Evidence map›Paper›PMID 35284124›Full record

ArticleJournal of gastrointestinal oncology2022

Identification of lncRNAs based on different patterns of immune infiltration in gastric cancer.

Shujia Chen, Xinyu Ben, Lianyi Guo, Xiaofei Li

Open access · diamondAbstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2022. 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
0.9field-weighted citation impact, top 29% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Shujia Chen *Department of Gastroenterology, the First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China.
Xinyu Ben *Key Laboratory of Brain Science Research and Transformation in Tropical Environment of Hainan Province & Laboratory of Neurology, the First Affiliated Hospital, Hainan Medical University, Haikou, China.
Lianyi GuoDepartment of Gastroenterology, the First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China.
Xiaofei LiDepartment of Gastroenterology, the First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China.
Jinzhou Medical University · CNHainan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gastric cancer is one of the most common malignant tumors in the world, which brings great challenges to people's life and health. The purpose of this study was to investigate immune related-lncRNAs and identify new biomarkers for the prognosis of gastric cancer (GC). Methods: We downloaded data from The Cancer Genome Atlas (TCGA) and used R software to determine the ESTIMATEScore, ImmuneScore, and StromalScore of each tumor sample. We performed prognostic analysis and identified the differentially expressed lnRNAs, which were then used to construct a prognostic model. Among the 44 hub genes in the competitive endogenous RNA (ceRNA) network, 3 differentially expressed genes were verified by qPCR. Results: Based on the degree of immune infiltration, cluster A had a higher ESTIMATEScore, ImmuneScore, and StromalScore and higher expression levels of Conclusions: We identified a risk score of 19 lncRNAs as a prognostic marker of GC. There was a relationship between these 19 prognostic-related lncRNAs and the subtypes of infiltrating immune cells. An approach for predicting the prognosis of GC was therefore provided in this study.

Indexed as

Gastric cancer (GC)immune infiltrationThe Cancer Genome Atlas (TCGA)

Identifiers

PMID35284124
PMCPMC8899746
OpenAlexW4213146789

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.