Evidence map›Paper›PMID 34222425›Full record

ArticleWorld journal of clinical cases2021

Evaluation of a five-gene signature associated with stromal infiltration for diffuse large B-cell lymphoma.

Ying-Yu Nan, Wen-Jun Zhang, De-Hong Huang, Qi-Ying Li, Yang Shi, Tao Yang, Xi-Ping Liang, Chun-Yan Xiao, Bing-Ling Guo, Ying Xiang

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2021. 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 53% 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, 2 citations in OpenAlex.

  1. Review
  2. Spatial transcriptomics reveals prognostically LYZCancer immunology, immunotherapy : CII · 2025
    Article
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

10 authors at 1 institution in 1 country.

Ying-Yu NanDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Wen-Jun ZhangDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
De-Hong HuangDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Qi-Ying LiDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Yang ShiDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Tao YangDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Xi-Ping LiangDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Chun-Yan XiaoDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Bing-Ling GuoDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Ying XiangDepartment of Hematology, Chongqing University Cancer Hospital, Chongqing 400030, China. xiangying0331@163.com.
Chongqing Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiffuse large B-cell lymphoma (DLBCL) is a common non-Hodgkin lymphoma. The development of immunotherapy greatly improves the patient prognosis but there are some exceptions. Thus, screening for better biomarkers for prognostic evaluation could contribute to the treatment of DLBCL patients.

aimTo screen the novel mediators involved in the development of DLBCL.

methodsThe GSE60 dataset was applied to identify the differentially expressed genes (DEGs) in DLBCL, and the principal components analysis plot was used to determine the quality of the included samples. The protein-protein interactions were analyzed by the STRING tool. The key hub genes were entered into to the GEPIA database to determine their expressions in DLBCL. Furthermore, these hub gene alterations were analyzed in cBioportal. The UALCAN portal was employed to analyze the expression of the hub genes in different stages of DLBCL. The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data Score was conducted to evaluate the correlation between the gene expression and tumor purity. The gene-gene correlation analysis was conducted in the GEPIA. The stromal score analysis was conducted in TIMER to confirm the correlation between the gene expression and infiltrated stromal cells. The correlation between the indicated genes and infiltration level of cancer-associated fibroblasts (CAFs) was also completed in TIMER with two methods, MCP-Counter and Tumor immune dysfunction and exclusion. The correlation between fibronectin (FN1) protein level and secreted protein acidic and cysteine-rich (SPARC) messenger ribonucleic acid expression was confirmed in the cBioportal.

resultsThe top 20 DEGs in DLBCL were identified, and the principal components analysis plot confirmed the quality of the significant DEGs. The pairwise correlation coefficient analysis among all samples showed that these DEGs have a certain co-expression pattern. The DEGs were subjected to STRING to identify the hub genes, alpha-2-macroglobulin (

conclusionThe top DEGs were identified, and the five hub genes were overexpressed in DLBCL. Furthermore, the gene alterations were confirmed and the positive correlation with tumor purity revealed the overexpression of the five genes and close association with the development of DLBCL. More interestingly, the five genes were positively correlated with stromal infiltration, especially in CAFs. The top two genes,

Indexed as

Cancer-associated fibroblastsCo-expressionDiffuse large B-cell lymphomaOverexpressionStromal scoreTherapeutic target

Identifiers

PMID34222425
PMCPMC8223837
OpenAlexW3167193091

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.