Proteomic landscapes of Ewing sarcoma unravel immunological regulation of tumor progression
Ontology highlight
ABSTRACT:
INSTRUMENT(S):
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Ewing's Sarcoma Cell
SUBMITTER: 
Tamar Geiger
LAB HEAD: Prof. Tamar Geiger
PROVIDER: PXD050234 | Pride | 2025-12-30
REPOSITORIES: Pride
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2024-07-15 | E-MTAB-14247 | biostudies-arrayexpress
Project description:In order to better understand the intra-tumor heterogeneity of colorectal cancer, we performed morphology-resolved profiling of stage II-IV primary tumors. The morphological patterns of interest were: complex tubular, desmoplastic, mucinous, papillary, serrated, and complex/tubular. In addition, we profiled a number of tumor-adjacent normal, supportive stroma, and polyp regions. Addionaly, several whole-tumor samples were added, from sections immediately successive to the ones used for region sampling. The manually-annotated regions were macrodissected, RNA extracted and hybridized on Clariom D (human) microarrays. The resulting gene expression profiles allowed the identification of major determinants of differences between the regions, differences that were present within tumors as well.
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Project description:Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behavior, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 99 men. These subgroups were able to consistently predict biochemical relapse (p=0.0017 and p=0.016 respectively) and were further validated in a third cohort with long-term follow-up (p=0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4) in prostate cancer, and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p=0•0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation For the first time this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts. A total of 482 samples from 289 men with prostate cancer from two cohorts were included in this study. The discovery cohort comprised 125 tumour samples from radical prostatectomy (RP) with 118 matched benign samples, and 85 matched blood samples. An additional 4 benign samples from men undergoing Holmium laser enucleation of the prostate (HoLEP) and 16 radical prostatectomy samples from men with castrate-resistant prostate cancer, with 13 matched blood samples were also included. These were assayed on several platforms, including Illumina HT12v4 gene expression arrays, Illumina OMNI2.5M genotyping arrays and Affymetrix SNP6 genotyping arrays. The validation cohort comprised 103 tumour tissue samples from men with prostate cancer, with 99 matched benign tissue samples and 103 matched blood samples. This datasheet describes samples in the VALIDATION COHORT only, with complete, QCd Illumina HT12v4 data for 94 RP samples. Extensive clinical metadata is available in the associated publication Ross-Adams et al. (2015, Suppl. Table 2)
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2009-05-11 | E-GEOD-14543 | biostudies-arrayexpress
Project description:The improvement of Ewing's sarcoma (EWS) therapy is currently linked to find strategies to select patients with poor and good prognosis at diagnosis and to generate modified treatment regimens. In this study, we analyze the molecular factors governing EWS response to chemotherapy in order to identify genetic signatures that may be used for risk-adapted therapy. Experiment Overall Design: Affimetrix platform was used for profiling 30 primary tumors of patients that were classified according to event-free survival and 7 metastasis. NED: no evidence of diseaase (event-free); REL: relapse; MET: metastasis. For selected genes, Real-Time PCR was applied in 42 EWS primary tumors as validation assay. MTT test was used to evaluate in vitro drug sensitivity.
2008-10-21 | E-GEOD-12102 | biostudies-arrayexpress
Project description:Chromosome 8 (chr8) gains are common in cancer. However, their potential contribution to tumor heterogeneity is largely unexplored. Ewing sarcoma (EwS) is characterized by pathognomonic FET::ETS fusions but a general paucity of other recurrent somatic mutations that could explain the observed clinical diversity. In EwS, chr8 gains are the second most common genetic alteration rendering EwS an ideal model to investigate the relevance of chr8 gains in an otherwise silent genomic context. Here, we report that chr8 gain-driven gene expression patterns correlate with poor overall survival of EwS patients. This effect is predominantly mediated by increased expression of the translation initiation factor binding protein 4E-BP1 encoded by EIF4EBP1 on chr8. High EIF4EBP1 expression showed the strongest association with poor patient survival among all chr8-encoded genes and correlated with chr8 gains in EwS tumors. Similar findings were made in numerous entities of The Cancer Genome Atlas (TCGA). Integrated multi-omics profiling uncovered that 4E-BP1 orchestrates a pro-proliferative proteomic network. Consistently, silencing of 4E-BP1 in the EwS model reduced cell proliferation, clonogenicity, spheroidal growth in vitro, and tumor growth in vivo. Drug screens and functional assays revealed that high 4E-BP1 expression sensitizes for pharmacological CDK4/6-inhibition in preclinical models. Collectively, we establish chr8 gains and high 4E-BP1 expression as prognostic biomarkers in EwS and demonstrate that their association with patient outcome is primarily mediated by 4E-BP1 orchestrating a pro-proliferative proteomic network sensitizing EwS for CDK4/6-inhibitors. Our data suggest that testing for chr8 gains may improve risk-stratification and therapeutic management in EwS and other cancers.
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
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