Evidence map›Paper›PMID 37648807›Full record

ArticleJournal of cancer research and clinical oncology2023

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

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

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Xiaorui Fu *Department of General Surgery, Colorectal Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Yiqi Deng *Department of General Surgery, Colorectal Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Heng XuState Key Laboratory of Biotherapy, Department of Biotherapy and Cancer Center, West China Hospital, Chengdu, China.
Yang ShuDepartment of General Surgery, Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, China. shuyang1986@gmail.com.
Hai-Ning ChenDepartment of General Surgery, Colorectal Cancer Center, West China Hospital, Sichuan University, Chengdu, China. hnchen@scu.edu.cn.
Sichuan University · CNState Key Laboratory of Biotherapy

Funding

National Natural Science Foundation of China 82073246Sichuan Province Science and Technology Support Program 2022JDRC0049Sichuan Province Science and Technology Support Program 2022YFS0202
6 · The paper itself

Abstract

backgroundSelenium, 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.

methodsWe 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.

resultsA 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.

conclusionOur 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.

Indexed as

NeoplasmsSeleniumApoptosisCarcinogenesisHumansSequence Analysis, RNASeleniumImmunotherapyMachine learningPan-cancerSelenium metabolismSingle-cell sequencing

Identifiers

PMID37648807
PMCPMC11797634
OpenAlexW4386283093

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.