Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA252042 | ENA |
REPOSITORIES: ENA
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Project description:Background: Clinical characteristics of ovarian clear cell adenocarcinoma (CCC) include 1) higher incidence among Japanese, 2) association with endometriosis, 3) poor prognosis in advanced stage, 4) higher incidence of thrombosis as complication. We applied high resolution comparative genomic hybridization (CGH) array to screen somatic copy number alterations (SCNAs) associated with these clinical characteristics. Methods: We conducted a prospective cohort study. DNA obtained from tumors was assayed by array comparative genomic hybridization using Agilent Whole Human Genome 244K.
2014-06-10 | GSE58342 | GEO
Project description:Background: Clinical characteristics of ovarian clear cell adenocarcinoma (CCC) include 1) higher incidence among Japanese, 2) association with endometriosis, 3) poor prognosis in advanced stage, 4) higher incidence of thrombosis as complication. We applied high resolution comparative genomic hybridization (CGH) array to screen somatic copy number alterations (SCNAs) associated with these clinical characteristics. Methods: We conducted a prospective cohort study. DNA obtained from tumors was assayed by array comparative genomic hybridization using Agilent Whole Human Genome 244K. 117 tumor samples were analyzed by Agilent-G4411B Human Genome CGH Microarray Kit 244A. Log2 Ratio (tumor sample DNA/normal DNA) were compared between Japanese and non-Japanese, between patients with thrombosis and without thrombosis, between patients with endometriosis and without endometriosis, among patients sensitive to, intermediate to and resistant to the chemotherapy, among FIGO stages, between relapsed and not relapsed, between survived and not survived.
2014-06-10 | E-GEOD-58342 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors.
2012-10-25 | E-GEOD-30274 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors. Data was pre-processed and normalized with Hapmap JPT using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30283 | biostudies-arrayexpress
Project description:Copy number profiling of 36 ovarian tumors on Affymetrix 100K SNP arrays Thirty-six ovarian tumors were profiled for copy-number alterations with the Affymetrix 100K Mapping Array. Copy number profiling of 36 ovarian tumors on Affymetrix 500K SNP arrays Sixteen ovary tumors were profiled for copy-number alterations with the high-resolution Affymetrix 500K Mapping Array.
2010-12-16 | GSE26075 | GEO
Project description:Background: Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. Methods: We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 M-bM-^@M-^\ovarian cancerM-bM-^@M-^] cell lines has been classified into histological types using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Results: Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histological type of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic M-bM-^@M-^\ovarian carcinomaM-bM-^@M-^] cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. The DNA copy number of 10 ovarian cancer cell lines was examined and changes in copy number of genes whose expression is assumed to be critical to the phenotype of ovarian clear cell carcinoma was evaluated. Copy number data was estimated from signal intensity on Affmetrix SNP 6.0 arrays. Copy number ratio values were generated in Partek Genomics Suite (v 6.6) using a Partek corporation distributed baseline file of normal (2N) genomic DNA and default parameters. Post import values were corrected for localized GC content using the inbuilt Partek feature based on methods described in Diskin et al. (Nucleic Acids Research. 2008. 36:19). The characteristic "literature reported histotype" is the reported histological subtype for each cell line from the originating laboratory or cell bank (repository). The characteristic "Predicted histology" is based on parameters described in Anglesio et al. (PLOS ONE 2013. in press), including immunohistochemical phenotype, presence of typical mutations, consistency in growth characteristics, and DNA copy number. All cell lines were grown under recomended conditions, collected near confluence (80%) and not subjected to any experimental treatments or modifications.
2013-08-01 | E-GEOD-48351 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 42 archived frozen tumor samples collected from Department of Obstetrics and Gynecology, Tri-Service General Hospital, Taiwan, containing 8 clear cell, 3 mucinous, and 31 serous.
2012-10-25 | E-GEOD-30284 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 46 archived frozen tumor samples collected from Department of Obstetrics and Gynecology, Tri-Service General Hospital, Taiwan, containing 9 clear cell, 6 mucinous, and 31 serous. Data was pre-processed and normalized with Hapmap CHB using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30300 | biostudies-arrayexpress
Project description:Using data from high-density genomic profiling arrays, we investigated the profiles of somatic copy-number aberrations (SCNAs) in 659 gastric adenocarcinomas drawn approximately even numbers of Asian and Western patients with two goals in mind: (1) using the power of our large data set to detect new, and refine existing, regions of significantly recurring SCNAs; (2) determining if there exist fundamental differences in the manifestation of gastric adenocarcinoma in Asian versus Western patients that affect pattern of SCNAs. Among the 83 regions of significant alteration we indeed found some new targets in gastric adenocarcinoma such as the tumor suppressor gene SMARCA4 and proto-oncogene MYB, and additionally refined the boundaries of known significant regions. We found only slight differences in the overall copy number patterns between Asian and Western gastric adenocarcinoma patients indicating that the disease is fundamentally similar in both populations and the divergent clinical outcomes cannot be ascribed to different underlying SCNAs. The 111 copy number profiles contained in this archive are the previously unpublished portion of our study.
2017-04-15 | GSE77775 | GEO
Project description:Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations and even more in women. Since epidermal growth factor receptor (EGFR) mutations or anaplastic lymphoma kinase (ALK) fusions are major alterations found in NSLA, studies have focused on NSLA with EGFR and ALK alteration (EA), but not for NSLA without EGFR and ALK alteration (NENA). To reveal the proteogenomic landscape of NENA, we selected 101 NSLA tissues without EGFR and ALK by targeted sequencing of 1597 FFPE samples, and performed multiomics analyses including whole genome, transcriptome, methylation EPIC array, total proteome, and phosphoproteome. Genome analysis revealed that TP53 (25%), KRAS (22%), ROS1 fusion (13%), SETD2 (11%), and ERRB2 (9%) were the most frequently mutated genes in NENA. Proteogenomic impact analysis found that STK11 and ERBB2 somatic mutations had more profound effects on cancer-associated genes in NENA. From DNA copy number alteration analysis, we identified 22 prognostic proteins whose expression was controlled through transcriptome from copy number alterations Intriguingly, from gene set enrichment analysis, estrogen signaling emerged as the key pathway activated in NENA compared with EA. Evidence from multiomics analysis including copy number gains in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14, also supported the increased estrogen signaling. Finally, the saracatinib, an Src inhibitor, was suggested as a potential drug for targeting activated estrogen signaling in NENA. Taken together, the proteogenomic landscape for NENA from this study will enhance our understanding of the etiology of NSLA.
2024-03-12 | PXD033360 | Pride