LUNGevity-Funded Grants for Early Detection

There are more treatment options than ever for people with early-stage lung cancer, but only 20% of people are diagnosed at stage I or II. Routinely diagnosing and treating lung cancer in its earliest stages should be the norm, not the exception.

The early detection research projects LUNGevity funds are focused on this goal so more people with lung cancer can live longer and fuller lives by starting treatment sooner when the disease is most treatable—and often curable.

Research grants are delivering exciting progress for early detection projects aimed at:

2026

Early Detection Research Award

RTFCCR/LUNGevity Early Detection Award

Steven Dubinett, MD

UCLA, Los Angeles, CA

Validation of an Integrated Radiomic and Cell-Free DNA Methylome Biomarker for Risk Stratification of Indeterminate Pulmonary Nodules

This grant was funded in part by Rising Tide Foundation for Clinical Cancer Research

Low-density computed tomography can catch lung cancer early, but most lung nodules it detects are benign. Current tools can't reliably tell dangerous nodules from harmless ones. The problem is worst for intermediate-risk nodules, which account for most diagnostic dilemmas. As a result, patients often undergo unnecessary biopsies and surgeries, some cancers are diagnosed late, patients face prolonged anxiety, and healthcare costs rise. This project will validate a diagnostic tool that combines computer analysis of CT images (radiomics) with a blood test for cancer-related DNA changes. If successful, the tool could speed accurate diagnosis, spare patients with benign nodules from invasive procedures, and provide doctors with personalized risk assessment tools to guide treatment decisions.

Research Summary

Lung cancer is the leading cause of cancer-related deaths in both the United States and worldwide. Although screening with low-dose CT scans can detect lung cancer earlier and reduce mortality, many people who develop lung cancer do not meet current screening guidelines. Most lung cancers are still diagnosed at an advanced, incurable stage, including in patients who have never smoked. Lung cancers are often first seen on CT scans as abnormal opacities, called nodules if smaller than 3 cm and masses if larger. However, most lung nodules are not cancerous, making it difficult for doctors to determine who needs additional testing or invasive procedures. As a result, many patients undergo unnecessary biopsies or surgeries. There is a critical need for better, noninvasive tools to accurately identify which nodules are likely to be cancer.

We have developed a novel, noninvasive approach that combines two powerful technologies: advanced imaging features from CT scans (radiomics) and a blood test that analyzes DNA methylation patterns in circulating cell-free DNA (cfDNA), which can reflect early cancer changes. This integrated “multimodal biomarker” uses artificial intelligence to combine these data sources and assess whether a lung nodule is likely to be malignant.

Our preliminary research has shown that this combined method can accurately distinguish cancerous from benign nodules, including at early stages. In this study, we will validate the performance of our biomarker in a prospective, real-world cohort of 500 patients with lung nodules undergoing diagnostic evaluation at UCLA and the VA Greater Los Angeles Healthcare System. We will also evaluate how well the test performs across different patient groups, including smokers, non-smokers, and across various nodule types.

If successful, this biomarker could lead to earlier diagnosis of lung cancer, reduce unnecessary procedures in patients with benign nodules, and support more personalized decision-making. Ultimately, our goal is to bring this tool into clinical practice to help doctors manage lung nodules more effectively using both imaging and a simple blood test.

Technical Abstract

RTFCCR/LUNGevity Early Detection Award

Lecia Sequist, MD, MPH

Massachusetts General Hospital, Boston, MA

The RESOLVE Study: Risk Estimation using Sybil for Lung Nodules

This grant was funded in part by Rising Tide Foundation for Clinical Cancer Research. Supported in part by Upstage Lung Cancer

Lung cancer is often found too late, and rates are rising even as tobacco use declines, especially among women, which points to other factors such as air pollution and genetics. Current tools for assessing lung nodule risk rely heavily on tobacco exposure history, making them less reliable as more people without tobacco exposure (non-smokers) develop the disease. This leads to unnecessary procedures and surveillance for some patients and dangerous diagnostic delays for others. Sybil, an AI tool, predicts future lung cancer risk from chest CT scans alone, without medical history or doctor annotations. The RESOLVE study will test Sybil's accuracy in patients aged 35 to 75 with lung nodules and evaluate whether its scores improve clinical decisions and follow-up scheduling. If successful, Sybil could enable personalized care, with closer monitoring for high-risk patients and fewer unnecessary procedures for low-risk ones. It could be especially valuable for people who don't qualify for traditional screening but still face elevated risk.

Research Summary

Risk factors for lung cancer are incompletely understood. As tobacco use falls globally, lung cancer rates continue to rise, especially among women, and air pollution, genetics, and other factors are thought to contribute. Powerful and validated tools to risk stratify individuals in terms of their lung cancer risk are lacking. We developed a novel artificial intelligence tool called Sybil that is able to visually examine the total volumetric imaging data contained within a chest CT to assess patterns imperceptible to human clinicians and make predictions about underlying lung cancer risk without the need for demographic or medical information, or clinician annotation of the images. Sybil’s performance has been well validated in a wide variety of patients who qualify for lung cancer screening.

In this project, we will study Sybil among people with pulmonary nodules on their chest CT. Pulmonary nodules are relatively common, and our preliminary work has shown that the lung cancer rate in this population is significantly higher than among those who qualify for lung cancer screening, even though the population with known pulmonary nodules has less tobacco exposure. The best way to risk-stratify and work-up patients with pulmonary nodules remains unclear and hence diagnosis of early-stage cancers can be needlessly delayed and we risk losing track of patients while following nodules. We will perform a prospective multi-site clinical trial to demonstrate that Sybil has high performance in risk stratifying people with pulmonary nodules. Confirming Sybil’s performance in this study is the first step toward incorporating Sybil into clinical decision-making algorithms to improve outcomes for people with pulmonary nodules.

Technical Abstract

2024

Early Detection Research Award

Rising Tide Foundation for Clinical Cancer Research/LUNGevity Foundation Lung Cancer Early Detection Award

Abhijit Patel, MD, PhD

Yale University, New Haven, CT

Steven Skates, PhD

Harvard Medical School, Cambridge, MA

Epigenetic Alterations in Blood as Markers for Early Lung Cancer Detection

This grant was co-funded by Rising Tide Foundation for Clinical Cancer Research

The objective of this project is to develop a blood test that can improve upon current limitations in lung cancer screening. Dr. Patel and his team have developed a method to accurately measure alterations in DNA that are cancer-specific by looking at levels of methylation of circulating tumor DNA (ctDNA) in the bloodstream. Using this method, Dr. Patel will develop a predictive model to identify patients with lung cancer based on these DNA alterations at a single time point, as well as an algorithm that can track these changes in a patient’s DNA over time. If successful, this could help detect lung cancer earlier in its development, thereby leading to better outcomes for patients.

Research Summary: Lung cancer is by far the most deadly cancer in the U.S., with total lung cancer deaths exceeding those of the next three major cancers combined. Such dismal statistics are largely attributable to the insidious nature of the disease; by the time symptoms appear, the cancer has often spread to an extent that makes cure unlikely or impossible. In contrast, patients who are diagnosed at earlier stages have much better outcomes, as their tumors can be entirely removed or eradicated prior to distant spread. Thus, annual chest CT scans for lung cancer screening have proven to be effective at reducing lung cancer deaths, and are currently recommended for patients with a heavy smoking history. However, CT-based screening programs have been practically challenging to implement, and uptake has been slow. An alternative screening approach that has been garnering much enthusiasm is based on development of a simple blood test that detects DNA fragments shed from tumor cells into the bloodstream. Several commercial and academic groups have been racing to develop blood tests for cancer screening based on this concept, and the field has made impressive progress. However, detection of early-stage lung cancers has remained particularly challenging, with sensitivities reaching only ~20-40% for Stage I disease. A key limitation for detection of small, early-stage tumors has been the extremely low abundance of DNA fragments bearing cancer-specific features (such as mutations) in the circulation. To overcome this limitation, our group has developed a technology that can accurately measure cancer-specific alterations in DNA which are more highly abundant (known as “hypermethylation”). In the current project, we propose to develop a predictive model to identify patients with lung cancer based on probabilities inferred from measurement of these DNA alterations. We will then further improve the sensitivity for detecting the earliest stages of lung cancer by developing an algorithm that tracks longitudinal changes in a patient’s DNA signal over time rather than relying on just a single time-point.

Technical Abstract: Early detection of cancer has long been one of the grand challenges of medicine. It is widely acknowledged that better methods for detection of small, asymptomatic tumors are likely to translate to substantial improvements in cancer survival rates. This is an especially important priority for lung cancer because of its high incidence, high rate of late-stage diagnosis, and high mortality. Over the past decade, liquid biopsy approaches based on detection of cancer-specific mutations or epigenetic changes in cell-free DNA (cfDNA) have made significant inroads towards this goal. However, detection of early-stage lung cancer has been particularly challenging because of the minute amounts of tumor DNA shed into blood. Methylation of cfDNA has emerged as a biomarker of choice for many early detection efforts, but existing technologies are designed to probe for cancer-specific methylation patterns either at pre-specified target sites or across broad genomic regions. The former approach prioritizes a limited subset of cancer-relevant signals, whereas the latter approach yields sparse cancer signals from extensive sequence data. Our group has developed a liquid biopsy technology that comprehensively profiles hypermethylated promoter sequences in cfDNA arising from anywhere in the genome. Using a high-stringency capture strategy based on methylation density rather than sequence, our method is able to globally profile hypermethylated promoters without pre-specifying targets. Gene silencing via promoter hypermethylation is a fundamental mechanism of carcinogenesis, and this aberrant signal can be detected at very low levels in plasma because background methylation patterns in healthy plasma are remarkably consistent. To optimize sensitivity for detection of early-stage lung cancer, we will develop a scoring scheme based on probabilistic machine learning to predict the likelihood of lung cancer by integrating hypermethylation signals across thousands of cell-free DNA fragments. Unlike most current liquid biopsy-based early detection efforts which are focused on identifying individuals with cancer based on a single time-point measurement, here we propose to develop a longitudinal early detection algorithm based on measurement of serial increases in cancer-specific epigenetic signals over time due to tumor growth and accumulating changes in the epigenome.

2023

Early Detection Research Award

Maximilian Diehn, MD, PhD

Stanford University, Stanford, CA

Integration of Liquid Biopsy Assays for the Early Detection of Lung Cancer

Lung cancer is the number one cause of cancer-related deaths in the US because it is often found only after it has spread to other organs in the body, decreasing the likelihood of surviving at least 5 years after diagnosis. Only 21% of patients are diagnosed then their lung cancer is early stage, when it is most treatable. The goal of this project is to create a new way to screen for lung cancer using a blood sample that can find early stage disease when patients can still be treated and/or cured. In preliminary work, Dr. Diehn has developed a blood test that can identify tiny amounts of DNA from lung cancer cells and in this study he will improve this test and apply it to patients and healthy controls. If successful, Dr. Diehn’s work has the potential to significantly improve early detection of lung cancer and improve outcomes for patients.

Research Summary

Lung cancer is the number one cause of cancer-related deaths in the U.S. and can affect both smokers and non-smokers. Lung cancer is often deadly because it is usually found after it has spread to other organs like the brain, liver, or bones, at which point it is no longer possible to cure the disease in most patients. But if caught early when the cancer cells are still confined to the lung, it can often be cured with surgery or radiation. Screening for lung cancer in current or former smokers using CT scans has been proven to reduce the number of patients who die from lung cancer by catching the disease early. Although insurance covers it in the U.S., only about 15% of those who qualify actually get screened. Some reasons for this low rate of screening include worries about false positives from CT scans and difficulty accessing radiology facilities. Our goal is to create a new way to screen for lung cancer using a blood sample that can find early stage cancers when they can still be cured. Our method looks for tiny amounts of DNA in the blood that comes from lung cancer cells. We have completed initial tests that show our idea could work. Now, we plan to further improve our test and to apply it to several hundred lung cancer patients and healthy controls. If our experiments are successful, our blood test could eventually be used alongside CT scans to cut down on unnecessary follow-up tests or even replace CT scans as the main way to screen for lung cancer. If so, this work could contribute to saving lives of patients with lung cancer.

Technical Abstract

Lung cancer is the leading cause of cancer in the U.S., with over 238,000 new cases and more than 125,000 deaths expected in 2023. Early detection is crucial for improving prognosis, and low-dose computed tomography (LDCT) scans are recommended for high-risk populations. However, LDCT screening has limitations, including a significant false positive rate and low compliance. New approaches are therefore needed to enhance early detection in high-risk individuals. Liquid biopsy assays that can detect circulating tumor DNA (ctDNA) represent a promising alternative early detection approach. Our group has developed three state-of-the-art liquid biopsy techniques that each have the potential to detect lung cancer noninvasively, including a somatic mutation approach (Lung-CLiP), a methylation-based approach (meCAPP-Seq), and a fragmentomic-based approach (EPIC-Seq). We hypothesize that combining mutation-, methylation-, and fragmentomic-based ctDNA analysis will maximize sensitivity for detecting early stage lung cancers. Our proposal includes three specific aims. In the first aim, we will compare the clinical sensitivity and specificity of meCAPP- Seq, EPIC-Seq, and Lung-CLiP for early lung cancer detection. In the second aim, we will determine the analytical limits of detection for the three methods, which is important for future regulatory considerations. In the third aim, we will develop an integrated liquid biopsy assay that combines meCAPP-Seq, EPIC-Seq, and/or Lung-CLiP. We will test if combining two or all three assays can improve performance over the best- performing single assay. The deliverable of this project will be the identification of the combination of liquid biopsy assays that achieves the best performance for early lung cancer detection. If successful, our work has the potential to significantly improve early lung cancer detection which would lead to improved outcomes for lung cancer patients.

Career Development Award

Jaclyn LoPiccolo, MD, PhD

Dana-Farber Cancer Institute, Boston, MA

The Germline-Somatic Interaction in Young-Onset Lung Cancer

This grant was funded in part by Lung Cancer Initiative

Although the average age at diagnosis is 70, thousands of new patients under 45 are diagnosed with lung cancer every year, most of whom have never smoked. Dr. LoPiccolo hypothesizes that these patients may share inherited genetic changes that predispose them to developing lung cancer at a younger age. In a preliminary analysis of young-onset lung cancer patients, Dr. LoPiccolo has found that approximately 30% of these patients carry rare mutations in known cancer-associated genes. In this study, Dr. LoPiccolo will investigate whether these mutations affect response to targeted or immune-based therapies. This insight is likely to identify risk factors among young lung cancer patients, which could lead to improved screening and treatment options for this population.

Research Summary

Lung cancer is the most common cause of cancer death in both men and women. Although the average age at lung cancer diagnosis is 70, thousands of new lung cancers occur in patients under 45 years old, most of whom have never smoked. There have been few efforts to analyze potential causes of young-onset lung cancer, particularly looking for inherited genetic changes, which are present in all cells in the body, that are shared among these patients and might predispose to developing lung cancer at a young age. To investigate whether inherited genes cause lung cancer in young patients, we collected blood samples from more than 350 lung cancer patients aged 45 and under at diagnosis and sequenced their genomes. In a preliminary analysis of 243 patients, we found that roughly 30% of young lung cancer patients carry rare, harmful inherited mutations in known cancer-associated genes, higher than many cancers known to have a strong genetic component. In addition to predicting cancer risk, inherited mutations that are present in every cell may influence how a tumor behaves and responds to treatment. We hypothesize that understanding the inherited contribution to tumor development may affect the response of cancer to targeted or immune-based therapies. Additionally, finding genetic risk factors could identify a group of people eligible for yearly CT screening and early detection of lung cancer (currently only used only for patients over 50 years old with heavy smoking histories), and/or guide therapies for lung cancer patients in the future.

Technical Abstract

Lung cancer is the most common cause of cancer-related mortality in North America. Although the average age at diagnosis is 70, thousands of new lung cancers are diagnosed each year in patients under 45 years over 45 years old (median age of diagnosis = 67). The work proposed here will further define this difference in a larger cohort, and address whether the identified variants or genes affect tumor evolution and treatment outcomes. The aims of our study are to identify a population of young lung cancer patients with elevated germline risk, and to investigate the mechanism of the germline-somatic interaction in young lung cancer. The young lung cancer population also provides a lens through which to better understand oncogene-driven lung cancer that occurs in non-smokers – increasingly important as global smoking rates decline.old, most of whom have never smoked. Given that younger patients develop lung cancer decades earlier and without known environmental insults, we hypothesized that underlying germline genetic variation predisposes to developing lung cancer at a young age. Here, we assembled a cohort of over 350 patients diagnosed with lung cancer at age 45 or younger and performed germline whole-genome sequencing (WGS). Preliminary data from 243 patients with median diagnosis age of 37 showed at least 30% of patients carry clinically actionable pathogenic germline alterations in cancer-associated genes, at rates exceeding those seen in many other cancer types – with key age-specific differences when compared to ancestry-matched lung cancer patients from The Cancer Genome Atlas diagnosed over 45 years old (median age of diagnosis = 67). The work proposed here will further define this difference in a larger cohort, and address whether the identified variants or genes affect tumor evolution and treatment outcomes. The aims of our study are to identify a population of young lung cancer patients with elevated germline risk, and to investigate the mechanism of the germline-somatic interaction in young lung cancer. The young lung cancer population also provides a lens through which to better understand oncogene-driven lung cancer that occurs in non-smokers – increasingly important as global smoking rates decline.

2021

Early Detection Research Award

Claudio Scafoglio, MD, PhD

University of California, Los Angeles, Los Angeles, CA

Pilot study of SGLT2 in the characterization of early lung adenocarcinoma

The protein SGL2 seems to be produced in higher quantities on abnormal lung cells than on normal lung cells. Dr. Scafoglio is testing whether SGL2 can be used to image lung cancer cells by using a new imaging technology.

Research Summary

Lung cancer claims around 140,000 lives in the United States every year; there is great need for early diagnosis strategies, and an attractive target is cancer metabolism. Cancer cells require more glucose than normal tissues for their unregulated growth; glucose cannot enter the cells freely, but needs to be transported by specific proteins called glucose transporters.

We have recently discovered that early-stage and pre-cancerous lesions rely on a specific glucose transporter to satisfy their metabolic needs: sodium-dependent glucose transporter 2 (SGLT2). We have introduced a new probe, Me4FDG, which can be used for positron emission tomography (PET) to detect accumulation of glucose in the patient’s tissues through a whole-body scan. We have started a pilot trial of Me4FDG PET in patients diagnosed with lung cancer as proof of principle that this diagnostic technique can be used for early lung cancer diagnosis. We propose to perform more thorough and systematic studies to evaluate the feasibility of Me4FDG PET as a novel diagnostic imaging technique for early stage lung cancer.

Technical Abstract

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.

Anil Vachani, MD

University of Pennsylvania, Philadelphia, PA

Optimizing biomarker based strategies for lung cancer screening

Currently, low-dose computed tomography (LDCT) is the only tool for the screening and early detection of lung cancer in individuals who meet screening criteria. LDCT is not very sensitive; often, abnormalities identified in an LDCT scan turn out to be benign. However, ruling out cancer requires an invasive biopsy. Dr. Vachani is testing whether a biomarker signature can be integrated into LDCT screening to improve the sensitivity of LDCT so that patients may be spared unnecessary biopsies.

Research Summary

Lung cancer remains the leading cause of cancer-related mortality in the US and globally accounting for 1.8 million deaths annually. Use of low-dose CT (LDCT) for lung cancer screening has been shown to save lives and is recommended for individuals at high-risk of lung cancer. However, LDCT has potential risks including a high rate of false positive findings, which may result in additional testing and potentially harmful invasive procedures. Several blood and imaging biomarkers have emerged as potentially useful complementary tools for lung cancer screening (LCS). Our proposed research will use a computational framework to estimate the population level impact of biomarker-based tests and identify the optimal strategy for integration of these emerging tools into LCS and pulmonary nodule evaluation.

Technical Abstract

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.

2018

Career Development Award

Kellie Smith, PhD

Johns Hopkins School of Medicine, Baltimore, MD

Immunometabolic T cell profiling as a prognostic liquid biopsy in NSCLC

Checkpoint inhibitors, a type of immunotherapy, are now available in the first-line and second-line settings for certain subsets of NSCLC patients. Furthermore, the U.S. Food and Drug Administration recently approved an immunotherapy-combination treatment regimen for the treatment of a subset of advanced-stage NSCLC patients. While we are making progress in combining and sequencing immunotherapy with other conventional treatments, it is still unclear which patients will respond to these combinations. Dr. Kellie Smith’s laboratory is studying immune cells in blood samples from patients who have received the recently approved combination therapy. She postulates that immune cells from patients receiving the combination behave very differently from immune cells from patients who have received single-agent immunotherapy. Dr. Smith’s team will identify and exploit these differences to develop a blood test that will help predict which patients may benefit from combination therapies, thereby sparing patients the exposure to ineffective treatments.

Research Summary

Lung cancer is the leading cause of cancer death and accounts for more than 160,000 deaths each year. Immunotherapy, aimed at improving the immune system’s response to cancer, has recently emerged as a profound breakthrough for patients with lung cancer. In particular, therapies targeting the programmed death-1 (PD-1) pathway have been successful. PD-1 is a molecule on immune cells, called T cells, that serves as the “brakes” of the immune system, and tumors can exploit this pathway to shut down the potentially effective anti-tumor immune response. PD-1 immunotherapy blocks this cancer-enabling pathway and allows the immune system to reject tumors. Recently, the FDA has approved PD-1 blockade in combination with traditional chemotherapy for the treatment of metastatic non-small cell lung cancer (NSCLC). This combination approach has resulted in significantly longer survival compared to chemotherapy alone. Despite this, many patients still do not achieve clinical benefit or extended survival. Prior studies have shown that tumors with a high number of genetic changes, called “mutations”, respond favorably to PD-1 immunotherapy, possibly because these mutations induce more immune activation that can then be unleashed following blockade of the PD-1 pathway. However, we are unsure how mutations play a role in the response to PD-1 blockade in combination with chemotherapy which, counter to PD-1 blockade, has traditionally been thought to dampen the immune system. It is therefore of immediate urgency that we understand how PD-1 blockade and chemotherapy work together to promote tumor regression and longer survival and to help clinicians better select patients most likely to benefit from these treatments. Here we propose to evaluate the effect of treatment on anti-tumor immune responses in patients receiving anti-PD-1 in combination with chemotherapy versus those receiving anti-PD-1 alone. The findings from this study will significantly advance our knowledge of the immune response to lung cancer and may result in a paradigm shift in how we select patients who are most likely to benefit from PD-1 immunotherapy.

Technical Abstract

Immune checkpoint blockade (ICB) has demonstrated profound effects on the anti-tumor immune response and has revolutionized the treatment landscape of non-small cell lung cancer (NSCLC). While chemotherapy has traditionally been viewed as detrimental to the immune system, recent clinical trials have demonstrated an impressive survival benefit when combining checkpoint blockade with chemotherapy (ICB+chemo) relative to chemotherapy alone. Despite this, many NSCLC patients do not achieve clinical benefit from ICB, even when combined with chemotherapy. The role of tumor mutational burden, and specifically T cells targeting neoantigens derived from these mutations, has been demonstrated in several ICB studies, however these factors have yet to be fully explored in chemotherapy-containing ICB treatment regimens. There is thus an urgent need to understand the effects of ICB+chemo on the anti-tumor immune response and to specifically evaluate how chemotherapy perturbs the phenotype and function of anti-tumor T cells. It is of paramount importance that we understand how PD-1 blockade and chemotherapy synergize to promote anti-tumor immunity in order to better stratify patients most likely to benefit from these treatments. We propose herein to perform the first comprehensive evaluation of the phenotype and function of neoantigen-specific T cells and their dynamics before and after treatment with ICB+chemo relative to ICB alone. The findings from this study will provide a detailed atlas of the immune system dynamics following treatment and will result in the development of an immunometabolic signature that will be correlated with clinical outcome. Importantly, the results of the proposed work will deepen our understanding of the immune response to ICB+chemo and will unravel the mechanisms underlying clinical response in NSCLC patients.

Edwin Yau, MD, PhD

Roswell Park Cancer Institute, Buffalo, NY

Lung cancer detection by CRISPR-based detection of circulating tumor DNA

This grant was funded in part by Schmidt Legacy Foundation and Upstage Lung Cancer

Currently, computed tomography (CT) is available as a tool for the early detection of lung cancer in high-risk individuals. Unfortunately, it has a high false-positive rate: less than 5% of people with nodules found through CT actually have lung cancer. Apart from the distress associated with false positives, individuals may have to undergo invasive procedures, such as a biopsy, to rule out lung cancer.

Circulating tumor DNA (ctDNA) is DNA released from dying cancer cells into the bloodstream. Individuals with early-stage lung cancer may have ctDNA in their blood, even when the cancer is localized. CRISPR-Cas technology is a novel DNA modifying tool that can be used to develop sensitive, specific, and economic ctDNA assays. Dr. Edwin Yau will develop a CRISPR-Cas-based blood test to detect ctDNA in the blood of individuals suspected of having lung cancer. While the immediate goal of the project is to evaluate this blood test in individuals who have already undergone a CT scan, the ultimate goal of the project is to develop a blood test for screening all individuals.

Research Summary

Lung cancer remains the leading cause of death related to cancer and the majority of lung cancer patients present with advanced disease that is for the most part incurable. Efforts to improve the early detection of lung cancer are crucial to help decrease the number of people who die from lung cancer. It has long been known that genetic information specific to cancer cells can be detected in the blood of cancer patients. Current technologies are enabling us to identify this cancer-specific genetic information directly from blood samples allowing for “liquid biopsies” that offer the potential of making cancer diagnoses directly from blood tests. However, the amount of cancer specific genetic information in the blood of patients with smaller tumors in early stages is often only present in very minute amounts that are difficult to detect. The development of new liquid biopsy technologies that can identify smaller amounts of genetic information more economically could potentially lead to blood tests that are able to detect smaller, more curable tumors and could be used for lung cancer screening. The recent identification of CRISPR-Cas systems, bacterial immune systems adapted to recognize specific genetic sequences, that can accurately detect very small quantities of specific genetic sequences are an attractive platform to develop liquid biopsy tests. The goal of the proposed project is to develop a CRISPR based blood test that can accurately identify genetic sequences specific to lung cancer and can accurately identify patients with early stage lung cancer.

Technical Abstract

The majority of lung cancer patients present with advanced disease that is largely incurable. Efforts to improve the early detection of this disease are critical to decrease lung cancer-related mortality. Low-dose computed tomography (CT) screening in high risk patients has demonstrated reduction in lung cancer related mortality through diagnosis of earlier stage disease at the cost of high false-positive rates and the frequent need for invasive diagnostic testing when indeterminate lung nodules are identified. Detecting tumor specific somatic mutations and/or epigenetic signatures in circulating tumor DNA (ctDNA) represents an attractive non-invasive method for identifying early stage lung cancer. However, to realize this promise for lung cancer screening, where ctDNA from small tumors is miniscule, the development of sensitive, specific, and economical ctDNA based assays is critical.
The bacterial innate immune system consisting of clustered regularly interspaced short palindromic repeats (CRISPR) and their associated endonucleases (CRISPR-Cas) are specifically adapted to recognize foreign nucleic acids. The recent identification and diagnostic adaptation of certain classes of CRISPR-Cas systems, such as CRISPR-Cas12a and -Cas13a, offer unique platforms on which to develop sensitive, specific, and economical assays for the detection of ctDNA. The goal of the current project is to develop CRISPR-Cas12a and -Cas13a based ctDNA assays that can sensitively detect somatic cancer mutations and aberrant promoter hypermethylation often found in lung cancer patients and to validate these assays in plasma samples of patients with early stage NSCLC and in discriminating between benign and malignant nodules identified by low-dose CT screening studies.

2017

Lung Cancer Interception Award

SU2C-LUNGevity Foundation-American Lung Association Lung Cancer Interception Translational Research Team

Lecia Sequist, MD

Massachusetts General Hospital, Boston, MA

Max Diehn, MD

Stanford University, Palo Alto, CA

Tilak Sundaresan, MD

Kaiser Permanente San Francisco, San Francisco, CA

Gad Getz, PhD

Broad Institute, Cambridge, MA

Integrated Blood-Based and Radiographic Interception of Lung Cancer

This grant was co-funded by Stand Up to Cancer, LUNGevity, and the American Lung Association

The SU2C-LUNGevity Foundation-American Lung Association Lung Cancer Interception Translational Research Team, headed by LUNGevity Scientific Advisory Board (SAB) member Dr. Lecia Sequist, is developing a lung cancer interception assay (LCIA) that can be used in conjunction with low-dose CT scans. This assay will be based on an integration of several blood-based assays that examine circulating tumor cells and circulating tumor DNA.

Technical Abstract

Statement of the Problem: Currently, low dose CT (LDCT) screening for lung cancer is recommended for high-risk individuals, defined as current or former smokers (quit within the past 15 years) with a 30-or-more pack-year smoking history, 55 to 74 years of age, and with no evidence of lung cancer. However, uptake of LDCT screening has been impeded by high rates of false-positive results, which in turn add significant physical and emotional stress to patients as well as additional healthcare costs. Since LDCT is now commonly available, lung nodules detected in LDCT scans are plentiful, but imprecise guidelines for care make it a challenge to ensure quality follow-up and expedited diagnoses for those with lung cancer. Furthermore, screening is not available for those who don’t meet the screening criteria (younger age or low smoking history) when they are the exact population among whom lung cancer rates are rising.

Proposed Solution: Leveraging expertise of academic research centers (Massachusetts General Hospital, Broad Institute, and Stanford University) and a non-profit managed-care consortium (Kaiser Permanente), the Dream Team will develop a test called the Lung Cancer Interception Assay (LCIA) to complement LDCT screening.

The proposal is novel in that it will develop complex computational algorithms to combine high-sensitivity/high-accuracy blood-based molecular biomarkers with image-based biomarkers to create the LCIA assay. At the end of the award period, a streamlined product, the LCIA, will be ready to use in population-level definitive trials for the early detection of lung cancer.

2016

Career Development Award

Joshua Campbell, PhD

Boston University, Boston, MA

Genome Alterations Associated With Airway Premalignant Lesion Progression

One of the challenges for early detection and prevention of squamous cell lung cancer, a type of non-small cell lung cancer (NSCLC), is the lack of understanding of how premalignant lesions develop and progress to lung cancer. Dr. Campbell is studying how normal lung cells acquire changes in their DNA to form premalignant lesions. His ultimate goal is to develop a biomarker to predict development of squamous cell lung cancer.

Research Summary

Lung cancer remains the leading cause of death from cancer in the US, and lung squamous cell carcinoma is the second most common type of lung cancer. Many regions of abnormal cell growth can be identified via autofluorescence bronchoscopy in the airway of high-risk smokers. Many of these abnormal regions, which are called premalignant lesions, will resolve without any clinical intervention. However, a small subset will turn into lung squamous cell carcinoma. An ability to identify the lesions that are going to progress before they grow to invasive cancer would allow clinicians to intervene earlier and should reduce the number of deaths from this type of lung cancer. Over the past several years, DNA sequencing of tumors has revealed many mutations in important genes that cause cells to grow and proliferate uncontrollably. In this study, DNA sequencing will be used to identify mutations in premalignant lesions from the airways of high-risk smokers that have been sampled over time. It will be determined whether the presence or types of mutations can predict progression or regression of these lesions and use this knowledge to build a test to rapidly identify the mutations associated with progression. This test could have utility in the setting of lung cancer screening to stratify patients into chemoprevention trials.

Technical Abstract

One of the challenges for early detection and prevention of lung squamous cell carcinoma is the lack of understanding of the molecular and cellular changes that cause initiation and progression of this disease. Airway premalignant lesions are the precursors of lung squamous cell carcinoma and can be detected and monitored by autofluorescence bronchoscopy. However, many of these lesions will regress without clinical intervention, and only a subset will progress to invasive carcinoma. The goal of this study is to characterize the landscape of somatic mutations in airway premalignant lesions and to develop an early detection biomarker using targeted DNA sequencing that can predict risk of lesion progression. Ultra-deep whole-exome sequencing will be performed on a previously collected cohort of airway premalignant lesions from high-risk smokers that have been sampled over time, characterized histologically, and classified into those that are stable, regress, or progress. Significantly mutated genes, recurrent copy number changes, and mutational signatures will be identified, and a determination will be made whether they are associated with lesion histology or progression or regression status. Finally, the findings from this study will be combined with the driver genes from The Cancer Genome Atlas (TCGA) to build a targeted DNA sequencing panel. This panel will serve as a rapid and relatively inexpensive method for monitoring premalignant lesions from patients over time and can be used in a clinical trial to assess the ability of autofluorescence bronchoscopy in combination with molecular profiling to stratify patients and serve as a companion diagnostic in chemoprevention trials.

Lida Hariri, MD, PhD

Massachusetts General Hospital/Harvard University, Boston, MA

Optical Imaging for Early Lung Cancer Diagnosis

A tissue biopsy is often required to make a definitive diagnosis of lung cancer. However, because of small size and inadequate biopsy yield, early-stage lung cancer is often difficult to diagnose. Dr. Hariri is using a novel imaging technique called optical coherence tomography (OCT) to develop tools to guide tissue biopsy sampling to improve tissue yield. These tools will also provide additional diagnostic information.

Research Summary

Early, accurate diagnosis of lung cancer is fundamental to improving patient survival. Tissue biopsy is key to early diagnosis in order to determine if a lung nodule is malignant or benign. Unfortunately, low-risk methods of biopsy, such as bronchoscopy, are often not able to adequately sample targeted nodules when they are small and/or difficult to navigate to. If a diagnosis cannot be made, patients must undergo repeat biopsy or even surgery, which increases risk and delays diagnosis and therapy. This project aims to dramatically improve lung cancer diagnosis on low-risk biopsy using cutting-edge optical imaging tools in combination with navigation techniques to provide (1) real-time, intra-procedural assessment of biopsy site locations to ensure adequate tissue sampling and (2) large-volume “virtual optical biopsy” of nodules for diagnosis as a complement to tissue biopsy. This project will result in a powerful new bronchoscopy tool that could reduce unnecessary risky procedures, eliminate delays in diagnosis, and allow earlier therapy initiation.

Technical Abstract

Inadequate biopsy yield is a significant limitation to early lung cancer diagnosis and is a two-pronged problem: (1) Early-stage lung cancers are not adequately targeted during biopsy due to their small size and (2) even if a nodule is adequately targeted, often there is insufficient tumor in the biopsy to make a definitive diagnosis and/or accomplish all diagnostic testing for patient care. Optical coherence tomography (OCT) is a high-resolution imaging modality that provides virtual visualization of tissue volumes orders of magnitude larger than biopsy without tissue removal. Dr. Hariri’s group has developed OCT catheters compatible with standard bronchoscopes and demonstrated that OCT can identify lung nodules and assess pathologic features of lung cancer with high sensitivity/specificity. This project’s aims are to dramatically improve diagnostic capability in lung cancer using large volume OCT to provide (1) virtual intra-procedural evaluation in real-time (VIPER) of biopsy site location and 2) large volume virtual optical biopsy for subsequent pathology diagnosis as a complement to tissue biopsy. In Aim 1, they will assess if in vivo OCT VIPER biopsy assessment increases tumor yield on bronchoscopic biopsy in a powered, blinded clinical study. In Aim 2, they will use the data obtained in Aim 1 to determine the diagnostic accuracy of large volume OCT optical biopsy with tissue biopsy as compared to tissue biopsy alone. This project will result in clinical translation of a powerful, robust new optical bronchoscopy tool that could reduce unnecessary diagnostic procedures, eliminate delayed diagnoses, provide earlier intervention, and improve patient morbidity/mortality.

2015

Early Detection Research Award

Vadim Backman, PhD

Northwestern University, Evanston, IL

Ankit Bharat, MBBS

Northwestern University, Evanston, IL

Lung screening via biophotonic analysis of nanoarchitecture of buccal cells

This grant was funded in part by Upstage Lung Cancer

Cells in the respiratory tract are usually stacked in an orderly fashion. As lung cancer develops, the cells get “un-stacked” and their shapes change, giving them the ability to grow and spread to other parts of the body. Dr. Vadim Backman from Northwestern University is utilizing a new technology called Partial Wave Spectroscopy for seeing those cells. With the LUNGevity Early Detection Award, he will check how cells taken from the cheeks of stage I lung cancer patients reflect these early changes with the ultimate goal of using partial wave spectroscopy technology for early detection of lung cancer.

Research Summary

The goal of this project is to translate a state-of-the-art nanoscale imaging technology, nanocytology, into an inexpensive and accurate lung cancer screening method among current/past smokers via an automated analysis of nanoscale morphology of buccal (cheek) cells obtained by a simple check swab. Dr. Backman and his group envision buccal nanocytology becoming a prescreen for lung cancer that is simple and reliable enough to be performed by a primary care physician or dentist as part of an annual exam of current or past smokers. If the buccal PWS is positive, a patient can be offered more expensive/invasive diagnostic tests such as low dose CT.

This is analogous to the other two-tier screening approach: Pap smear --> colposcopy paradigm, where the initial low-cost, patient-compliant screening test is applied on the entire screening population and used to identify a small subset of these patients who would actually benefit from more extensive examination. This two-tier screening strategy has been highly successful in reducing cervical cancer mortality by 90%. Their goal is to develop a similar approach for lung cancer screening.

Technical Abstract

The overarching goal of the project is to develop a new technology for accurate and cost-effective lung cancer screening in current/former smokers. Lung cancer is curable if detected early. However, there are no robust screening techniques with options such as CT scans fraught with cost, harms, and a high false positive rate. Dr. Backman and his group hope to transform the clinical practice of lung cancer screening by exploiting field carcinogenesis, the concept that the genetic/environmental milieu that results in lung tumor impacts upon the entire aerodigestive mucosa including the buccal mucosa, which was referred to as a “molecular mirror” of lung carcinogenesis.

Their data show that the alteration of nanoscale architecture of buccal cells is exquisitely sensitive to lung field carcinogenesis and may serve as a robust biomarker for lung cancer. These nanoarchitectural changes can be detected in a practical and highly accurate fashion via a new technology, partial wave spectroscopic (PWS) microscopy (‘nanocytology’).

In the proposed study, they will conduct a blinded validation case-control trial to determine the sensitivity and specificity of buccal nanocytology for lung cancer. They will evaluate the ability of the test to identify patients who have lung cancer and how many patients with lung cancer would be missed using this technique. They will perform a subgroup analysis for Stage I lung cancers. They will assess the potential confounding effects of smoking frequency and time of cessation and other aerodigestive malignancies.

This project will provide the requisite data for the future definitive multicenter validation trial followed by FDA submission.

Career Development Award

Rajan Kulkarni, MD, PhD

Oregon Health and Science University (formerly at UCLA Medical Center), Portland, OR

Detecting early stage lung cancer with circulating tumor cells

Dr. Kulkarni is studying how circulating tumor cells (cancer cells that are released into the blood stream) can be used to develop a blood test for lung cancer early detection and treatment. Funding from LUNGevity will help him use a novel technology called the Vortex Chip to test two things: first, if lung cancer be detected early by identifying circulating tumor cells in the blood and second, if there are biomarkers in circulating tumor cells that can differentiate patients who will respond to immunotherapy or chemotherapy.

Research Summary

Lung cancer can be caused by a variety of changes in the original cancer cells. Understanding this variability will be critical to predicting response to newer therapies. In lung cancer, small quantities of cells break off from the tumor and travel through the blood. These cells, called circulating tumor cells (CTCs), are thought to contribute to progression and may be the source of cells that cause spread of the cancer. Dr. Kulkarni and his group have developed a new technology for isolating lung CTCs from blood, which they call Vortex Chip. These CTCs hold promise for exploring variability in lung cancer because it is much easier to collect blood samples and study the collected cancer cells than to perform invasive biopsies every few weeks.

The Vortex Chip will allow them to monitor response to different treatments by following CTC count before, during, and after treatment (with PD-1/PD-L1 inhibitors). They will also isolate CTCs and analyze these to determine if any new mutations have occurred. Simultaneously, they plan to sample the original primary tumors from matched patients. They hope that these studies will allow them to better understand the variability in lung cancer and may help to design improved treatments for future patients. They also hope that they will better understand how resistance may occur, and that they may possibly use such information to better direct treatment. This work will provide additional information about how the tumor evolves in response to treatment, which can be utilized to design more specific treatments to combat lung cancer.

Technical Abstract

Circulating tumor cells (CTCs) are cancer cells that break away from either the primary tumor or metastatic sites. Increasingly, CTCs have been used as a readily accessible source of tumor cells (“liquid biopsy”). However, shortcomings in current CTC technologies limit downstream analyses to assessment of a selected set of nucleic acid markers. Genome and transcriptome-wide analyses of CTCs have been hampered by the low purity of CTC isolates. The complex and protracted nature of CTC capture protocols further impedes analysis.

Dr. Kulkarni and his group have developed a CTC capture technology known as Vortex Chip, which allows for rapid isolation of highly purified CTCs. In addition to standard immunofluorescence, they have generated proof-of-principle evidence that their capture technology allows for analysis of genetic material. Moreover, because the Vortex Chip isolates CTCs based on their size, their chip does not require antibody-based capture that can potentially bias isolation of CTC subpopulations. Serial CTC analyses performed in the context of treatment changes can characterize the mutational landscape of tumors as they evolve in response to therapy and thereby identify molecular predictors and drivers of treatment resistance and sensitivity to novel anti-tumor therapies.

Their project has two goals: 1) validate use of CTCs as biomarker in lung cancer and 2) explore use of CTC analysis to obtain genetic information about the tumor. They hypothesize that the unique microfluidic characteristics of lung CTCs will drive rapid isolation of pure CTC populations for analysis to characterize heterogeneity and profile therapeutic responsiveness.

2014

Early Detection Research Award

Zeynep H. Gümüş, PhD

Icahn School of Medicine at Mount Sinai, New York, NY

Steven M. Lipkin, MD, PhD

Joan & Sanford I. Weill Medical College of Cornell University, New York, NY

Kenneth Offit, MD, MPH

Memorial Sloan Kettering Cancer Center, New York, NY

Identifying germline risk mutations for early-onset and familial NSCLC

Each year, more than 22,000 people who have never smoked are diagnosed with lung cancer, many at younger ages. Dr. Gümüş and team will identify underlying genes that could indicate a higher risk of developing lung cancer, similar to what has been found with certain forms of breast, colorectal, and pancreatic cancers. People who carry the high-risk genes could then be monitored more carefully.

Research Summary

Lung cancer is the leading cause of cancer death in the United States. Early stage disease can be treated surgically with good outcomes; however, most patients are diagnosed at a later stage when potentially curative surgery is no longer possible. We clearly need improved strategies for early stage lung cancer detection. An important gap in these efforts is identifying persons at high risk. Some patients have a family history of the disease or are affected at a young age with no history of smoking. Indeed, lung cancer has been diagnosed in children as young as eleven. These findings are similar to those seen for breast and ovarian cancers in BRCA mutation carriers like Angelina Jolie; they suggest that genetics also play an important role in lung cancer risk. The overall goal of this project is to identify genes that, when mutated, increase the risk of developing lung cancer. This team has successfully discovered mutations in several genes that cause, respectively, hereditary breast, colon and pancreatic cancers or leukemias. They propose a similar approach for lung cancer patients who have never smoked to identify gene mutations that predispose them to the disease. By using genetics to identify high-risk patients, the team can focus efforts on frequent screening and, potentially, chemoprevention. As smoking is a primary disease risk factor, smokers with these mutations will also benefit from cessation efforts. Frequent surveillance of high-risk individuals will enable the early detection of cancer before it spreads; this can help improve patients’ chances of beating the disease entirely.

Technical Abstract

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.