Unveiling the prognostic and therapeutic landscape of the zinc transporter protein SLC39A family in colorectal cancer through multi-omics and machine learning approaches

Colorectal cancer (CRC) remains a significant global health challenge due to its high prevalence and mortality rates. Zinc transporter proteins of the SLC39A family are crucial mediators of metal ion transport and have been implicated in numerous diseases, including cancer. However, the specific molecular mechanisms underpinning their impact on CRC progression remain poorly understood. By analyzing thousands of CRC patient samples from large-scale public databases, we constructed a SLC39A family-related signature (SFRS) for prognostic prediction through the integration of 101 combinations of 10 machine learning algorithms. This model was utilized to explore tumor biology, immune microenvironment composition, mutation patterns, and responses to immunotherapy in CRC patients. To reinforce these findings, immunohistochemistry (IHC) analyses were conducted on our in-house cohort (RJ-TMA-Cohort) to examine expression levels of two key molecules, SLC39A8 and SLC39A14, and their associations with CRC progression. The SFRS model demonstrated excellent predictive performance, effectively stratifying CRC patients based on tumor characteristics, immune microenvironment, mutation features, and immunotherapy responses. Moreover, IHC and bioinformatic analyses revealed that SLC39A8 and SLC39A14 expression levels are closely associated with CRC progression, emphasizing their potential roles in tumor microenvironment regulation and their value as biomarkers and therapeutic targets. This study is the first to comprehensively investigate the functions of the SLC39A family in CRC, offering novel insights into their roles in tumor development, prognosis, and potential relevance to immunotherapy response. The SFRS model represents a powerful tool for clinical applications, while SLC39A8 and SLC39A14 present promising avenues for future research and therapeutic strategies.

Authors

Institutions

Publication Details

Journal
Clinical and Experimental Medicine
Published
2026-03-21
DOI
https://doi.org/10.1007/s10238-025-01996-2
Primary Topic
Trace Elements in Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unveiling the prognostic and therapeutic landscape of the zinc transporter protein SLC39A family in colorectal cancer through multi-omics and machine learning approaches

Qianru Yu, Haizhen Chen, Huang Zheng, Tingyan Lu et al.
Clinical and Experimental Medicine
Trace Elements in Health
article

Unveiling the prognostic and therapeutic landscape of the zinc transporter protein SLC39A family in colorectal cancer through multi-omics and machine learning approaches

Qianru Yu, Haizhen Chen, Huang Zheng, Tingyan Lu, Jie Chen, Chi Chen, Jin Zhou, Xinhao Zhu, Jiasheng Zong, Yanfei Shao, Minhua Zheng, Jing Sun
article en

Abstract

Colorectal cancer (CRC) remains a significant global health challenge due to its high prevalence and mortality rates. Zinc transporter proteins of the SLC39A family are crucial mediators of metal ion transport and have been implicated in numerous diseases, including cancer. However, the specific molecular mechanisms underpinning their impact on CRC progression remain poorly understood. By analyzing thousands of CRC patient samples from large-scale public databases, we constructed a SLC39A family-related signature (SFRS) for prognostic prediction through the integration of 101 combinations of 10 machine learning algorithms. This model was utilized to explore tumor biology, immune microenvironment composition, mutation patterns, and responses to immunotherapy in CRC patients. To reinforce these findings, immunohistochemistry (IHC) analyses were conducted on our in-house cohort (RJ-TMA-Cohort) to examine expression levels of two key molecules, SLC39A8 and SLC39A14, and their associations with CRC progression. The SFRS model demonstrated excellent predictive performance, effectively stratifying CRC patients based on tumor characteristics, immune microenvironment, mutation features, and immunotherapy responses. Moreover, IHC and bioinformatic analyses revealed that SLC39A8 and SLC39A14 expression levels are closely associated with CRC progression, emphasizing their potential roles in tumor microenvironment regulation and their value as biomarkers and therapeutic targets. This study is the first to comprehensively investigate the functions of the SLC39A family in CRC, offering novel insights into their roles in tumor development, prognosis, and potential relevance to immunotherapy response. The SFRS model represents a powerful tool for clinical applications, while SLC39A8 and SLC39A14 present promising avenues for future research and therapeutic strategies.

Clinical and Experimental Medicine
Shanghai Jiao Tong University (CN), Ruijin Hospital (CN)
Good health and well-being
Openalex Percentile: Top 14%
Trace Elements in Health
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.