Evidence map›Paper›PMID 30959550›Full record

ArticleMolecular oncology2019

Identification of lncRNAs associated with early-stage breast cancer and their prognostic implications.

Arunagiri Kuha Deva Magendhra Rao, Krishna Patel, Suneetha Korivi Jyothiraj, Balaiah Meenakumari, Shirley Sundersingh, Velusami Sridevi, Thangarajan Rajkumar, Akhilesh Pandey, Aditi Chatterjee, Harsha Gowda and 1 more

Abstract read
In one paragraph

Article in Molecular oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. MicroRNA Expression Profile in Early-Stage Breast Cancers.MicroRNA (Shariqah, United Arab Emirates) · 2024
    Article
  5. Article
  6. Article
  7. Expression profiling of luminal B breast tumor in Indian women.Journal of cancer research and clinical oncology · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

11 authors.

Arunagiri Kuha Deva Magendhra RaoDepartment of Molecular Oncology, Cancer Institute (WIA), Chennai, India.
Krishna PatelInstitute of Bioinformatics, Bangalore, India.ORCID 0000-0002-4986-0955
Suneetha Korivi JyothirajDepartment of Molecular Oncology, Cancer Institute (WIA), Chennai, India.
Balaiah MeenakumariDepartment of Molecular Oncology, Cancer Institute (WIA), Chennai, India.
Shirley SundersinghDepartment of Oncopathology, Cancer Institute (WIA), Chennai, India.
Velusami SrideviDepartment of Surgical Oncology, Cancer Institute (WIA), Chennai, India.
Thangarajan RajkumarDepartment of Molecular Oncology, Cancer Institute (WIA), Chennai, India.
Akhilesh PandeyInstitute of Bioinformatics, Bangalore, India.
Aditi ChatterjeeInstitute of Bioinformatics, Bangalore, India.
Harsha GowdaInstitute of Bioinformatics, Bangalore, India.
Samson ManiDepartment of Molecular Oncology, Cancer Institute (WIA), Chennai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most common malignancy among women, with the highest incidence rate worldwide. Dysregulation of long noncoding RNAs during the preliminary stages of breast carcinogenesis is poorly understood. In this study, we performed RNA sequencing to identify long noncoding RNA expression profiles associated with early-stage breast cancer. RNA sequencing was performed on six invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, seven ductal carcinoma in situ tissues, and five apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts (~ 58%) were the largest subtype among DElncRNAs. About 20% of the 375 DElncRNAs were supported by typical split readings leveraging their detection confidence. Validation was performed in n = 52 IDC and paired normal tissue by qRT-PCR for the identified targets (ADAMTS9-AS2, EPB41L4A-AS1, WDFY3-AS2, RP11-295M3.4, RP11-161M6.2, RP11-490M8.1, CTB-92J24.3, and FAM83H-AS1). We evaluated the prognostic significance of DElncRNAs based on TCGA datasets and report that overexpression of FAM83H-AS1 was associated with patient poor survival. We confirmed that the downregulation of ADAMTS9-AS2 in breast cancer was due to promoter hypermethylation through in vitro silencing experiments and pyrosequencing.

Indexed as

Biomarkers, TumorBreast NeoplasmsFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisRNA, Long NoncodingSequence Analysis, RNABiomarkers, TumorRNA, Long NoncodingADAMTS9-AS2breast cancerFAM83H-AS1long noncoding RNAsncRNAsRNA sequencing

Identifiers

PMID30959550
PMCPMC6547626

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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.