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Combined proteomics and miRNomics of a glioblastoma immunotherapy cohort reveal resistance factor candidates and potential counterstrategies

ABSTRACT: Combined proteomics and miRNomics of a glioblastoma immunotherapy cohort reveal resistance factor candidates and potential counterstrategies

PROVIDER: PRJNA548350 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR9273320.fastq.gz	Fastqsanger.gz
	SRR9273321.fastq.gz	Fastqsanger.gz
	SRR9273322.fastq.gz	Fastqsanger.gz
	SRR9273323.fastq.gz	Fastqsanger.gz
	SRR9273314.fastq.gz	Fastqsanger.gz

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Combined proteomics and miRNomics of a glioblastoma immunotherapy cohort reveal resistance factor candidates and potential counterstrategies

Project description:Glioblastoma is the most prevalent and aggressive brain cancer. With a median overall survival of ~15-20 months under standard therapy, novel treatment approaches are desperately needed. A recent phase II clinical trial with a personalized immunotherapy based on tumor lysate-charged dendritic cells (DCs), however, failed to prolong survival. Here, we investigated tumor tissue from patients from this trial to explore glioblastoma (immuno)resistancesurvival-related factors. and strategies to overcome them. We followed an innovative approach of combining mass spectrometry-based quantitative proteomics (n=36) with microRNA sequencing plus RT-qPCR (n=38). Protein quantification identified e.g. huntingtin interacting protein 1 (HIP1), retinol binding protein 1 (RBPP1), ferritin heavy chain (FTH1) and focal adhesion kinase 2 (FAK2) as resistance factor candidates. MicroRNA analysis identified miR-216b, miR-216a, miR-708 and let-7i as molecules potentially associated with overcoming resistancefavourable tissue characteristics as they were enriched in patients with a comparably longer survival. In silico target prediction and subsequent analyses indicated focal adhesion as a pathway of interest. Taken together, we here mapped possible drivers of glioblastoma outcome under immunotherapy’s (immuno)resistance in one of the largest DC vaccination tissue analysis cohorts so far – demonstrating usefulness and feasibility of combined proteomics/miRNomics approaches. Future research should investigate agents that sensitize glioblastoma to (immuno)therapy – potentially building on insights generated here.

2020-01-27 | GSE132554 | GEO

Combined proteomics and miRNomics of a glioblastoma immunotherapy cohort reveals resistance factor candidates and novel counterstrategy concepts

Project description:Glioblastoma is the most prevalent and aggressive form of brain cancer. With a median overall survival of ~20 months under current standard therapy (surgery, chemotherapy, radiotherapy), novel treatment approaches are desperately needed. Immunotherapies are being investigated in clinical trials but failed so far. This includes a recent phase II clinical trial with a personalized immunotherapy based on tumor lysate-charged dendritic cells (NCT01213407). Here, we investigated tumor tissue from patients from this trial to explore glioblastoma (immuno)resistance factors and strategies to overcome them. We followed an innovative approach of combining mass spectrometry-based quantitative proteomics (n=36) with microRNA sequencing plus RT-qPCR (n=38). Protein quantification identified e.g. huntingtin interacting protein 1 (HIP1), retinol binding protein 1 (RBPP1), ferritin heavy chain (FTH1) and focal adhesion kinase 2 (FAK2) as resistance factor candidates. MicroRNA analysis identified miR-216b, miR-216a, miR-708 and let-7i as molecules potentially associated with overcoming resistance as they were enriched in patients with a comparably longer survival. In silico pathway prediction indicated they down-regulate the focal adhesion pathway – among others. FAK2 was enriched in short-term surviving immunotherapy patients. In vitro, FAK inhibitors prevented the formation of glioblastoma cell adhesion in the form of gliomaspheres. Taken together, we here mapped possible drivers of glioblastoma’s immuno)resistance in one of the largest DC vaccination tissue analysis cohorts so far – demonstrating usefulness and feasibility of combined proteomics/miRNomics approaches. Future research should investigate agents that sensitize glioblastoma to (immuno)therapy – e.g. targeting focal adhesion. Small-molecule inhibitors or microRNAs capable of altering multiple pathways at once are candidates to explore.

2020-01-27 | PXD012616 | Pride

Chronic Renal Insufficiency Cohort (CRIC) Study Metabolomics and Proteomics

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Proteomics of immune cells from liver tumors reveals immunotherapy targets

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Proteomics of immune cells from liver tumors reveals immunotherapy targets [tumor]

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Characterization of Entamoeba histolytica adapted to auranofin by combined transcriptomics and redox proteomics

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Combined analysis of metabolomics, proteomics, and transcriptomics to identify biomarkers for resistant hypertension

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Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy

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

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