Evidence map›Paper›PMID 33042464›Full record

ArticleAmerican journal of translational research2020

Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer.

Rui Li, Xiao Liu, Xi-Jia Zhou, Xiao Chen, Jian-Ping Li, Yun-Hong Yin, Yi-Qing Qu

Abstract read
In one paragraph

Article in American journal of translational research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

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

26 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

7 authors.

Rui LiDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University Jinan 250012, China.
Xiao LiuDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University Jinan 250012, China.
Xi-Jia ZhouDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University Jinan 250012, China.
Xiao ChenDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University Jinan 250012, China.
Jian-Ping LiDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University Jinan 250012, China.
Yun-Hong YinDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University Jinan 250012, China.
Yi-Qing QuDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University Jinan 250012, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The aim of this research study was to identify differentially expressed immune-related genes (DEIRGs) and establish a Cox prediction model for the evaluation of prognosis in patients with non-small cell lung cancer (NSCLC). Transcription expression data, immune gene data, and tumor transcription factor data from The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and the Cistrome Cancer database were analyzed to detect differentially expressed genes (DEGs), DEIRGs, and differentially expressed transcription factors (DETFs). Multivariate Cox regression analysis was used to obtain potential DEIRGs as independent prognostic factors. Oncomine, The Human Protein Atlas (HPA), TIMER databases were performed to validate the mRNA and protein expression level of DEIRGs. TIMER database was performed to explore the immunocytes infiltration of DEIRGs. In total, 7448 DEGs, 536 DEIRGs, 87 DETFs were identified from 1,037 NSCLC tissues and 108 normal tissues in TCGA database. Fifteen-DEIRG signatures (THBS1, S100P, S100A16, DLL4, CD70, DKK1, IL33, NRTN, PDGFB, STC2, VGF, GCGR, HTR3A, LGR4, SHC3) could be perceived as independent prognostic factors for predicting the overall survival of patients with NSCLC (P = 4.89e--09). Immune cell correlation analysis showed that neutrophils and b cells were positively and negatively correlated with the riskscore of the prediction model, respectively. Our study identified a Cox prediction model based on DEIRGs to predict the overall survival of patients with NSCLC. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the NSCLC immune microenvironment.

Indexed as

immune-related genesNon-small cell lung canceroverall survivalprognostic biomarkerstranscription factorstumor immune microenvironment

Identifiers

PMID33042464
PMCPMC7540139

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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.