8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Integrative molecular characterization of sarcomatoid and rhabdoid renal cell carcinoma

      research-article
      1 , 1 , 2 , 1 , 3 , 2 , 4 , 1 , 1 , 1 , 1 , 1 , 5 , 1 , 1 , 1 , 1 , 1 , 1 , 4 , 4 , 1 , 2 , 6 , 1 , 7 , 1 , 1 , 1 , 4 , 1 , 1 , 8 , 8 , 1 , 1 , 1 , 1 , 1 , 1 , 9 , 4 , 10 , 1 , 4 , 1 , 11 , 1 , 6 , 12 , 13 , 14 , 7 , 1 , 4 , 10 , 1 , , 1 ,
      Nature Communications
      Nature Publishing Group UK
      Cancer genomics, Tumour heterogeneity, Tumour immunology, Renal cell carcinoma, Immunization

      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

          Sarcomatoid and rhabdoid (S/R) renal cell carcinoma (RCC) are highly aggressive tumors with limited molecular and clinical characterization. Emerging evidence suggests immune checkpoint inhibitors (ICI) are particularly effective for these tumors, although the biological basis for this property is largely unknown. Here, we evaluate multiple clinical trial and real-world cohorts of S/R RCC to characterize their molecular features, clinical outcomes, and immunologic characteristics. We find that S/R RCC tumors harbor distinctive molecular features that may account for their aggressive behavior, including BAP1 mutations, CDKN2A deletions, and increased expression of MYC transcriptional programs. We show that these tumors are highly responsive to ICI and that they exhibit an immune-inflamed phenotype characterized by immune activation, increased cytotoxic immune infiltration, upregulation of antigen presentation machinery genes, and PD-L1 expression. Our findings build on prior work and shed light on the molecular drivers of aggressivity and responsiveness to ICI of S/R RCC.

          Abstract

          Sarcomatoid and rhabdoid tumours are highly aggressive forms of renal cell carcinoma that are also responsive to immunotherapy. In this study, the authors perform a comprehensive molecular characterization of these tumours discovering an enrichment of specific alterations and an inflamed phenotype.

          Related collections

          Most cited references73

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

          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              KEGG: kyoto encyclopedia of genes and genomes.

              M Kanehisa (2000)
              KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
                Bookmark

                Author and article information

                Contributors
                eliezerm_vanallen@dfci.harvard.edu
                Toni_Choueiri@dfci.harvard.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                5 February 2021
                5 February 2021
                2021
                : 12
                : 808
                Affiliations
                [1 ]GRID grid.65499.37, ISNI 0000 0001 2106 9910, Department of Medical Oncology, , Dana-Farber Cancer Institute, ; Boston, MA USA
                [2 ]GRID grid.65499.37, ISNI 0000 0001 2106 9910, Translational Immunogenomics Laboratory, , Dana-Farber Cancer Institute, ; Boston, MA USA
                [3 ]GRID grid.32224.35, ISNI 0000 0004 0386 9924, Department of Medicine, Massachusetts General Hospital Cancer Center, ; Boston, MA USA
                [4 ]GRID grid.62560.37, ISNI 0000 0004 0378 8294, Department of Pathology, Brigham and Women’s Hospital, ; Boston, MA USA
                [5 ]GRID grid.65499.37, ISNI 0000 0001 2106 9910, Department of Data Sciences, Dana-Farber Cancer Institute, ; Boston, MA USA
                [6 ]GRID grid.66859.34, Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [7 ]GRID grid.22072.35, ISNI 0000 0004 1936 7697, Tom Baker Cancer Centre, , University of Calgary, ; Calgary, AB Canada
                [8 ]GRID grid.419971.3, Bristol-Myers Squibb, ; Princeton, NJ USA
                [9 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Genomic Medicine, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA
                [10 ]GRID grid.65499.37, ISNI 0000 0001 2106 9910, Department of Oncologic Pathology, , Dana-Farber Cancer Institute, ; Boston, MA USA
                [11 ]GRID grid.411667.3, ISNI 0000 0001 2186 0438, Lombardi Comprehensive Cancer Center, , Georgetown University Medical Center, ; Washington, DC USA
                [12 ]GRID grid.417468.8, ISNI 0000 0000 8875 6339, Division of Hematology and Medical Oncology, Mayo Clinic, ; Scottsdale, AZ USA
                [13 ]GRID grid.420086.8, ISNI 0000 0001 2237 2479, Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, ; Bethesda, MD USA
                [14 ]GRID grid.239395.7, ISNI 0000 0000 9011 8547, Beth Israel Deaconess Medical Center, ; Boston, MA USA
                Author information
                http://orcid.org/0000-0003-1906-5704
                http://orcid.org/0000-0003-4543-5553
                http://orcid.org/0000-0003-2445-3584
                http://orcid.org/0000-0001-5492-9796
                http://orcid.org/0000-0002-3766-5335
                http://orcid.org/0000-0002-8084-9105
                http://orcid.org/0000-0002-7073-3432
                http://orcid.org/0000-0002-5618-8079
                http://orcid.org/0000-0002-2005-9267
                http://orcid.org/0000-0002-7607-2428
                http://orcid.org/0000-0003-4739-5049
                http://orcid.org/0000-0002-3348-5054
                http://orcid.org/0000-0003-0023-2939
                http://orcid.org/0000-0001-7983-3109
                http://orcid.org/0000-0002-2675-5095
                http://orcid.org/0000-0003-1856-3023
                http://orcid.org/0000-0002-0201-4444
                http://orcid.org/0000-0002-9201-3217
                Article
                21068
                10.1038/s41467-021-21068-9
                7865061
                33547292
                590d8a91-4993-47c6-a728-be0f6d841b74
                © The Author(s) 2021

                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
                : 19 May 2020
                : 4 January 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000090, United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs (CDMRP);
                Award ID: W81XWH-18-1-0480
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100002491, Bristol-Myers Squibb (Bristol-Myers Squibb Company);
                Funded by: FundRef https://doi.org/10.13039/100000054, U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI);
                Award ID: R50RCA211482
                Award ID: R01 CA224917
                Award ID: R01 CA227388
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100004097, Fondation ARC pour la Recherche sur le Cancer (ARC Foundation for Cancer Research);
                Funded by: FundRef https://doi.org/10.13039/100003064, Kidney Cancer Association (KCA);
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                cancer genomics,tumour heterogeneity,tumour immunology,renal cell carcinoma,immunization

                Comments

                Comment on this article