Abstract
Purpose: Collagen type XI alpha 1 (COL11A1), a critical member of the collagen superfamily, is essential for tissue structure and integrity. This study aimed to validate previously identified variations in COL11A1 expression during breast cancer carcinogenesis and progression, as well as elucidate their clinical implications. Methods: COL11A1 mRNA expression levels were assessed using real-time reverse transcription-PCR (RT-PCR) in 30 pairs of normal breast tissue and primary breast cancer, 30 pairs of primary breast cancer and lymph node metastases, 30 benign tumors, and 107 primary breast cancers. COL11A1 protein expression was evaluated by Western blot in six matched trios of normal tissue, primary cancer, and lymph node metastasis. Results: COL11A1 mRNA levels were significantly higher in primary breast cancer tissues (n = 30) than in adjacent normal breast tissues (p < 0.001). Conversely, lymph node metastases (n = 30) showed significantly lower COL11A1 mRNA levels compared to their primary breast cancer counterparts (p=0.005). In a larger cohort, primary breast cancers (n = 107) had significantly elevated COL11A1 mRNA levels relative to adjacent normal tissues (n = 30) and benign tumors (n = 30) (p < 0.001). Benign tumors also demonstrated higher levels compared to normal tissues (p=0.012). The protein expression patterns were consistent with the mRNA findings. Receiver operating characteristic (ROC) curve analysis confirmed the diagnostic relevance of COL11A1 expression levels. Significant associations were found between COL11A1 mRNA levels and clinical parameters including lymph node involvement (p=0.046), clinical stage (p=0.004), and progesterone receptor status (p=0.048). Overexpression of COL11A1 was correlated with poor prognosis. Conclusions: COL11A1 expression varies during breast tumor initiation and progression, with elevated levels linked to worse prognoses. These findings underscore COL11A1's potential as a biomarker in breast cancer, suggesting its assessment could enhance diagnostic and prognostic strategies for more personalized patient management.