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Integrated genomic and proteomic analysis identifies PTEN loss and AKT/MTOR as drivers of resistance to MEK inhibitors in NSCLC cells Dianren Xia1, Lauren.

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Presentation on theme: "Integrated genomic and proteomic analysis identifies PTEN loss and AKT/MTOR as drivers of resistance to MEK inhibitors in NSCLC cells Dianren Xia1, Lauren."— Presentation transcript:

1 Integrated genomic and proteomic analysis identifies PTEN loss and AKT/MTOR as drivers of resistance to MEK inhibitors in NSCLC cells Dianren Xia1, Lauren Averett Byers1, Lixia Diao2, Jing Wang2, Steven H. Lin3, Don Lynn Gibbons1, Kathryn Ann Gold1, Juliane Paul4, Ningshu Liu4, and John V. Heymach1 Departments of Thoracic, Head and Neck Medical Oncology1, Bioinformatics2, and Radiation Oncology3, The University of Texas MD Anderson Cancer Center. Bayer HealthCare Pharmaceuticals, Mueller ST 178, Berlin 13342, Germany4. Introduction Lung cancer is the leading cause of cancer death worldwide. Non-small cell lung cancer (NSCLC) is diagnosed in 85% of lung cancer patients. NSCLC therapy has been largely limited to chemotherapy and radiotherapy with un-resectable tumors. Recent development in targeted therapy, such as EGFR inhibitors erlotinib, gefitinib, and afatinib, provides new hope for NSCLC patients. However, their therapeutic efficacy is impeded by the emergence of drug resistance. MEK inhibitors (MEKi) is a group of small molecule inhibitors targeting MEK1/2 of the RAS/RAF/MEK/ERK pathway. MEKi have shown promising clinical outcome in NSCLC in clinical development. Clinical and pre-clinical studies have demonstrated that MEKi is only effective in a sub-population of NSCLC patients, indicating the existence of intrinsic drug resistance. Thus, it is urgent to identify predictive biomarkers of MEKi to assist the patient selection and design combination treatment to overcome the resistance in future clinical application. Results Figure 2: PTEN mutation is associated with MEKi resistance in NSCLC cells Figure 4: PTEN knockdown renders sensitive cells more resistant to MEKi in vivo Figure 6. Decitabine sensitizes part of NSCLC cells to MEKi Figure 1: Diminished basal PTEN expression and elevated AKT activation are associated with MEKi resistance in NSCLC cells A A A No. of cell lines with mutations * P=0.0322 P=0.9808 P=0.0194 P=0.9475 Tumor volume (mm3) Trametinib (days) H661 H661 A AKT pT308 AKT pS473 GSK3 pS21.9 PDK1 pS211 p53BP1 4EBP1 pS65 PTEN Cyclin D1 SMAD3 Resistant Sensitive Sensitivity: RPPA expression Relative cell viability Relative cell viability Refametinib (μM) Trametinib (μM) B B IC50 to refametinib (μM) PTEN wild-type H838 H838 B PTEN del or lost Survival rate (%) Trametinib (days) Relative cell viability Relative cell viability B AKT pS473 (log2 ratio) Wilcox rank P=0.003 -1 1 -2 2 -3 Sensitive AKT pT308 (log2 ratio) PTEN (log2 ratio) Resistant P: 0.017 3 Refametinib (μM) Trametinib (μM) Figure 3: Decrease in PTEN expression causes NSCLC cells resistance to MEKi Conclusions Basal low PTEN expression is correlated with the activation of PI3K pathway and MEKi resistance. Genetic PTEN loss is associated with MEKi resistance in NSCLC cells. Alteration of PTEN expression through knockdown or forced expression affects MEKi resistance of NSCLC cells. Knockdown of PTEN increases the resistance to MEKi in vivo. Low PTEN expression in a subset of MEKi resistant cells is associated with higher DNA methylation. Pre-treatment with decitabine re-sensitizes these cells to MEKi. A H2009 H2009 Figure 5: PTEN promoter is hypermethylated in part of NSCLC cells resistant to MEKi PTEN HCC44 A549 H1666 H2108 H2405 H2887 HCC4006 H4017 H28 HCC193 H838 H1793 H1819 H2170 H2882 HCC3051 Sensitive Resistant H23 H1437 H2291 H2347 Calu1 H157 H441 H520 ACTB Relative cell viability Relative cell viability A C Methods We have employed an integrative, multi-dimensional approach to study the mechanisms of MEKi resistance of NSCLC cells, which include: Reverse Phase Protein Array (RPPA) for protein expression. cDNA microarray for mRNA expression. Genome-wide DNA methylation analysis (Infinium HumanMethylation27 BeadChip). Publicly available datasets for genomic alterations (COSMIC, CCLE). Xenograft validation and clinical confirmation. Cells with PTEN decreased with decitabine Cells with PTEN increased with decitabine H522 H661 H1793 H441 H838 H1975 Decitabine - + - + - + - + - + - + Refametinib (μM) Trametinib (μM) PTEN B ACTB B Relative cell viability Relative cell viability Cells with PTEN decreased with decitabine Cells with PTEN increased with decitabine M U PTEN H441 H838 H522 H1793 H661 H1975 Refametinib (μM) Trametinib (μM)


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