Identification of the shared gene signatures in retinoblastoma and osteosarcoma by machine learning DOI Creative Commons

Rongjie Ye,

Quan Yuan,

Wenkang You

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

Osteosarcoma (OS) is the most prevalent secondary sarcoma associated with retinoblastoma (RB). However, molecular mechanisms driving interactions between these two diseases remain incompletely understood. This study aims to explore transcriptomic commonalities and pathways shared by RB OS, identify biomarkers that predict OS prognosis effectively. RNA sequences patient information for were obtained from University of California Santa Cruz (UCSC) Xena Gene Expression Omnibus databases. When first identified, a common gene expression profile was discovered. Weighted Co-expression Network Analysis (WGCNA) revealed co-expression networks after immunotyping patients. To evaluate genes univariate multivariate Cox regression analysis then carried out. Three machine learning methods used pick key genes, risk models created verified. Next, medications target independent prognostic found using Cellminer database. The comparison differential 1216 primarily linked activation proliferation immune cells. WGCNA identified 12 modules related immunotyping, grey module showing strong correlation immune-inflamed phenotype. intersected RB, producing 65 RB-associated Immune-inflamed Genes (ROIGs). 6 hub model construction through three techniques. A based on established, demonstrating significant value OS. contribute progression both cancers multiple pathways. ROIGs score independently predicts overall survival Additionally, this highlights potential as therapeutic targets or clinical use.

Language: Английский

LncRNA HOTAIR promotes the migration and invasion of cervical cancer through DNMT3B/LATS1/ YAP1 pS127 axis DOI
Zhihao Zhang, Xianyi Zhou,

Jiulin Li

et al.

Reproductive Biology, Journal Year: 2024, Volume and Issue: 24(2), P. 100893 - 100893

Published: May 15, 2024

Language: Английский

Citations

2
Women’s Special Issue Series: Biomedicines DOI Creative Commons
Letizia Polito

Biomedicines, Journal Year: 2024, Volume and Issue: 12(3), P. 471 - 471

Published: Feb. 20, 2024

Following the invitation of Biomedicines, we decided to accept project this Special Issue because believe that in many situations gender prejudices still exist and put women a disadvantaged position for dissemination their research, preventing scientific community from benefiting plurality voices interpretation research [...]

Language: Английский

Citations

0
Pediatric cancer—pathology and microenvironment influence: a perspective into osteosarcoma and non-osteogenic mesenchymal malignant neoplasms DOI Creative Commons

Consolato M. Sergi

Discover Oncology, Journal Year: 2024, Volume and Issue: 15(1)

Published: Aug. 18, 2024

Pediatric cancer remains the leading cause of disease-related death among children aged 1-14 years. A few risk factors have been conclusively identified, including exposure to pesticides, high-dose radiation, and specific genetic syndromes, but etiology underlying most events unknown. The tumor microenvironment (TME) includes stromal cells, vasculature, fibroblasts, adipocytes, different subsets immunological cells. TME plays a crucial role in carcinogenesis, formation, progression, dissemination, resistance therapy. Moreover, autophagy seems be vital regulator controls immunity. Autophagy is an evolutionarily conserved intracellular process. It enables degradation recycling long-lived large molecules or damaged organelles using lysosomal-mediated pathway. multifaceted complicated neoplastic may depend on context. function as tumor-suppressive mechanism during early tumorigenesis by eliminating unhealthy components proteins, regulating antigen presentation immune supporting anti-cancer response. On other hand, dysregulation contribute progression promoting genome damage instability. This perspective provides assortment regulatory substances that influence features metastasis Mesenchymal cells bone soft-tissue sarcomas their signaling pathways play more critical than epithelial childhood youth. investigation pediatric malignancies uncharted primarily, this unique collection help include novel advances setting.

Language: Английский

Citations

0
Identification of the shared gene signatures in retinoblastoma and osteosarcoma by machine learning DOI Creative Commons

Rongjie Ye,

Quan Yuan,

Wenkang You

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

Osteosarcoma (OS) is the most prevalent secondary sarcoma associated with retinoblastoma (RB). However, molecular mechanisms driving interactions between these two diseases remain incompletely understood. This study aims to explore transcriptomic commonalities and pathways shared by RB OS, identify biomarkers that predict OS prognosis effectively. RNA sequences patient information for were obtained from University of California Santa Cruz (UCSC) Xena Gene Expression Omnibus databases. When first identified, a common gene expression profile was discovered. Weighted Co-expression Network Analysis (WGCNA) revealed co-expression networks after immunotyping patients. To evaluate genes univariate multivariate Cox regression analysis then carried out. Three machine learning methods used pick key genes, risk models created verified. Next, medications target independent prognostic found using Cellminer database. The comparison differential 1216 primarily linked activation proliferation immune cells. WGCNA identified 12 modules related immunotyping, grey module showing strong correlation immune-inflamed phenotype. intersected RB, producing 65 RB-associated Immune-inflamed Genes (ROIGs). 6 hub model construction through three techniques. A based on established, demonstrating significant value OS. contribute progression both cancers multiple pathways. ROIGs score independently predicts overall survival Additionally, this highlights potential as therapeutic targets or clinical use.

Language: Английский

Citations

0