Emerging targets to monitor and overcome docetaxel resistance in castration resistant prostate cancer (Review)

Magadoux, Léa; Isambert, Nicolás; Plenchette, Stéphanie; Jeannin, Jean–François; Laurens, Véronique

doi:10.3892/ijo.2014.2517

Cited by 37 publications

(24 citation statements)

References 114 publications

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“…As another example, the majority of the methods could not predict the CDR of taxane-based chemotherapy agents (docetaxel and paclitaxel). We suspect that this lack of success is due to the existence of various parameters that influence their response, such as tissue dependence or microenvironmental factors [24, 25], which may not be captured using these simple methods trained on gene expression profiles of CCLs. In fact, we later show that including the tissue of origin explicitly in the predicting model using TG-LASSO can significantly improve the drug response prediction for paclitaxel.…”

Section: Resultsmentioning

confidence: 99%

Tissue-guided LASSO for prediction of clinical drug response using preclinical samples

Huang

Bhope

Lim

et al. 2019

Preprint

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1Prediction of clinical drug response (CDR) of cancer patients, based on their clinical and 2 molecular profiles obtained prior to administration of the drug, can play a significant role 3 in individualized medicine. Machine learning models have the potential to address this 4 issue, but training them requires data from a large number of patients treated with each 5 drug, limiting their feasibility. While large databases of drug response and molecular 6 profiles of preclinical in-vitro cancer cell lines (CCLs) exist for many drugs, it is unclear 7 whether preclinical samples can be used to predict CDR of real patients. 8 9We designed a systematic approach to evaluate how well different algorithms, trained on 10 gene expression and drug response of CCLs, can predict CDR of patients. Using data from 11 two large databases, we evaluated various linear and non-linear algorithms, some of 12 which utilized information on gene interactions. Then, we developed a new algorithm 13 called TG-LASSO that explicitly integrates information on samples' tissue of origin with 14 gene expression profiles to improve prediction performance. Our results showed that 15 regularized regression methods provide significantly accurate prediction. However, 16including the network information or common methods of including information on the 17 tissue of origin did not improve the results. On the other hand, TG-LASSO improved the 18 predictions and distinguished resistant and sensitive patients for 7 out of 13 drugs. 19Additionally, TG-LASSO identified genes associated with the drug response, including 20 known targets and pathways involved in the drugs' mechanism of action. Moreover, 21 utilizes a new approach for explicitly incorporating the tissue of origin of samples in the 43 prediction task. Our results show that TG-LASSO outperforms all other algorithms and can 44 accurately distinguish resistant and sensitive patients for the majority of the tested drugs. 45Follow-up analysis reveal that this method can also identify biomarkers of drug sensitivity 46 in each cancer type. 47

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Section: Resultsmentioning

confidence: 99%

Tissue-guided LASSO for prediction of clinical drug response using preclinical samples

Huang

Bhope

Lim

et al. 2019

Preprint

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“…There remains a high level of unmet need in the management of this disease. In particular, the treatment for men who develop androgen-independent prostate cancers is limited to chemotherapy with the taxane docetaxel; however, the treatment output is very poor (2). Consequently, further options are needed as alternatives to docetaxel.…”

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confidence: 99%

Annatto Tocotrienol Induces a Cytotoxic Effect on Human Prostate Cancer PC3 Cells via the Simultaneous Inhibition of Src and Stat3

Sugahara

Sato

Uchida

et al. 2015

Journal of Nutritional Science and Vitaminology, J Nutr Sci Vit

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Summary Prostate cancer is one of the most frequently occurring cancers and often acquires the potential of androgen-independent growth as a malignant phenotype. Androgen-independent prostate cancer has severe chemoresistance towards conventional chemotherapeutic agents, so a new treatment approach is required for curing such prostate cancer. In this context, the present study was undertaken to check if annatto tocotrienol (main component d-tocotrienol) could suppress cell growth in human prostate cancer (PC3, androgen-independent type) cells via the inhibition of Src and Stat3. The tocotrienol showed cytotoxic effects on PC3 cells in a dose-dependent manner, and the effect depended on G1 arrest in the cell cycle and subsequent induction of apoptosis. In a cytotoxic dose, the tocotrienol suppressed cellular growth via the simultaneous inhibition of Src and Stat3. Similarly, the treatment combination of both Src and Stat3 inhibitors induced cytotoxic effects in PC3 cells in an additive manner compared to each by itself. With respect to cell cycle regulation and the induction of apoptosis, the combination treatment showed a similar effect to that of the tocotrienol treatment. These results suggest that annatto tocotrienol effectively induces cytotoxicity in androgen-independent prostate cancer cells via the suppression of Src and Stat3.

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“…23 Missense mutations of deoxycytidine kinase contribute to GEM resistance in cancer cells. 29 The IL6 could exacerbate chemoresistance via activating the ATM/NFkappa B pathway and increasing the expression of F I G U R E 7 The miRNA-DEGs regulatory network. 25,26 In current study, a total of 536 upregulated and 513 downregulated were screened and mainly enriched in 34 BP terms and 3 KEGG pathways.…”

Section: Discussionmentioning

confidence: 99%

“…28 IL6 was also involved in docetaxel resistance in castration resistant prostate cancer. 29 The IL6 could exacerbate chemoresistance via activating the ATM/NFkappa B pathway and increasing the expression of anti-apoptotic genes. 30 Similarly, IL6 was associated with epidermal growth factor receptor tyrosine kinase inhibitor resistance in non-small cell lung cancer cells and inhibition of IL6 could improve the situation.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of microRNA‐messenger RNA regulatory network in gemcitabine‐resistant bladder cancer cells

Zhang

Chang

Gong

et al. 2018

J of Cellular Biochemistry

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Chemotherapy is still a standard treatment of unresectable bladder cancer or distant metastases. The chemotherapy resistance always occurs after a period of treatment indicating poor prognosis. The current study aimed to explore the molecular mechanism of chemoresistance in bladder cancer cells. The gene expression profiles of GSE77883, including three untreated T24 cells samples and three gemcitabine‐resistant T24 cells samples, was downloaded from Gene Expression Omnibus database. The screening of differentially expressed genes (DEGs), gene function analysis, and interaction prediction between microRNAs (miRNAs) and DEGs were performed by R software. The protein‐protein interaction (PPI) and miRNA‐DEGs networks were constructed and visualized by Cytoscape software. Then, the small molecules, with potential synergistic or antagonistic effects to gemcitabine resistance, were identified using the Connectivity Map database. Finally, gemcitabine‐resistant T24 cell line was established and key genes were validated by quantitative real‐time polymerase chain reaction (qRT‐PCR). In total, 536 upregulated and 513 downregulated genes were screened and mainly enriched in oxidative stress response and signaling pathways related to extracellular matrix–receptor interaction and focal adhesion. PPI network showed interleukin 6, tumor necrosis factor, kinesin family member 11, and BUB1 mitotic checkpoint serine/threonine kinase B were key genes. The miRNA‐DEGs regulatory networks included 18 miRNAs and 185 DEGs, including miR‐182‐5p, miR‐590‐3p, miR‐320a and serum‐ and glucocorticoid‐regulated kinase 1 (SGK1). Then, the related key genes and miRNAs were confirmed by qRT‐PCR. Furthermore, 81 small molecules with antagonistic or synergistic effect to GEM were screened. We have investigated the molecular mechanisms driving GEM‐resistance in bladder cancer cells that would contribute to the development of chemotherapy for advanced bladder cancer.

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Emerging targets to monitor and overcome docetaxel resistance in castration resistant prostate cancer (Review)

Cited by 37 publications

References 114 publications

Tissue-guided LASSO for prediction of clinical drug response using preclinical samples

Tissue-guided LASSO for prediction of clinical drug response using preclinical samples

Annatto Tocotrienol Induces a Cytotoxic Effect on Human Prostate Cancer PC3 Cells via the Simultaneous Inhibition of Src and Stat3

Comprehensive analysis of microRNA‐messenger RNA regulatory network in gemcitabine‐resistant bladder cancer cells

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