Dataset Information

The choice of search engine affects sequencing depth and HLA allele-specific peptide repertoires.

ABSTRACT: Standardisation of Immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages commonly used to interrogate immunopeptidomics datasets, in order to understand to which extent differences in performance can be observed. We found that a de novo-assisted database search reports substantially more peptide sequences (~30-70%) compared to three database search engines at a global FDR of <1%. This effect was reproducible across four immunopeptidomic datasets. We validated the results using data generated with a synthetic library of 2000 HLA-associated peptides from four HLA alleles, half of which were previously observed by LC-MS, and half were predicted only. Our investigation reveals that search engines create a bias in peptide sequence length distribution and peptide amino acid composition. Therefore, the choice of peptide identification method highly influences the proportion of peptide sequences identified for each HLA allele, and resulting data should be interpreted with caution.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Cell Culture

DISEASE(S): Cervix Carcinoma,Glioblastoma,Cutaneous Malignant Melanoma 1

SUBMITTER: Robert Parker

LAB HEAD: Nicola Ternette

PROVIDER: PXD025655 | Pride | 2021-08-10

REPOSITORIES: Pride

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Publications

The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires.

Parker Robert R Tailor Arun A Peng Xu X Nicastri Annalisa A Zerweck Johannes J Reimer Ulf U Wenschuh Holger H Schnatbaum Karsten K Ternette Nicola N

Molecular & cellular proteomics : MCP 20210723

Standardization of immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages to interrogate immunopeptidomics datasets and found that Peaks reproducibly reports substantially more peptide sequences (~30-70%) compared with Maxquant, Comet, and MS-GF+ at a global false discovery rate (FDR) of <1%. We noted that these di ...[more]

PMID: 34303857

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Project description:Background Clinical success of T cell receptor (TCR) gene therapy has previously been demonstrated for NY-ESO-1 TCR gene therapy. To increase numbers of cancer patients that can be treated with TCR gene therapy we aimed to identify a novel set of high-affinity cancer specific TCRs targeting different cancer testis (CT) antigens in prevalent HLA class I alleles. Methods In this study, we selected based on publicly available gene expression databases the most promising CT genes to target. From these selected genes we identified by HLA peptidomics the naturally processed and presented HLA class I peptides. With these peptide-HLA tetramers were generated, and by single cell sorting CT specific CD8+ T cells were selected, and expanded from the allo-HLA repertoire of healthy donors. By several functional assays high avidity CT-specific T cell clones with safe recognition pattern were selected. To evaluate the potential for clinical application in TCR gene therapy, TCRs were sequenced and transferred into peripheral blood derived CD8+ T cells. Results In total we identified, 7 novel CT-specific TCRs that effectively target MAGE-A1, MAGE-A3, MAGE-A6 and MAGE-A9 in the context of human leukocyte antigen(HLA) -A1, -A2, -A3, -B7, -B35 and -C7. TCR gene transfer into CD8⁺ T cells resulted in efficient cytokine production and cytotoxicity of variety of different tumor types without detectable cross-reactivity. In addition, major in vivo antitumor effects of MAGE-A1 specific TCR engineered CD8⁺ T cells was observed in an orthotopic xenograft model for established multiple myeloma, in which bone marrow located tumor cells were completely eradicated after T cell injection. Conclusion The identification of 7 novel CT-specific TCRs, reactive against CT antigens presented in a variety of different HLA class I alleles, allows selection of therapeutic TCRs for an increased number of cancer patients, and will improve development of personalized TCR gene therapy.

Dataset Information

The choice of search engine affects sequencing depth and HLA allele-specific peptide repertoires.

Publications

The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires.

Similar Datasets

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