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Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer's Disease
Published on: May 20, 2024
Identifying Hub Genes Associated with Sex Disparities in Prolactinomas
Yuan Zhang1, Yuyang Peng1,2, Chengcheng Wang1,3
1Multidisciplinary Center for Pituitary Adenomas of Chongging, Department of Neurosurgery, Xingiao Hospital, Army Medical University, Chongqing, China.
Abstract:
Background: Male patients with prolactinomas exhibit greater invasiveness, resistance to dopamine agonists, making treatment more challenging. This study aims to explore the potential different genes contributing to sex disparities in prolactinomas. Materials and Methods: Weighted gene co-expression network analysis and differential expressed genes analysis were performed to identify sex-related hub genes. In addition, bioinformatics analyses were conducted to understand gene localization on chromosomes, gene regulatory networks, signaling pathways, and their relationship with immune function, which was verified in 21 human prolactinoma samples. Results: A total of 21 sex-related hub genes were identified. The hub genes in males included nine Y chromosome genes and six autosomal genes, while females had six specific genes. Further predictions using the NetworkAnalyst online tool suggested that transcription factors (REST, androgen receptor) and microRNAs (miR-27a-3p, miR-146a-5p) may be involved in regulating the above sex-related hub genes. CIBERSORT analysis revealed that prolactinomas in males showed significant infiltration of resting dendritic cells and naive CD4+ T cells. Correlation analysis between sex-related hub genes and immune checkpoint genes indicated that male hub genes were positively correlated with CD47 and CEACAM1, while showing a strong negative correlation with CD28, TNFSF14, and CD226. Finally, similar changes of gene expression in our surgical prolactinoma samples were confirmed by RT-qPCR. Conclusions: In prolactinomas, the male hub genes and female hub genes are identified by our bioinformatics analysis. Our findings suggest that KDM5D, PDCD1, ELOA3BP, XRRA1, and SIGLEC12 serve as potential biomarkers for male prolactinomas, while SOX3, DMGDH, and NPAS1 may serve as potential biomarkers for female prolactinoma, providing a theoretical basis for targeted therapy.
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