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      TFEB-mediated lysosomal biogenesis and lysosomal drug sequestration confer resistance to MEK inhibition in pancreatic cancer

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          Abstract

          Oncogenic KRAS mutations are encountered in more than 90% of pancreatic ductal adenocarcinomas. MEK inhibition has failed to procure any clinical benefits in mutant RAS-driven cancers including pancreatic ductal adenocarcinoma (PDAC). To identify potential resistance mechanisms underlying MEK inhibitor (MEKi) resistance in PDAC, we investigated lysosomal drug accumulation in PDAC models both in vitro and in vivo. Mouse PDAC models and human PDAC cell lines as well as human PDAC xenografts treated with the MEK inhibitor trametinib or refametinib led to an enhanced expression of lysosomal markers and enrichment of lysosomal gene sets. A time-dependent, increase in lysosomal content was observed upon MEK inhibition. Strikingly, there was a strong activation of lysosomal biogenesis in cell lines of the classical compared to the basal-like molecular subtype. Increase in lysosomal content was associated with nuclear translocation of the Transcription Factor EB ( TFEB) and upregulation of TFEB target genes. siRNA-mediated depletion of TFEB led to a decreased lysosomal biogenesis upon MEK inhibition and potentiated sensitivity. Using LC-MS, we show accumulation of MEKi in the lysosomes of treated cells. Therefore, MEK inhibition triggers lysosomal biogenesis and subsequent drug sequestration. Combined targeting of MEK and lysosomal function may improve sensitivity to MEK inhibition in PDAC.

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          Most cited references37

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          Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma

          (2017)
          We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine.
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            High-throughput oncogene mutation profiling in human cancer.

            Systematic efforts are underway to decipher the genetic changes associated with tumor initiation and progression. However, widespread clinical application of this information is hampered by an inability to identify critical genetic events across the spectrum of human tumors with adequate sensitivity and scalability. Here, we have adapted high-throughput genotyping to query 238 known oncogene mutations across 1,000 human tumor samples. This approach established robust mutation distributions spanning 17 cancer types. Of 17 oncogenes analyzed, we found 14 to be mutated at least once, and 298 (30%) samples carried at least one mutation. Moreover, we identified previously unrecognized oncogene mutations in several tumor types and observed an unexpectedly high number of co-occurring mutations. These results offer a new dimension in tumor genetics, where mutations involving multiple cancer genes may be interrogated simultaneously and in 'real time' to guide cancer classification and rational therapeutic intervention.
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              Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer: Early Results from the COMPASS Trial

              Purpose: To perform real-time whole genome sequencing (WGS) and RNA sequencing (RNASeq) of advanced pancreatic ductal adenocarcinoma (PDAC) to identify predictive mutational and transcriptional features for better treatment selection.Experimental Design: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy. Fresh tumor tissue was acquired by image-guided percutaneous core biopsy for WGS and RNASeq. Laser capture microdissection was performed for all cases. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures.Results: Sixty-three patients underwent a tumor biopsy between December 2015 and June 2017. WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range, 19-52 days) from biopsy, meeting the primary feasibility endpoint. Objective responses to first-line chemotherapy were significantly better in patients with the classical PDAC RNA subtype compared with those with the basal-like subtype (P = 0.004). The best progression-free survival was observed in those with classical subtype treated with m-FOLFIRINOX. GATA6 expression in tumor measured by RNA in situ hybridization was found to be a robust surrogate biomarker for differentiating classical and basal-like PDAC subtypes. Potentially actionable genetic alterations were found in 30% of patients.Conclusions: Prospective genomic profiling of advanced PDAC is feasible, and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes. Clin Cancer Res; 24(6); 1344-54. ©2017 AACR.
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                Author and article information

                Contributors
                j.siveke@dkfz.de
                Journal
                Cell Death Discov
                Cell Death Discov
                Cell Death Discovery
                Nature Publishing Group UK (London )
                2058-7716
                11 March 2020
                11 March 2020
                2020
                : 6
                : 12
                Affiliations
                [1 ]Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, partner site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany, Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, partner site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany, Essen, Germany
                [2 ]Institute for Developmental Cancer Therapeutics, West German Cancer Center, University Hospital Essen, Essen, Germany, Heidelberg, Germany
                [3 ]GRID grid.452435.1, Department of Hepatobiliary Surgery, , the First Affiliated Hospital of Dalian Medical University, ; Dalian, Liaoning Province China
                [4 ]ISNI 0000 0001 0262 7331, GRID grid.410718.b, Dept Med Oncol, , West German Cancer Center, University Hospital Essen, ; Essen, Germany
                [5 ]ISNI 0000 0001 0262 7331, GRID grid.410718.b, Institute for Cell Biology, University Hospital Essen, ; Essen, Germany
                [6 ]ISNI 0000 0001 0262 7331, GRID grid.410718.b, Translational Genomics in Solid Tumors, , West German Cancer Center, University Hospital Essen, ; Essen, Germany
                [7 ]EPO – Experimental Pharmacology and Oncology GmbH Berlin-Buch, Berlin, Germany
                [8 ]ISNI 0000 0004 0490 981X, GRID grid.5570.7, Department of Molecular GI-Oncology, Rurh University Bochum, ; Bochum, Germany
                Author information
                http://orcid.org/0000-0002-8772-4778
                http://orcid.org/0000-0002-2776-6706
                Article
                246
                10.1038/s41420-020-0246-7
                7066197
                32194992
                a2fb99f2-5265-4b52-985e-2584dd4f88dc
                © The Author(s) 2020

                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 2019
                : 20 February 2020
                : 24 February 2020
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                © The Author(s) 2020

                targeted therapies
                targeted therapies

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