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https://www.readbyqxmd.com/read/29021619/pan-cancer-analysis-of-bi-allelic-alterations-in-homologous-recombination-dna-repair-genes
#1
Nadeem Riaz, Pedro Blecua, Raymond S Lim, Ronglai Shen, Daniel S Higginson, Nils Weinhold, Larry Norton, Britta Weigelt, Simon N Powell, Jorge S Reis-Filho
BRCA1 and BRCA2 are involved in homologous recombination (HR) DNA repair and are germ-line cancer pre-disposition genes that result in a syndrome of hereditary breast and ovarian cancer (HBOC). Whether germ-line or somatic alterations in these genes or other members of the HR pathway and if mono- or bi-allelic alterations of HR-related genes have a phenotypic impact on other cancers remains to be fully elucidated. Here, we perform a pan-cancer analysis of The Cancer Genome Atlas (TCGA) data set and observe that bi-allelic pathogenic alterations in homologous recombination (HR) DNA repair-related genes are prevalent across many malignancies...
October 11, 2017: Nature Communications
https://www.readbyqxmd.com/read/28991261/esrp1-is-overexpressed-in-ovarian-cancer-and-promotes-switching-from-mesenchymal-to-epithelial-phenotype-in-ovarian-cancer-cells
#2
H M Jeong, J Han, S H Lee, H-J Park, H J Lee, J-S Choi, Y M Lee, Y-L Choi, Y K Shin, M J Kwon
Epithelial splicing regulatory protein 1 (ESRP1) and 2 (ESRP2), epithelial cell-specific regulators of alternative splicing, are downregulated during the epithelial-mesenchymal transition (EMT). These factors have roles in tumor progression and metastasis in some cancers; however, their expression and function in ovarian cancer (OC) remain unclear. We found that ESRP1 and ESRP2 mRNAs were expressed at higher levels in OC cells than in immortalized ovarian surface epithelial (IOSE) cells, and confirmed their overexpression in OC tissues at the protein level...
October 9, 2017: Oncogenesis
https://www.readbyqxmd.com/read/28978132/expression-profiles-analysis-reveals-an-integrated-mirna-lncrna-signature-to-predict-survival-in-ovarian-cancer-patients-with-wild-type-brca1-2
#3
Liyuan Guo, Yan Peng, Yuanyuan Meng, Yunduo Liu, Shangshang Yang, Hong Jin, Qi Li
Emerging evidence shows that dysregulated expression of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) were closely linked with disease progression, including cancers. However, the joint predictive power of miRNAs and lncRNAs in prognosis for ovarian cancer (OV) patients with wild-type BRCA1/2 is as yet unknown. In this study, we sought to assess the joint predictive power of miRNAs and lncRNAs by integrating miRNA and lncRNA expression profiles and clinical data of 281 OV patients with wild-type BRCA1/2 from The Cancer Genome Atlas (TCGA) project...
September 15, 2017: Oncotarget
https://www.readbyqxmd.com/read/28927463/towards-precision-medicine-discovering-novel-gynecological-cancer-biomarkers-and-pathways-using-linked-data
#4
Alokkumar Jha, Yasar Khan, Muntazir Mehdi, Md Rezaul Karim, Qaiser Mehmood, Achille Zappa, Dietrich Rebholz-Schuhmann, Ratnesh Sahay
BACKGROUND: Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, these datasets are published from the isolated and different sequencing facilities. Consequently, the process of sharing and aggregating multisite sequencing datasets are thwarted by issues such as the need to discover relevant data from different sources, built scalable repositories, the automation of data linkage, the volume of the data, efficient querying mechanism, and information rich intuitive visualisation...
September 19, 2017: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/28911005/ociad2-suppressed-tumor-growth-and-invasion-via-akt-pathway-in-hepatocelluar-carcinoma
#5
Dan Wu, Xufang Yang, Huiming Peng, Dongmin Guo, Weiling Zhao, Chen Zhao, Xiaobo Zhou
Hepatocellular carcinoma (HCC) is an aggressive tumor and the third leading cause of cancer-related death worldwide. Ovarian carcinoma immunoreactive antigen-like protein 2 (OCIAD2) has been found frequently methylated in various cancers, including HCC. The aim of the present study was to investigate the role of OCIAD2 in HCC progression. We analyzed liver hepatocellular carcinoma patients' data from the Cancer Genome Atlas (TCGA), including data extracted from 371 HCC tissues and 50 adjacent normal liver tissues...
September 1, 2017: Carcinogenesis
https://www.readbyqxmd.com/read/28891089/molecular-insights-into-the-transcriptional-regulatory-role-of-thyroid-hormones-in-ovarian-cancer
#6
Elena Shinderman-Maman, Chen Weingarten, Dotan Moskovich, Haim Werner, Aleck Hercbergs, Paul J Davis, Martin Ellis, Osnat Ashur-Fabian
The regulation of cancer-relevant genes by the thyroid hormones, 3, 5, 3'-Triiodo-L-thyronine (T3) and L-thyroxine (T4), was recently acknowledged. However, limited data exists on the hormonal effects on gene expression in ovarian cancer, a gynecological malignancy associated with a low cure rate. The expression of fifteen genes involved in DNA repair, cell cycle, apoptosis, and tumor suppression was evaluated in OVCAR-3 and A2780 cell lines, using real-time PCR following short incubation with T3 (1 nM) or T4 (100 nM)...
September 11, 2017: Molecular Carcinogenesis
https://www.readbyqxmd.com/read/28880866/ribosomal-dna-copy-number-amplification-and-loss-in-human-cancers-is-linked-to-tumor-genetic-context-nucleolus-activity-and-proliferation
#7
Meng Wang, Bernardo Lemos
Ribosomal RNAs (rRNAs) are transcribed from two multicopy DNA arrays: the 5S ribosomal DNA (rDNA) array residing in a single human autosome and the 45S rDNA array residing in five human autosomes. The arrays are among the most variable segments of the genome, exhibit concerted copy number variation (cCNV), encode essential components of the ribosome, and modulate global gene expression. Here we combined whole genome data from >700 tumors and paired normal tissues to provide a portrait of rDNA variation in human tissues and cancers of diverse mutational signatures, including stomach and lung adenocarcinomas, ovarian cancers, and others of the TCGA panel...
September 2017: PLoS Genetics
https://www.readbyqxmd.com/read/28852190/mutational-heterogeneity-in-non-serous-ovarian-cancers
#8
Jamie K Teer, Sean Yoder, Anxhela Gjyshi, Santo V Nicosia, Chaomei Zhang, Alvaro N A Monteiro
Epithelial ovarian cancer is a leading cause of death in gynecological cancers. While several systematic studies have revealed the mutation landscape of serous epithelial ovarian cancer, other non-serous subtypes of the disease have not been explored as extensively. Here we conduct exome sequencing of nine non-serous epithelial ovarian tumors (six endometrioid and three mucinous) and their corresponding normal DNA as well as a tumor-only granulosa cell sample. We integrated the exome data with targeted gene sequencing for 1,321 genes selected for their involvement in cancer from additional 28 non-serous ovarian tumors and compared our results to TCGA ovarian serous cystadenocarcinoma and uterine corpus endometrial carcinomas...
August 29, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28852147/proteomics-analysis-to-reveal-biological-pathways-and-predictive-proteins-in-the-survival-of-high-grade-serous-ovarian-cancer
#9
Hongyu Xie, Wenjie Wang, Fengyu Sun, Kui Deng, Xin Lu, Huijuan Liu, Weiwei Zhao, Yuanyuan Zhang, Xiaohua Zhou, Kang Li, Yan Hou
High-grade serous ovarian cancer (HGSC) is an aggressive cancer with a worse clinical outcome. Therefore, studies about the prognosis of HGSC may provide therapeutic avenues to improve patient outcomes. Since genome alteration are manifested at the protein level, we integrated protein and mRNA data of ovarian cancer from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) and utilized the sparse overlapping group lasso (SOGL) method, a new mechanism-driven variable selection method, to select dysregulated pathways and crucial proteins related to the survival of HGSC...
August 29, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28817186/a-prognostic-11genes-expression-model-for-ovarian-cancer
#10
Chuan-Di Men, Qiong-Na Liu, Qing Ren
The symptoms of ovarian cancer at early stages are usually absent which makes the diagnosis in its early stages exceedingly difficult. Previous research has proven that ovarian cancer is a genetic disease, which depends on the alteration of multi-cancer related genes and anti-cancer genes, multi-stages and multi-pathways, involving a variety of oncogene activation and anti-oncogene inactivation. For a better understanding of the prognostic classification of ovarian cancer, gene expression profiles were used to analyse the prognostic factors of ovarian cancer, and the prognostic model was used to classify the ovarian cancer samples...
August 17, 2017: Journal of Cellular Biochemistry
https://www.readbyqxmd.com/read/28781807/amplification-of-the-nsd3-brd4-chd8-pathway-in-pelvic-high-grade-serous-carcinomas-of-tubo-ovarian-and-endometrial-origin
#11
Derek H Jones, Douglas I Lin
Identification of novel therapeutics in pelvic high-grade serous carcinoma (HGSC) has been hampered by a paucity of actionable point mutations in target genes. The aim of the present study was to investigate the extent of amplification of the therapeutically targetable NSD3-CHD8-BRD4 pathway in pelvic HGSC, and to determine whether amplification is associated with worse prognosis. The Cancer Genome Atlas (TCGA) ovarian and endometrial cancer cohorts were retrospectively analyzed via online data-mining tools to test the association of NSD3, CHD8 and BRD4 genomic alterations with survival of pelvic HGSC patients...
August 2017: Molecular and Clinical Oncology
https://www.readbyqxmd.com/read/28759038/high-depth-high-accuracy-microsatellite-genotyping-enables-precision-lung-cancer-risk-classification
#12
K R Velmurugan, R T Varghese, N C Fonville, H R Garner
There remains a large discrepancy between the known genetic contributions to cancer and that which can be explained by genomic variants, both inherited and somatic. Recently, understudied repetitive DNA regions called microsatellites have been identified as genetic risk markers for a number of diseases including various cancers (breast, ovarian and brain). In this study, we demonstrate an integrated process for identifying and further evaluating microsatellite-based risk markers for lung cancer using data from the cancer genome atlas and the 1000 genomes project...
July 31, 2017: Oncogene
https://www.readbyqxmd.com/read/28670762/tribbles-2-mediates-cisplatin-sensitivity-and-dna-damage-response-in-epithelial-ovarian-cancer
#13
Daniel Kritsch, Franziska Hoffmann, Daniel Steinbach, Lars Jansen, Stella Mary Photini, Mieczyslaw Gajda, Alexander S Mosig, Jürgen Sonnemann, Sven Peters, Margarita Melnikova, Jürgen Thomale, Matthias Dürst, Ingo B Runnebaum, Norman Häfner
Aim was to identify methylated genes with functional involvement in cisplatin-resistance development of epithelial ovarian cancer (EOC). Genome-wide analyses of hypermethylated CpG-islands in resistant cell lines in combination with qRT-PCR analyses were used to identify epigenetically silenced genes. EOC-Type-II tumors were analyzed for gene methylation and expression and TCGA data were interrogated in-silico. Experiments revealed 37 commonly hypermethylated genes in resistant cells of which Tribbles 2 (TRIB2) showed the most pronounced downregulation on mRNA level and was characterized further...
October 15, 2017: International Journal of Cancer. Journal International du Cancer
https://www.readbyqxmd.com/read/28627585/role-of-metadherin-in-estrogen-regulated-gene-expression
#14
Yujun Li, Jesus Gonzalez Bosquet, Shujie Yang, Kristina W Thiel, Yuping Zhang, Haitao Liu, Kimberly K Leslie, Xiangbing Meng
The disruption of estrogen signaling is widely associated with the development of breast, endometrial and ovarian cancers. As a multifunctional mediator of carcinogenesis, metadherin (MTDH)/astrocyte elevated gene-1 (AEG-1) overexpression has been associated with numerous types of cancer, with reported roles in tumor initiation, proliferation, invasion, metastasis and chemoresistance. At the molecular level, MTDH has been shown to interact with proteins that drive tumorigenesis, including nuclear factor-κB (NF-κB), promyelocytic leukaemia zinc finger (PLZF), BRCA2- and CDKN1A (p21Cip1/Waf-1/mda-6)-interacting protein α (BCCIPα) and staphylococcal nuclease and tudor domain containing 1 (SND1)...
August 2017: International Journal of Molecular Medicine
https://www.readbyqxmd.com/read/28615526/identifying-prognostic-signature-in-ovarian-cancer-using-dirgenerank
#15
Jian-Yong Wang, Ling-Ling Chen, Xiong-Hui Zhou
Identifying the prognostic genes in cancer is essential not only for the treatment of cancer patients, but also for drug discovery. However, it's still a big challenge to select the prognostic genes that can distinguish the risk of cancer patients across various data sets because of tumor heterogeneity. In this situation, the selected genes whose expression levels are statistically related to prognostic risks may be passengers. In this paper, based on gene expression data and prognostic data of ovarian cancer patients, we used conditional mutual information to construct gene dependency network in which the nodes (genes) with more out-degrees have more chances to be the modulators of cancer prognosis...
July 11, 2017: Oncotarget
https://www.readbyqxmd.com/read/28606096/pan-cancer-analysis-reveals-technical-artifacts-in-tcga-germline-variant-calls
#16
Alexandra R Buckley, Kristopher A Standish, Kunal Bhutani, Trey Ideker, Roger S Lasken, Hannah Carter, Olivier Harismendy, Nicholas J Schork
BACKGROUND: Cancer research to date has largely focused on somatically acquired genetic aberrations. In contrast, the degree to which germline, or inherited, variation contributes to tumorigenesis remains unclear, possibly due to a lack of accessible germline variant data. Here we called germline variants on 9618 cases from The Cancer Genome Atlas (TCGA) database representing 31 cancer types. RESULTS: We identified batch effects affecting loss of function (LOF) variant calls that can be traced back to differences in the way the sequence data were generated both within and across cancer types...
June 12, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28579401/node-based-learning-of-differential-networks-from-multi-platform-gene-expression-data
#17
Le Ou-Yang, Xiao-Fei Zhang, Min Wu, Xiao-Li Li
Recovering gene regulatory networks and exploring the network rewiring between two different disease states are important for revealing the mechanisms behind disease progression. The advent of high-throughput experimental techniques has enabled the possibility of inferring gene regulatory networks and differential networks using computational methods. However, most of existing differential network analysis methods are designed for single-platform data analysis and assume that differences between networks are driven by individual edges...
June 1, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/28537669/e2f2-induces-mcm4-ccne2-and-whsc1-upregulation-in-ovarian-cancer-and-predicts-poor-overall-survival
#18
L Xie, T Li, L-H Yang
OBJECTIVE: To explore the genes co-upregulated with E2F2 in ovarian cancer and their association with survival outcomes in ovarian cancer patients. MATERIALS AND METHODS: The raw data of GDS3592 was downloaded from GEO datasets for reanalysis. The overlapping subset between the top 150 upregulated genes in ovarian cancer epithelial cells (CEPIs) and the E2F2 positively correlated genes (Pearson's r≥0.5) in ovarian cancer cohort in TCGA was identified. The association between E2F2, MCM4, CCNE2 and WHSC1 and overall survival (OS) and recurrence-free survival (RFS) in ovarian cancer patients were assessed using Kaplan-Meier plotter...
May 2017: European Review for Medical and Pharmacological Sciences
https://www.readbyqxmd.com/read/28520777/network-based-stratification-of-major-cancers-by-integrating-somatic-mutation-and-gene-expression-data
#19
Zongzhen He, Junying Zhang, Xiguo Yuan, Zhaowen Liu, Baobao Liu, Shouheng Tuo, Yajun Liu
The stratification of cancer into subtypes that are significantly associated with clinical outcomes is beneficial for targeted prognosis and treatment. In this study, we integrated somatic mutation and gene expression data to identify clusters of patients. In contrast to previous studies, we constructed cancer-type-specific significant co-expression networks (SCNs) rather than using a fixed gene network across all cancers, such as the network-based stratification (NBS) method, which ignores cancer heterogeneity...
2017: PloS One
https://www.readbyqxmd.com/read/28423358/characterization-of-fusion-genes-in-common-and-rare-epithelial-ovarian-cancer-histologic-subtypes
#20
Madalene A Earp, Rama Raghavan, Qian Li, Junqiang Dai, Stacey J Winham, Julie M Cunningham, Yanina Natanzon, Kimberly R Kalli, Xiaonan Hou, S John Weroha, Paul Haluska, Kate Lawrenson, Simon A Gayther, Chen Wang, Ellen L Goode, Brooke L Fridley
Gene fusions play a critical role in some cancers and can serve as important clinical targets. In epithelial ovarian cancer (EOC), the contribution of fusions, especially by histological type, is unclear. We therefore screened for recurrent fusions in a histologically diverse panel of 220 EOCs using RNA sequencing. The Pipeline for RNA-Sequencing Data Analysis (PRADA) was used to identify fusions and allow for comparison with The Cancer Genome Atlas (TCGA) tumors. Associations between fusions and clinical prognosis were evaluated using Cox proportional hazards regression models...
July 18, 2017: Oncotarget
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