Evidence map›Paper›PMID 35282059›Full record

ArticleAnnals of translational medicine2022

Autophagy related long non-coding RNA and breast cancer prognosis analysis and prognostic risk model establishment.

Zhizhai Luo, Binbin Nong, Yanfei Ma, Dalang Fang

Abstract read
In one paragraph

Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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  9. Characteristics of mJournal of Cancer · 2023
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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.

Zhizhai Luo *Department of Breast and Thyroid Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Binbin Nong *Department of Gynecology and Obstetrics, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Yanfei MaDepartment of Breast and Thyroid Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Dalang FangDepartment of Breast and Thyroid Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The role of autophagy-related long-stranded non-coding RNA (lncRNA) in breast cancer (BRCA) is unclear. We proposed to screen autophagy-related lncRNAs in BRCA and construct a prognostic risk assessment model to explore prognostic correlates. Methods: We extracted BRCA lncRNAs from The Cancer Genome Atlas (TCGA) database and autophagy-related genes from the Human Autophagy Database (HADb), to screen for autophagy-related lncRNA pairs (ARLP) in BRCA. Single-factor Cox regression analysis and multi-factor Cox regression analysis were used to screen lncRNAs associated with BRCA prognosis, and risk models were established. We divided BRCA patients into high-risk and low-risk groups based on median risk scores. The single-sample gene set enrichment analysis (ssGSEA) algorithm was used to calculate the abundance of 28 immune cells in the TCGA-BRCA cohort and to analyze the relationship between the risk score and the level of immune cell infiltration by ARLP characteristics. Results: Univariate Cox regression results showed that 42 ARLPs were significantly associated with overall survival (OS) in BRCA patients. Further multifactorial analysis showed that a total of 11 lncRNAs, including Conclusions: Our study suggested that a risk model consisting of 11 autophagy-related lncRNAs can be used to assess the prognosis of BRCA patients.

Indexed as

autophagy-related lncRNAs (arlncRNAs)bioinformatics analysisBreast cancer (BRCA)

Identifiers

PMID35282059
PMCPMC8848359

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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.