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Research Domains Biomedical and Clinical Sciences Oncology and Carcinogenesis Predictive and prognostic markers
Research Domains
Biomedical and Clinical Sciences
Oncology and Carcinogenesis
Predictive and prognostic markers
A novel defined manganese metabolism-related gene signature for predicting the prognosis of pancreatic ductal adenocarcinoma

A novel defined manganese metabolism-related gene signature for predicting the prognosis of pancreatic ductal adenocarcinoma

Zichao Xiong ^1,2,3, Zhen Zhang ^2,4, Shaodan Cheng ^1,3, Shaohua Liao ^1,3

Zichao Xiong ^1,2,3, Zhen Zhang ^2,4, Shaodan Cheng ^1,3

¹Department of Rehabilitation, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200050, P.R. China.
²Department of Rehabilitation, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, P.R. China.
³Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai 200052, P.R. China.
⁴Department of Neurosurgery, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, P.R. China.

⁰Department of Rehabilitation, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200050, P.R. China.

Oncology Letters +

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July 23, 2025

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July 23, 2025

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View abstract on PubMed

Summary

This summary is machine-generated.

This study identified 12 key genes linked to manganese metabolism that can predict outcomes in pancreatic ductal adenocarcinoma (PDAC). These novel biomarkers offer potential for improved PDAC prognosis and targeted therapies.

Area Of Science

Oncology
Bioinformatics
Molecular Biology

Background

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis and limited treatment options.
Understanding the molecular mechanisms driving PDAC is crucial for developing effective therapies.

Purpose Of The Study

To identify novel biomarkers associated with manganese metabolism for predicting PDAC patient outcomes.
To leverage bioinformatics to analyze transcriptomic data for prognostic markers.

Main Methods

Analysis of transcriptomic data from The Cancer Genome Atlas and Gene Expression Omnibus.
Application of differential expression analysis, LASSO regression, and multivariable Cox regression.
Validation of identified genes using training and external datasets (GSE62452, GSE28735).

Main Results

Twelve essential genes related to manganese metabolism were identified as significantly associated with PDAC prognosis.
The prognostic model demonstrated high accuracy with AUC values of 0.82 (training) and 0.83 (external validation).
The identified genes provide insights into the molecular processes and manganese metabolism in PDAC development.

Conclusions

The identified 12 genes serve as robust prognostic biomarkers for pancreatic ductal adenocarcinoma.
Manganese metabolism plays a critical role in PDAC development.
These biomarkers may guide the development of targeted therapeutic strategies for PDAC.

Keywords:

bioinformatics gene signature manganese metabolism pancreatic ductal adenocarcinoma prognosis

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