Characterizing the immune and genome landscapes for osteosarcoma
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ABSTRACT:
PROVIDER: EGAS00001003247 | EGA |
REPOSITORIES: EGA
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Project description:Osteosarcoma is the most common primary bone sarcoma. About 50% of patients develop metastatic disease and their 5-year survival lingers at around 20-30%. T cell checkpoint blockade immunotherapies have revolutionized cancer treatment in the last decade, but their impact remains limited in osteosarcoma. In order to reveal potentially novel immunotherapeutic strategies for advanced osteosarcoma, we conducted an immunogenomic characterization of a unique sample set comprising multiple osteosarcoma samples from seven patients, collected throughout the progression of the disease. We performed RNA-sequencing and imaging mass cytometry analysis on those samples to reveal the immunological landscape during osteosarcoma progression. Transcriptional and phenotypical hallmarks of cytotoxic T cell-driven anti-cancer immunity were enriched in metastatic lesions as compared to primary tumors. In parallel, we found a pronounced increase in the expression of cancer testis antigens, particularly MAGEA-related antigens, in osteosarcoma metastases. Their overexpression in metastatic lesions was confirmed at protein level and positive expression of MAGEA3 in primary tumors showed a significant association with metastasis free survival. Importantly, we demonstrated the presentation of MAGE-derived peptides in three osteosarcoma cell lines. These findings indicate a concurrent augmentation of cytotoxic anti-tumor immune responses and expression of MAGEA antigens from primary to metastatic osteosarcoma. This observation warrants the exploration of MAGEA antigens as potential targets for immunotherapy in the treatment of advanced osteosarcoma.
2024-02-07 | GSE237033 | GEO
Project description:Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.
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Project description:Osteosarcoma is an orphan disease affecting children and young adults that has seen little to no progress in survival outcomes for >30 years. Despite having heavily rearranged genomes, to date, clinical trials with immunotherapy have shown no benefit for patients with osteosarcoma. In this study, we conducted the first multi-platform immune profiling (whole genome, transcriptome, T-cell receptor sequencing, immunohistochemistry and reverse phase protein array) on every available pediatric and adult osteosarcoma patients from our institution (N = 48) with the goal of describing immune features that may contribute to immunotherapy resistance.
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Project description:Osteosarcoma is an orphan disease affecting children and young adults that has seen little to no progress in survival outcomes for >30 years. Despite having heavily rearranged genomes, to date, clinical trials with immunotherapy have shown no benefit for patients with osteosarcoma. In this study, we conducted the first multi-platform immune profiling (whole genome, transcriptome, T-cell receptor sequencing, immunohistochemistry and reverse phase protein array) on every available pediatric and adult osteosarcoma patients from our institution (N = 48) with the goal of describing immune features that may contribute to immunotherapy resistance.
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Project description:In this manuscript, the authors had hypothesized a multi-dimensional approach modeling of both tumor and immune-related molecular mechanisms would better predict immune checkpoint blockade (ICB) response than simpler mutation-focused biomarkers, such as tumor mutational burden (TMB). The authors showed that the predictive power increases with deeper modeling of neoantigens and immune-related resistance mechanisms of ICB. The neoantigen burden score (NBS) and composite neoantigen presentation score (NEOPS) mentioned in the transcript was fully reproduced. Internally they used XGBoost algorithm to generate the results and the same is provided as dataset file. That is, the dataset provided here demonstrates that their integrative approach outperformed single-analyte biomarkers such as those found in cohort of patients with late-stage melanoma. This model is now addresses the issues in reproducing itself which was caused by version changes and deprecation of some R packages. It uses checkpoint package, which acts as a time machine for CRAN packages thereby promoting FAIReR sharing of ML models.
2024-07-23 | MODEL2407210001 | BioModels
Project description:Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. Such neoantigens have been implicated in response to immunotherapies including immune checkpoint blockade, yet their identification and validation remains challenging. Here we discover neoantigens in human mantle cell lymphomas using an integrated strategy for genomic and proteomic tumor antigen discovery that interrogates peptides presented within the tumor major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically identify neoantigen peptides in diagnostic tumor specimens from 17 patients. Remarkably, the 52 discovered neoantigenic peptides were invariably derived from the lymphoma immunoglobulin (Ig) heavy or light chain variable regions. Although we could identify MHC presentation of private germline polymorphic alleles, no mutated peptides were recovered from non-Ig somatically mutated genes. The immunoglobulin variable region somatic mutations were almost exclusively presented by MHC-II. We found T-cells specific for an immunoglobulin-derived neoantigen in the blood of a patient using MHC-II tetramers, and these T-cell clones expanded in frequency following tumor vaccination. These results demonstrate that an integrative approach combining MHC isolation, peptide identification and exome sequencing is an effective platform to uncover tumor neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.
2017-03-27 | PXD004746 | Pride
Project description:Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. Such neoantigens have been implicated in response to immunotherapies including immune checkpoint blockade, yet their identification and validation remains challenging. Here we discover neoantigens in human mantle cell lymphomas using an integrated strategy for genomic and proteomic tumor antigen discovery that interrogates peptides presented within the tumor major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically identify neoantigen peptides in diagnostic tumor specimens from 17 patients and several cell lines. Remarkably, the discovered neoantigenic peptides were invariably derived from the lymphoma immunoglobulin (Ig) heavy or light chain variable regions. Although we could identify MHC presentation of private germline polymorphic alleles, no mutated peptides were recovered from non-Ig somatically mutated genes. The immunoglobulin variable region somatic mutations were almost exclusively presented by MHC-II. We found T-cells specific for an immunoglobulin-derived neoantigen in the blood of a patient using MHC-II tetramers, and these T-cell clones expanded in frequency following tumor vaccination. These results demonstrate that an integrative approach combining MHC isolation, peptide identification and exome sequencing is an effective platform to uncover tumor neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.
2017-03-27 | PXD005704 | Pride
Project description:All nucleated mammalian cells express major histocompatibility complex (MHC) proteins that present peptides on cell surfaces for immune surveillance. These MHC-presented peptides (pMHC) can convey non-self antigens derived from pathogens or mutations to amount T-cell responses. Alterations in tumor-specific antigens – particularly mutation-bearing peptides (neoantigens) presented by MHC — can serve as potent substrates for anti-tumor immune responses. Here we employed an integrated genomic and proteomic antigen discovery strategy aimed at measuring interferon gamma (IFN-γ) induced alterations to antigen presentation, using a lymphoma cell line. IFN-γ treatment resulted in a set of differentially expressed proteins (2 % of all quantified proteins) including components of antigen presentation machinery or interferon signaling pathways. In addition, several proteasome subunits were found to be modulated, consistent with previous reports of immunoproteasome induction by IFN-γ exposure. This finding suggests that a modest proteomic response to IFN-γ could create larger alteration to cells antigen repertoires. Accordingly, by surveying immunopeptides, distinct peptide repertoires were exclusively observed in the IFN-γ induced samples. Furthermore, an additional set of presented peptides distinguished control and the IFN-γ samples by their altered relative abundances including neoantigens. Accordingly, we developed a classification system to distinguish peptides which are differentially presented due to altered expression from novel peptides resulting from changes in antigen processing. Taken together, these data demonstrate that IFN-γ can re-shape antigen repertoires by identity and by abundance. Extending this approach to models with greater clinical relevance should help develop strategies by which immunopeptide repertoires are intentionally reshaped to improve endogenous or vaccine-induced anti-tumor immune responses and potentially anti-viral immune responses.
2021-09-09 | PXD020750 | Pride
Project description:We report on osteosarcoma and Ewing sarcoma tumours resected from human patients that the tumours express long non-coding RNA.
2021-04-27 | GSE113916 | GEO