Integrative multi-omics analysis uncovers tumor-immune-gut axis influencing immunotherapy outcomes in ovarian cancer
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ABSTRACT:
PROVIDER: PRJNA850634 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19745426_1.fastq.gz | Fastqsanger.gz | |||
| SRR19745426_2.fastq.gz | Fastqsanger.gz | |||
| SRR19745427_1.fastq.gz | Fastqsanger.gz | |||
| SRR19745427_2.fastq.gz | Fastqsanger.gz | |||
| SRR19745428_1.fastq.gz | Fastqsanger.gz |
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2023-05-17 | GSE206422 | GEO
Project description:Background: A pressing challenge in treating non-small cell lung cancer (NSCLC) lies in the significant variability of patient responses to immunotherapy. This issue underscores the critical need for innovative predictive models that can navigate beyond conventional biomarkers to enhance patient outcomes, particularly by addressing immunotherapy resistance or responsiveness. Hypothesis: We hypothesize that an integrated multi-omics approach will uncover interactions within the NSCLC tumor immune microenvironment (TIME) and identify novel biomarkers that are predictive of individual immunotherapy responses, thus aiding in the development of a robust personalized treatment planning model. Objective: To develop a predictive model for NSCLC immunotherapy response/resistance by identifying new biomarkers using co-detection by indexing (CODEX) and Digital Spatial Profiling of whole transcriptome atlas (DSP-WTA). Methods: We utilized a multi-omics approach, combining CODEX for spatial mapping of protein expression at the single-cell level and DSP-WTA for comprehensive transcriptomic insights from the cell types identified by CODEX. This methodology facilitated a detailed examination of the TIME in NSCLC samples from patients undergoing first-line immunotherapy. Results: Our analysis identified three cell types, proliferating tumor cells, granulocytes, and vessels, that are associated with resistance to immunotherapy. The high proportion of these cell types demonstrated a hazard ratio (HR) of 3.8 (p = 0.004) in the training cohort (N = 33) and 1.8 (p = 0.05) in the validation cohort (N = 35). In the response cell type model, higher levels of M1 macrophages, M2 macrophages, and CD4 T cells returned a HR of 0.4 (p = 0.019) in the training set and 0.49 (p = 0.036) in the validation set. Gene signatures related to these cell types also predicted outcomes with high accuracy. The resistant gene model, which included 8 genes associated with epithelial-mesenchymal transition (EMT) and cell migration showed a HR of 5.3 (p < 0.001) in the training set and 2.2 (p = 0.036) in the validation set. The response gene model, consisting of 8 genes associated with immunomodulation, had an HR of 0.22 (p = 0.005) in the training set and 0.38 (p = 0.034) in the validation set. Conclusion: This research highlights the potential of a multi-omics strategy in advancing NSCLC treatment toward precision oncology. By offering insights into the TIME and unveiling novel biomarkers, our model seeks to define resistance and to improve prediction of response to treatment.
2024-08-22 | GSE271689 | GEO
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Project description:Purpose: The efficacy of immunomodulators in improving pregnancy outcomes in infertile patients is controversial, with some reports finding improvements in pregnancy outcomes and some studies finding lack of efficacy in unselected patient populations. Therefore, the aim of this study was to identify people who could benefit from immunotherapy. Methods: 29 patients who had at least one previous embryo transfer failure and planned to undergo another frozen-thawed embryo transfer (FET) cycle were included. Peripheral blood of the patients was collected for detection of serum cytokines, T cell subsets at D3-D9 days of menstrual cycle before FET, mRNA was extracted from endometrial tissues during the window of implantation (WOI) for analysis. All patients began treatment with immunomodulators, including prednisone, hydroxychloroquine, cyclosporine, on the first day of the FET cycle. They were divided into pregnant group and non-pregnant group according to clinical pregnancy. Results: There were no differences in cytokines and T cell subsets between the two groups. Functional annotation of endometrial mRNA revealed functional enrichment in leucocyte mediated immunity, innate immune response, regulation of T cell receptor (TCR) signaling, T cell activation and positive T cell selection. Conclusion: The cytokines and immune cell subsets of peripheral blood cannot accurately predict the outcome of pregnancy after immunotherapy, and endometrial biopsy on the WOI may be a target to identify people who benefit from immunotherapy.
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Project description:Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different -omics technologies to identify ccRCC-specific HLA-presented peptides as potential drug targets for ccRCC immunotherapy. We analyzed frequent ccRCC-specific peptides by MS-based HLA ligandomics of 55 ccRCC tumors (cohort 1), paired non-tumor renal tissues and 158 benign tissues from other organs. Pathways enriched in ccRCC compared to its cell type of origin were identified by transcriptome and gene set enrichment analyses in 51 tumor tissues of the same cohort. To retrieve a list of candidate target genes with involvement in ccRCC pathogenesis, ccRCC-specific pathway genes were intersected with the source genes of tumor-exclusive peptides. The candidates were validated in an independent cohort from the Cancer Genome Atlas (TCGA KIRC, n=452), yielding 113 candidate genes. DNA methylation (TCGA KIRC, n=273), and somatic mutations (TCGA KIRC, n=392), as well as correlations with tumor metabolites (cohort 1, n=30) and immune-oncological markers (cohort 1, n=37) were analyzed to refine regulatory and functional involvements of candidates. Immunogenicity analysis identified candidate epitopes able to activate native CD8+ T cells. Functional analysis of EGLN3, a candidate with frequent ccRCC-specific immunogenic peptides, revealed possible tumor-promoting functions. Integration of HLA ligandomics, transcriptomics, genetic and epigenetic data leads to the identification of novel functionally relevant therapeutic targets for ccRCC immunotherapy. Validation of the identified targets is now mandatory to expand the treatment landscape of ccRCC.
2020-04-03 | PXD017149 | Pride
Project description:Immunotherapeutics represent highly promising agents with the potential to improve patient outcomes in a variety of cancer types. Unfortunately, single-agent immunotherapy has achieved limited clinical benefit to date in patients suffering from pancreatic ductal adenocarcinoma (PDAC). This may be due to the presence of a uniquely immunosuppressive tumor microenvironment (TME) present in PDACs, which creates a barrier to effective immune surveillance. Critical obstacles to immunotherapy in PDAC tumors include the dense desmoplastic stroma that acts as a barrier to T-cell infiltration and the high numbers of tumor-associated immunosuppressive cells. We have identified hyperactivated focal adhesion kinase (FAK) activity in neoplastic PDAC cells as a significant regulator of the fibrotic and immunosuppressive TME. We found that FAK activity was elevated in human PDAC tissues and correlates with high levels of fibrosis and poor CD8+ cytotoxic T-cell infiltration. Single-agent FAK inhibition (VS-4718) dramatically limited tumor progression, resulting in a doubling of survival in the p48-Cre/LSL-KrasG12D/p53Flox/+ (KPC) mouse model of human PDAC. This alteration in tumor progression was associated with dramatically reduced tumor fibrosis, decreased numbers of tumor-infiltrating immature myeloid cells and immunosuppressive macrophages. We postulated that these desirable effects of FAK inhibition on the TME might render PDAC tumors more sensitive to immunotherapy. Accordingly, we found that VS-4718 rendered the previously unresponsive KPC mouse model responsive to anti-PD1 and anti-CTLA4 antagonists leading to a nearly tripling of survival times. These data suggest that FAK inhibition increases immune surveillance by overcoming the fibrotic and immunosuppressive PDAC TME thus rendering tumors more responsive to immunotherapy. We treated KP orthotopic tumor-bearing mice with vehicle and FAK inhibitor (FAKi) for 14 days, then extracted total RNA from tumor tissues.
2015-11-21 | E-GEOD-75233 | biostudies-arrayexpress
Project description:BackgroundIn recent years, the application of functional genetic immuno-oncology screens has showcased the striking ability to identify potential regulators engaged in tumor-immune interactions. Although these screens have yielded substantial data, few studies have attempted to systematically aggregate and analyze them.MethodsIn this study, a comprehensive data collection of tumor immunity-associated functional screens was performed. Large-scale genomic data sets were exploited to conduct integrative analyses.ResultsWe identified 105 regulator genes that could mediate resistance or sensitivity to immune cell-induced tumor elimination. Further analysis identified MON2 as a novel immune-oncology target with considerable therapeutic potential. In addition, based on the 105 genes, a signature named CTIS (CRISPR screening-based tumor-intrinsic immune score) for predicting response to immune checkpoint blockade (ICB) and several immunomodulatory agents with the potential to augment the efficacy of ICB were also determined.ConclusionOverall, our findings provide insights into immune oncology and open up novel opportunities for improving the efficacy of current immunotherapy agents.
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