Predicting Response to Methotrexate, Vinblastine, Doxorubicin, and Cisplatin Neoadjuvant Chemotherapy for Bladder Cancers Through Genome-Wide Gene Expression Profiling

Takata, Ryo; Katagiri, Toyomasa; Kanehira, Mitsugu; Tsunoda, Takuya; Shuin, Taro; Miki, Tsuneharu; Namiki, Mikio; Kohri, Kenjiro; Matsushita, Yasuyuki; Fujioka, Takashi; Nakamura, Yusuke

doi:10.1016/s0022-5347(05)00371-x

Cited by 43 publications

(57 citation statements)

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“…For example, in the BL-Jap study, the original authors reported a 14-gene signature GEM, which we call the Takata-GEM, predictive of patients’ response to MVAC combination chemotherapy. (15) This Takata-GEM was developed from the initial set of 18 patients and evaluated on an additional set of 27 patients (total 45) from the same center. We compared the performance of the COXEN-based MVAC combination GEM, COXEN-GEM, to Takata-GEM for patients’ disease-free survival time stratification.…”

Section: Resultsmentioning

confidence: 99%

Concordant Gene Expression Signatures Predict Clinical Outcomes of Cancer Patients Undergoing Systemic Therapy

Williams

Cheon²,

Havaleshko³

et al. 2009

Cancer Res

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Conventional development of multivariate gene expression models (GEM) predicting therapeutic response of cancer patients is based on analysis of patients treated with specific regimens, which limits generalization to different or novel drug combinations. We overcome this limitation by developing GEMs based on in vitro drug sensitivities and microarray analyses of the NCI-60 cancer cell line panel. These GEMs were evaluated in blind fashion as predictors of tumor response and/or patient survival in seven independent cohorts of patients with breast (n = 275), bladder (n = 59), and ovarian (n = 143) cancer treated with multiagent chemotherapy, of which 233 patients were from prospectively enrolled clinical trials. In all studies, GEMs effectively stratified tumor response and patient survival independent of established clinical and pathologic tumor variables. In bladder cancer patients treated with neoadjuvant methotrexate, vinblastine, Adriamycin (doxorubicin), and cisplatin, the 3-year overall survival for those with favorable GEM scores was 81% versus 33% for those with less favorable scores (P = 0.002). GEMs for breast cancer patients treated with 5-fluorouracil, Adriamycin (doxorubicin), and cyclophosphamide and ovarian cancer patients treated with platinum-containing regimens also stratified patient survival [5-year overall survival 100% versus 74% (P = 0.05) and 3-year overall survival 68% versus 43% (P = 0.008), respectively]. Importantly, clinical prediction using our in vitro GEM was superior to that of conventionally derived GEMs. We show a facile yet effective approach to GEM derivation that identifies patients most likely to benefit from selected multiagent therapy. Use of such in vitro-based GEMs may provide a robust and generalizable approach to personalized cancer therapy. [Cancer Res 2009;69(21):8302-9]

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Section: Resultsmentioning

confidence: 99%

Concordant Gene Expression Signatures Predict Clinical Outcomes of Cancer Patients Undergoing Systemic Therapy

Williams

Cheon²,

Havaleshko³

et al. 2009

Cancer Res

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“…When single drug GEMs for each of MVAC were combined, and prediction scores found to be significantly different between responders and non-responders (P=0.002 and 0.03, respectively), resulting in a sensitivity of 83%, specificity 64%, positive predictive value of 71%, and negative predictive value of 78%. Compellingly, in the neoadjuvant dataset(3, 15), which was large enough for multivariate analysis, the COXEN GEM scores were found to be independent of a variety of traditional clinicopathologic parameters and the only parameter independently associated with response.…”

Section: Applications Of Coxen In Therapeutic Response Predictionmentioning

confidence: 94%

“…Importantly, for two studies of bladder cancer tested, these COXEN GEMs performed well for patients in both the neoadjuvant (N=45) (3, 15) and advanced tumor (N=14) (4) settings. When single drug GEMs for each of MVAC were combined, and prediction scores found to be significantly different between responders and non-responders (P=0.002 and 0.03, respectively), resulting in a sensitivity of 83%, specificity 64%, positive predictive value of 71%, and negative predictive value of 78%.…”

Section: Applications Of Coxen In Therapeutic Response Predictionmentioning

confidence: 99%

“…Recent advances suggest that these technologies may change the way pathologists and oncologists approach the diagnosis and nosology of tumors, while key recent reports suggest that use of prediction frameworks developed from gene expression profiling data, roughly, “gene expression models (GEMs),” can be developed and clinically implemented to provide accurate prognostication of disease course (1) and even therapeutic benefit (2). For example, in bladder cancer, studies have developed GEMs predicting chemotherapeutic response of muscle invasive tumors (3, 4). …”

Section: Introductionmentioning

confidence: 99%

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The COXEN Principle: Translating Signatures of In vitro Chemosensitivity into Tools for Clinical Outcome Prediction and Drug Discovery in Cancer

et al. 2010

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Substantial effort has been devoted to in vitro testing of candidate chemotherapeutic agents. In particular, the United States National Cancer Institute Developmental Therapeutics Program (NCI-DTP) Human Tumor Cell Line Screen has screened hundreds of thousands of compounds and extracts, for which data on more than 40,000 compounds tested on a panel of 60 cancer cell lines (NCI-60) are publically available. In tandem, gene expression profiling has brought about a sea change in our understanding of cancer biology, allowing discovery of biomarkers or signatures able to characterize, classify, and prognosticate clinical behavior of human tumors. Recent studies have used tumor profiling matched to clinical trial outcome data to derive gene expression models predicting therapeutic outcomes, though such efforts are costly, time-consuming, tumor type-specific, and not amenable to rare diseases. Furthermore, addition of new or established drugs to multidrug combinations in which such models are already available requires the entire model to be re-derived. Can the aforementioned in vitro testing platform, coupled to the universal language of genomics, be used to develop, a priori, gene expression models predictive of clinical outcomes? Recent advances, including the CO-eXpression ExtrapolatioN (COXEN) algorithm, suggest that development of these models may be possible and raise important implications for future trial design and drug discovery.

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“…A number of studies aimed to develop a molecular signature capable of assessing response to cytotoxic chemotherapy in selected BC cases 67,69 . Using the known geneexpression profiling and drug sensitivity data from the NCI-60 panel of tumor cell lines, Theodorescu et al have recently developed a bioinformatic approach called Coexpression Extrapolation (COXEN) 70,71 , which is able to predict response to neoadjuvant chemotherapy in MIBC.…”

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confidence: 99%

Molecular markers in bladder cancer: Novel research frontiers

Sanguedolce

Cormio

Bufo

et al. 2015

Critical Reviews in Clinical Laboratory Sciences

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Bladder cancer (BC) is a heterogeneous disease encompassing distinct biologic features that lead to extremely different clinical behaviors. In the last 20 years, great efforts have been made to predict disease outcome and response to treatment by developing risk assessment calculators based on multiple standard clinical-pathological factors, as well as by testing several molecular markers. Unfortunately, risk assessment calculators alone fail to accurately assess a single patient's prognosis and response to different treatment options. Several molecular markers easily assessable by routine immunohistochemical techniques hold promise for becoming widely available and cost-effective tools for a more reliable risk assessment, but none have yet entered routine clinical practice. Current research is therefore moving towards (i) identifying novel molecular markers; (ii) testing old and new markers in homogeneous patients' populations receiving homogeneous treatments; (iii) generating a multimarker panel that could be easily, and thus routinely, used in clinical practice; (iv) developing novel risk assessment tools, possibly combining standard clinical-pathological factors with molecular markers. This review analyses the emerging body of literature concerning novel biomarkers, ranging from genetic changes to altered expression of a huge variety of molecules, potentially involved in BC outcome and response to treatment. Findings suggest that some of these indicators, such as serum circulating tumor cells and tissue mitochondrial DNA, seem to be easily assessable and provide reliable information. Other markers, such as the phosphoinositide-3-kinase (PI3K)/AKT (serine-threonine kinase)/mTOR (mammalian target of rapamycin) pathway and epigenetic changes in DNA methylation seem to not only have prognostic/predictive value but also, most importantly, represent valuable therapeutic targets. Finally, there is increasing evidence that the development of novel risk assessment tools combining standard clinical-pathological factors with molecular markers represents a major quest in managing this poorly predictable disease.

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Predicting Response to Methotrexate, Vinblastine, Doxorubicin, and Cisplatin Neoadjuvant Chemotherapy for Bladder Cancers Through Genome-Wide Gene Expression Profiling

Cited by 43 publications

References 0 publications

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

The COXEN Principle: Translating Signatures of In vitro Chemosensitivity into Tools for Clinical Outcome Prediction and Drug Discovery in Cancer

Molecular markers in bladder cancer: Novel research frontiers

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