27
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Multiple ABCB1 transcriptional fusions in drug resistant high-grade serous ovarian and breast cancer

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          ABCB1 encodes Multidrug Resistance protein (MDR1), an ATP-binding cassette member involved in the cellular efflux of chemotherapeutic drugs. Here we report that ovarian and breast samples from chemotherapy treated patients are positive for multiple transcriptional fusions involving ABCB1, placing it under the control of a strong promoter while leaving its open reading frame intact. We identified 15 different transcriptional fusion partners involving ABCB1, as well as patients with multiple distinct fusion events. The partner gene selected depended on its structure, promoter strength, and chromosomal proximity to ABCB1. Fusion positivity was strongly associated with the number of lines of MDR1-substrate chemotherapy given. MDR1 inhibition in a fusion positive ovarian cancer cell line increased sensitivity to paclitaxel more than 50-fold. Convergent evolution of ABCB1 fusion is therefore frequent in chemotherapy resistant recurrent ovarian cancer. As most currently approved PARP inhibitors (PARPi) are MDR1 substrates, prior chemotherapy may precondition resistance to PARPi.

          Abstract

          ABCB1 encodes Multidrug Resistance Protein which promotes efflux of chemotherapeutic and targeted agents. Here, in breast and ovarian cancer the authors identify multiple transcriptional fusion partners involving ABCB1 that are associated with treatment failure and previous treatment regimens.

          Related collections

          Most cited references16

          • Record: found
          • Abstract: found
          • Article: not found

          Anchored multiplex PCR for targeted next-generation sequencing.

          We describe a rapid target enrichment method for next-generation sequencing, termed anchored multiplex PCR (AMP), that is compatible with low nucleic acid input from formalin-fixed paraffin-embedded (FFPE) specimens. AMP is effective in detecting gene rearrangements (without prior knowledge of the fusion partners), single nucleotide variants, insertions, deletions and copy number changes. Validation of a gene rearrangement panel using 319 FFPE samples showed 100% sensitivity (95% confidence limit: 96.5-100%) and 100% specificity (95% confidence limit: 99.3-100%) compared with reference assays. On the basis of our experience with performing AMP on 986 clinical FFPE samples, we show its potential as both a robust clinical assay and a powerful discovery tool, which we used to identify new therapeutically important gene fusions: ARHGEF2-NTRK1 and CHTOP-NTRK1 in glioblastoma, MSN-ROS1, TRIM4-BRAF, VAMP2-NRG1, TPM3-NTRK1 and RUFY2-RET in lung cancer, FGFR2-CREB5 in cholangiocarcinoma and PPL-NTRK1 in thyroid carcinoma. AMP is a scalable and efficient next-generation sequencing target enrichment method for research and clinical applications.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly

            The identification of genomic rearrangements with high sensitivity and specificity using massively parallel sequencing remains a major challenge, particularly in precision medicine and cancer research. Here, we describe a new method for detecting rearrangements, GRIDSS (Genome Rearrangement IDentification Software Suite). GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based assembler. By combining assembly, split read, and read pair evidence using a probabilistic scoring, GRIDSS achieves high sensitivity and specificity on simulated, cell line, and patient tumor data, recently winning SV subchallenge #5 of the ICGC-TCGA DREAM8.5 Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods while matching or exceeding their sensitivity. GRIDSS identifies nontemplate sequence insertions, microhomologies, and large imperfect homologies, estimates a quality score for each breakpoint, stratifies calls into high or low confidence, and supports multisample analysis.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Selective induction of chemotherapy resistance of mammary tumors in a conditional mouse model for hereditary breast cancer.

              We have studied in vivo responses of "spontaneous" Brca1- and p53-deficient mammary tumors arising in conditional mouse mutants to treatment with doxorubicin, docetaxel, or cisplatin. Like human tumors, the response of individual mouse tumors varies, but eventually they all become resistant to the maximum tolerable dose of doxorubicin or docetaxel. The tumors also respond well to cisplatin but do not become resistant, even after multiple treatments in which tumors appear to regrow from a small fraction of surviving cells. Classical biochemical resistance mechanisms, such as up-regulated drug transporters, appear to be responsible for doxorubicin resistance, rather than alterations in drug-damage effector pathways. Our results underline the promise of these mouse tumors for the study of tumor-initiating cells and of drug therapy of human cancer.
                Bookmark

                Author and article information

                Contributors
                d.bowtell@petermac.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                20 March 2019
                20 March 2019
                2019
                : 10
                : 1295
                Affiliations
                [1 ]ISNI 0000000403978434, GRID grid.1055.1, Peter MacCallum Cancer Centre, ; Melbourne, 3000 VIC Australia
                [2 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Sir Peter MacCallum Department of Oncology, , The University of Melbourne, ; Parkville, 3010 VIC Australia
                [3 ]ISNI 0000 0000 9983 6924, GRID grid.415306.5, Kinghorn Cancer Centre, , Garvan Institute for Medical Research, ; Darlinghurst, 2010 NSW Australia
                [4 ]ISNI 0000 0001 2193 0096, GRID grid.223827.e, The University of Utah, ; Salt Lake City, UT 84112 USA
                [5 ]Centre for Cancer Research, The Westmead Institute for Medical Research, Westmead, 2145 NSW Australia
                [6 ]ISNI 0000 0001 0180 6477, GRID grid.413252.3, Department of Gynaecological Oncology, , Westmead Hospital, ; Westmead, 2145 NSW Australia
                [7 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, The University of Sydney, ; Sydney, 2052 NSW Australia
                [8 ]GRID grid.492639.3, City of Hope, ; Los Angeles, CA 91010 USA
                Author information
                http://orcid.org/0000-0001-5518-7800
                http://orcid.org/0000-0002-4727-5533
                Article
                9312
                10.1038/s41467-019-09312-9
                6426934
                30894541
                fbb7ce28-b9c1-45cf-b867-604007ca930d
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 October 2018
                : 28 February 2019
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                Uncategorized

                Comments

                Comment on this article