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.
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.
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.
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.
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.
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