stromal remodeling is an alternative non-genetic mechanism of cetuximab resistance

          • Cetuximab-mediated immune modulation may sensitize CRCs to immunotherapy

          Abstract

          Woolston et al. show that in metastatic colorectal cancer cetuximab resistance can be conferred by genetic mechanisms, such as NF1 loss or RAS/RAF alterations, or by transcriptomic changes that induce a stroma-rich phenotype. They also provide a rationale for combining cetuximab with immunotherapy.

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          Most cited references104

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Contributors
                Journal
                Cancer Cell
                Cancer Cell
                Cancer Cell
                Cell Press
                1535-6108
                1878-3686
                08 July 2019
                08 July 2019
                : 36
                : 1
                : 35-50.e9
                Affiliations
                [1 ]Translational Oncogenomics Lab, The Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, UK
                [2 ]GI Cancer Unit, The Royal Marsden Hospital, London SW3 6JJ, UK
                [3 ]Centre for Evolution and Cancer Bioinformatics Team, The Institute of Cancer Research, London SW3 6JB, UK
                [4 ]Systems and Precision Cancer Medicine Lab, The Institute of Cancer Research, London SW3 6JB, UK
                [5 ]Cancer Institute, University College London, London WC1E 6AG, UK
                [6 ]Tumour Microenvironment Lab, The Institute of Cancer Research, London SW3 6JB, UK
                [7 ]Department of Radiology, The Royal Marsden Hospital, London SW3 6JJ, UK
                [8 ]Departments of Pathology and Histopathology, University College Hospital, London NW1 2PG, UK
                [9 ]Barts Cancer Institute, Queen Mary University, London EC1M 6BQ, UK
                [10 ]Division of Structural Biology, The Institute of Cancer Research, London SW3 6JB, UK
                Author notes
                []Corresponding author marco.gerlinger@ 123456icr.ac.uk
                [11]

                These authors contributed equally

                [12]

                Senior author

                [13]

                Lead Contact

                Article
                S1535-6108(19)30255-7
                10.1016/j.ccell.2019.05.013
                6617392
                31287991
                2f37399c-169f-41d9-b3de-8d18c3cb71e9
                © 2019 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 9 November 2018
                : 1 April 2019
                : 23 May 2019
                Categories
                Article

                Oncology & Radiotherapy
                cancer evolution,egfr,drug resistance mechanisms,molecular subtype,colorectal cancer,cetuximab,predictive biomarker,immunotherapy,cancer genomics,cancer-associated fibroblasts

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