Evidence map›Paper›PMID 39126025›Full record

ArticleInternational journal of molecular sciences2024

Comprehensive Transcriptome Analysis Expands lncRNA Functional Profiles in Breast Cancer.

Wenyong Zhu, Hao Huang, Zixi Hu, Yu Gu, Rongxin Zhang, Huiling Shu, Hongjia Liu, Xiao Sun

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Wenyong ZhuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Hao HuangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Zixi HuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Yu GuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Rongxin ZhangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Huiling ShuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Hongjia LiuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Xiao SunState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0003-1048-7775

Funding

Natural Science Foundation of Jiangsu Province BK20220823the Leading Technology Program of Jiangsu Province BK20222008
6 · The paper itself

Abstract

Breast cancer is a heterogeneous disease that arises as a multi-stage process involving multiple cell types. Patients diagnosed with the same clinical stage and pathological classification may have different prognoses and therapeutic responses due to alterations in molecular genetics. As an essential marker for the molecular subtyping of breast cancer, long non-coding RNAs (lncRNAs) play a crucial role in gene expression regulation, cell differentiation, and the maintenance of genomic stability. Here, we developed a modular framework for lncRNA identification and applied it to a breast cancer cohort to identify novel lncRNAs not previously annotated. To investigate the potential biological function, regulatory mechanisms, and clinical relevance of the novel lncRNAs, we elucidated the genomic and chromatin features of these lncRNAs, along with the associated protein-coding genes and putative enhancers involved in the breast cancer regulatory networks. Furthermore, we uncovered that the expression patterns of novel and annotated lncRNAs identified in breast cancer were related to the hormone response in the PAM50 subtyping criterion, as well as the immune response and progression states of breast cancer across different immune cells and immune checkpoint genes. Collectively, the comprehensive identification and functional analysis of lncRNAs revealed that these lncRNAs play an essential role in breast cancer by altering gene expression and participating in the regulatory networks, contributing to a better insight into breast cancer heterogeneity and potential avenues for therapeutic intervention.

Indexed as

Breast NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksRNA, Long NoncodingBiomarkers, TumorFemaleHumansPrognosisTranscriptomeBiomarkers, TumorRNA, Long Noncodingfunctional genomelong non-coding RNAmolecular subtyping of breast cancer

Identifiers

PMID39126025
PMCPMC11313538

What OpenQuestion holds

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LicenceCC BY
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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.