Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA338668 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease whose underlying etiology has not been explained by traditional prognostic factors such as tumor site, stage, or histology. Although previous studies have shown that molecular subtypes of HNSCC exist, the benefit of such a classification scheme has not been fully realized. We show that molecular subtypes of HNSCC exist; that these subtypes have distinct patterns of chromosomal gain and loss, some of which affect canonical oncogenes and tumor suppressors; and that the subtypes are biologically and clinically relevant. These subtypes provide new insight into HNSCC etiology, as well as a valuable method for classifying HNSCC tumors.
2013-03-01 | GSE39367 | GEO
Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease whose underlying etiology has not been explained by traditional prognostic factors such as tumor site, stage, or histology. Although previous studies have shown that molecular subtypes of HNSCC exist, the benefit of such a classification scheme has not been fully realized. We show that molecular subtypes of HNSCC exist; that these subtypes have distinct patterns of chromosomal gain and loss, some of which affect canonical oncogenes and tumor suppressors; and that the subtypes are biologically and clinically relevant. These subtypes provide new insight into HNSCC etiology, as well as a valuable method for classifying HNSCC tumors.
2013-03-01 | GSE39366 | GEO
Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease whose underlying etiology has not been explained by traditional prognostic factors such as tumor site, stage, or histology. Although previous studies have shown that molecular subtypes of HNSCC exist, the benefit of such a classification scheme has not been fully realized. We show that molecular subtypes of HNSCC exist; that these subtypes have distinct patterns of chromosomal gain and loss, some of which affect canonical oncogenes and tumor suppressors; and that the subtypes are biologically and clinically relevant. These subtypes provide new insight into HNSCC etiology, as well as a valuable method for classifying HNSCC tumors. A total of 163 samples were considered. Quality control procedures were applied to microarray probe-level intensity files. A total of 138 tumor arrays remained after removing low-quality arrays, duplicate arrays, and arrays from non-HNSCC samples. The normexp background correction and loess normalization procedures were applied to the probe-level data. After log transformation, probes were matched to a common gene database to produce expression values for 15595 genes.
2013-03-01 | E-GEOD-39366 | biostudies-arrayexpress
Project description:Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies – mainly studying nucleic acids – has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pGroup3myc), and synapses/immunological processes (pSHHs, pGroup3 and pGroup4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favourable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures. This SuperSeries is composed of the SubSeries listed below.
2024-04-22 | GSE243796 | GEO
Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease whose underlying etiology has not been explained by traditional prognostic factors such as tumor site, stage, or histology. Although previous studies have shown that molecular subtypes of HNSCC exist, the benefit of such a classification scheme has not been fully realized. We show that molecular subtypes of HNSCC exist; that these subtypes have distinct patterns of chromosomal gain and loss, some of which affect canonical oncogenes and tumor suppressors; and that the subtypes are biologically and clinically relevant. These subtypes provide new insight into HNSCC etiology, as well as a valuable method for classifying HNSCC tumors. A total of 141 samples were considered. CEL files were subject to quality control (QC) procedures using the Affymetrix Genotyping Console, and arrays that produced contrast QC measurements above the default threshold of .4 were removed from subsequent analysis. The remaining 99 CEL files were processed with aroma, and log2 intensity ratios were produced using a pooled collection of normal samples as a reference. After segmenting the log2 ratios with DNAcopy, the resulting copy number profiles were subjected to manual review. Arrays that produced low quality copy number profiles were removed from subsequent analysis. Copy number values from chr1 - chr22 were considered.
2013-03-01 | E-GEOD-39367 | biostudies-arrayexpress
Project description:Molecular characterization of choroid plexus tumors reveals novel clinically relevant subgroups
| PRJNA259766 | ENA
Project description:Characterization of patterns of gene expression measured by cDNA microarrays to subclassify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors and 7 benign tissues were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into a basal epithelial-like, an ERBB2-overexpressing, two luminal epithelial-like and a normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Computed
2006-03-06 | E-GEOD-4335 | biostudies-arrayexpress
Project description:In this study, we profiled gene expressions on 20 biopsy tissues of early stage breast carcinoma using Applied Biosystem’s Human Genome Survey Microarrays. Two main previously defined clinically relevant subtypes of breast tumors, Luminal A (longest survival time) and Basal (shortest survival time) were identified. Statistical analysis identified 1210 genes as signature genes characterizing the two subtypes of breast cancer. PantherTM functional classification and biological pathway analysis on these signature genes depicts a more detailed molecular portrait of these expression-based subtypes: Genes over expressed in Luminal A subtype were over-represented by biological function/processes such as cell structure and amino acid metabolism, while genes over expressed in the Basal subtype are over-represented by kinases, oncogenesis, cell cycle regulatory genes and TGF-beta signaling pathways. Our results provided further evidence that these breast tumor subtypes represent biologically distinct disease entities. In an attempt to identify the best set of genes as potential biomarkers for sub-classifying breast cancer, parallel data were generated on the same 20 patients samples using Stanford 42K cDNA Arrays and Agilent Human Whole Genome Arrays. Same subtypes of breast cancer were identified and the results from the three microarray platforms were found to be highly correlated. Using PAM (Prediction Analysis of Microarray) analysis, a minimal numbers of genes were selected to best characterize and distinguish the Luminal A and Basal subtypes of tumors. These classifier genes were further verified by TaqMan assays. Validated by multiple gene expression platforms, the classifier genes identified in this study defined potential prognostic molecular markers for breast cancers. Keywords: sub-classification and characterization of early breast carcinomas
2005-11-30 | GSE3155 | GEO
Project description:Background: Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction. Results: We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day’s signatures. Conclusions: We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.
2019-06-20 | GSE131599 | GEO
Project description:[original title] Combined gene expression and genomic profiling define two intrinsic molecular subtypes of urothelial carcinoma and gene signatures for molecular grading and outcome. In the present investigation we sought to refine the classification of urothelial carcinoma by combining information on gene expression, genomic, and gene mutation levels. For these purposes we performed gene expression analysis of 144 carcinomas, and whole genome array-CGH analysis and mutation analyses of FGFR3, PIK3CA, KRAS, HRAS, NRAS, TP53, CDKN2A, and TSC1, in 103 of these cases. Hierarchical cluster analysis identified two intrinsic molecular subtypes, MS1 and MS2, which were validated and defined by the same set of genes in three independent bladder cancer data sets. The two subtypes differed with respect to gene expression and mutation profiles, as well as with the level of genomic instability. The data shows that genomic instability was the most distinguishing genomic feature of MS2 tumors, and that this trait was not dependent on TP53/MDM2 alterations. By combining molecular and pathological data it was possible to distinguish two molecular subtypes of Ta and T1 tumors, respectively. In addition, we define gene signatures validated in two independent data sets that classify urothelial carcinoma into low (G1/G2) and high grade (G3) tumors as well as non-muscle and muscle-invasive tumors with high precisions and sensitivities, suggesting molecular grading as a relevant complement to standard pathological grading. We also present a gene expression signature with independent prognostic impact on metastasis and disease specific survival. We conclude that the combination of molecular and histopathological classification systems may provide a strong improvement for bladder cancer classification and produce new insights into the development of this tumor type.
2010-06-14 | GSE19915 | GEO