Evidence map›Paper›PMID 37980291›Full record

ArticleDiscover oncology2023

Novel diagnostic biomarkers of oxidative stress, immune- infiltration characteristics and experimental validation of SERPINE1 in colon cancer.

Kaisheng Yuan, Di Hu, Xiaocong Mo, Ruiqi Zeng, Bing Wu, Zunhao Zhang, Ruixiang Hu, Cunchuan Wang

Abstract read
In one paragraph

Article in Discover oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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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

8 authors.

Kaisheng Yuan *Department of Metabolic and Bariatric Surgery, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China.
Di Hu *Department of Neurology and Stroke Centre, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China.
Xiaocong Mo *Department of Oncology, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China.
Ruiqi ZengDepartment of Urology, the Second People's Hospital of Yibin City, Yibin, 644000, Sichuan, China.
Bing WuDepartment of Metabolic and Bariatric Surgery, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China.
Zunhao ZhangDepartment of Metabolic and Bariatric Surgery, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China.
Ruixiang HuDepartment of Metabolic and Bariatric Surgery, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China. huruixiang123@jnu.edu.cn.
Cunchuan WangDepartment of Metabolic and Bariatric Surgery, the First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510000, Guangdong, China. twcc@jnu.edu.cn.

Funding

the Science and Technology Projects in Guangzhou No. 202201020063
6 · The paper itself

Abstract

backgroundColon cancer (CC) is a prevalent malignant tumor that affects the colon in the gastrointestinal tract. Its aggressive nature, strong invasiveness, and rapid progression make it a significant health concern. In addition, oxidative stress can lead to the production of reactive oxygen species (ROS) that surpass the body's antioxidant defense capacity, causing damage to proteins, lipids, and DNA, potentially promoting tumor development. However, the relationship between CC and oxidative stress requires further investigation.

methodsWe collected gene expression data and clinical data from 473 CC patients from The Cancer Genome Atlas (TCGA) dataset. Additionally, we obtained 433 oxidative stress genes from Genecards ( https://www.genecards.org/ ). Using univariate, multivariate, and LASSO Cox regression analyses, we developed predictive models for oxidative stress-related genes in CC patients. To validate the models, we utilized data from the Gene Expression Omnibus (GEO) database. We assessed the accuracy of the models through various techniques, including the creation of a nomogram, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA). The Cytoscape program was utilized to identify hub genes among differentially expressed genes (DEGs) in tumor patients using the TCGA dataset. Subsequently, we conducted survival analysis, clinical relevance analysis, and immune cell relevance analysis for the intersected genes obtained by combining the hub genes with the genes from the predictive models. Moreover, we investigated the mRNA expression and potential functions of these intersected genes using a range of experimental approaches.

resultsIn both the TCGA and GSE17538 datasets, patients classified as high-risk had significantly shorter overall survival compared to those in the low-risk group (TCGA: p < 0.001; GSE17538: p = 0.010). As a result, we decided to further investigate the role of SERPINE1. Our survival analysis revealed that patients with high expression of SERPINE1 had a significantly lower probability of survival compared to those with low expression (p < 0.05). Additionally, our clinical correlation analysis showed a significant relationship between SERPINE1 expression and T, N, and M stages, as well as tumor grade. Furthermore, our immune infiltration correlation analysis demonstrated notable differences in multiple immune cells between the high- and low-expression groups of SERPINE1. To validate our findings, we conducted experimental tests and observed that knocking down SERPINE1 in colon cancer cells resulted in significant reductions in cell viability and proliferation. Interestingly, we also noticed an increase in oxidative stress parameters, such as ROS and MDA levels, while the levels of reduced GSH decreased upon SERPINE1 knockdown. These findings suggest that the antineoplastic effect of silencing SERPINE1 may be associated with the induction of oxidative stress.

conclusionIn conclusion, this study introduces a new approach for the early diagnosis and treatment of CC, and further exploration of SERPINE1 could potentially lead to a significant advancement.

Indexed as

Bioinformatics analysisColon cancerOxidative stressPrognosis modelSERPINE1

Identifiers

PMID37980291
PMCPMC10657345

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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.