Evidence map›Paper›PMID 36915426›Full record

ArticleJournal of gastrointestinal oncology2023

Model construction and risk analysis of the lncRNA genes associated with the prognosis of esophageal adenocarcinoma with immune infiltration.

Jun Lu, Juan Yang, Chi Ma, Xinxin Wang, Jiangyan Luo, Xiaoying Ma, Xinnian Fu, Sheng Zheng

Open access · diamondAbstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2023. 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
0.7field-weighted citation impact, top 25% 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, 3 citations in OpenAlex.

  1. Review
  2. The Expression Patterns and Implications ofInternational journal of molecular sciences · 2023
    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

8 authors at 3 institutions in 1 country.

Jun LuIntensive Care Unit, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Juan YangDepartment of Gastroenterology, The Third People's Hospital of Yunnan Province, Kunming, China.
Chi MaGraduate School of Clinical Medicine, Dali University, Dali, China.
Xinxin WangGraduate School of Clinical Medicine, Dali University, Dali, China.
Jiangyan LuoGraduate School of Clinical Medicine, Dali University, Dali, China.
Xiaoying MaGraduate School of Clinical Medicine, Dali University, Dali, China.
Xinnian FuGraduate School of Clinical Medicine, Dali University, Dali, China.
Sheng ZhengDepartment of Gastroenterology, The Third People's Hospital of Yunnan Province, Kunming, China.
Dali University · CNThird People's Hospital of Yunnan Province · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Our study analyzed the immune infiltration of esophageal adenocarcinoma (EAC) tumor cells and identified long non-coding ribonucleic acid (lncRNA) genes to construct a prognostic model of EAC to evaluate the survival prognosis of patients and explore potential therapeutic targets. Methods: The data of 89 patients with EAC, including 11 normal tissue samples and 78 EAC of tumor tissue samples, were downloaded from The Cancer Genome Atlas public database. Perl script and R software were used to run the code, conduct the statistical analysis, calculate the risk coefficients of the patients, and conduct the Cox regression analysis, immune-related lncRNA survival analysis, risk analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) curve analysis. Results: We screened and identified 19 prognostic biomarkers, including LINC01612, AC008443.2, and LINC02582, allocated the patients into high- and low-risk groups, and found significant differences in the prognosis between the high- and low-risk groups using the Kaplan-Meier survival analysis (P<0.001). A ROC curve was used to evaluate the feasibility of the prognostic model for EAC, and we found that the model had high predictability (area under the curve =0.964). A PCA analysis was performed of the complex transcriptome sequencing data and other cubes to transform the data into a 3-dimensional space constructed by feature vectors. Conclusions: Our study effectively screened and identified the lncRNA genes related to the immune infiltration of EAC and successfully constructed a prognostic model. In total, 19 potential diagnostic and therapeutic target genes, including LINC01612, AC008443.2, and LINC02582, were identified that have certain significance in guiding the clinical treatment of EAC patients.

Indexed as

Esophageal adenocarcinoma (EAC)immune infiltrationlong non-coding ribonucleic acids (lncRNAs)prognostic modelprognostic risk

Identifiers

PMID36915426
PMCPMC10007919
OpenAlexW4320185436

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.