Elevated ITGA3 expression serves as a novel prognostic biomarker and regulates tumor progression in cervical cancer

Patients with advanced and recurrent cervical cancer often lack satisfactory treatment outcomes. Thus, it is necessary to seek reliable biomarkers that provide the ability to identify the disease at an early stage and predict the patient prognosis, providing new strategies for the treatment of cervical cancer. The sequencing data of ITGA3 were retrieved from public datasets. Immune infiltration and sensitivity of potential immunotherapy and chemotherapy have been analyzed between two subgroups. Functional analysis was applied to excavate the related pathways of ITGA3 in cervical cancer. Furthermore, the impact of ITGA3 in tumor progression has been verified in vitro. The results revealed that the level of ITGA3 was upregulated in cervical cancer, and was positively correlated with worse prognosis. The tumor microenvironment of patients in the high-risk group was immunosuppressed. Patients in high-risk group may not benefit from immunotherapy, but be may be sensitive to several chemotherapy drugs. Notably, the angiogenesis, epithelial mesenchymal transition, and PI3K pathway were increased in high-risk group. Collectively, ITGA3 is a marker of poor prognosis and promotes tumor progression by regulating PI3K/AKT pathway in cervical cancer. Our results provide new insights for potential molecular targeted therapy and prognostic prediction of cervical cancer.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-11-07
DOI
https://doi.org/10.1038/s41598-024-75770-x
Citations
9
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
2.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Elevated ITGA3 expression serves as a novel prognostic biomarker and regulates tumor progression in cervical cancer

Gantao Chen, Ran Gu, Wei Tan, Yanxiang Cheng et al.
9 citations
Scientific Reports
Cancer Immunotherapy and Biomarkers
2.54
article

Elevated ITGA3 expression serves as a novel prognostic biomarker and regulates tumor progression in cervical cancer

Gantao Chen, Ran Gu, Wei Tan, Yanxiang Cheng, Hua Liu, Dongyong Yang, Fangfang Dai, Zhimin Deng, Qinyu Ci
article en
9 citations

Abstract

Patients with advanced and recurrent cervical cancer often lack satisfactory treatment outcomes. Thus, it is necessary to seek reliable biomarkers that provide the ability to identify the disease at an early stage and predict the patient prognosis, providing new strategies for the treatment of cervical cancer. The sequencing data of ITGA3 were retrieved from public datasets. Immune infiltration and sensitivity of potential immunotherapy and chemotherapy have been analyzed between two subgroups. Functional analysis was applied to excavate the related pathways of ITGA3 in cervical cancer. Furthermore, the impact of ITGA3 in tumor progression has been verified in vitro. The results revealed that the level of ITGA3 was upregulated in cervical cancer, and was positively correlated with worse prognosis. The tumor microenvironment of patients in the high-risk group was immunosuppressed. Patients in high-risk group may not benefit from immunotherapy, but be may be sensitive to several chemotherapy drugs. Notably, the angiogenesis, epithelial mesenchymal transition, and PI3K pathway were increased in high-risk group. Collectively, ITGA3 is a marker of poor prognosis and promotes tumor progression by regulating PI3K/AKT pathway in cervical cancer. Our results provide new insights for potential molecular targeted therapy and prognostic prediction of cervical cancer.

Scientific ReportsVol. 14(1)
Wuhan University (CN), Renmin Hospital of Wuhan University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province, Wuhan University, Renmin Hospital of Wuhan University, Division of Undergraduate Education
Good health and well-being
Openalex Percentile: Top 8%
Cancer Immunotherapy and Biomarkers
2.54
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.