Evidence map›Paper›PMID 35959932›Full record

ReviewWiley interdisciplinary reviews. RNA

Noncoding RNAs in oral cancer.

Jaikrishna Balakittnen, Chameera Ekanayake Weeramange, Daniel F Wallace, Pascal H G Duijf, Alexandre S Cristino, Liz Kenny, Sarju Vasani, Chamindie Punyadeera

Open access · hybridAbstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. RNA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.9field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Article
  3. Oral Cancer Prognostic Disparities among Black Individuals: A Scoping Review.Journal of racial and ethnic health disparities · 2026
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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

8 authors at 5 institutions in 4 countries.

Jaikrishna BalakittnenThe Centre for Biomedical Technologies, The School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia.ORCID 0000-0002-9882-5152
Chameera Ekanayake WeeramangeSaliva & Liquid Biopsy Translational Laboratory, Griffith Institute for Drug Discovery, Griffith University, Nathan, Queensland, Australia.ORCID 0000-0001-7384-5512
Daniel F WallaceCentre for Genomics and Personalised Health, School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID 0000-0002-6019-9424
Pascal H G DuijfCentre for Genomics and Personalised Health, School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID 0000-0001-8646-9843
Alexandre S CristinoGriffith Institute for Drug Discovery, Griffith University, Nathan, Queensland, Australia.ORCID 0000-0002-3468-0919
Liz KennyRoyal Brisbane and Women's Hospital, Cancer Care Services, Herston, Queensland, Australia.ORCID 0000-0002-7556-0542
Sarju VasaniRoyal Brisbane and Women's Hospital, Cancer Care Services, Herston, Queensland, Australia.ORCID 0000-0003-1471-9692
Chamindie PunyadeeraSaliva & Liquid Biopsy Translational Laboratory, Griffith Institute for Drug Discovery, Griffith University, Nathan, Queensland, Australia.ORCID 0000-0001-9039-8259
Griffith University · AUOslo University Hospital · NOQueensland University of Technology · AURoyal Brisbane and Women's Hospital · AUThe University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral cancer (OC) is the most prevalent subtype of cancer arising in the head and neck region. OC risk is mainly attributed to behavioral risk factors such as exposure to tobacco and excessive alcohol consumption, and a lesser extent to viral infections such as human papillomaviruses and Epstein-Barr viruses. In addition to these acquired risk factors, heritable genetic factors have shown to be associated with OC risk. Despite the high incidence, biomarkers for OC diagnosis are lacking and consequently, patients are often diagnosed in advanced stages. This delay in diagnosis is reflected by poor overall outcomes of OC patients, where 5-year overall survival is around 50%. Among the biomarkers proposed for cancer detection, noncoding RNA (ncRNA) can be considered as one of the most promising categories of biomarkers due to their role in virtually all cellular processes. Similar to other cancer types, changes in expressions of ncRNAs have been reported in OC and a number of ncRNAs have diagnostic, prognostic, and therapeutic potential. Moreover, some ncRNAs are capable of regulating gene expression by various mechanisms. Therefore, elucidating the current literature on the four main types of ncRNAs namely, microRNA, lncRNA, snoRNA, piwi-RNA, and circular RNA in the context of OC pathogenesis is timely and would enable further improvements and innovations in diagnosis, prognosis, and treatment of OC. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Indexed as

MicroRNAsMouth NeoplasmsRNA, Long NoncodingBiomarkers, TumorHumansRNA, UntranslatedBiomarkers, TumorMicroRNAsRNA, Long NoncodingRNA, Untranslateddiagnosisnoncoding RNAoral cancerprognosistherapeutics

Identifiers

PMID35959932
PMCPMC10909450
OpenAlexW4293154010

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.