Dataset Information

Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells.

ABSTRACT: The presentation of tumor antigen-derived peptides by human leukocyte antigen (HLA) class I surface antigens on tumor cells is a key prerequisite to trigger effective T-cell responses in cancer patients. Multiple complementary strategies like cDNA and serological expression cloning, reverse immunology and different 'ome'-based methods have been employed to identify potential T-cell targets. This report focuses on a ligandomic profiling approach leading to the identification of 49 naturally processed HLA class I peptide ligands presented on the cell surface of renal cell carcinoma (RCC) cells. The source proteins of the defined HLA ligands are classified according to their biological function and subcellular localization. Previously established cDNA microarray data of paired tissue specimen of RCC and renal epithelium assessed the transcriptional regulation for 28 source proteins. In addition, HLA-A2-restricted, peptide-specific T cells directed against a HLA ligand derived from sulfiredoxin-1 (SRXN1) were generated, which were able to recognize and lyse ligand-presenting target cells in a HLA class I-restricted manner. Furthermore, tumor-infiltrating T cells isolated from a RCC patient were also able to kill SRXN1 expressing tumor cells. Thus, this experimental strategy might be suited to define potential candidate biomarkers and novel targets for T-cell-based immunotherapies of this disease.

SUBMITTER: Seliger B

PROVIDER: S-EPMC3517181 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells.

Seliger Barbara B Dressler Sven P SP Massa Chiara C Recktenwald Christian V CV Altenberend Florian F Bukur Juergen J Marincola Francesco M FM Wang Ena E Stevanovic Stefan S Lichtenfels Rudolf R

Proteomics 20110518 12

The presentation of tumor antigen-derived peptides by human leukocyte antigen (HLA) class I surface antigens on tumor cells is a key prerequisite to trigger effective T-cell responses in cancer patients. Multiple complementary strategies like cDNA and serological expression cloning, reverse immunology and different 'ome'-based methods have been employed to identify potential T-cell targets. This report focuses on a ligandomic profiling approach leading to the identification of 49 naturally proce ...[more]

PMID: 21595034

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Project description:Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA-peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II-peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II-peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at http://sysbio.icm.edu.pl/HLA .

Project description:BACKGROUND:Associations between human leukocyte antigens (HLA) alleles and cervical cancer are largely representative of squamous cell carcinoma (SCC), the major histologic subtype. We evaluated the association between HLA class I (A, B, and C) and class II (DRB1 and DQB1) loci and risk of cervical adenocarcinoma (ADC), a less common but aggressive histologic subtype. METHODS:We pooled data from the Eastern and Western US Cervical Cancer studies, and evaluated the association between individual alleles and allele combinations and ADC (n = 630 ADC; n = 775 controls). Risk estimates were calculated for 11 a priori (based on known associations with cervical cancer regardless of histologic type) and 38 non a priori common alleles, as odds ratios (OR) and 95% confidence intervals (CI), adjusted for age and study. In exploratory analysis, we compared the risk associations between subgroups with HPV16 or HPV18 DNA in ADC tumor tissues in the Western US study cases and controls. RESULTS:Three of the a priori alleles were significantly associated with decreased risk of ADC [DRB1*13:01 (OR = 0.61; 95% CI: 0.41-0.93), DRB1*13:02 (OR = 0.49; 95% CI: 0.31-0.77), and DQB1*06:03 (OR = 0.64; 95% CI: 0.42-0.95)]; one was associated with increased risk [B*07:02 (OR = 1.39; 95% CI: 1.07-1.79)]. Among alleles not previously reported, DQB1*06:04 (OR = 0.46; 95% CI: 0.27-0.78) was associated with decreased risk of ADC and remained significant after correction for multiple comparisons, and C*07:02 (OR = 1.41; 95% CI: 1.09-1.81) was associated with increased risk. We did not observe a difference by histologic subtype. ADC was most strongly associated with increased risk with B*07:02/C*07:02 alleles (OR = 1.33; 95% CI: 1.01-1.76) and decreased risk with DRB1*13:02/DQB1*06:04 (OR = 0.41; 95% CI: 0.21-0.80). CONCLUSION:RESULTS suggest that HLA allele associations with cervical ADC are similar to those for cervical SCC. An intriguing finding was the difference in risk associated with several alleles restricted to HPV16 or HPV18-related tumors, consistent with the hypothesis that HLA recognition is HPV type-specific.

Dataset Information

Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells.

Publications

Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells.

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