Career Development Award

Developing EGFRxHER3 bispecific CAR-T cells for targeting EGFR TKI DTPCs

Career Development Award
Yan Yang, PhD
MD Anderson Cancer Center
Houston
TX

In patients with EGFR-mutant NSCLC, tyrosine kinase inhibitors (TKIs) have been an effective treatment, but over time these patients develop resistance to TKIs, leading to tumor relapse.  Dr. Yang’s project focuses on cancer cells called drug-tolerant persisters (DTPs), which are implicated in TKI resistance.  A gene called HER3 is expressed in DTPs, and Dr. Yang will use specially engineered immune cells, called CAR-T cells, to target both HER3 and EGFR simultaneously.  If successful, this approach would result in a bi-specific CAR-T cell that can be further evaluated in clinical trials.

Research Summary

In lung cancer patients with a specific genetic mutation in EGFR, certain drugs can be helpful, but over time, the cancer can learn to resist these drugs, making them less effective. We're focusing on a small group of tough cancer cells, called DTPCs, that survive the initial treatment because they might be the key to curing the cancer for good. We've noticed that a gene called HER3 is expressed more in these cells. We also have promising results from CAR-T cell therapy. It is a treatment using T cells, a type of immune cells, engineered with the chimeric antigen receptor (CAR) so they can find and destroy cancer cells. We've found that CAR-T cells targeting EGFR can kill DTPCs. We believe if we use these T cells to attack both HER3 and EGFR at the same time, we might have a better chance of killing off these stubborn cancer cells. To make sure this idea works, we'll first check if HER3 is indeed more expressed in these DTPCs in the lab and samples from patients. Then, we'll test our HER3-targeting CAR-T cells to see if they can kill these DTPCs. If that looks promising, we'll tweak the T cells to target both HER3 and EGFR and see if they work even better. If all goes well, we'll be able to make one of the first effective CAR-T cells to target both HER3 and EGFR and try them out in clinical trials.

Technical Abstract

In NSCLC patients harboring mutant EGFR, treatment with tyrosine kinase inhibitors (TKIs) has demonstrated efficacy. However, the emergence of resistance to EGFR TKIs remains a significant challenge, leading to disease progression. Targeting drug-tolerant persister cells (DTPCs), a rare subpopulation surviving initial treatment, emerges as a more effective strategy than awaiting the development of complete drug resistance, holding potential for curative cancer therapy. Based on our preliminary data on the upregulation of HER3 in DTPCs resistant to EGFR TKIs and the potent antitumor activity of EGFR-targeting chimeric antigen receptor (CAR)-T cells against DTPCs. We propose that HER3 is a promising target expressed on EGFR-TKI DTPCs and that CAR-T cells simultaneously targeting both EGFR and HER3 are an effective approach for targeting DTPCs with improved overall efficacy. In this proposal, we will evaluate HER3 as a therapeutic target for CAR-T cell therapy against EGFR-TKI DTPCs by validating its expression in DTPCs using in vitro cell models, in vivo xenograft and PDX models, and patient tissues. Additionally, we will evaluate the anti-tumor activity of HER3-targeting CAR-T cells against DTPCs. Subsequently, we will develop and characterize EGFRxHER3 bispecific CAR-T cells, evaluating their CAR expression, antigen binding affinity, and anti-tumor activity. We next will assess their anti-tumor efficacy in xenograft and PDX models to guide the selection of the most promising bispecific CAR-T cells for further development. If completed successfully, we will have EGFRxHER3 bispecific CAR-T cells ready for GMP-compliant clinical-grade CAR manufacturing, in preparation for clinical trial evaluation.

Building Reliable Oncology Navigation to Ensure Adjuvant Management: BRONx-TEAM Project

Career Development Award
Tamar Nobel, MD, MPH
Montefiore Medical Center
Bronx
NY

The introduction of targeted therapies and immunotherapy for early-stage lung cancer is associated with improved survival, but patients can only benefit if they partake in adjuvant and neoadjuvant therapies.  Data has shown that inequalities exist for patients with lower socioeconomic status as well as non-White patients when it comes to being referred for and receiving treatment after surgery.  These inequalities are likely to increase as new drugs are developed in clinical trials comprised of predominantly white patients.  In this project, Dr. Nobel will study the impact of disparities on uptake of adjuvant therapy for NSCLC in a largely minority patient population at Montefiore Medical Center in Bronx, NY.  She will provide social support and health literacy to engage patients in their care and collect genetic data about their tumors, which will contribute to future clinical trials that are more inclusive.

Research Summary

Systemic therapy after surgery to remove lung cancer has been demonstrated to improve survival. However, data has shown that there are inequalities in which patients are referred for and receive treatment after surgery, specifically for lower socioeconomic status and non-White patients. As new treatments have been developed, these inequalities are likely to increase as these drugs have been developed in clinical trials predominantly composed of White patients and the benefits in other populations are not known. We have previously demonstrated that using nursing and peer navigators to help guide patients in their cancer care improves treatment adherence in our predominantly Black and Hispanic low socioeconomic status population in the Bronx. The BRONx-TEAM project aims to improve patient outcomes by using a navigation pathway focused on increasing patient adherence to systemic therapy after surgery for non-small cell lung cancer resection. We believe that by providing social support and improving health literacy we can get patients to be more informed and engaged in their cancer care. Furthermore, we will gather genetic data about the patients tumors. Given our patient population, we have a unique opportunity to contribute to the literature to understand the relationships between tumor genetics, treatment types and outcomes in non-White patients. Furthermore, we will investigate the use of a commercial genetic panel to assess risk for recurrence. Given the lack of this type of data in low income non-White patients, we believe that this exploratory portion of our study will serve as an important foundation for future clinical trials that are more inclusive than the currently available literature.

Technical Abstract

As seen in the phase III trial CheckMate 816 (CM816), neoadjuvant anti-PD-1+chemotherapy improves survival for patients with resectable non-small cell lung cancer (NSCLC), with pathologic response as a major trial endpoint. Our team led the Central Pathology Review for CM816, and we showed the first prospective evidence that the full spectrum of % residual viable tumor (%RVT) associates with event free survival. Given the data supporting pathologic response as a survival surrogate, %RVT will likely be incorporated into the next generation of clinical trials and may ultimately guide clinical decision-making. %RVT is primarily evaluated using visual assessment of routine hematoxylin and eosin-stained slides. We developed a machine learning-based approach to score %RVT, which allows for a standardized approach that can be completed rapidly for a large volume of patients, and we propose to test this algorithm in resection specimens from CM816. Additionally, we will use multiplex immunofluorescence (mIF) to quantify individual features of pathologic response, locate them within the larger tumor bed, and determine the relative contribution in predicting patient outcomes. Furthermore, we will use the novel AstroPath platform, a mIF whole-slide imaging platform that uses algorithms first developed in astronomy to generate tumor-immune maps, to identify additional pre- and on-treatment biomarkers of response. Our goal is to leverage emerging technologies (i.e, machine learning and mIF) to develop the next generation of pathology biomarkers, including pathologic response assessment, and to identify additional features that can potentially be targeted in combination with anti-PD-(L)1+chemotherapy to improve clinical benefit in patients with NSCLC.

Next-generation pathologic response assessment in patients with lung cancer

Career Development Award
Julie Deutsch, MD
Johns Hopkins School of Medicine
Baltimore
MD

Dr. Deutsch’s proposal centers around finding better pathologic predictors of response to neoadjuvant IO in early stage NSCLC.  She will utilize machine learning/artificial intelligence to test an algorithm that she and her team have developed that assesses percent residual viable tumor (%RVT), which is the amount of tumor left at the time of surgery.  Dr. Deutsch will also characterize tissue specimens using a novel immunofluorescence platform to identify cell types and spatial relationships that are associated with patient benefit to immunotherapy+chemotherapy.  This approach can help inform which patients should receive a given therapy, how they will respond, and additional possible targets for the development of new therapies.

Research Summary

Immunotherapy revolutionized the treatment of lung cancer, and is now being extended so patients can receive therapy before surgery. This was supported by a large clinical trial, CheckMate 816 (CM816), where patients with lung cancer showed improved survival when treated with immunotherapy+chemotherapy before surgery, compared to chemotherapy alone followed by surgery. However, there is an unmet need to identify who is most likely to benefit from such an approach. To address this gap, we will apply novel, next-generation pathology biomarkers utilizing machine learning/artificial intelligence and multispectral imaging. Specifically, we have shown that the amount of tumor left at the time of surgery, termed percent residual viable tumor (%RVT), predicts survival. To date, %RVT assessment is primarily performed visually on glass slides using a light microscope. We developed a machine learning-based algorithm for assessing %RVT on digitized glass slides using a small cohort of patients at Johns Hopkins to improve standardization and throughput in preparation for broad usage. Here, we will test the algorithm’s performance in a larger cohort of patients (the CM816 patients). Additionally, we will characterize tissue specimens using the novel multiplex immunofluorescence AstroPath platform, which uses algorithms first developed in astronomy, to identify cell types and spatial relationships that are associated with patient benefit to immunotherapy+chemotherapy. Our goal is to use cutting-edge technologies to improve the care of lung cancer patients by informing which patients should receive a given therapy, how well patients will do after receiving therapy, and possible additional targets for the development of new therapies.

Technical Abstract

As seen in the phase III trial CheckMate 816 (CM816), neoadjuvant anti-PD-1+chemotherapy improves survival for patients with resectable non-small cell lung cancer (NSCLC), with pathologic response as a major trial endpoint. Our team led the Central Pathology Review for CM816, and we showed the first prospective evidence that the full spectrum of % residual viable tumor (%RVT) associates with event free survival. Given the data supporting pathologic response as a survival surrogate, %RVT will likely be incorporated into the next generation of clinical trials and may ultimately guide clinical decision-making. %RVT is primarily evaluated using visual assessment of routine hematoxylin and eosin-stained slides. We developed a machine learning-based approach to score %RVT, which allows for a standardized approach that can be completed rapidly for a large volume of patients, and we propose to test this algorithm in resection specimens from CM816. Additionally, we will use multiplex immunofluorescence (mIF) to quantify individual features of pathologic response, locate them within the larger tumor bed, and determine the relative contribution in predicting patient outcomes. Furthermore, we will use the novel AstroPath platform, a mIF whole-slide imaging platform that uses algorithms first developed in astronomy to generate tumor-immune maps, to identify additional pre- and on-treatment biomarkers of response. Our goal is to leverage emerging technologies (i.e, machine learning and mIF) to develop the next generation of pathology biomarkers, including pathologic response assessment, and to identify additional features that can potentially be targeted in combination with anti-PD-(L)1+chemotherapy to improve clinical benefit in patients with NSCLC.

Role of KIRs in Regulating Anti-tumor Immunity and Autoimmunity

Career Development Award
Diane Tseng, MD, PhD
University of Washington and Fred Hutchinson Cancer Center
Seattle
WA

Checkpoint immunotherapy has advanced treatment of NSCLC, but the majority of patients do not experience long-term disease control and are at risk for autoimmune-related side effects.  In this study, Dr. Tseng will examine specialized cells called CD8+ T that express receptors (KIR+) that suppress autoimmunity to understand how these cells regulate the immune system’s cancer-fighting ability during checkpoint immunotherapy treatment.  Insights gained from this study could result in better strategies for improving efficacy while decreasing immune-related side effects.

The Germline-Somatic Interaction in Young-Onset Lung Cancer

Career Development Award
This grant was funded in part by Lung Cancer Initiative
Jaclyn LoPiccolo, MD, PhD
Dana-Farber Cancer Institute
Boston
MA

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.

Randomized Phase II Trial of Iadademstat with ICI Maintenance in SCLC

Career Development Award
Noura Choudhury, MD
Memorial Sloan Kettering Cancer Center
New York
NY

Small cell lung cancer (SCLC) is difficult to treat, and most patients diagnosed have a poor prognosis. Most patients with SCLC treated with first line chemoimmunotherapy progress within months of immune checkpoint inhibitor (ICI) maintenance therapy. Previous studies in mice have revealed that SCLC treated with iadademstat and maintenance ICI shows enhanced tumor response compared to ICI alone. Dr. Choudhury will conduct a phase II randomized trial investigating this combination in patients with SCLC versus standard of care ICI alone to evaluate progression free survival.

Combination checkpoint blockade plus VEGF inhibitor in EGFR-mutated NSCLC

Career Development Award
This grant was funded in part by The Huff Project
Joshua Reuss, MD
Georgetown University
Washington
DC

Osimertinib is the standard of care for treating non-small cell lung cancer with EGFR mutations. Unfortunately, the tumors inevitably develop resistance to osimertinib. Currently, very few treatment options exist for patients whose cancers have become resistant to osimertinib. Dr. Reuss is conducting a phase 2 clinical trial to test whether two immunotherapy drugs, atezolizumab and tiragolumab, given with a VEGF inhibitor, bevacizumab, are effective in controlling EGFR-positive NSCLC that has become resistant to osimertinib.

Therapeutic targeting of BRAF fusion altered lung cancer

Career Development Award
Michael Offin, MD
Memorial Sloan Kettering Cancer Center
New York
NY

Alterations in the BRAF gene can lead to the development of non-small cell lung cancer. BRAF fusions are a type of BRAF gene alterations. These fusions are powerful growth stimulators of lung cancer. Currently, no treatment exists for cancers that harbor these BRAF fusions. Dr. Offin will be testing a series of new drugs in preclinical cell line and animal models of lung cancer. The ultimate goal of his project is to identify new drugs that can be tested in clinical trials.

Phase 2 trial of neoadjuvant KRAS G12C directed therapy in resectable NSCLC

Career Development Award
Kristen Marrone, MD
Johns Hopkins School of Medicine
Baltimore
MD

Around one in three patients with non-small cell lung cancer are diagnosed with early-stage disease, where surgery is offered as curative therapy. Unfortunately, the cancer can recur in 50%-60% of patients. The rate of recurrence is higher in patients whose tumors have certain mutations, such as mutations in the KRAS gene. Dr. Marrone and her team will be conducting a phase 2 trial to test whether treatment with a KRAS G12C blocking drug, adagrasib, given as a single drug or in combination with an immunotherapy drug, nivolumab, before a patient undergoes surgery can delay or prevent recurrence in patients whose tumors have a KRAS G12C mutation.

Innate immunity as a mechanism of TKI resistance in fusion-driven NSCLC

Career Development Award
This grant was funded in part by The Huff Project
Erin Schenk, MD, PhD
University of Colorado
Boulder
CO

Fusion-driven NSCLC is a group of lung cancers that are driven by specific changes in oncogenes. These lung cancers tend to be addicted to these oncogenes. Such fusion-driven NSCLCs are treated with targeted therapies that block the effect of the oncogenes. However, the cancer inevitably comes back because the tumors become resistant. Traditionally, fusion-driven NSCLCs have not been successfully treated with immunotherapy. Dr. Schenk is testing how these cancers can be treated with immunotherapy through another immune pathway—the innate immunity pathway.