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Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different -omics technologies to identify ccRCC-specific HL...

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Autores principales: Reustle, Anna, Di Marco, Moreno, Meyerhoff, Carolin, Nelde, Annika, Walz, Juliane S., Winter, Stefan, Kandabarau, Siahei, Büttner, Florian, Haag, Mathias, Backert, Linus, Kowalewski, Daniel J., Rausch, Steffen, Hennenlotter, Jörg, Stühler, Viktoria, Scharpf, Marcus, Fend, Falko, Stenzl, Arnulf, Rammensee, Hans-Georg, Bedke, Jens, Stevanović, Stefan, Schwab, Matthias, Schaeffeler, Elke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106651/
https://www.ncbi.nlm.nih.gov/pubmed/32228647
http://dx.doi.org/10.1186/s13073-020-00731-8
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author Reustle, Anna
Di Marco, Moreno
Meyerhoff, Carolin
Nelde, Annika
Walz, Juliane S.
Winter, Stefan
Kandabarau, Siahei
Büttner, Florian
Haag, Mathias
Backert, Linus
Kowalewski, Daniel J.
Rausch, Steffen
Hennenlotter, Jörg
Stühler, Viktoria
Scharpf, Marcus
Fend, Falko
Stenzl, Arnulf
Rammensee, Hans-Georg
Bedke, Jens
Stevanović, Stefan
Schwab, Matthias
Schaeffeler, Elke
author_facet Reustle, Anna
Di Marco, Moreno
Meyerhoff, Carolin
Nelde, Annika
Walz, Juliane S.
Winter, Stefan
Kandabarau, Siahei
Büttner, Florian
Haag, Mathias
Backert, Linus
Kowalewski, Daniel J.
Rausch, Steffen
Hennenlotter, Jörg
Stühler, Viktoria
Scharpf, Marcus
Fend, Falko
Stenzl, Arnulf
Rammensee, Hans-Georg
Bedke, Jens
Stevanović, Stefan
Schwab, Matthias
Schaeffeler, Elke
author_sort Reustle, Anna
collection PubMed
description BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different -omics technologies to identify ccRCC-specific HLA-presented peptides as potential drug targets for ccRCC immunotherapy. METHODS: We analyzed HLA-presented peptides by MS-based ligandomics of 55 ccRCC tumors (cohort 1), paired non-tumor renal tissues, and 158 benign tissues from other organs. Pathways enriched in ccRCC compared to its cell type of origin were identified by transcriptome and gene set enrichment analyses in 51 tumor tissues of the same cohort. To retrieve a list of candidate targets with involvement in ccRCC pathogenesis, ccRCC-specific pathway genes were intersected with the source genes of tumor-exclusive peptides. The candidates were validated in an independent cohort from The Cancer Genome Atlas (TCGA KIRC, n = 452). DNA methylation (TCGA KIRC, n = 273), somatic mutations (TCGA KIRC, n = 392), and gene ontology (GO) and correlations with tumor metabolites (cohort 1, n = 30) and immune-oncological markers (cohort 1, n = 37) were analyzed to characterize regulatory and functional involvements. CD8(+) T cell priming assays were used to identify immunogenic peptides. The candidate gene EGLN3 was functionally investigated in cell culture. RESULTS: A total of 34,226 HLA class I- and 19,325 class II-presented peptides were identified in ccRCC tissue, of which 443 class I and 203 class II peptides were ccRCC-specific and presented in ≥ 3 tumors. One hundred eighty-five of the 499 corresponding source genes were involved in pathways activated by ccRCC tumors. After validation in the independent cohort from TCGA, 113 final candidate genes remained. Candidates were involved in extracellular matrix organization, hypoxic signaling, immune processes, and others. Nine of the 12 peptides assessed by immunogenicity analysis were able to activate naïve CD8(+) T cells, including peptides derived from EGLN3. Functional analysis of EGLN3 revealed possible tumor-promoting functions. CONCLUSIONS: Integration of HLA ligandomics, transcriptomics, genetic, and epigenetic data leads to the identification of novel functionally relevant therapeutic targets for ccRCC immunotherapy. Validation of the identified targets is recommended to expand the treatment landscape of ccRCC.
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spelling pubmed-71066512020-04-01 Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy Reustle, Anna Di Marco, Moreno Meyerhoff, Carolin Nelde, Annika Walz, Juliane S. Winter, Stefan Kandabarau, Siahei Büttner, Florian Haag, Mathias Backert, Linus Kowalewski, Daniel J. Rausch, Steffen Hennenlotter, Jörg Stühler, Viktoria Scharpf, Marcus Fend, Falko Stenzl, Arnulf Rammensee, Hans-Georg Bedke, Jens Stevanović, Stefan Schwab, Matthias Schaeffeler, Elke Genome Med Research BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different -omics technologies to identify ccRCC-specific HLA-presented peptides as potential drug targets for ccRCC immunotherapy. METHODS: We analyzed HLA-presented peptides by MS-based ligandomics of 55 ccRCC tumors (cohort 1), paired non-tumor renal tissues, and 158 benign tissues from other organs. Pathways enriched in ccRCC compared to its cell type of origin were identified by transcriptome and gene set enrichment analyses in 51 tumor tissues of the same cohort. To retrieve a list of candidate targets with involvement in ccRCC pathogenesis, ccRCC-specific pathway genes were intersected with the source genes of tumor-exclusive peptides. The candidates were validated in an independent cohort from The Cancer Genome Atlas (TCGA KIRC, n = 452). DNA methylation (TCGA KIRC, n = 273), somatic mutations (TCGA KIRC, n = 392), and gene ontology (GO) and correlations with tumor metabolites (cohort 1, n = 30) and immune-oncological markers (cohort 1, n = 37) were analyzed to characterize regulatory and functional involvements. CD8(+) T cell priming assays were used to identify immunogenic peptides. The candidate gene EGLN3 was functionally investigated in cell culture. RESULTS: A total of 34,226 HLA class I- and 19,325 class II-presented peptides were identified in ccRCC tissue, of which 443 class I and 203 class II peptides were ccRCC-specific and presented in ≥ 3 tumors. One hundred eighty-five of the 499 corresponding source genes were involved in pathways activated by ccRCC tumors. After validation in the independent cohort from TCGA, 113 final candidate genes remained. Candidates were involved in extracellular matrix organization, hypoxic signaling, immune processes, and others. Nine of the 12 peptides assessed by immunogenicity analysis were able to activate naïve CD8(+) T cells, including peptides derived from EGLN3. Functional analysis of EGLN3 revealed possible tumor-promoting functions. CONCLUSIONS: Integration of HLA ligandomics, transcriptomics, genetic, and epigenetic data leads to the identification of novel functionally relevant therapeutic targets for ccRCC immunotherapy. Validation of the identified targets is recommended to expand the treatment landscape of ccRCC. BioMed Central 2020-03-30 /pmc/articles/PMC7106651/ /pubmed/32228647 http://dx.doi.org/10.1186/s13073-020-00731-8 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Reustle, Anna
Di Marco, Moreno
Meyerhoff, Carolin
Nelde, Annika
Walz, Juliane S.
Winter, Stefan
Kandabarau, Siahei
Büttner, Florian
Haag, Mathias
Backert, Linus
Kowalewski, Daniel J.
Rausch, Steffen
Hennenlotter, Jörg
Stühler, Viktoria
Scharpf, Marcus
Fend, Falko
Stenzl, Arnulf
Rammensee, Hans-Georg
Bedke, Jens
Stevanović, Stefan
Schwab, Matthias
Schaeffeler, Elke
Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy
title Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy
title_full Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy
title_fullStr Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy
title_full_unstemmed Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy
title_short Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy
title_sort integrative -omics and hla-ligandomics analysis to identify novel drug targets for ccrcc immunotherapy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106651/
https://www.ncbi.nlm.nih.gov/pubmed/32228647
http://dx.doi.org/10.1186/s13073-020-00731-8
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