Molecular profile or molecular testing

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.

Recently, the National Lung Screening Trial reported a 20% reduction in lung cancer mortality and lung cancer chemoprevention trials targeting the arachidonic acid pathway have demonstrated decreases in lung cancer associate markers .These studies highlight possibilities for future reductions in lung cancer mortality through early detection and chemoprevention. Our group has previously identified smoking- and lung cancer-specific gene expression alterations in cytologically normal airway epithelial cells that can serve s a clinically relevant biomarker for the early detection of lung cancer. We propose to extend our studies of the field of injury by profiling  these cells from high-risk smokers with preinvasive lesions (dysplasia) and matched controls without lesions by RNA-Seq. We will characterize the molecular alterations (coding, noncoding, and novel RNA expression and alterative splicing) associated with the field of injury in premalignancy and identify whether these differences are similar in both current and former smokers. Next, we will develop molecular signatures that predict subsequent progression or regression of premalignant lesions as well as changes that occur as a result of progression or regression. Collectively, these signatures will aid in the stratification of high-risk smokers for chemoprevention trials, serve as intermediate markers of efficacy in these trials, and identify new targets for chemoprevention. Finally, we will explore whether these molecular signatures re associated with occult lung cancer or future lung cancer development in independent cohorts as common alterations may indicate early events in lung carcinogenesis and have additional utility as biomarkers in the early detection of lung cancer.

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.

Small cell lung cancer (SCLC) exhibits aggressive clinical behavior and poor outcome and response to therapy. Moreover, there are no effective strategies for early detection of SCLC. Therefore, there is an urgent need to identify new strategies and markers for SCLC detection. We recently characterized the molecular airway field cancerization (FC) in non-small cell lung carcinoma (NSCLC) patients and identified airway profiles that varied spatially (n=1165) and with time (n=1395) following surgery. Moreover, we characterized the adjacent airway FC in NSCLC (n=1606 genes), a subset of which (n=299) significantly distinguished airways of smokers with lung cancer from those of healthy smokers and another (n=208) separated airways of different NSCLC subtypes. Although we previously showed that SCLCs and adjacent airways are characterized by higher level of allelic losses compared to those of NSCLC cases, the global airway FC in SCLC and its relevance to detection has not been explored. We hypothesize that the molecular airway FC in SCLC is different compared to that in NSCLC or benign lung disease and comprises biomarkers specific for early detection of SCLC. We will 1) perform global expression profiling of the airway FC and tumors or nodules in patients with SCLC, NSCLC, and benign disease for identification of airway markers specific to SCLC and 2) test identified airway mRNA markers for SCLC detection in bronchial and nasal compartments in patients with suspect lung cancer. We anticipate that our proposal, due to its unique resources and approaches, will identify novel markers for SCLC detection.

Platinum-based concurrent chemoradiation (CRT) remains the standard treatment for patients with locally advanced, stage III non-small cell lung cancer (NSCLC). Outcomes for this large subgroup remain dismal, and no progress has been made in this area in the last three decades. Novel treatment options and predictive biomarkers to improve upon the outcome and reduce the toxicity of our current treatment paradigms are sorely needed. Our overall hypothesis is that the identification of acquired resistance pathways and synergistic targets for platinum-radiation therapy will lead to improved treatments and patient selection. We will pursue in vitro and in vivo xenograft studies to assess the synergistic role of PARP inhibition and ERCC1 modulation in the setting of CRT and will correlate these findings with a biomarker study using human tumor specimens. We will further validate YAP as a promising actionable target and will assess the interactions of concurrent chemoradiation with YAP blockade based on our preliminary data of synergy. Then, we will pursue an unbiased, functional shRNA genetic screen to identify further essential treatment resistance pathways, and carefully selected targets will be validated through a series of biochemical and functional assessment steps. The predictive value of biomarkers will be tested in retrospective cohorts of patients treated with cisplatin-radiation for locally advanced non-small cell lung cancer enrolled in our lung cancer database. Last, our unique tissue bank of pre- and post-neoadjuvant treatment specimens will be used for the identification of novel resistance markers based on modulation of expression upon neoadjuvant therapy, and functional validation of resistance biomarkers and novel treatment candidates will be pursued. These studies should provide the foundation for biomarker-driven translational and clinical studies in this area of major unmet clinical need.

Screening smokers with CT can detect lung cancer at relatively early stages, and thus reduce mortality. However, CT screening for lung cancer has a poor specificity, often resulting in unnecessary treatments to smokers who have benign diseases. The objective of this proposal is to develop genomic- and non-coding RNA (ncRNA)-based biomarkers in sputum that can complement CT for lung cancer early detection in smokers.  Proposed aim 1 is to define sputum ncRNA signatures of early-stage lung cancer using next-generation sequencing (NGS). Proposed aim 2 is to optimize a panel of sputum ncRNA biomarkers with CT for the early detection of lung cancer. Proposed aim 3 is to integrate our previously identified genomic biomarkers and the newly optimized panel of ncRNA biomarkers with CT for the early detection of lung cancer in independent case-control series. Future use of the biomarkers in clinical practice for screening smokers for lung cancer will increase CT’s specificity, and hence reduce harmful and unnecessary treatments to many smokers who have benign diseases. Integrating the biomarkers with CT could assist making decisions for the management of abnormal findings in the lungs and enabling effective treatments to be immediately initiated for lung cancer. The study will translate the strengths of novel ncRNA profiling data developed from NGS into clinical settings by using a simple and cost-effective approach, and thus bridge the gap between basic research and patient care.