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      HSP70 Inhibition Blocks Adaptive Resistance and Synergizes with MEK Inhibition for the Treatment of NRAS-Mutant Melanoma

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          Abstract

          NRAS-mutant melanoma is currently a challenge to treat. This is due to an absence of inhibitors directed against mutant NRAS, along with adaptive and acquired resistance of this tumor type to inhibitors in the MAPK pathway. Inhibitors to MEK have shown some promise for NRAS-mutant melanoma. In this work, we explored the use of MEK inhibitors for NRAS-mutant melanoma. At the same time, we investigated the impact of the brain microenvironment, specifically astrocytes, on the response of a melanoma brain metastatic cell line to MEK inhibition. These parallel avenues led to the surprising finding that astrocytes enhance the sensitivity of melanoma tumors to MEK inhibitors (MEKi). We show that MEKi cause an upregulation of the transcriptional regulator ID3, which confers resistance. This upregulation of ID3 is blocked by conditioned media from astrocytes. We show that silencing ID3 enhances the sensitivity of melanoma to MEKi, thus mimicking the effect of the brain microenvironment. Moreover, we report that ID3 is a client protein of the chaperone HSP70, and that HSP70 inhibition causes ID3 to misfold and accumulate in a detergent-insoluble fraction in cells. We show that HSP70 inhibitors synergize with MEKi against NRAS-mutant melanoma, and that this combination significantly enhances the survival of mice in two different models of NRAS-mutant melanoma. These studies highlight ID3 as a mediator of adaptive resistance, and support the combined use of MEK and HSP70 inhibitors for the therapy of NRAS-mutant melanoma.

          Significance:

          MEKi are currently used for NRAS-mutant melanoma, but have shown modest efficacy as single agents. This research shows a synergistic effect of combining HSP70 inhibitors with MEKi for the treatment of NRAS mutant melanoma.

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          Most cited references50

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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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            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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              RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

              Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing - original draftRole: Writing - review and editing
                Role: InvestigationRole: Writing - review and editing
                Role: InvestigationRole: Writing - review and editing
                Role: InvestigationRole: Writing - review and editing
                Role: InvestigationRole: Writing - review and editing
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: Formal analysisRole: Writing - review and editing
                Role: InvestigationRole: Writing - review and editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: Writing - review and editing
                Role: ConceptualizationRole: Writing - review and editing
                Role: ConceptualizationRole: InvestigationRole: Writing - review and editing
                Role: ConceptualizationRole: SupervisionRole: Funding acquisitionRole: ValidationRole: InvestigationRole: Writing - original draftRole: Project administrationRole: Writing - review and editing
                Journal
                Cancer Res Commun
                Cancer Res Commun
                Cancer Research Communications
                American Association for Cancer Research
                2767-9764
                October 2021
                13 October 2021
                : 1
                : 1
                : 17-29
                Affiliations
                [1 ]Program(s) in Molecular and Cellular Oncogenesis, The Wistar Institute, Philadelphia, Pennsylvania.
                [2 ]Graduate Group in Cell and Molecular Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
                [3 ]Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
                [4 ]Immunology, Microenvironment and Metastasis, The Wistar Institute, Philadelphia, Pennsylvania.
                [5 ]Gene Expression and Regulation, The Wistar Institute, Philadelphia, Pennsylvania.
                [6 ]Department of Biochemistry and Molecular Biology, Johns Hopkins University, Baltimore, Maryland 21205.
                Author notes
                Corresponding Author: Maureen Murphy, The Wistar Institute, 3601 Spruce Street, Room 356, Philadelphia, PA 19104. Phone: 215-495-6870; E-mail: mmurphy@ 123456wistar.org
                Author information
                https://orcid.org/0000-0003-2174-823X
                https://orcid.org/0000-0001-9682-9160
                https://orcid.org/0000-0001-5907-2859
                https://orcid.org/0000-0001-6288-9229
                https://orcid.org/0000-0001-9964-580X
                https://orcid.org/0000-0002-2184-5980
                Article
                CRC-21-0033
                10.1158/2767-9764.CRC-21-0033
                8849551
                35187538
                161a8308-ec76-4223-adc2-d04b76dfbfd8
                © 2021 The Authors; Published by the American Association for Cancer Research

                This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

                History
                : 16 August 2021
                : 17 August 2021
                : 20 September 2021
                Page count
                Pages: 13
                Funding
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA114046
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA139319
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA139319
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA241490
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA009171
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA009171
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: CA009171
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100000054, HHS | NIH | National Cancer Institute (NCI);
                Award ID: K99CA241367
                Award Recipient :
                Categories
                Research Article
                Tumor Microenvironment
                Host-Tumor Interactions
                Progression, Invasion & Metastasis
                Cell Signaling
                Protein Serine-Threonine Kinases
                Small Molecule Agents
                Skin Cancers
                Melanoma
                Drug Mechanisms
                Drug Resistance
                Reversal of Drug Resistance
                Custom metadata
                true

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