Funded Projects

Lung cancer is the leading cause of cancer-related death in US, and lung adenocarcinoma (LUAD) is the most frequent histology. Early diagnosis is crucial. High-resolution CT has increased the discovery of solitary lung lesions, many of which are benign, whereas some progress to invasive cancer; the identification of novel biomarkers to predict the malignant potential of these lesions is of paramount importance. We found that sodium-dependent glucose transporter 2 (SGLT2) is expressed in human pre-malignant and early-stage LADC, and is required for progression of LUAD. SGLT activity can be measured by PET imaging with methyl-4-[18F] fluorodeoxyglucose (Me4FDG). Importantly, we identified SGLT2 activity in FDG-negative, early-stage lesions in mouse models and in human lung nodules.

Specific aims of the study are: 1. To assess the safety and efficacy of Me4FDG in patients with lung cancer, via a pilot study in 60 patients (30 with pathological diagnosis of LUAD, 30 with a clinical diagnosis of benign nodule); 2. To evaluate the prognostic significance of SGLT2 expression in early lung adenocarcinoma, through SGLT2 staining of 674 samples embedded in tissue microarrays.

The proposed research is likely to introduce a novel diagnostic tool for early diagnosis of lung adenocarcinoma, and further define the prognostic role of SGLT2 in lung cancer. If successful, this pilot trial will open the way for larger clinical studies where we will evaluate the ability of Me4FDG PET to predict the malignant behavior of indeterminate subsolid lung nodules. This will improve the early diagnosis of lung cancer.

Lung cancer remains the leading cause of cancer related mortality in the US and globally— responsible for ~1.8 million deaths annually. Randomized trials of low dose CT (LDCT) for lung cancer screening have demonstrated a clear mortality benefit and are recommended by the United States Preventive Services Task Force (USPSTF). However, most individuals currently eligible for screening do not have lung cancer and many at risk populations are not candidates for screening. Additionally, LDCT has a relatively high rate of false positives leading to potentially harmful tests and invasive procedures. Moreover, early experience suggests that LCS outcomes in clinical practice may differ from those observed in randomized trials. Given the concerns with the performance of LDCT, the use of blood and imaging biomarkers to complement the screening process has the potential to enhance its efficacy and effectiveness. Biomarkers could be employed at two different steps of the screening process – as the initial test for cancer screening, to better define the best candidates for screening, or following a positive LDCT scan, to inform lung nodule evaluation and management. While several screening and diagnostic biomarkers have been developed, they have not been formally evaluated in prospective comparative effectiveness trials, nor have they been subjected to cost-effectiveness analyses. More importantly, their impact on lung cancer burden at the population level is still unknown. Our proposed research will inform the following areas of LCS and biomarker discovery: 1) generate a computational framework to estimate and compare the population impact of emerging screening and diagnostic biomarkers, 2) identify the optimal strategy of integrating biomarker tests into LCS, and 3) highlight and identify the characteristics of biomarkers (sensitivity and specificity for histological subtypes, etc.) which are critical for cost-effective biomarker applications.

Activating mutations in KRAS are found in 20 to 40% of lung cancers and not infrequently in combination with additional alterations in genes such as tumor suppressor TP53 or STK11. How activating KRAS mutations and/or co-mutations affect gene expression in both tumor cells and the cells in the surrounding microenvironment is not known. The impact, if any, of these mutations on intra-tumoral heterogeneity in gene expression is not known. Applying single cell RNA sequencing to resected lung adenocarcinoma samples from US Veterans, I will examine and compare the gene expression profiles of tumor cells from lung adenocarcinomas harboring either mutant and wild-type KRAS, and the expression profiles of cells in the surrounding microenvironment, including tumor infiltrating lymphocytes. In addition, I will determine whether KRAS mutational status affects the degree of intra-tumoral heterogeneity in gene expression, a known factor in survival and resistance to treatment. In sum, we hope to identify specific pathways affected by KRAS in both tumor and surrounding non-tumor cells that could be hypothesis-generating and learn use this knowledge to understand how resistance to KRAS specific therapies might be facilitated by pre-existing intra-tumoral heterogeneity.

Immune checkpoint inhibitors have revolutionized the care of patients with metastatic non-small cell lung cancer (NSCLC). Unfortunately, not all patients benefit from this therapy, and rational combinatorial strategies to enhance immune checkpoint inhibitors (ICI) efficacy in therapy non-responders are needed. We and others have shown that patients with liver metastases derive limited clinical benefit from ICI across a wide variety of disease types. In preclinical models, we discovered that liver metastases cause anti-PD-L1 resistance by siphoning tumor-specific T cells from systemic circulation. Within the liver, activated antigen-specific CD8+ T cells undergo apoptosis. Consequently, liver metastases create a systemic immune desert in preclinical models. Similarly, patients with liver metastases have reduced peripheral T cell numbers and diminished tumoral T cell diversity and function. In preclinical models, liver-directed radiotherapy eliminates immunosuppressive hepatic macrophages, increases hepatic T cell survival, and reduces hepatic siphoning of T cells. The central hypothesis of this proposal is that liver SBRT can enhance CPP therapy non-responders in NSCLC patients with liver metastases. In Aim 1, we will conduct a Phase IB clinical trial establishing the feasibility of delivering multi-target liver SBRT following the first cycle of carboplatin, pembrolizumab, and pemetrexed (CPP) in metastatic NSCLC patients with liver metastases. Up to four liver metastases will be targeted. In Aim 2, we will determine whether liver SBRT combined with ipilimumab and nivolumab modulates the hepatic and systemic immune microenvironment in NSCLC patients with liver metastases. The completion of these aims will assess the feasibility of ablating liver metastases with SBRT in combination with chemoimmunotherapy and deepen our understanding of the contribution of hepatic immune tolerance mechanisms in patients. The ultimate goal of this work is to test rationally-developed combinatorial treatment approaches in hopes of improving the care of NSCLC patients.

Background: Provider engagement is key for successful implementation of evidence-based practices. Our prior work reported that providers’ guideline knowledge is strongly correlated to screening practices but other behavioral factors have not yet been measured in lung cancer screening.

Long-term Career Goal: To be a leader in implementation science with expertise in translating evidence-based lung cancer prevention and early detection into clinical practice through mixed-methods research (qualitative and quantitative) and pragmatic trials in the Veterans Affairs (VA). This award will advance the following career goals: To gain experience in: a) measurement science; b) quantitative analysis methods, and to transition to research independence.

Specific Aim: To measure and validate providers’ behavioral factors that influence lung cancer screening implementation.

Methodology: We will adapt the Determinants of Implementation Behavior Questionnaire (DIBQ) for lung cancer screening and leverage ongoing research infrastructure to survey primary care providers at 10 VA medical centers (VAMCs) participating in the Veterans Affairs Partnership to increase Access to Lung Screening (VA-PALS). The adapted questionnaire will be validated using factor analysis and association with prior screening practices. We will assess which behavioral factors are associated with screening using multivariable regression.

Future Directions: The data gathered will be used to design future interventions aimed at increasing provider engagement and measure how provider engagement changes before and after interventions. This proposal will advance the field of implementation science while also leading towards my independence as an implementation researcher.

Veterans have significantly greater rates of lung cancer and mortality as compared to civilians. In our prior work, these disparities are partly due to lack of receipt of evidence-based cancer care especially among patients with complex comorbidities, psychosocial concerns, and limited social support, characteristics common among Veteran populations. The overall goal of this research is to overcome structural barriers to ensure delivery of evidence-based lung cancer care among Veterans. In our prior work we identified workforce shortages along with complex psychosocial factors and medical conditions that prevent Veterans from fully engaging in their care. We used community-based participatory research and expert panel methods to develop Engagement of Patients with Advanced Cancer (EPAC) – an intervention that integrates community health workers into care.1 In our randomized trial, EPAC improved evidence-based end-of-life care, Veteran satisfaction and reduced acute care use and total healthcare costs. In this study, with our established Advisory Board comprised of Veterans, caregivers, oncology clinicians, and VA leaders, we will refine EPAC to incorporate evidence-based lung cancer care (Aim 1). We will randomize 60 Veterans newly diagnosed with advanced lung cancer to establish feasibility of the refined EPAC intervention (primary outcome) and secondarily, the effects on evidence-based lung cancer care and Veteran activation (Aim 2). The results will inform a multisite randomized study in the VA.

Lung cancer remains the leading cause of cancer death worldwide and clinical trials show that annual lung cancer screening with low-dose Computed Tomography can reduce lung cancer-related mortality by 20%. Marginalized populations are disproportionately affected by lung cancer and our prior work has shown that these disparities extend to lung cancer screening; in a national cohort of Veterans we found that Black Veterans, those with mental health disorders and lower income were less likely to adhere to lung cancer screening follow-up recommendations. Currently, little is known about how to optimize lung cancer screening in underserved populations and marginalized populations from diverse backgrounds.

This proposed project focuses on identifying barriers and facilitators to lung cancer screening at the patient, provider, facility and community-levels. We plan to use mixed methods to quantitatively explore factors associated with delayed or lack of adherence to lung cancer screening and then perform in-depth qualitative analysis to identify which factors are critical and modifiable. We will use an implementation strategy mapping tool to select evidence-based strategies best suited to address the identified barriers and develop a tailored implementation plan to improve adherence to lung cancer screening, both overall and among underserved populations, at Baystate Health System. This work is critical in achieving equity in lung cancer screening and improving overall lung cancer mortality among patients.

A common source of lung cancer morbidity is presented by incidental pulmonary nodules (IPNs), which can represent missed cancers when incompletely followed. Underrepresented patients are particularly at risk of guidelines discordant care. Our institution cares for a large proportion of these minority communities. We therefore propose to develop a comprehensive program for the identification, risk stratification and management of IPNs identified through imaging in the emergency setting. We first seek to incorporate lung nodule detection and management software into our electronic medical record (EMR). To facilitate recognition of nodules, we will utilize natural language processing to screen and flag imaging. A multidisciplinary ensemble of practitioners will validate findings and participate in management. At the crux of this team will be a patient navigator to communicate with patients and assist in follow-up. We next seek to create an IPN risk prediction algorithm. Clinical and radiographic elements from the EMR will be subjected to artificial intelligence-based review to automatically leverage data towards a machine learning-derived algorithm. The final element of our proposal will investigate a blood-based gene expression assay as a marker for malignancy. Following its evaluation using a cohort of biobanked samples, we will apply this RNA-based detection assay to look for markers of malignancy to facilitate the early detection of lung cancers. We ultimately seek to improve lung cancer care within our largely underserved population through a combination of incorporating patients with IPNs into the health care system and providing appropriate and automated risk stratification to expedite care and diagnosis.

Background: Patients with NSCLC whose tumors harbor a targetable molecular alteration have improved outcomes when they receive targeted therapy. Historically, targetable alterations have been associated with specific patient characteristics such as female gender, young age, non-smokers, and Asians. Given this association, patients with characteristics not commonly associated with targetable mutations do not always receive timely and complete molecular testing. We hypothesize that male gender, age >65, history of smoking, African American race and Hispanic ethnicity will be independently associated with delayed detection and treatment of a targetable alteration. We will evaluate the impact of delayed targeted therapy on overall survival and brain metastasis development.

Methods: We will perform a retrospective cohort study of approximately 2200 patients with EGFR, ALK or ROS1 targetable alterations obtained through multi-institution retrospective chart review. Multivariate logistic regression will be used to evaluate the association of patient characteristics with complete molecular testing prior to first-line therapy, targeted therapy as first-line therapy, and development of brain metastases. Kaplan-Meier methodology will be used to estimate median overall survival. The log rank test will be used to compare median overall survivals. Multivariate Cox Regression will further evaluate interactions between delayed targeted therapy and patient characteristics as well as help control for potential confounders.

Importance: This will be the first study to evaluate the impact of delayed detection and delayed treatment of driver mutations in NSCLC. This information is critical to designing interventions to improve outcomes in patient groups with characteristics not usually associated with driver mutations.

Despite high tumor response rates, patients treated with osimertinib inevitably develop disease progression. Mechanisms of both intrinsic, adaptive, and acquired drug resistance remain incompletely understood on a genomic and proteomic level. Our overall objective is to find new targeted treatments and drug combinations that can tackle cancer evolution and drug resistance.

We seek to:

1. Understand biological determinants of response prior to therapy (poor prognosis features)
2. Utilize correct combination therapies in the first line to enhance response, based on biological features of subpopulations present at the start
3. Reprogram cells toward a more drug-sensitive state through understanding network plasticity.

More specifically, our aims are:

1. To define the genomic and proteomic characteristics of drug-tolerant persister cells (DTPCs) under dynamic treatment with osimertinib. Our goal is to identify new vulnerabilities in EGFR-mutant tumors which, when therapeutically targeted, can maximize the depth and duration of benefit to first-line osimertinib therapy.
2. To decipher mechanisms of altered cell cycle progression and osimertinib-induced DNA damage that drive tumor progression.

We have assembled a collaborative, multi-disciplinary team of laboratory scientists and clinical investigators combined with cutting edge technologies to assess genetic and proteomic heterogeneity at the single cell level, access to a robust pipeline of patient samples, and strong preliminary data to support our studies. The proposed aims are expected to define the molecular determinants of tumor heterogeneity and to develop rational therapeutic strategies for delaying / overcoming resistance. These synergistic aims are highly relevant to the current landscape of EGFR-mutant lung cancer.

EGFR-mutant lung cancers (LC) serve as the prototype oncogene-driven cancer and mechanisms of resistance to EGFR therapy are well-established. Selective pressure of EGFR inhibitors can induce lineage plasticity to escape oncogene-dependence. While we have shown EGFR/TP53/RB1-mutations are necessary but insufficient to induce small cell transformation, no other genomic signatures and transcriptomic/epigenomic effectors that induce transformation have been identified.

Using parallel exome sequencing, bulk RNA sequencing, and bisulfite sequencing, we will characterize the biomarkers of transformation in EGFR/TP53/RB1-mutant LC and mixed adenocarcinoma/squamous cell tumors. We will also utilize single-cell RNA sequencing to identify the transcriptional changes associated with transformation and to identify distinct cell types within a heterogenous tumor. We will reconstruct a phenotypic landscape to identify subclones in a transitional state between histologies. The information obtained from these studies will nominate novel biomarkers of lineage plasticity that will be validated and proposed for study in clinical trials.

Lung cancer patients and survivors are a growing underserved group, with the lowest quality of life of any cancer survivor group. Lung cancer is also the deadliest form of cancer, with the five year survival rate being 18.6%; survival rates are even lower for intersectional underserved groups. Stigma about having lung cancer, or a feeling of blame and shame for having lung cancer, having caused lung cancer through historical or current smoking, or having others assume one caused their own lung cancer, leads to higher rates of depressive symptoms, lower disclosure of smoking, lower likelihood of engaging with smoking cessation services, and decreased likelihood of following through on treatment recommendations. Thus, lung cancer stigma likely significantly contributes to a lower five-year survival rate for cancer. Importantly, stigmatized intersectional groups experience stark health disparities, with Latinx and Black lung cancer survivors reporting lower quality of life, with Black and LGBTQ lung cancer survivors reporting higher rates of smoking, and with all three groups reporting low access to care and righteous medical mistrust. We have no current interventions to treat this intersectional stigma across the cancer continuum. Promisingly, mindfulness interventions have been shown to decrease stigma in other health contexts and are easily disseminable. In this study, we propose an innovative Multiphase Optimization Strategy (MOST) methodology to build and optimize a brief virtual mindfulness intervention to decrease lung cancer stigma. We will measure behavioral outcomes, too, such as likelihood of accepting a referral to smoking cessation services, in order to detect an effect on the five-year survival rate of lung cancer. We will examine the reach, acceptability, and preliminary efficacy of this intervention in these underserved groups in order to decrease health disparities and extend the five-year survival rate.

Lung cancer is the leading cause of cancer death in the United States, and disproportionate risk is faced in the lesbian, gay, bisexual, trans and queer (LGBTQ) community due to higher smoker rates. Lung cancer screening (LCS) with annual low-dose chest CT has been demonstrated to reduce lung cancer mortality by up to 20% in a subset of high-risk smokers, a benefit that is doubled with sustained smoking cessation. Little is known about LCS in LGBTQ patients; however, in general, this population faces healthcare discrimination and other unique barriers to preventive care. This study will bridge this significant knowledge gap through partnership with an urban LGBTQ community center to tailor and evaluate a smoking cessation and LCS program for the LGBTQ community through a robust mixed-methods approach centered in community-based participatory research. In Aims 1 and 2, we will use a qualitative approach to engage the community and build a tailored cessation and screening navigation program, and in Aim 3 we will pilot the program in single-arm study, evaluating both effectiveness and the implementation outcomes of the program. Results from this study will assist with the development of a sustainable local LGBTQ LCS and smoking cessation program and will be used to inform a larger multicenter trial of the intervention.

KRAS mutations are the most common activating mutation in lung cancer and are identified in 25-30% of cases of lung adenocarcinoma. The clinical activity of molecularly targeted therapy in KRAS mutant lung cancer has been limited, as most prior approaches focused on downstream targets of the MAPK pathway, an approach which was largely ineffective. KRAS G12C is the most common subtype of activating KRAS mutation in NSCLC. Identification of a binding pocket of KRAS G12C enabled the development of covalent inhibitors (Ostrem et al. Nature, 2013), which selectively bind to the mutant cysteine and spare wild type or other mutant KRAS proteins (hereafter referred to as G12Ci). These drugs bind only to GDP-bound (i.e. inactive) KRAS G12C and trap the oncoprotein in its inactive state by preventing nucleotide exchange (Lito et al. Science, 2016). Of this new class of agents, two drugs (MRTX849 and AMG510) have demonstrated efficacy in early phase clinical trials, representing a remarkable breakthrough in the management of KRAS G12C mutant lung cancer. Acknowledging the limited number of patients treated thus far, response rates of 40-50% have been reported, demonstrating clinical activity far superior to prior molecularly targeted approaches for the management of KRAS mutant lung cancer. Despite this major advance it is clear that resistance to therapy, both primary and acquired, will remain a challenge and may in part be due to upstream receptor tyrosine kinase (RTK) signaling. Understanding the mechanisms of resistance to this new class of therapy is of paramount importance to improve the efficacy and durability of response, and for identifying rational combinatorial therapies for future clinical trials.

Small cell lung cancer (SCLC) is an aggressive, neuroendocrine malignancy that accounts for approximately 15% of lung cancers. Despite recent advances, including the approval of immunotherapy combined with chemotherapy for frontline treatment, the median overall survival for patients with extensive-stage SCLC remains approximately one year. These dismal outcomes are attributable, in part, to the lack of approved biomarkers for SCLC, which, in turn, is due to the dearth of available tissue for molecular analysis. Using transcriptomic data, we have developed a gene signature that defines four distinct molecular subtypes of SCLC – each with unique biology and therapeutic vulnerabilities. These subtypes are driven by the presence (or absence) of three transcription factors (ASCL1 – SCLC-A; NEUROD1 – SCLC-N; POU2F3 – SCLC-P; and a fourth triple-negative subtype “Inflamed” – SCLC-I) that are largely mutually exclusive. Our preliminary data suggests that inter- and intra-tumoral heterogeneity among these subtypes drives response and resistance to standard and novel therapies for SCLC, including classes such as PARP inhibitors (PARPi) and immunotherapy. We propose applying bulk and single-cell molecular approaches to assign and longitudinally monitor subtype among our established cohort of patient-derived xenograft models treated with PARPi, as well as patient tumor biopsies from an investigator-initiated trial assessing a PARPi/immunotherapy combination. Based on our preliminary data, we hypothesize that SCLC-P and SCLC-I will preferentially benefit from PARP inhibitors and immunotherapy, respectively, and that subtype shifts detectable at the single-cell level along with accompanying shifts in the composition of the immune microenvironment, will govern response and resistance.