Reprogramming the Tumor Microenvironment to Increase the Efficacy of Treatment in Therapy-Resistant Patients with Pancreatic Ductal Adenocarcinoma

Abstract

SIGNIFICANCE OF THESE STUDIES: Pancreatic Ductal Adenocarcinoma (PDAC) is one of the leading causes of cancer deaths (51,750 in 2024) in the United States and has a 5-year survival rate of only 12.8% (2014-2020). The poor prognosis and high mortality rate of patients with PDAC is attributed to the tumor stroma consisting of a heterogeneous population of cancer associated fibroblasts (CAFs) that allow cancer cells to evade immune surveillance by promoting the infiltration of immunosuppressive cells and cancer cell proliferation and metastasis. Even though certain cancer patients in clinical trials have shown response towards PD-1/PD-L1 inhibitors, PDAC patients have failed to show any improvement. PD-1/PD-L1 inhibitors only block the interaction between the T-cells and cancer cells without targeting any specific cells and as a result allows the patient’s immune system to respond against cancer. PDAC tumors display immunosuppressive mechanisms that decrease the efficacy of T-cell function by preventing it from infiltrating/proliferating within the TME. The heterogeneous TME plays a critical role in progression of pancreatic cancer and its low survival outcome. Therefore, it is important to improve the efficacy of immunotherapy and drug targetability to increase the anti-tumor effect of T-cells. Our studies identified the modulated cell types in PDAC TME that are targeted by cabozantinib in the PDAC tumor microenvironment (TME) and allowed us to explore the therapeutic treatment responses in immune-resistant patients. OBJECTIVE AND MAJOR FINDINGS: Objective and Major Finding 1 (Chapter 3): Objective 1 of these studies was to target the immunosuppressive myeloid derived suppressor cells (MDSC) within the tumor microenvironment (TME) to increase the efficacy of immunotherapy. An orthotopically transplanted mouse model of PDAC was used to identify the multitargeted reprogramming of the PDAC TME in response to cabozantinib. Using a combination of high‐plex spatial profiling and organoid technologies of matched patient biospecimens we 1) assessed the biological implications of heterogeneity quantitatively within small and limited PDAC core biopsies and resected surgical tissues, 2) identified the therapeutic benefit of cabozantinib in increasing the efficacy of pembrolizumab and atezolizumab by depleting the TME of MDSCs and reprograming the CAFs to an anti-tumor phenotype, and 3) identified a potential tumor CD44v9 expressing cell population that may attribute to residual disease in patients with PDAC. Objective and Major Findings 2 (Chapter 4): Our preclinical studies were the foundation for the development of an ongoing Phase II Trial evaluating the safety and efficacy of atezolizumab in combination with cabozantinib for the treatment of metastatic, refractory PDAC (ClinicalTrials.gov ID NCT04820179). Prior to the treatment, we collected patient tissues from the metastatic site, FFPE samples and blood samples. A subsequent collection of patient tissue from the same metastatic site, FFPE samples and blood samples were done after these patients were treated for 3 cycles (21days/cycle) with cabozantinib and atezolizumab (atezo). Using the Nanostring CosMx SMI and organoid/immune cell co-culture we investigated the cellular composition, morphology and underlying mechanism of PDAC tumor. CosMx SMI revealed major intra-tumoral heterogeneity among metastatic pancreatic patients. We show a significant decrease in the tumor cells, MDSC population and a change in the CAF phenotype after 3 treatment cycles with cabozantinib and atezolizumab. It also revealed an upregulation of immune cell populations such as CD8+ and CD4+ cells in post treatment group. The patient-derived organoids were co-cultured with autologous immune cells to serve as a predictive model for PDAC patients. Upon investigating the responsiveness of the treatment in co-cultures, we found that the results correspond with the clinical data.