Association of PRKCQ variants with breast cancer susceptibility and clinicopathological features.

BACKGROUND

Breast cancer (BC) continues to be the most common malignant neoplasm and leading cause of mortality in women globally and genetic predisposition is one of the important risk determinants of this disease. PRKCQ which encodes PKCθ contributes to several human cancers due to its crucial role in several cellular processes such as cell cycle progression, cell survival and immune response. The purpose of this study was to evaluate the relation between five pathogenic missense variants in the PRKCQ gene (rs1838691533, rs1248923790, rs1837738907, rs1837738573, and rs1403981107) and risks of breast cancer, tumor characteristics, and molecular types.

METHODS

Blood samples were collected from 361 breast cancer patients and 364 cancer-free women in hospitals in Islamabad and Rawalpindi, Pakistan. DNA extraction was performed using the phenol-chloroform method, and genotyping was conducted via Tetra ARMS PCR. Statistical analyses, including Chi-square and Fisher's exact tests, were applied using GraphPad Prism to assess associations between PRKCQ genotypes and clinical parameters such as TNM staging, molecular subtypes, and metastasis.

RESULTS

Our results revealed significant associations between several genotypes and breast cancer risk. Among the analyzed variants, rs1248923790 TT was significantly associated with increased breast cancer risk (OR = 2.106, RR = 1.446, p < 0.0001), particularly in Luminal A BC (OR = 2.530, p < 0.0001), while the CT genotype was more frequent in late-stage and metastatic cases (OR = 3.751, RR = 2.323, p < 0.0001). rs1403981107 AA was associated with HER2 + BC (OR = 2.338, p = 0.0177) and metastatic disease (OR = 1.680, p = 0.0137). rs1837738907 GA was significantly associated with early-stage BC (OR = 2.552, p = 0.0002), suggesting its role in early diagnosis.

CONCLUSION

These results emphasize the functional role of PRKCQ variants in breast cancer and indicate that employing these SNPs as diagnostic, prognostic, and therapeutic biomarkers can be useful for the development of targeted therapeutic strategies. Large sample studies are called for to reinforce these correlations and investigate PKCθ-targeted drugs and their application in breast cancer treatment.