Deubiquitinases as Prognostic Biomarker and Potential Drug Target for Gynecological Cancers DOI

Mavika Kondapally,

Anubha Dey,

Harshitha Velangani Golagana

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 7, 2025

Abstract Background To develop Deubiquitinase-Associated Signatures (DAS) to predict the prognosis of gynecological cancer patients. Methods Using a cox-lasso regression model, we have developed Deubiquitinase-associated signatures for Cervical, Ovarian, and Uterine cancers. Developed DAS were validated in TCGA GEO datasets. Survival analysis was carried out know effect factors like menopausal stage grade on DAS. The survival prediction accuracy analyzed using ROC curves. Immune infiltration scores 22 immune subtypes explored CIBERSORT package risk groups classified by Further, target unfavorable deubiquitinases (DUBs), compounds identified CMap database. Results Three types. able classify patients into two is an independent predictor irrespective tumor stage. DAS, along with clinical features, improves predictions. has shown that cell associated divided CMap, 52 DUBs. Conclusion good survival, targeting DUBs can decrease progression

Язык: Английский

Deubiquitinases as Prognostic Biomarker and Potential Drug Target for Gynecological Cancers DOI

Mavika Kondapally,

Anubha Dey,

Harshitha Velangani Golagana

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 7, 2025

Abstract Background To develop Deubiquitinase-Associated Signatures (DAS) to predict the prognosis of gynecological cancer patients. Methods Using a cox-lasso regression model, we have developed Deubiquitinase-associated signatures for Cervical, Ovarian, and Uterine cancers. Developed DAS were validated in TCGA GEO datasets. Survival analysis was carried out know effect factors like menopausal stage grade on DAS. The survival prediction accuracy analyzed using ROC curves. Immune infiltration scores 22 immune subtypes explored CIBERSORT package risk groups classified by Further, target unfavorable deubiquitinases (DUBs), compounds identified CMap database. Results Three types. able classify patients into two is an independent predictor irrespective tumor stage. DAS, along with clinical features, improves predictions. has shown that cell associated divided CMap, 52 DUBs. Conclusion good survival, targeting DUBs can decrease progression

Язык: Английский

Процитировано

0