Evidence map›Paper›PMID 35035517›Full record

ArticleComputational and mathematical methods in medicine2022

Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response.

Bin-Bin Da, Shuai Luo, Ming Huang, Fei Song, Rong Ding, Yao Xiao, Yang Fu, Yin-Shan Yang, Hai-Lei Wang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Bin-Bin Da *Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
Shuai Luo *Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
Ming HuangDepartment of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
Fei SongDepartment of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
Rong DingDepartment of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
Yao XiaoDepartment of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
Yang FuCT Room, Kunming First People's Hospital, Kunming 650000, China.
Yin-Shan YangDepartment of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.ORCID https://orcid.org/0000-0001-6118-6839
Hai-Lei WangHepatobiliary Pancreatic Vascular Surgery, Kunming First People's Hospital, Kunming 650031, China.ORCID https://orcid.org/0000-0002-5510-5040
The First Hospital of Kunming · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularComputational BiologyGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansInflammationKaplan-Meier EstimateLiver NeoplasmsLymphocytes, Tumor-InfiltratingPrognosisProportional Hazards ModelsTumor MicroenvironmentBiomarkers, Tumor

Identifiers

PMID35035517
PMCPMC8759924
OpenAlexW4205561214

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.