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Journal of Cancer Research and Clinical Oncology

Erschienen in:

30.08.2023 | Research

Selenium metabolism heterogeneity in pan-cancer: insights from bulk and single-cell RNA sequencing

verfasst von: Xiaorui Fu, Yiqi Deng, Heng Xu, Yang Shu, Hai-Ning Chen

Erschienen in: Journal of Cancer Research and Clinical Oncology | Ausgabe 17/2023

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Abstract

Background

Selenium, a natural microelement with both nutritional and toxicological properties, is intertwined with tumorigenesis and progression. However, it is not fully understood how selenium metabolism affects immune response and cancer biology.

Methods

We estimated selenium metabolism by Gene Set Enrichment Analysis (GSEA) to delineate the selenium metabolism landscape using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and a integrated pan-cancer single-cell dataset. We systematically explored the prognostic implications of selenium metabolism and selenium-related regulatory patterns. The therapeutic value of selenium metabolism was explored through machine learning and examined in several immunotherapy cohorts. The heterogeneity and underlying mechanism of selenium metabolism were investigated by cell‒cell communication analysis at the single-cell level.

Results

A GSEA analysis based on 86 genes was used to evaluate the selenium metabolism landscape. The selenium metabolism score exhibited prognostic value in predicting the lower risk of mortality, possibly due to its correlation with multiple cancer hallmarks, including a positive correlation with complement (R = 0.761, P < 0.001), inflammatory response (R = 0.663, P < 0.001), apoptosis (R = 0.626, P < 0.001), hypoxia (R = 0.587, P < 0.001), reactive oxygen species (ROS) (R = 0.558, P < 0.001), and interferon gamma response (R = 0.539, P < 0.001). We also observed heterogeneity in the relationship between selenium metabolism and immunity across different cancers. Based on selenium-related genes, we constructed a machine learning model with area under the ROC curve (AUC) of 0.82 in predicting immune checkpoint inhibitor (ICI)-based immunotherapy response. Single-cell selenium metabolism quantification revealed that adjacent and tumor tissues had higher selenium metabolism compared with normal tissues, especially in epithelial cells, fibroblasts and macrophages. The communication between high-selenium epithelium and high-selenium fibroblast was significantly higher than other cells, especially in cytokines, chemokines, collagen, Wnt, VEGF, IGF and FGF pathways.

Conclusion

Our study provides a comprehensive landscape of selenium metabolism levels and diverse regulatory patterns in different cancers, deepening the understanding of selenium’s roles in tumorigenesis and immunity.

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Titel: Selenium metabolism heterogeneity in pan-cancer: insights from bulk and single-cell RNA sequencing
verfasst von: Xiaorui Fu
Yiqi Deng
Heng Xu
Yang Shu
Hai-Ning Chen
Publikationsdatum: 30.08.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Cancer Research and Clinical Oncology / Ausgabe 17/2023
Print ISSN: 0171-5216
Elektronische ISSN: 1432-1335
DOI: https://doi.org/10.1007/s00432-023-05333-6

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Selenium metabolism heterogeneity in pan-cancer: insights from bulk and single-cell RNA sequencing

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Conclusion

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