Molecular profile or molecular testing

Folate/homocysteine (Hcy) metabolism facilitates the methylation of DNA, proteins and carcinogens; nucleic acid synthesis; and glutathione generation. Dysregulation of folate/Hcy metabolism, due to suboptimal vitamin status and/or functional polymorphisms of key enzymes, is an etiologic feature of some cancers, including lung cancer. Several drugs that target enzymes of folate/Hcy metabolism have become mainstays of cancer chemotherapy, most recently pemetrexed (PMX), which targets dihydrofolate reductase (DHFR) and thymidylate synthase (TS) and is used to treat patients with non-small cell lung cancer (NSCLC). Our primary and secondary hypotheses are that folate/Hcy phenotype, perhaps underpinned by genotype, is a major contributor to (i) clinical response to PMX, and (ii) risk of NSCLC itself. We will use archived and newly acquired samples from PMX-treated NSCLC patients to define pre-treatment and in-treatment folate/Hcy phenotypes using LC-MRM/MS technology that can precisely determine the concentrations and relative proportions of key folates (tetrahydrofolate; 5-methyltetrahydrofolate; 5,10-methenyltetrahydrofolate) and Hcy. Genotypes will be determined for approximately twenty folate-related genes. Biostatistical analyses will be used to establish

whether aspects of folate/Hcy phenotype and/or genotype are prospectively or concurrently associated with time to tumor progression, survival time, toxicity, etc. Case-control analysis of genetic and phenotypic data will also be undertaken to determine whether any genetic and/or biomarker variables predict case status. This project has the potential to identify biomarkers and/or genetic factors that can be used to predict or monitor responses of NSCLC patients to PMX, and may provide the basis for the future deployment of personalized medicine strategies in lung cancer treatment.

Inhibitors of the VEGF pathway, including the VEGF antibody bevacizumab (BV) and multitargeted VEGFR tyrosine kinase inhibitors such as vandetanib, have in some cases improved progression-free survival (PFS) and/or overall survival (OS) in patients with advanced NSCLC. While benefits in the overall NSCLC population have thus far been modest, it is clear that a subset of patients have dramatic benefit, while others may experience no benefit or even life-threatening toxicities. Furthermore, virtually all patients who respond inevitably develop therapeutic resistance. Thus, the development of markers predictive of response or resistance for VEGF inhibitors is critically needed to advance NSCLC treatment. There are currently no validated predictive markers for VEGF inhibitors, and the development of such markers is made more challenging by the impact of both tumor- and host-derived circulating factors on tumor angiogenesis. Useful predictive markers will likely need to reflect factors from both sources. We hypothesize that by comprehensively profiling angiogenesis-related CAFs and other peptides in the blood, as well as germline variations in angiogenesis-related genes, non-invasive predictive markers for identifying which patients benefit from VEGF inhibitors (alone or with chemotherapy) can be developed and validated.

The investigators of this proposal have a longstanding collaboration to develop predictive markers for VEGF inhibitors and, along with other investigators, have identified three promising and potentially complementary approaches using blood-based markers that will be tested in this grant. We have also played leadership roles in major randomized clinical trials of VEGF inhibitors, which have enabled us to leverage a unique set of resources to address these questions.

In Aim 1, we will use multiplexed CAF profiling to identify high-priority candidate predictive markers for differential benefit from VEGF inhibitors with chemotherapy compared to chemotherapy alone using two independent sets of samples from randomized phase II trials: one testing bevacizumab (BV) with chemotherapy (pemetrexed/carboplatin or Pem/C) vs. Pem/C alone (BATTLE-FL) trial, and another testing the VEGFR/EGFR tyrosine kinase inhibitor vandetanib (VAN) plus carboplatin/paclitaxel (VCP) vs. CP, in first-line NSCLC trial. We will also test CAF markers of benefit for VAN vs. standard therapy with erlotinib using specimens from a recently completed randomized phase III trial (ZEST).

In Aim 2, we will use MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectroscopy to develop a serum proteomic classifier for benefit for VEGF inhibitors, using samples from the same trials as in Aim 1. We previously used a similar approach to develop a serum proteomic marker of benefit (Veristrat) for EGFR inhibitors.

Finally, in Aim 3, we will validate a signature of SNPs from three angiogenesis-related genes that were found to be predictive of benefit for BV with CP (BCP) vs. CP in the ECOG4599 trial. This will be tested in the same three trials of VEGF inhibitors. It is worth noting that our interest is not in developing markers for a particular drug, but rather to identify markers and pathways relevant to predicting response or resistance to inhibitors of the VEGF pathway, a validated therapeutic target in NSCLC. Our data thus far suggest there will be overlap in markers for BV and VEGFR TKIs but it will be important to determine whether this is true, particularly as more potent and specific inhibitors are tested.

Impact. This project has the potential to address a critical unmet need in NSCLC by producing validated, non-invasive blood-based predictive markers for identifying patients more likely to benefit from VEGF inhibitors, and can provide critical insights into mechanisms of resistance to guide future combination regimens.

Targeted therapies such as erlotinib or gefitinib for EGFR-mutated lung cancer and crizotinib for ALK-translocated lung cancer can yield remarkable responses and significant clinical benefit. Other mutations in genes such as K-RAS, BRAF, and PI3K, among others, are also being actively investigated as targets of new drugs in clinical trials. However, a substantial number of patients (~40%) have no mutations when tested with a panel of known oncogenic mutations. The aim of this research proposal is to identify novel somatic genomic alterations in lung cancer, using an existing tumor bank of lung cancer cases with known clinical and tumor genetic information. We will focus on those lung cancers that are known to be wildtype on SNaPshot and ALK FISH (fluorescence in situ hybridization) (i.e., negative for over 50 tested oncogenic mutations), and perform both deep sequencing of exomes and a comprehensive search for translocations involving kinases. We believe that this effort will identify novel tumor genomic changes that can be targets for therapy.

There is recent evidence that metformin, a drug commonly used to treat diabetes, has anticancer effects and can significantly improve the rate of pathological response in breast cancers treated with chemotherapy. We propose to review clinical records of lung cancer patients treated over the past 25 years at Johns Hopkins to determine whether metformin treatment is associated with improved clinical response to chemotherapy for lung cancer. Because our preliminary laboratory work suggests that lung cancer cells with mutations of the LKB1 gene are particularly sensitive to metformin, we will secondarily determine whether mutations of the LKB1 gene (which is mutated in up to 40% of lung adenocarcinomas) are associated with a higher frequency of response to chemotherapy among these patients treated with metformin. In a second specific aim, we will conduct studies using xenografts of human lung cancers in the laboratory to further examine possible links between LKB1 mutations and response to metformin, with or without paclitaxel. Establishing such a link could lead to improved chemotherapy (using metformin in combination with conventional chemotherapy drugs) and to development of a biomarker that can identify patients with cancers who might have improved response to chemotherapy with metformin.

The most effective curative modality we have for lung cancer is still surgery, but, even with optimum surgery, many patients relapse and die of their lung cancer, and this fraction is improved only slightly by adjuvant chemotherapy, which is nonetheless toxic for everybody. Thus, we need to identify prognostic biomarkers (to define which patients are likely to relapse after surgery) and predictive biomarkers (to define who will benefit from adjuvant therapy, and what specific type of adjuvant therapy should be used on each particular patient). In this proposal, collaborators from two different lung cancer SPOREs in three different universities will use two sets of high information-content analyses of protein and RNA expression already acquired on a cohort of early-stage lung cancer patients who did not receive adjuvant chemotherapy and in a panel of cell lines rigorously characterized for sensitivity to platinum doublets, and will add to that data funded by this proposal on a new cohort of patients treated with adjuvant chemotherapy to generate our classifier. This classifier will then be reduced to a small number of RNA or protein assays and tested in a larger set of resected patients with and without adjuvant chemotherapy.

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.

Prognosis for non-small cell lung cancer (NSCLC) is substantially better in early-stage as opposed to late-stage disease. If high-risk individuals could be effectively identified, they could significantly benefit from intensive surveillance, early detection, and prevention strategies. While smoking is a primary risk factor, only about 15% of smokers develop the disease. Consistent with a genetic predisposition, some patients have a family history of the disease and are affected at a young age, although they have never smoked. Unfortunately, NSCLC predisposing gene mutations are poorly characterized. We aim to identify novel NSCLC germline risk gene mutations. Our team members have previously identified novel risk gene mutations for several familial cancers. We have assembled a large clinically and molecularly well-characterized NSCLC case-control cohort of never-smokers, performed whole-exome sequencing (WES) on familial and early onset NSCLC probands, identified promising candidate risk genes, and externally validated selected samples. We follow a resource-conscious approach by focusing on a founder population, Ashkenazi Jews (AJ), to decrease genetic heterogeneity and to increase the allele frequencies of candidate recurrent risk mutations. We will perform WES on additional familial and early onset NSCLC probands to identify recurrently mutated NSCLC genes and cross-validate the genes using whole-genome sequencing on matching tumors. The gene candidates identified will be validated using a targeted sequencing approach in a larger non-AJ cohort. These are anticipated to provide new biological insights, serve as future chemoprevention targets, and be used in the development of a genetic diagnostic test to identify high-risk individuals.

Better methods are required to accurately risk stratify patients with a solitary pulmonary nodule (SPN) who may undergo unnecessary procedures to exclude a cancer diagnosis. 18F-FDG Positron Emission Tomography (PET) is a widely available clinical test used to evaluate concerning SPNs and stage malignant lung nodules. It therefore facilitates clinical assessment but remains an imperfect tool for the diagnosis, localization, and prognostication of SPNs, be they infectious or malignant in nature. Furthermore, it performs well for staging lung cancer, but inaccurately categorizes patients in some cases who receive futile thoracotomies for disseminated disease, or conversely, are undertreated for localized disease. The applicant therefore plans on investigating whether circulating molecular biomarkers can increase the utility of 18F-FDG-PET imaging in clinical practice using statistical models that incorporate in vivo and in vitro diagnostics The concept here is “one-stop shopping,” where a patient can obtain routine molecular imaging and molecular diagnostics from routine blood work during an appointment that in combination increase the accuracy of a clinician’s diagnosis and facilitate the appropriate decision-making process. For this proposal we will develop a model that incorporates a circulating microRNA profile to discriminate infectious from malignant SPNs for patients along with clinical and FDG-PET data and, secondly, identify patients with malignant nodules and detectable circulating tumor cells to determine whether these cells upstage or augment clinical staging or prognosis post-operatively when compared to FDG-PET alone.

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.