Soluble CTLA-4 and high-risk genetic variants: A new frontier in pancreatic ductal adenocarcinoma (PDAC) biomarkers
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: CTLA-4 is regarded as the "leader" of immune checkpoint inhibitors, as it suppresses autoreactive T cells at the initial phase of naïve T-cell activation. Its genetic variability may impair its effectiveness in the anti-tumor response. Additionally, the presence of soluble CTLA-4 (sCTLA-4) in the tumor microenvironment suppresses effector T-cell activation, allowing for tumor evasion. Therefore, this study aimed to explore the relationship between CTLA-4 polymorphisms and sCTLA-4 and the risk of pancreatic ductal adenocarcinoma (PDAC) in an Egyptian population. Method: Three single-nucleotide polymorphisms of the CTLA-4 gene (rs231726, rs11571317, and rs13384548) were analyzed, and sCTLA-4 levels were assessed in 125 PDAC patients and 125 healthy controls. Results: The rs231726 TT genotype was associated with a six-fold greater risk of PDAC, advanced disease grades, and elevated carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA). Also, the T-allele increased the likelihood of developing PDAC by four times. Conversely, the CC genotype and C-allele conferred protection against PDAC development. The rs11571317 CC genotype and C-allele elevated the PDAC risk by 4.91 and 3.49-fold, respectively, with no relationship to disease severity. The rs13384548 polymorphism showed no significant association with PDAC susceptibility. sCTLA-4 correlated positively with CA19-9 and CEA levels, with the highest levels found in individuals possessing the rs231726 TT genotype and high malignancy grades. Conclusions: These findings highlight the potential of CTLA-4 SNPs and sCTLA-4 as biomarkers for PDAC diagnosis and prognosis. Integrating these biomarkers into screening programs can offer improved strategies for early detection and disease management in high-risk populations.
Authors: Marwa Hassan, Yasmine Elhusseny, Fatma Elbatol Agamy, Mariam Magdy Azmy, Mahmoud Balata
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,700
OpenAlex ID: W4415198774
