CDKN1C as a prognostic biomarker correlated with immune infiltrates and therapeutic responses in breast cancer patients. Issue 19 (31st August 2021)

• Record Type: Journal Article
• Authors: Lai, Jianguo; Lin, Xiaoyi; Cao, Fangrong; Mok, Hsiaopei; Chen, Bo; Liao, Ning
• Is Part Of: Journal of cellular and molecular medicine. Volume 25:Issue 19(2021)
• Page Start: 9390
• Page End: 9401
• Publication Date: 2021-08-31
• Subjects: breast cancer -- CDKN1C -- overall survival -- prognosis -- therapeutic response; Cytology; Medicine; Molecular Biology; Cytologie -- Périodiques; Médecine -- Périodiques; Biologie moléculaire -- Périodiques; Cytology -- Periodicals; Medicine -- Periodicals; Molecular biology -- Periodicals; 611.01805
• DOI: 10.1111/jcmm.16880
• Languages: English
• ISSNs: 1582-1838

Abstract

Abstract: Breast cancer (BC) prognosis and therapeutic sensitivity could not be predicted efficiently. Previous evidence have shown the vital roles of CDKN1C in BC. Therefore, we aimed to construct a CDKN1C‐based model to accurately predicting overall survival (OS) and treatment responses in BC patients. In this study, 995 BC patients from The Cancer Genome Atlas database were selected. Kaplan‐Meier curve, Gene set enrichment and immune infiltrates analyses were executed. We developed a novel CDKN1C‐based nomogram to predict the OS, verified by the time‐dependent receiver operating characteristic curve, calibration curve and decision curve. Therapeutic response prediction was followed based on the low‐ and high‐nomogram score groups. Our results indicated that low‐CDKN1C expression was associated with shorter OS and lower proportion of naïve B cells, CD8 T cells, activated NK cells. The predictive accuracy of the nomogram for 5‐year OS was superior to the tumour‐node‐metastasis stage (area under the curve: 0.746 vs. 0.634, p < 0.001). The nomogram exhibited excellent predictive performance, calibration ability and clinical utility. Moreover, low‐risk patients were identified with stronger sensitivity to therapeutic agents. This tool can improve BC prognosis and therapeutic responses prediction, thus guiding individualized treatment decisions.