Evidence map›Paper›PMID 39349529›Full record

SynthesisScientific reports2024

Comprehensive investigation of long non-coding RNA HOTAIR polymorphisms and cancer risk: a current meta-analysis encompassing 96,458 participants.

B Madhu Krishna, Pankaj Garg, Sravani Ramisetty, Ayalur Raghu Subbalakshmi, Prakash Kulkarni, Ravi Salgia, Sharad S Singhal

Abstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

7 authors.

B Madhu KrishnaDepartment of Medical Oncology, Beckman Research Institute, City of Hope Comprehensive Cancer Center and National Medical Center, Duarte, CA, 91010, USA.
Pankaj GargDepartment of Chemistry, GLA University, Mathura, Uttar Pradesh, 281406, India.
Sravani RamisettyDepartment of Medical Oncology, Beckman Research Institute, City of Hope Comprehensive Cancer Center and National Medical Center, Duarte, CA, 91010, USA.
Ayalur Raghu SubbalakshmiDepartment of Medical Oncology, Beckman Research Institute, City of Hope Comprehensive Cancer Center and National Medical Center, Duarte, CA, 91010, USA.
Prakash KulkarniDepartment of Chemistry, GLA University, Mathura, Uttar Pradesh, 281406, India.
Ravi SalgiaDepartment of Medical Oncology, Beckman Research Institute, City of Hope Comprehensive Cancer Center and National Medical Center, Duarte, CA, 91010, USA.
Sharad S SinghalDepartment of Medical Oncology, Beckman Research Institute, City of Hope Comprehensive Cancer Center and National Medical Center, Duarte, CA, 91010, USA. ssinghal@coh.org.ORCID https://orcid.org/0000-0002-6415-8160

Funding

United States Department of Defense HT9425-23-1-0581United States Department of Defense W81XWH-22-1-0331
6 · The paper itself

Abstract

Cancer ranks as the second leading cause of mortality worldwide, prompting extensive investigations into factors contributing to its development. Among these factors, genetic variations, known as genotypic polymorphisms, have been identified as significant influencers in the susceptibility to various types of cancer. Recent research has focused on exploring the connection between polymorphisms in the Long Non-coding RNA HOTAIR and cancer risk. However, the results from these studies have been inconsistent, leading to ambiguity and controversy. To address this uncertainty, we conducted a systematic analysis by gathering relevant studies from PubMed, EMBASE, and Google Scholar. Specifically, we focused on three well-studied polymorphisms within the HOTAIR lncRNA (HOTAIR rs920778 C > T, HOTAIR rs1899663 G > T, HOTAIR rs4759314 A > G) and their association with cancer risk. Our meta-analysis included data from 48 case-control studies involving 42,321 cases and 54,137 controls. The results of our updated meta-analysis revealed a significant correlation between HOTAIR rs1899663 G > T and HOTAIR rs4759314 A > G polymorphisms and overall cancer risk, particularly in the homozygous and recessive genetic models. Subgroup analysis further revealed that these associations were notably pronounced in the Asian population but not observed in the Iranian population. Furthermore, our findings underscore the potential of HOTAIR polymorphisms as diagnostic markers for overall cancer risk, particularly in gynecological cancers, precisely, HOTAIR rs1899663 G > T polymorphism in breast cancer. In conclusion, our systematic analysis provides compelling evidence that Long Non-coding RNA HOTAIR polymorphisms are linked to cancer risk, particularly in certain populations and cancer types, suggesting their potential clinical relevance as diagnostic indicators.

Indexed as

Genetic Predisposition to DiseaseNeoplasmsPolymorphism, Single NucleotideRNA, Long NoncodingCase-Control StudiesHumansRisk FactorsHOTAIR long untranslated RNA, humanRNA, Long NoncodingGynecological cancerHOX transcript antisense intergenic RNA (HOTAIR)Long non-coding RNA (lncRNA)Single nucleotide polymorphisms (SNPs)

Identifiers

PMID39349529
PMCPMC11442654

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LicenceCC BY-NC-ND
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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.