Taxane-Platin-Resistant Lung Cancers Co-develop Hypersensitivity to JumonjiC Demethylase Inhibitors

Although non-small cell lung cancer (NSCLC) patients benefit from standard taxane-platin chemotherapy, many relapse, developing drug resistance. We established preclinical taxane-platin-chemoresistance models and identified a 35-gene resistance signature, which was associated with poor recurrence-free survival in neoadjuvant-treated NSCLC patients and included upregulation of the JumonjiC lysine demethylase KDM3B. In fact, multi-drug-resistant cells progressively increased the expression of many JumonjiC demethylases, had altered histone methylation, and, importantly, showed hypersensitivity to JumonjiC inhibitors in vitro and in vivo. Increasing taxane-platin resistance in progressive cell line series was accompanied by progressive sensitization to JIB-04 and GSK-J4. These JumonjiC inhibitors partly reversed deregulated transcriptional programs, prevented the emergence of drug-tolerant colonies from chemo-naive cells, and synergized with standard chemotherapy in vitro and in vivo. Our findings reveal JumonjiC inhibitors as promising therapies for targeting taxane-platin-chemoresistant NSCLCs.Fil: Dalvi, Maithili P.. University of Texas. Southwestern Medical Center; Estados UnidosFil: Wang, Lei. University of Texas. Southwestern Medical Center; Estados UnidosFil: Zhong, Rui. University of Texas. Southwestern Medical Center; Estados UnidosFil: Kollipara, Rahul K.. University of Texas. Southwestern Medical Center; Estados UnidosFil: Park, Hyunsil. University of Texas. Southwestern Medical Center; Estados UnidosFil: Bayo Fina, Juan Miguel. University of Texas. Southwestern Medical Center; Estados Unidos. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; ArgentinaFil: Yenerall, Paul. University of Texas. Southwestern Medical Center; Estados UnidosFil: Zhou, Yunyun. University of Texas. Southwestern Medical Center; Estados UnidosFil: Timmons, Brenda C.. University of Texas. Southwestern Medical Center; Estados UnidosFil: Rodriguez Canales, Jaime. University of Texas; Estados UnidosFil: Behrens, Carmen. Md Anderson Cancer Center; Estados UnidosFil: Mino, Barbara. University of Texas; Estados UnidosFil: Villalobos, Pamela. University of Texas; Estados UnidosFil: Parra, Edwin R.. University of Texas; Estados UnidosFil: Suraokar, Milind. University of Texas; Estados UnidosFil: Pataer, Apar. University of Texas; Estados UnidosFil: Swisher, Stephen G.. University of Texas; Estados UnidosFil: Kalhor, Neda. University of Texas; Estados UnidosFil: Bhanu, Natarajan V.. University of Pennsylvania; Estados UnidosFil: Garcia, Benjamin A.. University of Pennsylvania; Estados UnidosFil: Heymach, John V.. University of Texas; Estados UnidosFil: Coombes, Kevin. University of Texas; Estados UnidosFil: Xie, Yang. University of Texas. Southwestern Medical Center; Estados UnidosFil: Girard, Luc. University of Texas. Southwestern Medical Center; Estados UnidosFil: Gazdar, Adi F.. University of Texas. Southwestern Medical Center; Estados UnidosFil: Kittler, Ralf. University of Texas. Southwestern Medical Center; Estados UnidosFil: Wistuba, Ignacio I.. University of Texas; Estados UnidosFil: Minna, John D.. University of Texas. Southwestern Medical Center; Estados UnidosFil: Martinez, Elisabeth D.. University of Texas. Southwestern Medical Center; Estados Unido

miR-337-3p and Its Targets STAT3 and RAP1A Modulate Taxane Sensitivity in Non-Small Cell Lung Cancers

NSCLC (non-small cell lung cancer) often exhibits resistance to paclitaxel treatment. Identifying the elements regulating paclitaxel response will advance efforts to overcome such resistance in NSCLC therapy. Using in vitro approaches, we demonstrated that over-expression of the microRNA miR-337-3p sensitizes NCI-H1155 cells to paclitaxel, and that miR-337-3p mimic has a general effect on paclitaxel response in NSCLC cell lines, which may provide a novel adjuvant strategy to paclitaxel in the treatment of lung cancer. By combining in vitro and in silico approaches, we identified STAT3 and RAP1A as direct targets that mediate the effect of miR-337-3p on paclitaxel sensitivity. Further investigation showed that miR-337-3p mimic also sensitizes cells to docetaxel, another member of the taxane family, and that STAT3 levels are significantly correlated with taxane resistance in lung cancer cell lines, suggesting that endogenous STAT3 expression is a determinant of intrinsic taxane resistance in lung cancer. The identification of a miR-337-3p as a modulator of cellular response to taxanes, and STAT3 and RAP1A as regulatory targets which mediate that response, defines a novel regulatory pathway modulating paclitaxel sensitivity in lung cancer cells, which may provide novel adjuvant strategies along with paclitaxel in the treatment of lung cancer and may also provide biomarkers for predicting paclitaxel response in NSCLC

Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations

BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC