P16-CD8-Ki67 Triple Algorithm for Prediction of CDKN2A Mutations in Patients with Multiple Primary and Familial Melanoma

P16-CD8-Ki67三重算法用于预测多发性原发性和家族性黑色素瘤患者的CDKN2A突变

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Abstract

Melanoma, a malignant neuroectodermic tumor originating from the neural crest, presents a growing global public health challenge and is anticipated to become the second most prevalent malignancy in the USA by 2040. The CDKN2A gene, particularly p16INK4a, plays a pivotal role in inhibiting the cell cycle via the cyclin D/CDK2-pRb pathway in certain tumors. In familial melanomas (FM), 40% exhibit CDKN2A mutations affecting p16INK4a, impacting checkpoint G1, and stabilizing p53 expression. This study aims to establish a scoring system using immunohistochemical antibodies, providing a cost-saving approach to classify multiple primary melanomas (MPM) and FM patients based on their mutational status, thus mitigating genetic testing expenses. This retrospective study included 23 patients with MPM and FM, assessing the p16, CD8, and Ki67 immunohistochemical status. Analyses of each parameter and associations between their value intervals and genetic CDKN2A status were conducted. A total score of at least 9 out of 10 points per tumor defined melanomas with homozygous CDKN2A deletions, exhibiting a sensitivity of 100% and specificity of 94.11%. In conclusion, p16, CD8, and Ki67 individually serve as valuable indicators for predicting melanoma evolution. The algorithm, comprising these three immunohistochemical parameters based on their prognostic and evolutionary significance, proves to be a valuable auxiliary diagnostic tool for cost-effective prediction of mutational status in detecting multiple and familial primary melanomas with CDKN2A homozygous deletion.

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