Expression date from endothelial cells stimulated with anti-HLA class I and anti-A antibody
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PROVIDER: PRJNA493548 | ENA |
REPOSITORIES: ENA
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Project description:The sensitivity of malignant tissues to T cell-based cancer immunotherapies is dependent on the presence of targetable HLA class I ligands on the tumor cell surface. Peptide intrinsic factors, such as HLA class I affinity, likelihood of proteasomal processing, and transport into the ER lumen have all been established as determinants of HLA ligand presentation. However, the role of sequence features at the gene and protein level as determinants of epitope presentation has not been systematically evaluated. To address this, we performed HLA ligandome mass spectrometry on patient-derived melanoma lines and used this data-set to evaluate the contribution of 7,124 gene and protein sequence features to HLA sampling. This analysis reveals that a number of predicted modifiers of mRNA and protein abundance and turn-over, including predicted mRNA methylation and protein ubiquitination sites, inform on the presence of HLA ligands. Importantly, integration of gene and protein sequence features into a machine learning approach augments HLA ligand predictions to a comparable degree as predictive models that include experimental measures of gene expression. Our study highlights the value of gene and protein features to HLA ligand predictions.
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Project description:We compared the expression of genes related to inflammatory cytotoxic functions between MSI and MSS (HLA class I negative and positive) gastrointestinal adenocarcinomas (GIACs), seeking evidence of differences in inflammatory mediators and cytotoxic T-cell responses. Twenty-two GIACs were divided into three study groups as a function of HLA class I expression and MSI phenotype. Comparison between eight high-level MSI (MSI-H) and 8 MSS/HLA+ (control) cancers identified 2170 differentially expressed genes (p< 0.05) after microarray analysis on the Affymetrix HG-U133-Plus-PM plate. We grouped genes in Gene Ontology functional categories: apoptotic programme (119 genes, p=5.1·10-7), leukocyte activation (32 genes, p=0.01), T cell activation (20 genes, p= 0.01), and cytokine production (19 genes, p= 0.04). Real-time RT-PCR and immunohistochemical evaluation were used to confirm some microarray data, finding that increased mRNA levels of pro-inflammatory cytokines and cytotoxic mediators were associated with greater infiltration by CD8+ T lymphocytes in the MSI-H group (p<0.001). Finally, tumours with immunohistochemical HLA class I negative pattern were not grouped together but rather in accordance with features of the gene expression profile of MSI or MSS tumours. As expected, genes associated with antigen processing machinery and MHC class I molecules (TAP2, B2m) were downregulated in MSS/HLA-ABC negative CRCs. In conclusion, microarray and immunohistochemical data may be useful to comprehensively assess tumour-host interactions and differentiate MSI from MSS cancers. The two types of tumours, MSI/HLA- and MSS/HLA-, showed marked differences in the composition and intensity of infiltrating leukocytes, suggesting that their immune escape strategies involve distinct pathways. Case-control study. Samples were selected according to immunological criteria: those with total loss of HLA antigens and those without alterations in the expression of HLA molecules. In addition, the microsatellite instability genotype of all the samples was also analyzed, resulting in microsatellite stability (MSS) and microsatellite instability (MSI) samples. Therefore, three groups of samples were selected: MSS/HLA+, MSS/HLA-, and MSI. The MSS/HLA+ group was used as the control.
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Project description:HLA-DRB1 alleles have been associated with several autoimmune diseases. In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), HLA-DRB1 shared epitope (SE) alleles are the major genetic risk factors. In order to investigate whether expression of different alleles of major histocompatibility complex (MHC) Class II genes influence functions of immune cells, we investigated transcriptomic profiles of a variety of immune cells from healthy individuals carrying different HLA-DRB1 alleles. Sequencing libraries from peripheral blood mononuclear cells, CD4+ T cells, CD8+ T cells, and CD14+ monocytes of 32 genetically pre-selected healthy female individuals were generated, sequenced and reads were aligned to the standard reference. For the MHC region, reads were mapped to available MHC reference haplotypes and AltHapAlignR was used to estimate gene expression. Using this method, HLA-DRB and HLA-DQ were found to be differentially expressed in different immune cells of healthy individuals as well as in whole blood samples of RA patients carrying HLA-DRB1 SE-positive versus SE-negative alleles. In contrast, no genes outside the MHC region were differentially expressed between individuals carrying HLA-DRB1 SE-positive and SE-negative alleles. Existing methods for HLA-DR allele-specific protein expression were evaluated but were not mature enough to provide appropriate complementary information at the protein level. Altogether, our findings suggest that immune effects associated with different allelic forms of HLA-DR and HLA-DQ may be associated not only with differences in the structure of these proteins, but also with differences in their expression levels.
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