Introduction

By 2030, pancreatic ductal adenocarcinoma (PDAC) is predicted to become the second leading cause of cancer-related death. Due to its resistance to conventional therapies and heterogeneous mutational landscape, molecular stratification and the development of targeted therapeutic options are essential for improving survival of PDAC patients. Previous work from our group investigated loss-of-function mouse models for the ATM serine/threonine kinase causing homologous recombination deficiency (HRD) in PDAC. Specifically, ATM loss was reported to accelerate tumorigenesis, support metastatic burden, and coincide with oncogenic programs, including epithelial-mesenchymal transition (EMT). Interestingly, ATM-deficient tumors accumulated EZH2, suggesting that ATM status contributes to rewiring the epigenetic landscape of pancreatic tumors, subsequently supporting oncogenic features.

Aims & Methods

To investigate whether and how EZH2 impacts ATM-deficient PDAC pathogenesis, we generated conditional double ATM and EZH2 knockouts in Kras^G12D/+; Ptf1a^Cre/+ mice. In vitro approaches were conducted using primary cell lines isolated from murine endpoint tumors. Additionally, CRISPR/Cas9 strategy was implemented on ATM-deficient cell lines to decipher the ATM-EZH2 molecular axis.

Results

Double-null mice showed extended mouse survival and decreased undifferentiated malignant cell features. Strikingly, interrogation of publicly available human datasets (TCGA, PanCancer Atlas) revealed a significant extended progression-free survival of ATM^neg EZH2^neg PDAC patients compared to ATM^neg EZH2^pos PDAC cases. Furthermore, we identified the histone-methyltransferase EZH2 as a direct ATM substrate impacting the mesenchymal phenotype of ATM-depleted tumors. Interestingly, RNA-seq analysis of ATM-deficient pancreatic cancer cells revealed upregulation of a transcriptomic program associated with cell differentiation upon EZH2 depletion by CRISPR/Cas9 strategy. In line, EZH2 depletion restored differentiated tumor features ex vivo. Further in vitro investigations revealed that ATM status significantly impacts EZH2 activity via a post-translational regulation axis, leading to a fostered tumor supporting EZH2 activity during pancreatic carcinogenesis. Specifically, the ATM kinase activity results in EZH2 ubiquitination and degradation by promoting Cullin1 E3-ubiquitin ligase recruitment. Finally, we demonstrated that a combinatorial therapy involving a potent EZH2 inhibitor promotes genomic instability and exacerbates the cytotoxic effects of PARP interference in ATM-deficient HRD PDAC.

Conclusion

Overall, we show that ATM deficiency significantly impacts EZH2 epigenetic functions and highlight the molecular stratification according to ATM status prior to pharmacological EZH2 interference in PDAC therapies as a valuable approach to target ATM-deficient HRD tumors.

Introduction

Chronic pancreatitis is a progressive inflammatory disease characterized by irreversible damage to the pancreas. The etiology of the disease is heterogenous and includes alcohol abuse, smoking, genetic risk factors and autoimmune diseases. Several clinical classification and severity scoring systems have been proposed, but none have been globally accepted or reached broad clinical use. Identifying patients at a higher risk of death is crucial for improving patient care and management.

Aims & Methods

This study aimed to develop a prediction model based on promoter hypermethylation of specific genes and clinical factors to differentiate patients with chronic pancreatitis who are at a higher risk of mortality. Clinical variables such as age, sex, smoking status, alcohol consumption, exocrine insufficiency, and endocrine insufficiency, as well as the methylation status of 16 genes, were analyzed using a backward stepwise Cox regression model. The methylation status was determined by a specialized bisulfite based PCR technique. The final model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), and used to determine a risk score for each patients. The “cutpt” package in Stata was used to determine an optimal cut-off, in order to stratify patients into low and high-risk groups. Kaplan-Meier survival curves, and cox regression, and AUC were used to determine the accuracy of the risk groups.

Results

Ninety-seven patients with chronic pancreatitis were included in the study. The final prediction model included age, sex, exocrine insufficiency, endocrine insufficiency, and the methylation status of 5 genes: SFRP2, HIC1, MLH1, RASSF1A, and CDKN2B. The AUC of the model was 0.84, indicating high reliability. The model was superior to a model including only clinical variables (AUC = 0.76), indicating added value of the methylation markers. The optimal cut-off value for the risk score was 7.76. According to this, 67 patients were in the low-risk group, and 30 in the high-risk group. The 5-year survival in the high-risk group was 53% compared to 94% in the low-risk group. Being in the high-risk group was significantly associated with an increased HR of death of 10.2 (95% CI; 4.9-21.1), demonstrating the model's strong prognostic value.

Conclusion

The developed prediction model, which combines clinical factors and gene promoter hypermethylation status, could be a valuable tool for identifying patients with chronic pancreatitis who are at a higher risk of death. This study serves as proof-of-concept of the unexplored potential of methylation analysis in cell-free DNA in chronic pancreatitis. This model can potentially enhance patient care by enabling targeted interventions and monitoring for high-risk individuals, ultimately improving their prognosis and quality of life.

Disclosure

S.D.H., P.H.M., O.T.-U., and H.B.K. declare that they have a patent on a diagnostic panel including the promoter hypermethylation status of 8 genes. Application No. 16161073.8 – 1403 Pancreatic Cancer methylation Markers (18.03.2016)