Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Background: Lysosomes are monolayer membrane-encapsulated organelles containing acid hydrolases, crucial for intracellular substance breakdown and cellular homeostasis. They are also involved in autophagy. Although autophagy is linked to cancer, the role of lysosome-related genes in cervical cancer prognosis remains unclear. This study aimed to develop a prognostic model for cervical cancer based on lysosome-related genes and explore its applications in the tumor microenvironment, radiotherapy prognosis, and clinical pharmacology.
Methods: We identified differentially expressed lysosome-related genes in cervical cancer and normal tissues using the TCGA database. A prognostic model was constructed using LASSO-Cox regression, validated with ROC curves and PCA analysis, and further verified using the GEO dataset GSE63514. In vitro and in vivo experiments were conducted to explore key genes, and their biological significance and pharmacological potential were analyzed.
Results: A five-gene (AP1B1, DNASE2, LAMP3, NPC1, and LAPTM4A) lysosome-associated prognostic model was developed. LAMP3 was identified as the most differentially expressed gene. Knockdown of LAMP3 significantly reduced cervical cancer cell migration and invasion through lysosomal and autophagic pathways. Daidzein was found to have high binding affinity for LAMP3, suggesting its therapeutic potential.
Conclusion: Lysosome-related gene modeling has significant clinical value. LAMP3 knockdown inhibits cervical cancer progression by reducing autophagy and lysosomal function. Daidzein shows potential as a novel therapeutic agent. However, further validation in larger cohorts is needed due to the limited sample size in this study.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12288217 | PMC |
| http://dx.doi.org/10.1186/s12885-025-14596-w | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Trends in cervical cancer incidence in the Netherlands: A join-point and age-period-cohort analysis (1989-2023).
Int J Cancer
September 2025
Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Cervical cancer remains a significant public health issue, ranking as the fourth most common cancer in women globally. In the Netherlands, cervical cancer incidence declined steadily from 1989 to 2001 but increased between 2001 and 2007. This study updates trends in cervical cancer incidence from 1989 to 2023 in the Netherlands and evaluates the impact of screening practices and participation rates in the national population-based screening program.
View Article and Find Full Text PDFHuman papillomavirus (HPV) vaccination in women with conisation.
Cochrane Database Syst Rev
September 2025
Institute for Evidence in Medicine, Medical Center - University of Freiburg / Medical Faculty - University of Freiburg, Freiburg, Germany.
Rationale: Cervical cancer is the fourth most common cancer affecting women worldwide, caused by persistent infection with oncogenic human papillomavirus (HPV) types. While HPV infections usually resolve spontaneously, persistent infections with high-risk HPV types can progress to premalignant glandular or - mostly - squamous intraepithelial lesions, usually classified in cervical intraepithelial neoplasia (CIN). Women with CIN 2 and CIN 3 (i.
View Article and Find Full Text PDFDeep dive into deep learning methods for cervical cancer detection and classification.
Rep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Cervical cancer continues to pose a significant global health challenge, highlighting the urgent need for accurate and efficient diagnostic techniques. Recent progress in deep learning has demonstrated considerable potential in improving the detection and classification of cervical cancer. This review presents a thorough analysis of deep learning methods utilized for cervical cancer diagnosis, with an emphasis on critical approaches, evaluation metrics, and the ongoing challenges faced in the field.
View Article and Find Full Text PDFOptimizing cervical cancer diagnosis with accurate cell classification using modified HDFF.
Rep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Background: Cervical cancer (CC) is a leading cause of cancer-related deaths worldwide, emphasizing the need for accurate and efficient diagnostic tools. Traditional methods of cervical cell classification are time-consuming and susceptible to human error, highlighting the need for automated solutions.
Materials And Methods: This study introduces the modified hierarchical deep feature fusion (HDFF) method for cervical cell classification using the SIPaKMeD and Herlev datasets.
Case Report: Immune-mediated acute liver failure induced by tislelizumab in a patient with advanced cervical cancer.
Front Oncol
August 2025
Hunan Cancer Hospital, The Affiliated Cancer Hospital, Xiangya School of Medicine, Central South University, Changsha, Hunan, China.
Tislelizumab, an anti-PD-1 monoclonal antibody, is associated with immune-related hepatitis in 1.8% of cases, but reports of acute liver failure (ALF) remain exceedingly rare. We present a case of fulminant hepatitis and ALF following Tislelizumab therapy in a 55-year-old woman with locally advanced cervical adenocarcinoma.
View Article and Find Full Text PDF