Biological Insights into Chemotherapy Resistance in Ovarian Cancer
暂无分享,去创建一个
T. Starr | P. Argenta | J. Abrahante | P. Croonquist | M. Khalifa | Mihir Shetty | M. Glasgow | S. Talukdar | Paula A. Croonquist
[1] Xia Liu,et al. Microarray‐based identification of genes associated with prognosis and drug resistance in ovarian cancer , 2018, Journal of cellular biochemistry.
[2] Gregory M. Chen,et al. Consensus on Molecular Subtypes of High-Grade Serous Ovarian Carcinoma , 2018, Clinical Cancer Research.
[3] Wyeth W. Wasserman,et al. Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer , 2018, Cell.
[4] P. Dey,et al. The chemotherapy response score is a useful histological predictor of prognosis in high‐grade serous carcinoma , 2018, Histopathology.
[5] S. Cooper,et al. Molecular Response to Neoadjuvant Chemotherapy in High-Grade Serous Ovarian Carcinoma , 2016, Molecular Cancer Research.
[6] A. Kopp-Schneider,et al. Prediction of clinical response to drugs in ovarian cancer using the chemotherapy resistance test (CTR-test) , 2017, Journal of Ovarian Research.
[7] Min Zhao,et al. Integrative analysis to identify oncogenic gene expression changes associated with copy number variations of enhancer in ovarian cancer , 2017, Oncotarget.
[8] C. Lindskog,et al. A pathology atlas of the human cancer transcriptome , 2017, Science.
[9] M. Sonego,et al. Common biological phenotypes characterize the acquisition of platinum-resistance in epithelial ovarian cancer cells , 2017, Scientific Reports.
[10] Gregory M. Chen,et al. Consensus on Molecular Subtypes of Ovarian Cancer , 2017, bioRxiv.
[11] Timothy K Starr,et al. Single cell sequencing reveals heterogeneity within ovarian cancer epithelium and cancer associated stromal cells. , 2017, Gynecologic oncology.
[12] Ralf Herwig,et al. Analyzing and interpreting genome data at the network level with ConsensusPathDB , 2016, Nature Protocols.
[13] Zhongming Zhao,et al. Concordance of copy number loss and down-regulation of tumor suppressor genes: a pan-cancer study , 2016, BMC Genomics.
[14] Zhe Zhang,et al. Molecular Subtyping of Serous Ovarian Cancer Based on Multi-omics Data , 2016, Scientific Reports.
[15] S. R. Terlecky,et al. Peroxisome biogenesis in mammalian cells: The impact of genes and environment. , 2016, Biochimica et biophysica acta.
[16] Chen Wang,et al. Gene-expression signatures in ovarian cancer: Promise and challenges for patient stratification. , 2016, Gynecologic oncology.
[17] I. Selcuk,et al. In vitro chemosensitivity in ovarian carcinoma: Comparison of three leading assays. , 2016, Journal of the Turkish German Gynecological Association.
[18] J. Mesirov,et al. The Molecular Signatures Database Hallmark Gene Set Collection , 2015 .
[19] A. Tinker,et al. Chemotherapy Response Score: Development and Validation of a System to Quantify Histopathologic Response to Neoadjuvant Chemotherapy in Tubo-Ovarian High-Grade Serous Carcinoma. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[20] M. Quinn,et al. Paclitaxel and Its Evolving Role in the Management of Ovarian Cancer , 2015, BioMed research international.
[21] Joshy George,et al. Whole–genome characterization of chemoresistant ovarian cancer , 2015, Nature.
[22] G. Inghirami,et al. Stromal contribution to the colorectal cancer transcriptome , 2015, Nature Genetics.
[23] Camille Stephan-Otto Attolini,et al. Stromal gene expression defines poor-prognosis subtypes in colorectal cancer , 2015, Nature Genetics.
[24] Katherine L. Lloyd,et al. Prediction of resistance to chemotherapy in ovarian cancer: a systematic review , 2015, BMC Cancer.
[25] J. Mesirov,et al. The Molecular Signatures Database (MSigDB) hallmark gene set collection. , 2015, Cell systems.
[26] E. Goode,et al. Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer. , 2014, Journal of the National Cancer Institute.
[27] S. Chanock,et al. Analysis of chemotherapeutic response in ovarian cancers using publicly available high-throughput data. , 2014, Cancer research.
[28] P. Colombo,et al. Sensitivity and resistance to treatment in the primary management of epithelial ovarian cancer. , 2014, Critical reviews in oncology/hematology.
[29] Wei Shi,et al. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features , 2013, Bioinform..
[30] G. Getz,et al. Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.
[31] K. Cibulskis,et al. Prognostically relevant gene signatures of high-grade serous ovarian carcinoma. , 2012, The Journal of clinical investigation.
[32] Ralf Herwig,et al. The ConsensusPathDB interaction database: 2013 update , 2012, Nucleic Acids Res..
[33] R. Wenham,et al. In vitro analysis of ovarian cancer response to cisplatin, carboplatin, and paclitaxel identifies common pathways that are also associated with overall patient survival , 2012, British Journal of Cancer.
[34] V. A. Flørenes,et al. Predicting platinum resistance in primary advanced ovarian cancer patients with an in vitro resistance index , 2012, Cancer Chemotherapy and Pharmacology.
[35] D. Brizel,et al. National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology , 2012 .
[36] David R. Kelley,et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks , 2012, Nature Protocols.
[37] K. Becker,et al. Gene expression and pathway analysis of ovarian cancer cells selected for resistance to cisplatin, paclitaxel, or doxorubicin , 2011, Journal of ovarian research.
[38] S. Eschrich,et al. BAD Phosphorylation Determines Ovarian Cancer Chemosensitivity and Patient Survival , 2011, Clinical Cancer Research.
[39] Benjamin J. Raphael,et al. Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.
[40] H. Itamochi,et al. Side population is increased in paclitaxel-resistant ovarian cancer cell lines regardless of resistance to cisplatin. , 2011, Gynecologic oncology.
[41] V. Velculescu,et al. Expression of p16 and Retinoblastoma Determines Response to CDK4/6 Inhibition in Ovarian Cancer , 2011, Clinical Cancer Research.
[42] P. Veldhoven. Biochemistry and genetics of inherited disorders of peroxisomal fatty acid metabolism , 2010 .
[43] Thomas J. Hardcastle,et al. Genomic analysis of genetic heterogeneity and evolution in high-grade serous ovarian carcinoma , 2010, Oncogene.
[44] Jung-Hsien Chiang,et al. Analysis of chemotherapy response programs in ovarian cancers by the next-generation sequencing technologies. , 2010, Gynecologic oncology.
[45] Mark D. Robinson,et al. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..
[46] L. Rice,et al. The role of in vitro directed chemotherapy in epithelial ovarian cancer. , 2010, Reviews in obstetrics & gynecology.
[47] A. Nobel,et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[48] R. Tothill,et al. Novel Molecular Subtypes of Serous and Endometrioid Ovarian Cancer Linked to Clinical Outcome , 2008, Clinical Cancer Research.
[49] Pablo Tamayo,et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[50] J. Foekens,et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.
[51] M. Cronin,et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.
[52] S Miyano,et al. Open source clustering software. , 2004, Bioinformatics.
[53] Yudong D. He,et al. A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .
[54] Roderic D. M. Page,et al. TreeView: an application to display phylogenetic trees on personal computers , 1996, Comput. Appl. Biosci..