Validation Set for Prediction of Outcome in Adult Male Germ Cell Tumors
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10783 | GEO | 2008/09/30
SECONDARY ACCESSION(S): PRJNA107469
REPOSITORIES: GEO
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Project description:This series represents expression profiles of 34 non-seminoma germ cell tumors (NSGCTs) from patients who received cisplatin based chemotherarpy for treatment of their disease for whom full clinical follow-up information was available. These specimens were used as a validation set to test outcome prediction models using a subset of previously profiled GCT specimens (see GEO accession #GSE3218). Experiment Overall Design: Tumor tissues were collected under IRB-approved protocols at the Memorial Sloan-Kettering Cancer Center, New York, between 1987 and 2003. The tumor samples consist of 34 NSGCT specimens. RNA was isolated, labeled, and hybridized to Affymetrix U133A and U133B microarrays using standard protocols. Data were processed by the RMA method.
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Project description:Germ cell tumors (GCT) can be distinguished into seminoma and non-seminoma. The latter comprises embryonal carcinoma, which can further differentiate into choriocarcinoma, teratoma (TER), and yolk-sac tumors (YST). However, GCT can transform into a somatic-type malignancy (STM), eventually resulting in an unfavorable outcome. This study aimed at enlightening the molecular mechanisms leading to STM formation by comparing them to TER and YST as presumable tissues of origin, thereby paving the way for the identification of novel druggable targets.
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Project description:Expression profiling of a panel of 101 adult male germ cell tumors and 5 normal testis specimens was performed on Affymetrix U133A and U133B microarrays. This data has been used to: 1) generate a gene classifier that predicts histology (see PMID 15870693). 2) identify candidate target genes on 12p, a region that is gained in almost 100% of germ cell tumors (see PMID 16424014) 3) identify pluripotency associated genes through comparison of pluripotent embryonal carcinoma vs. undifferentiated seminoma. ONGOING: 4) Identification of genes associated with patient outcome and cisplatin resistance. Keywords: germ cell tumor, histologic subtypes
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Project description:Germ cell tumors (GCT) originate from germ cells at different developmental stages (GCT type I – V) They are thought to inherit their methylation profile from (early embryonic) germ cells which undergo a characteristic epigenetic “reset” during maturation. This study aims to provide insight into the developmental timing and underlying biology of the various subtypes of GCTs and their (embryonic) cells of origin by identifying specific and global methylation differences between GCT subtypes. In total, 91 type I-IV GCTs and four cell lines were profiled using the Illumina HumanMethylation450 BeadChip (450K) platform. The data were pre-processed using a validated pipeline and analyzed using an in-house generated extension of the annotation manifest. Marked methylation differences were identified between GCT subtypes both on the global and local level (i.e. differentially methylated regions, imprinting control regions, promoters, etc). GCT subtypes indeed show major similarities to specific stages of (early) developing embryonic germ cells with regard to their methylation profile. The extended annotation manifest for the Illumina 450K platform and methylation datasets are readily available on GEO (GEO accession: GSE58538, GPL18809), providing an integrated hypothesis generating data source for future research. File S1. Differentially methylated regions between tumors classes as discussed in Table 1 of the associated publication. All figures. Please investigate using the genomic position as search term. File S2. Differentially methylated regions between GCT cell lines. DMRforPairs output. Significant results only. Please start from the html file.
2015-02-26 | GSE58538 | GEO
Project description:Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of patients with very different five-year overall survival rates (70% versus 12%). The model also effectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention. golub-00095 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Tissue Sites: Lymphoid tissue Material Types: synthetic_DNA, synthetic_RNA, organism_part Cell Types: B-Lymphocyte Disease States: Diffuse large B-cell Lymphoma, Follicular Lymphoma
2015-05-15 | E-GEOD-68895 | biostudies-arrayexpress
Project description:In our early study ([GEO Accession: GSE16987], [PMID: 21939527]), we have created a ClinicoMolecular Triad Classification (CMTC) to improve prediction and prognostication of breast cancer by using a training cohort contained 161 breast cancer patients (2003 to 2008). Here, a supplemental internal validation cohort contained 340 breast cancer patients was collected (2008 to 2010) for development of the CMTC. Total 340 fine-needle aspirates (FNA) specimens from breast tumors without replicate were collected and prepared for microarray examination. Finally, 284 invasive breast cancers were used in this study.
2014-06-19 | E-GEOD-45725 | biostudies-arrayexpress
Project description:Gene expression profiling to predict outcome after chemoradiation in head and neck cancer Purpose. The goal of the present study was to improve prediction of outcome after chemoradiation in advanced head and neck cancer using gene expression analysis. Materials and Methods. We collected 92 biopsies from untreated head and neck cancer patients subsequently given cisplatin-based chemoradiation (RADPLAT) for advanced squamous cell carcinomas (HNSCC). After RNA extraction and labeling we performed dye swap experiments using 35k oligo-microarrays. Supervised analyses were performed to create classifiers to predict local control, locoregional control and disease recurrence. Published gene sets with prognostic value in other studies were also tested. Results. Using supervised classification on the whole series, gene sets separating good and poor outcome could be found for all end-points. However, when splitting tumors into training and validation groups, no robust classifiers could be found. Also previously published signatures with prognostic value have been tested. Conclusion. Gene sets can be found with predictive potential for locoregional control after combined radiation and chemotherapy in HNSCC. How treatment-specific these gene sets are needs further study.
2008-02-19 | E-NCMF-8 | biostudies-arrayexpress
Project description:Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. The initial lesion is believed to be the relatively benign precursor lesion (ICGNU), from which either highly chemosensitive seminomas or the more aggressive non-seminomas develop. Previous analyses of selected genes have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. However, the genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumoursâ biology have not yet been established. Here genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data. This demonstrated that the seminoma cells exhibited very little aberrant DNA methylation while non-seminoma cells exhibited very high levels of DNA methylation. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested did indeed play a role in their silencing and many of these genes were also differentially expressed in primary tumours. Through this approach the genes silenced in the various GCT cell lines were identified. Conclusions: Several pluripotency-associated genes, never before implicated in this type of cancer, were identified as a major functional group of silenced genes. Silencing of these factors that normally suppress somatic differentiation might play an important role in the progression to non-seminoma formation. Genomic DNA and RNA was extracted from cell lines representing four subtypes of GCT. RNA was subjected to Affymetric expression array analysis while DNA was bisulfite treated and analysed using Illumina Infinium 450K arrays. Statistical approaches were used to correlate methylation and expression for each gene.
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