Concise prediction models of anticancer efficacy of 8 drugs using expression data from 12 selected genes

Tanaka, Tomotaka; Tanimoto, Keiji; Otani, Keiko; Satoh, Kenichi; Ohtaki, Megu; Yoshida, Kazuhiro; Toge, Tetsuya; Yahata, Hiroshi; Tanaka, Shinji; Chayama, Kazuaki; Okazaki, Yasushi; Hayashizaki, Yoshihide; Hiyama, Keiko; Nishiyama, Masahiko

doi:10.1002/ijc.20289

Cited by 36 publications

(34 citation statements)

References 27 publications

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“…The in vivo relevance of the model was tested for 5-fluorouracil treatment in gastric cancer patients. The model of predictive value in terms of survival, time to treatment failure and tumour growth showed that the tumour phenotype was indeed related to the therapeutic response to 5-fluorouracil (Tanaka et al, 2004). Miyoshi et al (2002Miyoshi et al ( , 2005 showed that a low CYP3A4 expression in breast tumours, as determined at mRNA and protein level, resulted in a better response to docetaxel, which is inactivated by CYP3A4.…”

Section: Oh-docmentioning

confidence: 98%

“…With respect to the impact of tumour P450s on drug therapy outcome, Tanaka et al (2004), using 19 human cancer cell lines and eight common anticancer drugs, measured the cytotoxic activity of the drugs and performed cDNA microarray analysis to identify associations between specific gene expression and effect of the drug in question (Tanaka et al, 2004). In all, 12 genes with proven functional significance to drug sensitivity, which included CYP2C8 and CYP3A4, were selected and prediction models to accurately predict the in vitro efficacy of the drugs were developed.…”

Section: Oh-docmentioning

confidence: 99%

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Cytochrome P450 pharmacogenetics and cancer

2006

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The cytochromes P450 (CYPs) are key enzymes in cancer formation and cancer treatment. They mediate the metabolic activation of numerous precarcinogens and participate in the inactivation and activation of anticancer drugs. Since all CYPs that metabolize xenobiotics are polymorphic, much emphasis has been put on the investigation of a relationship between the distribution of specific variant CYP alleles and risk for different types of cancer, but a consistent view does not yet exist. This is to a great extent explained by the fact that the CYPs involved in activation of precarcinogens are in general not functionally polymorphic. This is in contrast to CYPs that are active in drug biotransformation where large interindividual differences in the capacity to metabolize therapeutic drugs are seen as a consequence of polymorphic alleles with altered function. This includes also some anticancer drugs like tamoxifen and cyclophosphamide metabolized by CYP2D6, CYP2C19 and CYP2B6. Some P450 forms are also selectively expressed in tumours, and this could provide a mechanism for drug resistance, but also future therapies using these enzymes as drug targets can be envisioned. This review gives an upto-date description of our current knowledge in these areas.

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Section: Oh-docmentioning

confidence: 98%

Section: Oh-docmentioning

confidence: 99%

Cytochrome P450 pharmacogenetics and cancer

2006

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“…We previously showed the first concise prediction models of the in vitro activity for 8 drugs (5-FU, CDDP, MMC, DOX, CPT-11, SN-38, TXL, and TXT) using various cancer cell lines, along with individual clinical responses to 5-FU using expression data of 12 genes selected from functionally proven genes alone (11). However, since biological behavior and the molecular basis of cancer differ significantly among cancer origins, it suggests the limited value of the prediction models in esophageal cancer.…”

Section: Discussionmentioning

confidence: 99%

“…We have attempted to develop such a prediction system, and have shown the first concise prediction models of the in vitro activity for 8 drugs (5-FU, CDDP, MMC, DOX, CPT-11, SN-38, TXL, and TXT) using 19 cancer cell lines of various origin, along with individual clinical responses to 5-FU using the expression data of 12 genes selected solely from 50 function-proven genes (11). In that study, we used only cDNA microarray to distinguish potential prediction marker genes, followed by confirmation analysis with realtime RT-PCR.…”

Section: Introductionmentioning

confidence: 99%

Chemosensitivity prediction in esophageal squamous cell carcinoma: Novel marker genes and efficacy-prediction formulae using their expression data

Shimokuni

Tanimoto²,

Hiyama³

et al. 2006

Int J Oncol

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Abstract. Esophageal cancer is a highly lethal disease and the optimal therapy remains unclear. Since adjuvant chemotherapy gives a better chance of survival, we attempted to develop a chemosensitivity prediction model to improve individual responses to therapy. Comprehensive gene expression analyses (cDNA and oligonucleotide microarrays) and MTT assay of 8 drugs in 20 KYSE squamous cell carcinoma cell lines were performed to distinguish candidate marker genes whose expression levels reproducibly correlated with cellular drug sensitivities. After confirmation with real-time RT-PCR, we performed multiple regression analyses to develop drugsensitivity prediction formulae using the quantified expression data of selected marker genes. Using the same sets of genes, we also constructed prediction models for individual clinical responses to 5-FU-based chemotherapy using 18 cases. We selected 5 better marker genes, known as drug sensitivity determinants, identified 9 novel predictive genes for 4 of 8 anticancer drugs [5-FU, CDDP, DOX, and CPT-11 (SN-38)], and developed highly predictive formulae of in vitro sensitivities to the 4 drugs and clinical responses to 5-FU-based adjuvant chemotherapies in terms of overall and disease-free survivals. Our selected genes are likely to be effective drug-sensitivity markers and formulae using the 9 novel genes would provide advantages in prediction.

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“…Lin et al [75] described the link between integrated genomic signatures, the biological functions, and the background molecular pathways [76]. There were developed prediction models of activity for eight anticancer drugs [76], along with clinical responses to 5-FU (cDNA microarray analysis) [77] and resistance-related genes such as dihydropyrimidine dehydrogenase (DPD) and HB-EGF-like growth factor genes [78].…”

Section: Genetic Markersmentioning

confidence: 99%

Molecular Prognostic Factors in Gastric Cancer

Lazăr¹,

Tăban²,

Cornianu³

et al. 2017

Gastric Cancer

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Gastric cancer represents a major health problem worldwide. Literature data have demonstrated that gastric tumors present a high molecular heterogeneity, responsible for the process of carcinogenesis and dissemination. By revealing the molecular subtype of the tumor, it is possible to assess its behavior, the outcome of the patient, and the treatment approach, according to its genetic and epigenetic proile. This chapter aims to highlight some of the many diferent genetic mutations, epigenetic alterations, as well as aberrant signaling pathways involved in the pathogenesis of stomach cancers, each of these molecular abnormalities acting in a speciic stage of the disease. Moreover, the manuscript describes the novel therapeutic agents that target some of these aberrant molecular signaling pathways. Unfortunately, only a few agents are currently part of the standard treatment of gastric cancer, while most of the others remain to prove their therapeutic eicacy in the seting of clinical trials. By discovering the diferent molecular subtypes of gastric cancer, as well as numerous classes of targeted molecular agents, in the future, we would be able to perform an individualized treatment, associated with maximum eiciency and less costs.Keywords: gastric cancer, molecular classiication, gene expressions-based prognostic scoring system, molecular biomarkers, molecular targeted treatment IntroductionDespite a decline in the incidence in past decades, gastric cancer remains a major health problem globally [1,2], being the ifth most common type of cancer worldwide, with almost one million new cases estimated to have occurred in 2012, according to Globocan [3]. Furthermore, stomach cancer represents the third leading cause of cancer death in both sexes worldwide (723,000 deaths) [3].© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.According to the World Health Organization classiication, the vast majority of gastric cancers are adenocarcinomas, divided into papillary, tubular, mucinous (colloid), and poorly cohesive carcinomas (including signet-ring cell carcinoma and other variants) [4]. Although it was proposed a long time ago (1965), the Lauren classiication is still widely used in clinical practice and subdivides gastric carcinomas into intestinal and difuse types, associated with diferent pathogenesis, ways of spreading, and outcome [5]. Unfortunately, these two classiication systems have litle clinical impact, making the development of classiiers that can deine prognosis and guide patient's treatment as an urgent need.Literature data have demonstrated that the development of gastric cancer is associated in the majority of cases with infectious agents such as the Gram-negative spiral bacterium Helicobacter pylori (most often) [6] and Epstein-Barr virus (EBV) (about 9% o...

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Concise prediction models of anticancer efficacy of 8 drugs using expression data from 12 selected genes

Cited by 36 publications

References 27 publications

Cytochrome P450 pharmacogenetics and cancer

Cytochrome P450 pharmacogenetics and cancer

Chemosensitivity prediction in esophageal squamous cell carcinoma: Novel marker genes and efficacy-prediction formulae using their expression data

Molecular Prognostic Factors in Gastric Cancer

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