MD Anderson Cancer Center's Research Highlights at the Society for Immunotherapy of Cancer (SITC) 2024 Annual Meeting showcased breakthroughs in cancer care, research, and prevention, emphasizing immunotherapy advances and insights into the tumor microenvironment.
TAC01-CLDN18.2 Shows Promise in Gastric Cancer
Ecaterina Dumbrava, M.D., and colleagues presented initial data from a first-in-human Phase I trial of TAC01-CLDN18.2, a T cell antigen coupler (TAC) therapy targeting Claudin18.2, a protein abnormally expressed in some gastric cancers and other solid tumors. The trial enrolled heavily pre-treated patients with various cancer types expressing Claudin18.2. The results indicated that TAC01-CLDN18.2 is safe, with no dose-limiting toxicities reported in the first two cohorts. Disease control was observed in five out of six (83%) initial patients eligible for assessment, including an ongoing confirmed partial response in the first cohort. These findings suggest promising clinical activity, leading to further treatment of cohort three.
COVID-19 mRNA Vaccines Enhance Immunotherapy Response
Adam Grippin, M.D., and Steven Lin, M.D., Ph.D., presented updated results demonstrating that COVID-19 mRNA vaccines stimulate the secretion of IFN-λ, a signaling protein that enhances responses to immune checkpoint inhibitors. Previous findings suggested that COVID-19 mRNA vaccines could improve survival by increasing PD-L1 expression. Patients with non-small cell lung cancer who were vaccinated within 100 days of their biopsies and treated with immune checkpoint inhibitors lived twice as long as those who were unvaccinated. Patients with metastatic melanoma also had better outcomes, including improved survival and lower risk of disease progression. The new data showed a significant increase in plasma IFN-λ levels in healthy volunteers 24 hours after vaccination compared to baseline, providing further insights into the mechanisms behind the improved outcomes of vaccinated patients treated with immunotherapy.
Neuromuscular Side Effects Increase Mortality in ICT-My
Keila Ostos-Mendoza and Nicolas Palaskas, M.D., and colleagues found that neuromuscular immune-related adverse events, such as myositis and myasthenia gravis (MG), occurring simultaneously with immune checkpoint therapy-related myocarditis (ICT-My), may significantly increase the risk of death. In a study of 103 patients who experienced ICT-My, the all-cause mortality rate was 51.4%, with only 30.2% attributed to ICT-My. Deaths related to diaphragm failure and ICT-My occurred more frequently in those with concurrent myositis and/or MG compared to those with isolated ICT-My. The findings suggest that neuromuscular toxicities and diaphragm failure are major contributors to the high mortality rates associated with ICT-My, underscoring the need for better management strategies.
AI Predicts Pembrolizumab Outcomes in Rare Tumors
Mohamed Derbala, M.D., and researchers used an AI-powered analysis of biopsies from 84 patients with 10 different histologic subtypes of rare tumors to characterize tumor responses and changes in the tumor microenvironment before and during pembrolizumab treatment. Changes in tumor-infiltrating lymphocyte density and tumor content were significantly associated with progression-free survival and overall survival, especially in subgroups with a higher density of tumor-infiltrating lymphocytes. This AI-powered assessment could potentially inform future personalized treatment strategies and better predict responses in immunotherapy trials for patients with rare tumors.
Tumor Microenvironment in Pleural Mesothelioma
Katarzyna Tomczak, Ph.D., and researchers used multi-omics analysis to examine the tumor immune microenvironment (TIME) in tumor samples from 26 patients with pleural mesothelioma (PM) who underwent surgical resection. The study characterized the immune-genomic landscape of the TIME, highlighting the tumor-infiltrating lymphocytes and, in some immunosuppressive tumors, the presence of hyperexpanded T cell receptor clones with a potential antitumor response. The findings provide further insights into the TIME of PM and define distinct immune features to inform future clinical trial design.
VCAM-1+ TAMs Drive Immunotherapy Resistance
Mehdi Chaib, Ph.D., and colleagues found a subset of tumor-associated macrophages (TAMs) that express the vascular cell adhesion molecule 1 (VCAM-1) in models of melanoma and pancreatic cancer. This subset was elevated in melanoma tumors after anti-CTLA-4 immunotherapy, and the TAMs caused dysfunctional activation of CD8 T cells and promoted resistance to immunotherapy in vivo. Expression of the VCAM-1 gene signature in patients treated with anti-CTLA-4 immunotherapy was associated with a poor prognosis, suggesting that VCAM-1+ TAMs are negative regulators of T cells associated with anti-CTLA-4 treatment resistance.
Iron-Rich Immune Cells Promote Tumor Growth
Ian Folkert, M.D., Ph.D., and colleagues studied how TAMs respond to red blood cells in lab models of sarcoma. The study uncovered a specific type of iron-rich TAM (iTAM) that helps tumors grow by supporting blood vessel formation and suppressing T cell activity. They also identified a receptor, Ednrb, as a key player in iTAM function. Blocking this receptor, especially when combined with anti-PD1 immunotherapy, reduced tumor growth, suggesting that targeting iTAMs and their receptors could offer new treatments for cancers with similar characteristics.
STING Activation Overcomes Glioblastoma Resistance
Spencer Lea and Michael Curran, Ph.D., examined the use of a STING pathway activator, which reprograms the TME to be proinflammatory, combined with CD47 blockade in treatment-resistant lab models of glioblastoma. STING activation reduced immune suppression and extended T cell-dependent survival. The combination enhanced phagocytosis and further extended survival, highlighting the therapeutic potential of this approach for treatment-resistant glioblastoma.
Machine Learning Highlights Biomarkers in Lung Cancer
Stephanie Schmidt, Ph.D., Tina Cascone, M.D., Ph.D., Don Gibbons, M.D., Ph.D., and colleagues used a machine learning approach to integrate multi-platform data from the ImmunogenomiC PrOfiling of NSCLC Project (ICON) and the NEOSTAR trial. The researchers generated a novel framework to analyze how different combinations of chemotherapies and immunotherapies affect the immune and microbial landscape of NSCLC and to identify potential response biomarkers. Their model identified 65 treatment-specific impacts and three potential biomarkers of response from over 1,100 measurements in 150 patients. The researchers are currently validating and refining this integrated approach to provide additional insights for clinical impact.
