Evidence map›Paper›PMID 39830983›Full record

ReviewFrontiers in molecular biosciences2024

LncRNA HOXA10-AS as a novel biomarker and therapeutic target in human cancers.

Xin Hu, Yong Wang, Sijia Zhang, Xiaosi Gu, Xiaoyu Zhang, Lianlian Li

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 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. Article
  2. Review
  3. Review
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.

Xin Hu *Department of Immunology, School of Clinical and Basic Medical Sciences, Shandong First Medical University, Jinan, Shandong, China.
Yong Wang *Shandong Provincial Engineering Research Center for Bacterial Oncolysis and Cell Treatment, Jinan, Shandong, China.
Sijia ZhangDepartment of Immunology, School of Clinical and Basic Medical Sciences, Shandong First Medical University, Jinan, Shandong, China.
Xiaosi GuDepartment of Immunology, School of Clinical and Basic Medical Sciences, Shandong First Medical University, Jinan, Shandong, China.
Xiaoyu ZhangDepartment of Immunology, School of Clinical and Basic Medical Sciences, Shandong First Medical University, Jinan, Shandong, China.
Lianlian LiDepartment of Immunology, School of Clinical and Basic Medical Sciences, Shandong First Medical University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are crucial regulatory molecules that participate in numerous cellular development processes, and they have gathered much interest recently. HOXA10 antisense RNA (HOXA10-AS, also known as HOXA-AS4) is a novel lncRNA that was identified to be dysregulated in some prevalent malignancies. In this review, the clinical significance of HOXA10-AS for the prognosis of various cancers is analyzed. In addition, the major advances in our understanding of the cellular biological functions and mechanisms of HOXA10-AS in different human cancers are summarized. These cancers include esophageal carcinoma (ESCA), gastric cancer (GC), glioma, laryngeal squamous cell carcinoma (LSCC), acute myeloid leukemia (AML), lung adenocarcinoma (LUAD), nasopharyngeal carcinoma (NPC), oral squamous cell carcinoma (OSCC), and pancreatic cancer. We also note that the aberrant expression of HOXA10-AS promotes malignant progression through various underlying mechanisms. In conclusion, HOXA10-AS is expected to serve as an ideal clinical biomarker and an effective cancer therapy target.

Indexed as

biomarkerHOXA10-ASlong non-coding RNAsignaling pathwaytherapeutic target

Identifiers

PMID39830983
PMCPMC11738949

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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.