Evidence map›Paper›PMID 26715988›Full record

ArticleBiomarker research2015

A meta-analysis of hypoxia inducible factor 1-alpha (HIF1A) gene polymorphisms: association with cancers.

Md T Anam, Alokta Ishika, Md B Hossain, Jesmin

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Article in Biomarker research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
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9citing papers in PubMed, 5 pooled it
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  2. Association ofJCO global oncology · 2022
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Md T AnamDepartment of Statistics, Biostatistics & Informatics, University of Dhaka, Dhaka, 1000 Bangladesh.
Alokta IshikaDepartment of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.
Md B HossainDepartment of Statistics, Biostatistics & Informatics, University of Dhaka, Dhaka, 1000 Bangladesh.
JesminDepartment of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypoxia inducible factor 1-alpha (HIF1A) is a transcription factor that plays important role in regulating cascade of reactions. In this study, the effect of rs11549465 (1772 C/T) and rs11549467 (1790 G/A) polymorphisms of HIF1A gene and its association with cancers were investigated through meta-analysis.

methodsMeta-analysis of genome wide association studies of HIF1A 1772 C/T polymorphism were conducted on 22 case-control studies of sample size 19024 and for 1790 G/A polymorphism 19 case-control studies were included with sample size 10654. Genotype and allelic frequency compared between cases and controls together with further subgroup analyses were carried out by cancer type and ethnicity.

resultsMeta-analysis from this study indicated that HIF1A 1772 C/T polymorphism is significantly associated with overall cancer risk. T allele and genotype TT are significantly associated with increasing overall cancer risk; odds ratios (OR) dominant model [TT + CT vs. CC: OR 1.30, 95 % CI (1.06-1.59), p-value: 0.0115], and T allele vs. C allele: OR 1.32, 95 % CI (1.07-1.63), p-value: 0.0098. Also, HIF1A 1790 G/A polymorphism, analyses showed that A allele and genotype AA are significantly associated with increasing overall cancer risk; odds ratios (OR) homozygote comparison [AA vs. GG: OR 5.10, 95 % CI (3.12-8.33), p-value: <0.0001], heterozygote comparison [GA vs. GG: OR 1.74, 95 % CI (1.20-2.52), p-value: 0.0033], dominant model [AA + GA vs. GG: OR 1.82, 95 % CI (1.26-2.62), p-value: 0.0014], recessive model [AA vs. GA + GG: OR 3.79, 95 % CI (2.34-6.15), p-value: <0.0001] and A allele vs. G allele: OR 1.82, 95 % CI (1.31-2.52), p-value: 0.0003.

conclusionIn detail meta-analysis indicated that both the polymorphisms 1772 C/T and 1790 G/A are significantly associated with overall cancer risk. The subgroup analyses showed that lung cancer is significantly associated with both polymorphisms. Although the 1772 C/T polymorphism is significantly associated with decreasing risk of renal cell carcinoma but the 1790 G/A polymorphism has shown to significantly increase the cancer risk in both Caucasian and Asian population. Thus, HIF1A could be a useful prognostic marker for cancers early predisposition.

Indexed as

CancerGenome wide association studiesHIF1AMeta-analysis

Identifiers

PMID26715988
PMCPMC4693423

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