KRAS

The overarching concept guiding our work is that combinations of biomarkers and imaging characteristics will be most robust in predicting which patients with lung nodules should receive an aggressive diagnostic and/or therapeutic approach and which patients should be monitored for nodule stability over time. Our objectives are to improve two biomarker tests that already have shown significant promise-- sputum chromosomal aneusomy by fluorescence in situ hybridization (CA-FISH) and the analysis of multiple serum analytes by a highly multiplexed aptamer-based assay developed by SomaLogic, Inc.-- and then to compare test performance with predictive models based on nodule and patient characteristics. These objectives are based on two separate hypotheses: 1. The current CA-FISH assay panel can be further improved by the development of two sub-panels, one for detection of squamous cell carcinoma of the lung (SCC) and the second for the detection of adenocarcinoma of the lung (AC). 2. The current aptamer-based analysis can be further improved by developing separate assays specifically designed for the detection of AC, SCC, K-ras, and EGFR-mutated lung tumors. The assays will then be applied to sputum and blood specimens from the Pittsburgh SPORE Pittsburgh Lung Screening Study (PLuSS) and Colorado SPORE Lung Nodule cohorts, in concert with analysis of the CT characteristics of the corresponding lung nodules, including size, volume, density, location, or airway involvement, to compare test performances and to assess whether combining tests would be valuable.

Approximately 30% of patients with stage 1 non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection . Currently, there is a lack of reliable molecular predictors being routinely used in the clinic for identifying patients at high risk for developing recurrent disease and therefore may benefit from more aggressive therapies. To date several groups have applied microarray-based methods for global gene expression profiling of frozen tumor tissues in an attempt to identify prognostic ‘signatures’ in patients with early stage NSCLC.  Building upon this, through a meta-analysis of seven independent microarray studies Govindan et al. were able to identify a 64-gene signature that is highly predictive of survival in patients with stage I NSCLC. However, recent advances in high-throughput sequencing have enabled an unbiased view of the transcriptome including novel transcriptional events such as gene fusions, splicing variants, and novel transcripts. This offers an opportunity to incorporate additional markers, which may have eluded previous technologies, but could serve for improving a predictive signature of survival in non-small cell lung cancer (NSCLC). However, despite the potential of RNA-Seq to improve existing predictive signatures, we are still faced with the challenge of translating these findings into a platform where they can be reliably applied to formalin fixed paraffin embedded (FFPE) clinical tissue specimens routinely collected in tertiary referral centers. Therefore, this proposal focuses on refining the 64-gene predictive signature using transcriptome sequencing and developing a NanoString nCounter assay to reliably predict survival of patients with resected stage I NSCLC, using RNA derived from FFPE tumor blocks. To accomplish this we have proposed the following specific aims: (1) use transcriptome sequencing to detect molecular predictors of outcome in patients with stage I NSCLC, (2) validate the technical performance of the NanoString nCounter using an RNA-Seq predictive signature across FFPE tumor blocks of resected stage I NSCLC, and (3) clinically validate the prognostic power of the predictive signature across an independent sample set. Overall, if the proposed aims are met, this research could lead to an improved assay that could be translated into future prospective studies for risk-stratifying stage I NSCLC patients.

Cancer therapy needs to be better personalized to individual patients, each of whom carries a unique spectrum of mutations, inherited and/or acquired. One of the best cases for this is lung cancer, where molecular subgrouping patients and targeting their mutations has shown promise. While many groups have searched fervently for additional tumor-acquired mutations that are associated with drug sensitivity and resistance, few have emerged since the discovery of the initial mutations, such as EGFR. In contrast, we have applied our expertise in microRNAs (miRNAs), their biologic function and interaction with oncogenes, and as a result have discovered a new class of inherited, germ-line mutations that appear to have strong potential as companion diagnostics. These mutations are in a relatively unexplored region of the genome, the 3’ untranslated regions (UTRs), once thought to be junk DNA. The first such discovered biomarker, the “KRAS-variant,” is an inherited 3’UTR mutation in KRAS, which affects microRNA (miRNA) binding and KRAS pathway expression, as well as tumor biology. The KRAS-variant was first shown to be a genetic marker for an increased risk of developing non-small cell lung cancer (NSCLC). In addition, our data indicate that this variant represents an inherited form of an activated KRAS allele, one of the most important human oncogenes. Several groups have found that the KRAS-variant acts as a biomarker of poor outcomes across multiple cancers, including head and neck cancer, ovarian cancer, and colon cancer. We as well as others have shown that this biomarker is predictive of response to specific cancer treatments, and is not just prognostic of aggressive tumor biology. For example, the KRAS-variant predicts resistance to cisplatin in ovarian and head and neck cancer, resistance to cetuximab in combination with irinotecan chemotherapy, but sensitivity to cetuximab when delivered alone. Furthermore, our preliminary data in this proposal indicate that the KRAS-variant is a powerful companion diagnostic predicting poor response to specific agents, and excellent response to others. These findings, combined with evidence that this allele of KRAS can be targeted using siRNA and miRNA strategies that we have pioneered, leads us to believe that this KRAS-3’UTR mutation is a powerful companion diagnostic in lung cancer, and ultimately may be a critical new target for cancer therapy.

A significant fraction of NSCLC have mutant KRAS which predicts poor response to cytotoxic therapy and portends a poor prognosis. Despite the discovery of the first mutation in the KRAS oncogene in NSCLC over two decades ago, there are no current therapies targeting this critical oncogene. In this proposal we explore a novel and exciting therapeutic strategy to target KRAS-mutant NSCLC through the combination of Hsp90 and mTOR inhibition. We have preclinical evidence suggesting that the combination of ganetespib and an mTOR inhibitor may be an effective therapeutic strategy for patients with KRAS- mutant NSCLC. In Aim 1, we will define resistance mechanisms to single-agent ganetespib in KRAS- mutant NSCLC. The identification of resistance mechanisms to single-agent ganetespib will reveal novel pathways that we can then target in combination with an Hsp90 inhibitor. In Aim 2, we will test the hypothesis that activation of the mTOR pathway through alterations in STK11 or PI3KCA mutations will predict response to the combination. Finally, in Aim 3 we will translate our studies to the clinic in a phase I/II trial of the combination of ganetespib and an mTOR inhibitor in patients with advanced KRAS-mutant lung adenocarcinoma. Importantly, we will have correlative studies looking at response in subpopulations of KRAS-mutant tumors that are hyperactive for the mTOR pathway (STK11, PIK3CA mutations). This translational approach will allow us to identify biomarkers that we can use to effectively target this combination to the patients with greatest chance to benefit from this therapy.