SUMMARY Context-specific molecular vulnerabilities that arise during tumor evolution represent an attractive intervention target class. However, the frequency and diversity of somatic lesions detected among lung tumors can confound efforts to identify these targets. To confront this challenge, we have applied parallel screening of chemical and genetic perturbations within a panel of molecularly annotated NSCLC lines to identify intervention opportunities tightly linked to molecular response indicators predictive of target sensitivity. Anchoring this analysis on a matched tumor/normal cell model from a lung adenocarcinoma patient identified three distinct target/response-indicator pairings that are represented with significant frequencies (6–16%) in the patient population. These include NLRP3 mutation/inflammasome activation-dependent FLIP addiction, co-occuring KRAS and LKB1 mutation-driven COPI addiction, and selective sensitivity to a synthetic indolotriazine that is specified by a 7-gene expression signature. Target efficacies were validated in vivo, and mechanism of action studies uncovered new cancer cell biology.

The common participation of oncogenic KRAS proteins in many of the most lethal human cancers, together with the ease of detecting somatic KRAS mutant alleles in patient samples, has spurred persistent and intensive efforts to develop drugs that inhibit KRAS activity1. However, advances have been hindered by the pervasive inter- and intra-lineage diversity in the targetable mechanisms that underlie KRAS-driven cancers, limited pharmacological accessibility of many candidate synthetic-lethal interactions and the swift emergence of unanticipated resistance mechanisms to otherwise effective targeted therapies. Here we demonstrate the acute and specific cell-autonomous addiction of KRAS-mutant non-small-cell lung cancer cells to receptor-dependent nuclear export. A multi-genomic, data-driven approach, utilizing 106 human non-small-cell lung cancer cell lines, was used to interrogate 4,725 biological processes with 39,760 short interfering RNA pools for those selectively required for the survival of KRAS-mutant cells that harbour a broad spectrum of phenotypic variation. Nuclear transport machinery was the sole process-level discriminator of statistical significance. Chemical perturbation of the nuclear export receptor XPO1 (also known as CRM1), with a clinically available drug, revealed a robust synthetic-lethal interaction with native or engineered oncogenic KRAS both in vitro and in vivo. The primary mechanism underpinning XPO1 inhibitor sensitivity was intolerance to the accumulation of nuclear IκBα (also known as NFKBIA), with consequent inhibition of NFκB transcription factor activity. Intrinsic resistance associated with concurrent FSTL5 mutations was detected and determined to be a consequence of YAP1 activation via a previously unappreciated FSTL5–Hippo pathway regulatory axis. This occurs in approximately 17% of KRAS-mutant lung cancers, and can be overcome with the co-administration of a YAP1–TEAD inhibitor. These findings indicate that clinically available XPO1 inhibitors are a promising therapeutic strategy for a considerable cohort of patients with lung cancer when coupled to genomics-guided patient selection and observation.

No abstract

A challenge for large-scale siRNA loss-of-function studies is the biological pleiotropy resulting from multiple modes of action of siRNA reagents. A major confounding feature of these reagents is the microRNA-like translational quelling resulting from short regions of oligonucleotide complementarity to many different messenger RNAs. We developed a computational approach, deconvolution analysis of RNAi screening data, for automated quantitation of off-target effects in RNAi screening data sets. Substantial reduction of off-target rates was experimentally validated in five distinct biological screens across different genome-wide siRNA libraries. A public-access graphical-user-interface has been constructed to facilitate application of this algorithm.

Diversity in the genetic lesions that drive cancer initiation and progression is extreme. This diversity exists not only among tumors from different patients, but also among cancer cells within the same patient. This nefarious complexity is, in large measure, responsible for the capacity of this disease to evade current best efforts for effective therapy. “Personalized medicine” has been proposed in response to this conundrum as a mechanism to tailor cancer treatment to a specific tumor's genetic and epigenetic characteristics. However, selection of appropriate treatment is dramatically limited by the paucity of appropriate drugs and by the difficulty of linking treatment options to the appropriate patients. The challenge is to identify authentic intervention targets for development of an appropriately diverse cohort of therapies to contend with disease heterogeneity. We are addressing this challenge by a focused investigation of common vulnerabilities that arise as a consequence of oncogene expression and tumor evolution. Here we will describe a cancer intervention discovery pipeline using parallel genetic and chemical perturbations within an extensive panel of cell lines representative of the molecular lesions detected in lung cancer by national and international cancer genome sequencing efforts. We have found that current first line targeted therapies are discoverable within this panel together with the enrollment biomarkers required to stratify patient treatment regimens. Further, we have found that new genetic and chemical vulnerabilities can be revealed that are linked to recurrent mutations in lung cancer patients that are not currently “actionable”. We are leveraging this approach to stratify lung cancer subtypes and elaborate intervention targets that are linked to those subtypes by robust molecular discriminators. Note: This abstract was not presented at the conference. Citation Format: Hyun Seok Kim, Saurabh Mendiratta, Jiyeon Kim, Chad Victor Pecot, Jill E. Larsen, Iryna Zubovych, Bo Yeun Seo, Jimi Kim, Banu Eskiocak, Hannah Chung, Elizabeth McMillan, Sherry Wu, Jef De Brabander, Kakajan Komurov, Bruce A. Posner, Rolf Brekken, Anil K. Sood, Ralph J. Deberardinis, Michael G. Roth, John D. Minna, Michael A. White. Mapping synthetic vulnerabilities in non-small cell lung cancer. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr C16.