Abstract 1474: An RNAi-based functional classification of lung cancer reveals recurring subgroups strongly correlated with EMT status.

Introduction: Personalized therapeutic approaches which stratify patients into subgroups based on mutation, amplification, or expression profiles have proven effective. Previously, we showed that mRNA expression profiling of nuclear receptors (NRs) segregated NSCLC patients into prognostic groups. Using a gene-library knockdown strategy, we aim to demonstrate the diagnostic and therapeutic value of NRs and their co-regulators (Co-Regs). Aims and Methods: We used a large panel of lung and breast cell lines of various types to develop a patient stratification scheme based on functional/survival response to pooled siRNA “mini” library screens. The first siRNA mini-library consists of 48 NR and 72 CoReg targets. Screens were performed in triplicate across a panel of 54 lung cancers (NSCLC and SCLC), 20 breast cancers, 6 immortalized human bronchial epithelial cell lines (HBECs), and a series of oncogenically progressed HBECs. Each triplicate assay was repeated three times using optimized transfection conditions and followed by statistical analysis (r>0.83 for replicate screens). A second siRNA library targeting 53 chromatin remodelers, 26 jumonji enzymes, and 23 palmitoyl transferases was also screened against these same lines using the same protocol. Results and Conclusions: 1) Response (inhibition or stimulation of growth) to any given siRNA knockdown was heterogeneous across the panel, reflecting the high degree of genetic/functional variability between cancer lines. 2) 85% of the siRNA knockdowns reduced viability in at least one tumor line. Several knockdowns demonstrated selective killing of a significant portion of the cancer lines but not the “normal” HBECs. Many knockdowns differentially affected subsets of cell lines (suggesting possible personalized therapeutics) while others uniformly affected nearly the entire panel. 3) Screening a series of oncogenically progressed HBECs (with p53, KRAS, LKB1) revealed new vulnerabilities detected by a change in response to NR/CoReg knockdown, highlighting the underlying biological changes accompanying oncogenesis. 4) Unexpectedly, we found that classification of the tumor cells by the NR/CoReg mini-library was similar to the classification derived from the second library. The two libraries independently produced a similar subgrouping of the tumor panel. Combined analysis of the two libraries found similar groups. 5) Although there was no obvious correlation between oncogenotypes or mRNA expression of individual NRs or CoRegs, one subgroup (n=26) consisted almost exclusively of lines that had undergone EMT, suggesting possible subtypes of mesenchymal cells. We conclude that siRNA-minilibrary screens targeting NRs, CoRegs, and chromatin remodeling genes provide a new functional classification of lung and breast cancer with strong translational potential. Work funded by CPRIT. Citation Format: Ryan Carstens, Kenneth Huffman, Shuguang Wei, Luc Girard, Yang Xie, Sandra Hofmann, Ignacio Wistuba, Suzanne Fuqua, Bruce Posner, Adi F. Gazdar, Steven Kliewer, Bert O9Malley, David Mangelsdorf, John D. Minna. An RNAi-based functional classification of lung cancer reveals recurring subgroups strongly correlated with EMT status. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1474. doi:10.1158/1538-7445.AM2013-1474