Evidence map›Paper›PMID 34894405›Full record

ArticleJournal of clinical laboratory analysis2022

Development of a novel five-lncRNA prognostic signature for predicting overall survival in elderly patients with breast cancer.

Yang Luo, Yue Zhang, Yu-Xin Wu, Han-Bing Li, Di Shen, Yi-Qun Che

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

6 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. ST8SIA6-AS1, a novel lncRNA star in liver cancer.Frontiers in cell and developmental biology · 2024
    Review
  5. Article
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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

6 authors at 2 institutions in 1 country.

Yang LuoDepartment of Medical Oncology, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yue ZhangDepartment of Clinical Laboratory, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0003-4597-9964
Yu-Xin WuDepartment of Clinical Laboratory, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Han-Bing LiDepartment of Clinical Laboratory, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Di ShenDepartment of Clinical Laboratory, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yi-Qun CheCenter for Clinical Laboratory, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNCapital Medical University · CN

Funding

Beijing Municipal Natural Science Foundation 7162164Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2017-I2 M-1-013Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2017-I2 M-3-012National Natural Science Foundation of China 81972016
6 · The paper itself

Abstract

backgroundBreast cancer (BC) is an age-related disease. Long noncoding RNAs (lncRNAs) have been proven to be crucial contributors in tumorigenesis. This study aims to develop a novel lncRNA-based signature to predict elderly BC patients' prognosis.

methodsThe RNA expression profiles and corresponding clinical information of 182 elderly BC patients were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) between BC and adjacent normal samples were used to construct the signature in the training set through univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the predictive performance. Besides, we developed the nomogram. Gene set enrichment analysis (GSEA) was performed to reveal the underlying molecular mechanisms.

resultsWe constructed the five-lncRNA signature (including LEF1-AS1, MEF2C-AS1, ST8SIA6-AS1, LINC01224, and LINC02408) in the training set, which successfully divided the patients into low- and high-risk groups with significantly different prognosis (p = 0.000049), and the AUC at 3 and 5 years of the signature was 0.779 and 0.788, respectively. The predictive performance of this signature was validated in the test and entire set. The 5-lncRNA signature was an independent prognostic factor of OS (p = 0.007) and the nomogram constructed by independent prognostic factors was an accurate predictor of predicting overall survival probability. Besides, several pathways associated with tumorigenesis have been identified by GSEA.

conclusionsThe 5-lncRNA signature and nomogram are reliable in predicting elderly BC patients' prognosis and provide clues for clinical decision-making.

Indexed as

Breast NeoplasmsAgedFemaleHumansNomogramsPrognosisRNA, Long NoncodingTranscriptomeRNA, Long Noncodingelderly breast cancerlncRNAprognosissignature

Identifiers

PMID34894405
PMCPMC8761441
OpenAlexW4200577861

What OpenQuestion holds

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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.