Evidence map›Paper›PMID 33024415›Full record

ArticleCancer cell international2020

Integrated analysis of immune-related genes in endometrial carcinoma.

Yiru Wang, Yunduo Liu, Yue Guan, Hao Li, Yuan Liu, Mengjun Zhang, Ping Cui, Dan Kong, Xiuwei Chen, Hang Yin

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

9 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

10 authors at 1 institution in 1 country.

Yiru Wang *The Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.
Yunduo Liu *The Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.
Yue GuanThe Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.
Hao LiThe Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.
Yuan LiuThe Department of Radiotherapy Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang China.
Mengjun ZhangThe Department of Radiotherapy Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang China.
Ping CuiThe Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.
Dan KongThe Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.
Xiuwei ChenThe Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin, 150040 Heilongjiang China.ORCID 0000-0002-5771-6662
Hang YinThe Department of Radiotherapy Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis.

methodsTranscription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan-Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results.

resultsA network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan-Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma and in cells.

conclusionsOverall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.

Indexed as

BiomarkersEndometrial cancerImmuneLong non-coding RNAThe cancer genome atlasTranscription factor

Identifiers

PMID33024415
PMCPMC7531161
OpenAlexW3090628506

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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.