Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapy - Wikidata - awgldk - TriplyDB

Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapy

Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapy

http://www.wikidata.org/entity/Q30434260

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Risk based neoadjuvant chemotherapy in muscle invasive bladder cancer Cytotoxic and DNA-targeted therapy in urothelial cancer: have we squeezed the lemon enough?Elevating the Horizon: Emerging Molecular and Genomic Targets in the Treatment of Advanced Urothelial Carcinoma Consensus-phenotype integration of transcriptomic and metabolomic data implies a role for metabolism in the chemosensitivity of tumour cells Multi-gene expression predictors of single drug responses to adjuvant chemotherapy in ovarian carcinoma: predicting platinum resistance.5-Fluorouracil induced intestinal mucositis via nuclear factor-κB activation by transcriptomic analysis and in vivo bioluminescence imaging Retrospective analysis of survival improvement by molecular biomarker-based personalized chemotherapy for recurrent ovarian cancer.Transcriptional signatures of Ral GTPase are associated with aggressive clinicopathologic characteristics in human cancer.A 20-gene model for molecular nodal staging of bladder cancer: development and prospective assessment.Molecular prediction for atherogenic risks across different cell types of leukocytes.Cyclophilin B expression is associated with in vitro radioresistance and clinical outcome after radiotherapy.Multigene expression-based predictors for sensitivity to Vorinostat and Velcade in non-small cell lung cancer.The COXEN principle: translating signatures of in vitro chemosensitivity into tools for clinical outcome prediction and drug discovery in cancer.Use of yeast chemigenomics and COXEN informatics in preclinical evaluation of anticancer agents.Point success rate for patient therapeutic response prediction by continuous biomarker scores.Shifting from population-wide to personalized cancer prognosis with microarrays.Expression profiling for bladder cancer: strategies to uncover prognostic factors.Low penetrance breast cancer susceptibility loci are associated with specific breast tumor subtypes: findings from the Breast Cancer Association Consortium Prediction of resistance to chemotherapy in ovarian cancer: a systematic review.Predicting response to multidrug regimens in cancer patients using cell line experiments and regularised regression models.Biomarkers for prognosis and treatment selection in advanced bladder cancer patients.Identification and Validation of Protein Biomarkers of Response to Neoadjuvant Platinum Chemotherapy in Muscle Invasive Urothelial Carcinoma Comprehensive Assessment of Host Responses to 5-Fluorouracil-Induced Oral Mucositis through Transcriptomic Analysis Progress in personalizing chemotherapy for bladder cancer Contemporary management of muscle-invasive bladder cancer Drug Selection in the Genomic Age: Application of the Coexpression Extrapolation Principle for Drug Repositioning in Cancer Therapy.Pharmacogenomics in bladder cancer.Perspectives on personalized cancer care.Genomic approach towards personalized anticancer drug therapy.Neoadjuvant chemotherapy for invasive bladder cancer.Primary mixed neuroendocrine carcinoma of the bladder with large cell component: a case report and review of the literature.Novel molecular targets for the therapy of urothelial carcinoma.Emerging personalized approaches for the management of advanced urothelial carcinoma.Emerging drugs for urothelial carcinoma.Molecular markers in bladder cancer: Novel research frontiers.The role of biomarkers in the management of epithelial ovarian cancer.Clinical Evaluation of Cisplatin Sensitivity of Germline Polymorphisms in Neoadjuvant Chemotherapy for Urothelial Cancer.CONCORD biomarker prediction for novel drug introduction to different cancer types.Bladder cancer pharmacogenomics: recent insights and future perspectives.Single drug biomarker prediction for ER- breast cancer outcome from chemotherapy.

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P2860

Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapy

http://www.wikidata.org/entity/Q30434260

description

2009 nî lūn-bûn

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2009 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2009 թվականի հոտեմբերին հրատարակված գիտական հոդված

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2009年の論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年论文

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name

Concordant gene expression sig ...... ts undergoing systemic therapy

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Concordant gene expression sig ...... ts undergoing systemic therapy

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type

label

Concordant gene expression sig ...... ts undergoing systemic therapy

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Concordant gene expression sig ...... ts undergoing systemic therapy

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prefLabel

Concordant gene expression sig ...... ts undergoing systemic therapy

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Concordant gene expression sig ...... ts undergoing systemic therapy

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Cancer Research

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Concordant gene expression sig ...... ts undergoing systemic therapy

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Dan Theodorescu

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Dmytro M Havaleshko

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Hyeon Jeong

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Jae K Lee

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Paul D Williams

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Sooyoung Cheon

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P2860

A novel method for gene expression mapping of metastatic competence in human bladder cancer

Prediction of drug combination chemosensitivity in human bladder cancer.

A strategy for predicting the chemosensitivity of human cancers and its application to drug discovery

Predicting response to methotrexate, vinblastine, doxorubicin, and cisplatin neoadjuvant chemotherapy for bladder cancers through genome-wide gene expression profiling.

Evidence that p53-mediated cell-cycle-arrest inhibits chemotherapeutic treatment of ovarian carcinomas.

An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival

Genomic signatures to guide the use of chemotherapeutics.

Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial.

Index for rating diagnostic tests

An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer.

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2784269

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