98%
921
2 minutes
20
Purpose: The fourth most common cause of cancer-related deaths in women is cervical cancer. Though treatment of early-stage cervical cancer is often effective, middle and advanced stage cervical cancer is hard to treat and prone to recurrence. We sought to explore the mechanism underlying cervical cancer progression to identify new therapeutic approaches.
Methods: Label-free mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins in cervical cancer and normal tissues. The findings were confirmed by Western blotting, RT-qPCR, and immunohistochemistry. The function of RCN1 in tumor invasion, metastasis, and proliferation was investigated using in vitro and in vivo tests. Immunoprecipitation tandem mass spectrometry (IP-MS) was performed in RCNI knockdown cells to identify downstream pathways. Western blotting was used for detecting the expressions of the key proteins included in KIF14 and PI3K-AKT-mTOR signaling pathways before and after RCN1 knockout.
Results: RCN1 expression is elevated in patients with lymph node metastases and recurrent cervical cancer and correlates with poor prognosis. Knockdown and overexpression assays revealed that RCN1 promotes proliferation, migration and invasion of cervical cancer cells. RCN1 overexpression encourages metastasis in a mouse xenograft model. Furthermore, RCN1 targets KIF14, an activator of AKT, thus providing a molecular basis that could explain the malignant behavior of RCN1-expressing cervical cancer.
Conclusion: RCN1 is significantly expressed in cervical cancer, which is associated with a poor prognosis, spread and recurrence. By promoting KIF14-induced activation of the PI3K-AKT-mTOR pathway, RCN1 may facilitate the malignant development of cervical cancer.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12415097 | PMC |
http://dx.doi.org/10.2147/IJGM.S531003 | DOI Listing |
Cancer Causes Control
September 2025
College of Public Health, Iowa Cancer Registry, Epidemiology Department, University of Iowa, Iowa City, IA, USA.
Purpose: Human papillomavirus (HPV) causes oral and anogenital cancers, the incidence of which is increasing. Late-stage diagnosis is associated with increased mortality. Neighborhood-level characteristics and distance to place of diagnosis may impact timely diagnosis.
View Article and Find Full Text PDFJpn J Clin Oncol
September 2025
International Health Program, National Yang Ming Chiao Tung University, No. 155, Sec. 2, Linong St., Beitou Dist., Taipei City 112, Taipei, Taiwan.
Objectives: Treatment delay can adversely affect cancer prognosis and public health. However, previous studies have not examined the association between cancer treatment delay and 5-year mortality risk for various cancer types in a single study population.
Methods: We used retrospective cohort data from 21 740 patients diagnosed with common cancers between 2000 and 2017, with mortality follow-up to 2022, from the Philippines' Department of Health-Rizal Cancer Registry to understand how treatment delay of <30, 30-90, or >90 days was associated with 5-year all-cause mortality risk, by cancer type and stage at diagnosis.
Int J Gen Med
September 2025
Suzhou Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Purpose: The fourth most common cause of cancer-related deaths in women is cervical cancer. Though treatment of early-stage cervical cancer is often effective, middle and advanced stage cervical cancer is hard to treat and prone to recurrence. We sought to explore the mechanism underlying cervical cancer progression to identify new therapeutic approaches.
View Article and Find Full Text PDFFront Immunol
September 2025
Department of Medicine, Division of Hematology, Bioclinicum and Center for Molecular Medicine, Karolinska Institute and Karolinska University Hospital Solna, Stockholm, Sweden.
Background: Metabolic reprogramming is an important hallmark of cervical cancer (CC), and extensive studies have provided important information for translational and clinical oncology. Here we sought to determine metabolic association with molecular aberrations, telomere maintenance and outcomes in CC.
Methods: RNA sequencing data from TCGA cohort of CC was analyzed for their metabolic gene expression profile and consensus clustering was then performed to classify tumors into different groups/subtypes.