Previously Funded Research

Joseph Chan, MD, PhD

Memorial Sloan Kettering Cancer Center

Research Project:

Biomarkers of Response and Toxicity to Tarlatamab in Patients with Metastatic Small Cell Lung Cancer

Summary:

Small cell lung cancer (SCLC) is an aggressive and deadly form of lung cancer with limited treatment options and poor long-term survival. However, a newly approved drug called tarlatamab represents a promising advance. Tarlatamab is a type of immunotherapy that helps the immune system target cancer cells by binding to a protein called DLL3, commonly found on SCLC cells. Although tarlatamab has shown encouraging early results with a 40% response rate in patients with relapsed cancer following chemotherapy, it does not confer benefit for all patients and can carry significant risks. One side effect is cytokine release syndrome (CRS)—a potentially serious immune reaction that can cause fever, low blood pressure, and difficulty breathing.

Identifying the patients who are most likely to respond to treatment as well as those at high risk of toxicity will be critical for optimizing tarlatamab therapy in SCLC. Currently, no reliable biomarkers exist to guide treatment decisions with tarlatamab. For example, simply measuring DLL3 levels in a tumor does not predict whether a patient will respond to treatment. Our research suggests that multiple molecular factors related to the SCLC subtype may be more informative. Additionally, new technologies allow us to track the behavior of immune cells in the blood as well as dynamic changes in the tumor over time—especially in response to treatment. These factors may hold important clues for assessing both response to tarlatamab as well as toxicity.

The goal of this study is to utilize these new technologies in tandem with advanced computer modeling to improve how we predict which patients will benefit from tarlatamab and who is at higher risk for CRS. Advanced techniques will allow the team to analyze both tumor characteristics and immune cells from blood samples that can be readily acquired non-invasively over time before, during, and after treatment. One method, called cell-free ChIP-sequencing (cfChIP-seq), allows for tracking changes in tumor activity through DNA fragments in the blood. Another method, single-cell RNA sequencing (scRNA-seq), provides a detailed picture of how individual immune cells behave before and after tarlatamab treatment. The team has already tested and optimized these techniques in patient samples and is now ready to apply them to a larger patient cohort.

The study has two main aims:

1. Predicting who responds to tarlatamab. We will examine tumor-related features (i.e. SCLC subtypes, DLL3-related pathways) and immune system markers (i.e. T-cells phenotypes or suppressive immune cells) to determine which factors are linked to better treatment response. We will use machine learning models to identify patterns that could predict who benefits most from tarlatamab.
2. Identifying who is at risk for CRS. We will also look for blood-based markers that may predict which patients are more likely to develop CRS. This includes measuring common inflammatory markers (like c-reactive protein and ferritin) and analyzing immune cell behavior (particularly certain immune cells that may produce inflammatory signals). We hope to build a CRS risk score to guide how tarlatamab should be given—for example, identifying patients who could safely be treated at home versus those who need to be monitored in the hospital or even treated with additional supportive agents to prevent or reduce the severity of CRS.

The study team includes clinicians and scientists with deep expertise in SCLC, immunotherapy, computational biology, and cutting-edge sequencing technologies. By combining their skills, the team aims to develop a new framework for personalizing tarlatamab treatment, making it more effective and safer. This could allow patients to receive treatment more conveniently, avoid dangerous side effects, and ultimately live longer. In the long term, this approach may also be useful for understanding and managing similar immunotherapies or other DLL3-directed therapies for other types of lung cancer and solid tumors.