Gene Mutations and Related Molecular Events in Distant Metastasis of Cervical Cancer: A Review

Cervical cancer, a serious gynecological malignancy, often leads to poor patient prognosis due to distant metastasis. The metastasis mechanism is not fully understood. This study explores the link between gene mutations and distant metastasis in cervical cancer. <i>PDGFRA</i>, <i>TP53</i>, and <i>PIK3CA</i> mutations significantly influence metastasis. Despite its low incidence, <i>PDGFRA</i> mutation is closely tied to lymph node and distant metastasis. <i>TP53</i> mutation disrupts p53 protein function, promoting tumor cell proliferation, inhibiting apoptosis, and enhancing metastasis. <i>PIK3CA</i> mutation activates the PI3K/Akt pathway, stimulating cell proliferation and migration. Detecting these mutations is crucial for diagnosing distant metastasis. It helps identify high-risk patients early, improving diagnostic accuracy and specificity, and guiding clinical treatment decisions. Targeted therapies for <i>PDGFRA</i> and <i>PIK3CA</i> mutations can control tumor growth and metastasis but face challenges like drug resistance and high costs. This study offers a new theoretical basis and treatment strategy for cervical cancer, pointing to future research directions. Gene mutation detection enhances early identification of high-risk patients, improving diagnostic accuracy. Targeted therapies for <i>PDGFRA</i> and <i>PIK3CA</i> mutations control tumor growth but face drug resistance and cost issues. This study provides a new theoretical basis and treatment strategy for cervical cancer, guiding future research.

Authors

Institutions

Publication Details

Journal
International Journal of Medical Sciences
Published
2026-02-11
DOI
https://doi.org/10.7150/ijms.123727
Primary Topic
Endometrial and Cervical Cancer Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gene Mutations and Related Molecular Events in Distant Metastasis of Cervical Cancer: A Review

Xiaolong Chang, Yinghua Guo, Tingting Liu, Na Lv et al.
International Journal of Medical Sciences
Endometrial and Cervical Cancer Treatments
article

Gene Mutations and Related Molecular Events in Distant Metastasis of Cervical Cancer: A Review

Xiaolong Chang, Yinghua Guo, Tingting Liu, Na Lv, Furong Hao, Shilong Li, Yingxiao Jiang, Peiyan Qin, Niannian Li, Nan Wang
article en

Abstract

Cervical cancer, a serious gynecological malignancy, often leads to poor patient prognosis due to distant metastasis. The metastasis mechanism is not fully understood. This study explores the link between gene mutations and distant metastasis in cervical cancer. <i>PDGFRA</i>, <i>TP53</i>, and <i>PIK3CA</i> mutations significantly influence metastasis. Despite its low incidence, <i>PDGFRA</i> mutation is closely tied to lymph node and distant metastasis. <i>TP53</i> mutation disrupts p53 protein function, promoting tumor cell proliferation, inhibiting apoptosis, and enhancing metastasis. <i>PIK3CA</i> mutation activates the PI3K/Akt pathway, stimulating cell proliferation and migration. Detecting these mutations is crucial for diagnosing distant metastasis. It helps identify high-risk patients early, improving diagnostic accuracy and specificity, and guiding clinical treatment decisions. Targeted therapies for <i>PDGFRA</i> and <i>PIK3CA</i> mutations can control tumor growth and metastasis but face challenges like drug resistance and high costs. This study offers a new theoretical basis and treatment strategy for cervical cancer, pointing to future research directions. Gene mutation detection enhances early identification of high-risk patients, improving diagnostic accuracy. Targeted therapies for <i>PDGFRA</i> and <i>PIK3CA</i> mutations control tumor growth but face drug resistance and cost issues. This study provides a new theoretical basis and treatment strategy for cervical cancer, guiding future research.

International Journal of Medical SciencesVol. 23(3)
Weifang People's Hospital (CN)
Openalex Percentile: Top 58%
Endometrial and Cervical Cancer Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.