Dataset Information

Digital mapping of immunopeptidomes

ABSTRACT: We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

INSTRUMENT(S): LTQ Orbitrap, TripleTOF 5600, LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Dr Ruedi Aebersold

PROVIDER: MSV000079623 | MassIVE | Mon Apr 04 01:32:00 BST 2016

SECONDARY ACCESSION(S): PXD001872

REPOSITORIES: MassIVE

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Publications

An open-source computational and data resource to analyze digital maps of immunopeptidomes.

Caron Etienne E Espona Lucia L Kowalewski Daniel J DJ Schuster Heiko H Ternette Nicola N Alpízar Adán A Schittenhelm Ralf B RB Ramarathinam Sri H SH Lindestam Arlehamn Cecilia S CS Chiek Koh Ching C Gillet Ludovic C LC Rabsteyn Armin A Navarro Pedro P Kim Sangtae S Lam Henry H Sturm Theo T Marcilla Miguel M Sette Alessandro A Campbell David S DS Deutsch Eric W EW Moritz Robert L RL Purcell Anthony W AW Rammensee Hans-Georg HG Stevanovic Stefan S Aebersold Ruedi R

eLife 20150708

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first ...[more]

PMID: 26154972

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Project description:Treatment of cancer cells with anti-cancer drugs often fails to achieve complete remission. Yet, such drug treatments may induce alteration in the tumorâs gene expression patterns, including those of Cancer/Testis Antigens (CTA). The degradation products of such antigens can be presented as HLA peptides on the surface of the tumor cells and be developed into anti-cancer immunotherapeutics. For example, the DNA methyl transferase inhibitor, 5-aza-2'-deoxycytidine (Decitabine) has limited anti-tumor efficacy, yet it induces the expression of many genes, including CTAs that are normally silenced in the healthy adult tissues. In this study, the presentation of many new HLA peptides derived from CTAs and induced by Decitabine was demonstrated in three human Glioblastoma cell lines. Such presentation of CTA-derived HLA peptides can be exploited for development of new treatment modalities, combining drug treatment with anti-CTA targeted immunotherapy. The Decitabine-induced HLA peptidomes include many CTAs that are not normally detected in healthy tissues or in cancer cells, unless treated with the drug. In addition, the study included large-scale analyses of the simultaneous effects of Decitabine on the transcriptomes, proteomes and HLA peptidomes of the human Glioblastoma cells. It demonstrates the poor correlations between these three levels of gene expression, both in their total levels and in their response to the drug. The transcriptomes, proteomes and HLA peptidomes of the U-87, T98G and LNT-229 GBM human cell lines were analyzed before and after treatment with Decitabine. Overall, the RNA-Seq transcriptome analyses resulted in the identification of above 26000 transcripts, the proteome analyses identified about 7500 proteins and the HLA class I peptidome analyses resulted in above 25000 identified HLA peptides. Two biological repetitions of the transcriptome, three of the proteome and three of the HLA peptidome were performed with each of the cell lines and treatment, resulting in highly reproducible datasets.