Adenocarcinoma

Evaluating suspicious pulmonary nodules in the setting of a lung cancer diagnostic work-up is a common clinical management challenge. High resolution multi-detector computed tomography visualizes many noncalcified lesions that could represent either potentially lethal cancers or benign processes. Although the vast majority of these nodules are benign, non-neoplastic lesions, a subset will be malignant and in these cases, patients could benefit from immediate treatment. A non-invasive test that maintains a high sensitivity and specificity across the spectrum of clinical presentations of pulmonary nodules would be of tremendous clinical benefit by reducing the number unnecessary invasive procedures and minimizing the time between detection and definitive treatment. The overall goal for the proposed studies is to develop a convenient and low-cost serum test that will, either alone or in combination with clinical features, accurately classify indeterminate nodules and direct proper clinical management. Our approach to develop such a test will be to profile and identify which proteins detected in the serum at the time of the detection of these nodules were immunogenic and induced the production of circulating autoantibodies. Differences in the autoantibody profile between the malignant and non-malignant groups will then be further evaluated against additional clinical specimens from both our institution and two pre-specified collaborator institutions to identify the optimal test for this urgent clinical need. Once completed, we anticipate this test will aid clinicians in deciding the optimal treatment for patients found to have suspicious nodules and improve the current standard of care.

Advanced (stage IV) lung adenocarcinoma is an incurable disease. Treatment mostly consists of chemotherapy, which provides a consistent but small survival benefit. Standard therapy includes a platinum-doublet (pemetrexed or paclitaxel) often in combination with bevacizumab, followed by maintenance bevacizumab or pemetrexed. Programmed death 1 (PD-1) is a T-cell surface receptor that when activated, delivers a negative signal to T cells. This feedback mechanism dampens immune responses when no longer needed, preventing damaging autoimmune reactions. Tumors can co-opt this T-cell control mechanism to escape surveillance and/or rejection by the immune system. Thus, reversing this tumor action can result in antitumor activity worthy of clinical evaluation. Recently it has been demonstrated that inhibition of the PD-1 receptor with an anti-PD-1 monoclonal antibody (nivolumab) has significant clinical activity in lung cancer with an ORR of 26%. As remarkable as this may be, given the heavily pretreated population of lung cancer patients studied, this also indicates that 74% of patients did not respond and remained resistant to this approach. Therefore, going forward it is important to develop combination therapies to improve the efficacy of this approach, and to discover resistance mechanisms that may allow for better patient (and tumor) selection. One potential class of agents to be used in combination with anti-PD-1 is the adenosine A2AR antagonists. Given that A2AR on T cells within the tumor microenvironment contributes to immune escape and therapeutic resistance, the addition of PBF-509 is expected to improve the efficacy of nivolumab.

Lung cancer remains the leading cause of cancer-related death due to the limited ability to detect the disease at an early and potentially curable stage. Low-dose computerized tomography (LDCT) screening of high-risk patients improves mortality. However, the high proportion of false positive tests, the majority of which are pulmonary nodules, has limited widespread adoption of this life-saving screening modality. Since screen-detected pulmonary nodules contribute to the overall cost of screening and potential morbidity due to the need for further diagnostic testing, there is an urgent need for accurate tools to stratify patients with screen-detected nodules for routine follow-up or additional intervention. Our data suggests that, similar to the smoking-associated field effect, the lung cancer-associated airway field of injury can be measured less invasively using gene-expression profiling of the nasal epithelium. Because early-stage lung cancers detected by CT screening may have distinct biologic characteristics compared to those diagnosed in patients evaluated for clinical symptoms, we propose to develop an accurate biomarker integrating expression profiling of genes and microRNA, clinical variables, and nodule characteristics in order to distinguish early lung malignancies from benign pulmonary nodules. The immediate clinical application of this test will be in the evaluation of patients with LDCT-detected lung nodules, and will allow clinicians to more accurately stratify patients to or from further diagnostic intervention. Ultimately, this test may also have utility for further stratifying lung cancer risk in patients eligible for screening prior to undergoing LDCT.

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.

The development of non-invasive diagnostic tools to detect lung cancer at an early stage is the subject of active investigations because of its enormous potential impact on the number-one cause of cancer-related deaths. We have recently discovered by shotgun proteomics profiling 164 candidate biomarkers that are differentially expressed in stage 1 lung cancer tissue compared to non-malignant matched controls tissues and found in the circulation. Validation of these candidates by traditional methods using western blot or ELISA is a slow, low throughput, and expensive process. In this application, we propose to take advantage of the individual’s immune response to capture and detect autoantibodies directed against these 164 candidate protein targets identified by shotgun proteomics. To achieve this goal, we intend (1) to establish immune-based assays for the detection and quantitation  of lung cancer autoantibodies using an indirect ELISA; (2) to validate the diagnostic performance of our autoantibody signature in blood samples from individuals with early-stage lung cancer or matched nodule controls; and (3) to determine whether the diagnostic performance of our panel of autoantibody signatures augments the diagnostic accuracy of known predictive models for the evaluation of lung nodules. These studies may lead to the development and early validation of a new molecular diagnostic tool for lung cancer.

The genotype-directed use of EGFR TKIs in EGFR-mutant lung cancer patients has fundamentally changed the face of the disease with improved response to therapy, preserved quality of life, and prolonged progression-free survival. However, tumors that initially respond become resistant after ~ 1 year (i.e., acquired resistance, AR). The biology of AR is incompletely understood and is largely inferred from pre-clinical models. Our group at Mass General implemented a wide-scale program to perform repeat biopsies on EGFR-mutant patients with AR to first-generation EGFR inhibitors (gefitinib, erlotinib). This translational research paradigm has been instrumental in gaining insight into AR and has led to novel observations such as PIK3CA and BRAF mutations as mechanisms of AR and the abundant frequency of phenotypic changes at the time of AR like small cell lung cancer and epithelial-to-mesenchymal transitions. The repeat biopsy results have directly helped our patients as well, by informing choices about the most relevant clinical trials or alternative treatments. Currently, a new cohort of EGFR TKIs is entering the clinic: 2^nd-generation irreversible pan-HER inhibitors and 3^rd-generation T790M-specific inhibitors. Little is known about how AR develops to these newer therapies or how the biology of EGFR-mutant cancers evolves over time after exposure to sequential EGFR blockers.

Our proposal aims to discover the mechanisms of AR to next-generation EGFR TKIs and to understand the evolution of EGFR-mutant cancers as they face the selective pressure of sequential types of EGFR-directed therapies. To accomplish this we will collaborate across institutions to amass a large number of pre-treatment and post-treatment paired patient biopsies which we will interrogate via allele-specific genotyping as well as whole genome sequencing to define mechanisms of AR. In addition we will utilize an innovative technique of taking tumor tissue directly from a biopsy and deriving patient-specific in vitro and in vivo models in the laboratory. Expansion of these models will yield a larger supply of AR cancer material to aid descriptive and functional research about the biology of AR. In addition, establishment of pre-treatment patient-specific models will allow us to verify whether the mechanism of AR derived in the lab through ex-vivo therapy mirrors the eventual clinical mode of AR.

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.

Lung cancer remains the leading cause of cancer death in the world for both men and women. Prevention studies have largely been ineffective. A chemoprevention trial using the prostacyclin analogue iloprost demonstrated improvement in endobronchial histology in former smokers. An ongoing trial is investigating lung cancer chemoprevention with pioglitazone, which decreases lung cancer risk in diabetics. The effects of iloprost and pioglitazone are mediated by PPARγ and its downstream targets. We hypothesize that response to iloprost and pioglitazone depends on expression of PPARγ and that measures of prostacyclin and PPARγ activity will correlate with histology. We will measure a PPARγ expression in biopsy tissues to determine if expression can predict response to iloprost. We will assess methylation and acetylation in tissues with loss of PPARγ expression, which could identify a potential role for demethylation or deacetylation agents in creating a response to chemoprevention. We will measure activity of iloprost and pioglitazone through QPCR of downstream targets. Previously generated tissues from mouse models of lung cancer chemoprevention will be used to correlate markers with human samples. miRNA have the potential to be important markers but there is little information on miRNA associated with lung cancer chemoprevention. We identify potential miRNA markers of iloprost and pioglitazone activity in dysplastic cell lines treated with iloprost or pioglitazone and in tissues from mouse models of chemoprevention. Data from this project will inform future clinical trials using iloprost and pioglitazone, improve targeted lung cancer chemoprevention, and identify relevant miRNA markers for future chemoprevention studies.

Whole genome pooled retroviral shRNA screens were performed in NSCLC cell lines A549 and NCI-H460. Out of nearly 18,000 genes, the top hit whose knockdown most reproducibly showed cytoxicity was PSMA1, a core subunit of the 20S proteasome. The combination of radiotherapy and PSMA1 knockdown significantly enhanced tumor control in a mouse xenograft model. We observed that proteasome inhibition results in increases in nuclear 1κBa, which in turn decreases NF-κB binding to the promoters of Fanconi Anemia/Homologous Recombination (HR) genes including FANCD2 and BRCA1. This reduces the expression and subsequent availability of these DNA repair proteins for recruitment to double strand breaks (DSBs) induced by radiation. These mechanistic studies provided the basis for the proposed hypothesis-driven translational research.

The central hypothesis is that high levels of HR-mediated repair of radiation-induced DNA DSBs are associated with poor tumor control, which may be improved with proteasome inhibitors. First, CT-guided fractionated radiotherapy ± bortezomib will be tested in diverse genetically engineered mouse models of NSCLC to identify mutations and other biomarkers associated with responses to radiation and/or proteasome inhibitors. Immunofluorescence and immunohistochemistry against proteins, identified in prior mechanistic studies, as well as gene expression profiling (GEP), will be performed. Then, the biomarkers will be examined in archived specimens from patients treated with radiotherapy, to assess associations with outcomes. DASL will be used to perform GEP studies using formalin-fixed, paraffin-embedded specimens. The goal will be to identify pathway-based expression signatures that predict poor outcomes with radiotherapy and improved outcomes with addition of proteasome inhibitors.

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.