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

Exploring the Correlation Between Hypoxia, HIF1A Variants, and Breast Cancer in Different Ethnicities, and Bangladeshi Women: Through ELISA and Integrative Multi-Omics Analysis

Background

Hypoxia, a condition where there is a lack of oxygen, is known to play a role in cancer progression.

Objective

This study investigates the correlation between HIF1A gene-altered expression and hypoxia in Bangladeshi breast cancer (BC) cases and TCGA_BC datasets.

Design

This case-control study compares BC cases to healthy controls to understand the relationship between gene changes and cancer.

Method

This study used advanced analysis methods to examine the transcriptional landscape of BC, and quantitatively assessed its correlation using integrated multi-omics analysis.

Results

In Bangladeshi BC cases, the T allele of HIF1A rs1154946 correlates notably (P-value < .001) with BC incidence. ELISA results confirmed a significant association (P-value < .005) between elevated HIF1A expression and BC-related hypoxia. Bioinformatics eQTL analysis validated the correlation between increased HIF1A expression and rs11549465 T allele (P-value < .01). Structural analyses suggested that rs11549465 (P582S) mutation may decrease protein stability (ΔΔG-value: -1.24 kcal/mole), potentially affecting HIF1A function. HIF1A enrichment analysis in BC underscores strong associations with oxygen levels, hypoxia, metabolic processes, apoptosis, and programed cell death (P-value < .001). Transcriptomic data demonstrated a robust correlation (P-value < .0001) between HIF1A expression and copy-number alterations, mutations, and abnormal methylation. Altered HIF1A expression showed strong negative correlations (P-value < .00001) with methylation and the expression of the ER (ESR1), in Whites. Survival analysis revealed marked differences in overall survival linked to high and low HIF1A expression (P-value < .00001). Furthermore, HIF1A expression significantly correlated (P-value < .000001) with hypoxia, TMB, MSI, and immune infiltration by CD8+ T cells, neutrophils, dendritic, and macrophages, providing deeper insights into the BC microenvironment.

Conclusion

Thus, the HIF1A gene could serve as a promising biomarker for breast cancer progression, control, and survival across ethnicities, emphasizing its role in disease development and regulation.

HIF1A protein expression is correlated with clinical features in gastric cancer: an updated systematic review and meta-analysis

To elucidate the correlation of HIF1A with clinicopathologic characteristics in patients with gastric cancer (GC), we conducted a systematic review and meta-analysis. We searched PubMed, Embase and Web of Science for studies on GC and HIF1A, covering studies published until January 31st, 2022. We calculated odds ratios (ORs) and 95% confidence intervals (CIs) for clinical characteristics based on high and low HIF1A protein levels. We used random-effects and fixed-effects meta-analysis methods to determine mean effect sizes of ORs and evaluated publication heterogeneity with τ2, I2, and Q values. Additionally, we generated funnel plots to inspect publication bias. Our meta-analysis included 20 publications with 3416 GC patients to estimate the association between high or low HIF1A expression and clinical characteristics. Positive HIF1A expression was significantly associated with T stage progression (OR: 2.46; 95% CI 1.81-3.36; P < 0.01), TNM stage progression (OR: 2.50; 95% CI 1.61-3.87; P < 0.01), lymph node metastasis (OR: 2.06; 95% CI 1.44-2.94; P < 0.01), undifferentiated status (OR: 1.83; 95% CI 1.45-2.32; P < 0.01), M stage progression (OR: 2.34; 95% CI 1.46-3.77; P < 0.01), Borrmann stage progression (OR: 1.48; 95% CI 1.02-2.15; P = 0.04), larger tumor size (OR: 1.27; 95% CI 1.06-1.52; P < 0.01), vascular invasion (OR: 1.94; 95% CI 1.38-2.72; P < 0.01), and higher vascular endothelial growth factor (VEGF) protein expression (OR: 2.61; 95% CI 1.79-3.80; P < 0.01) in our meta-analysis. GC Patients highly expressing HIF1A protein might be prone to tumor progression, poorly differentiated GC cell types, and a high VEGF expression.

Association of Hypoxia-Inducible Factor 1α Gene Polymorphisms With Breast Cancer Susceptibility: A Meta-Analysis

PURPOSE

Overexpression of the hypoxia-inducible factor 1α (HIF1A) gene is significantly associated with different types of cancers, including breast cancer. In this study, the effects of single-nucleotide polymorphisms rs11549465, rs11549467, and rs2057482 of the HIF1A gene and their association with breast cancer were systematically investigated through meta-analysis.

MATERIALS AND METHODS

After a systematic review, nine case-control studies of the HIF1A rs11549465 C/T polymorphism, six case-control studies of the HIF1A rs11549467 G/A polymorphism, and one case-control study of the HIF1A rs2057482 C/T polymorphism were included in this meta-analysis. The summary pooled odds ratios with 95% CIs were evaluated to detect the relationship between HIF1A polymorphisms and breast cancer susceptibility.

RESULTS

Subgroup-stratified analyses showed that the T and TT genotypes of the HIF1A rs11549465 C/T polymorphism were significantly associated with increased breast cancer risk in the Asian population under three genetic models (allele, homozygous, and recessive). HIF1A rs11549467 G/A analyses indicated that the A and AA genotypes were significantly associated with increased breast cancer risk in the Asian population under allele and dominant models. However, no association with breast cancer was observed in the White population for the HIF1A rs11549465 C/T and rs11549467 G/A polymorphisms. In addition, the HIF1A rs2057482 C/T polymorphism showed no association with breast cancer under any genetic models or by ethnicity-stratified analyses.

CONCLUSION

The results of this meta-analysis suggested that the HIF1A rs11549465 C/T and rs1154946 G/A polymorphisms were significantly associated with increased breast cancer risk in the Asian population, but no associations were found in the White population. Thus, HIF1A could be an important biomarker for population-based breast cancer screening.

A Novel Analysis Method for Evaluating the Interplay of Oxygen and Ionizing Radiation at the Gene Level

Whilst the impact of hypoxia and ionizing radiations on gene expression is well-understood, the interplay of these two effects is not. To better investigate this aspect at the gene level human bladder, brain, lung and prostate cancer cell lines were irradiated with photons (6 Gy, 6 MV LINAC) in hypoxic and normoxic conditions and prepared for the whole genome analysis at 72 h post-irradiation. The analysis was performed on the obtained 20,000 genes per cell line using PCA and hierarchical cluster algorithms to extract the most dominant genes altered by radiation and hypoxia. With the help of the introduced novel radiation-in-hypoxia and oxygen-impact profiles, it was possible to overcome cell line specific gene regulation patterns. Based on that, 37 genes were found to be consistently regulated over all studied cell lines. All DNA-repair related genes were down-regulated after irradiation, independently of the oxygen state. Cell cycle-dependent genes showed up-regulation consistent with an observed change in cell population in the S and G2/M phases of the cell cycle after irradiation. Genes behaving oppositely in their regulation behavior when changing the oxygen concentration and being irradiated, were immunoresponse and inflammation related genes. The novel analysis method, and by consequence, the results presented here have shown how it is important to consider the two effects together (oxygen and radiation) when analyzing gene response upon cancer radiation treatment. This approach might help to unrevel new gene patterns responsible for cancer radioresistance in patients.

Statistical meta-analysis to investigate the association between the Interleukin-6 (IL-6) gene polymorphisms and cancer risk

A good number of genome-wide association studies (GWAS), including meta-analyses, reported that single nucleotide polymorphisms (SNPs) of the IL-6 gene are significantly associated with various types of cancer risks, though some other studies reported insignificant association with cancers, in the literature. These contradictory results may be due to variations in sample sizes and/or deficiency of statistical modeling. Therefore, an attempt is made to provide a more comprehensive understanding of the association between the IL-6 gene SNPs (rs1800795, rs1800796, rs1800797) and different cancer risks, giving the weight on a large sample size, including different cancer types and appropriate statistical modeling with the meta-dataset. In order to attain a more reliable consensus decision about the association between the IL-6 gene polymorphisms and different cancer risks, in this study, we performed a multi-case statistical meta-analysis based on the collected information of 118 GWAS studies comprising of 50053 cases and 65204 control samples. Results from this Meta-analysis indicated a significant association (p-value < 0.05) of the IL-6 gene rs1800796 polymorphism with an overall increased cancer risk. The subgroup analysis data based on cancer types exhibited significant association (p-value < 0.05) of the rs1800795 polymorphism with an overall increased risk of cervical, liver and prostate cancers; the rs1800796 polymorphism with lung, prostate and stomach cancers; and the rs1800797 polymorphism with cervical cancer. The subgroup analysis of ethnicity data showed a significant association (p-value < 0.05) of an overall cancer risk with the rs1800795 polymorphism for the African and Asian populations, the rs1800796 polymorphism for the Asian only and the rs1800797 polymorphism in the African population. Comparative discussion showed that our multi-case meta-analyses received more support than any previously reported individual meta-analysis about the association between the IL-6 gene polymorphisms and cancer risks. Results from this study, more confidently showed that the IL-6 gene SNPs (rs1800795, rs1800796 and rs1800797) in humans are associated with increased cancer risks. Therefore, these three polymorphisms of the IL-6 gene have the potential to be evaluated as a population based rapid, low-cost PCR prognostic biomarkers for different types of cancers diagnosis and research.

Prediction of potential deleterious nonsynonymous single nucleotide polymorphisms of HIF1A gene: A computational approach

Hypoxia-inducible factor-1α (HIF-1α) is the oxygen sensitive subunit of HIF1 transcription factor. Its variations is associated with several diseases including different type of cancer, cardiovascular diseases, and liver and kidney failure. Despite all the investigations carried out on the single nucleotide polymorphisms (SNPs) of HIF1A gene and diseases, there are many uncharacterized nonsynonymous SNPs of this gene, which might have damaging effect on the protein function. Therefore, it is worthwhile to analyze these potential damaging nsSNPs, using different bioinformatics tools before launching large population studies. The objective of the present study was to predict the possible deleterious nsSNPs of HIF1A gene and their effects on the function and structure of HIF-1alpha protein, using different bioinformatics tools. Various prediction servers were used including SIFT, PROVEAN, PolyPhen-2, PANTHER, phD-SNP, SNP-GO, I-Mutant 2.0, Fathmm, SNPeffect 4.0, Mutation taster, CADD and RAMPAGE in a stepwise approach. After analyzing all 454 missense variants of the HIF1A gene using the abovementioned tools, we reported 11 variants with a significant impact on the function or structure of HIF-1α protein. Furthermore, among these variants only S274 P was predicted as stability enhancing variant with effect on protein function by increasing its stability. Although there are many advantages for computational analysis, the results has to be confirmed by experimental investigations.

Association of hypoxia-inducible factor-1α (HIF1α) 1790G/A gene polymorphism with renal cell carcinoma and prostate cancer susceptibility: a meta-analysis

BACKGROUND

This meta-analysis was performed to evaluate the relationship between hypoxia-inducible factor-1α (HIF1α) 1790G/A gene polymorphism and the susceptibility to renal cell carcinoma (RCC) and prostate cancer (PCa).

METHODS

Association investigations were identified and included from the Embase, Cochrane Library and PubMed databases on March 1, 2018, and eligible investigations were analyzed by meta-analysis. Odds ratios (OR) were used to express the dichotomous data, and the 95% confidence intervals (CI) were also calculated.

RESULTS

In this meta-analysis, we found that the AA genotype of HIF1α 1790G/A was positively associated with the risk of RCC in overall populations, Caucasians, but not for Asians. G allele and GG genotype were not associated with the susceptibility of RCC in overall populations, Caucasians, and Asians. The G allele was negatively associated with PCa susceptibility in overall populations, Asians, but not for Caucasians. GG genotype was negatively associated with PCa susceptibility in Asians, but not for overall populations and Caucasians. HIF1α 1790G/A AA genotype was not associated with PCa susceptibility in overall populations of Caucasians or Asians.

CONCLUSION

AA genotype of HIF1α 1790G/A was positively associated with RCC risk in overall populations and Caucasians. Furthermore, the G allele was negatively associated with prostate cancer susceptibility in overall populations, Asians, and GG genotype was negatively associated with PCa susceptibility in Asians.

A Genetic Association Study of a Specific Gene and Severe Form of Resorption in the Edentulous Mandible in the Egyptian Population

PURPOSE

To investigate for the first time in Egypt and the Middle East the relationship between a specific gene and the presence of severely resorbed edentulous mandibular ridges in a sample of the Egyptian population.

MATERIALS AND METHODS

The study was conducted on 50 subjects divided into case and control groups according to the residual ridge height. Saliva was used as a convenient source of DNA in the dental clinic. A certain genetic variation (1772C>T) in an important gene related to bone healing (hypoxia-inducible factor-1 alpha [HIF1-α] gene) was selected. The genetic variation 1772C>T is a single nucleotide polymorphism (SNP) that occurs when corresponding sequences of DNA from different individuals differ at one base. Then, we have 2 forms of the gene (2 alleles): C and T. SNPs typically have 3 genotypes; in this study, they are the CC, CT, and TT genotypes. Polymerase chain reaction (PCR) restriction fragment length polymorphism (RFLP) was the method performed for genotyping. The statistical significance of the results was evaluated by the Chi-square test and Fisher Exact test.

RESULTS

A statistically significant difference in the distribution of the TT genotype between both groups was detected with p-value = 0.049. There was also a difference in the distribution of the CC and CT genotypes, but it was not statistically significant, since the p-values were 0.733 and 0.145, respectively. The T alleles were more abundant in the case group, while the control group showed more frequency of the C allele with no statistical significance.

CONCLUSION

The TT genotype of the 1772C>T polymorphism of HIF1-α gene is related to the presence of severely atrophied residual ridges in completely edentulous Egyptians. This can be used as a marker to predict the future condition of the ridge using saliva samples. Further studies on larger scale are recommended.

Cancer stem cells and hypoxia-inducible factors (Review)

Cancer stem cells (CSCs), also known as tumor-initiating cells, are a subpopulation of tumor cells that exhibit properties similar to those of normal stem cells. Oxygen is an important regulator of cellular metabolism; hypoxia-inducible factors (HIFs) mediate metabolic switches in cells in hypoxic environments. Hypoxia clearly has the potential to exert a significant effect on the maintenance and evolution of CSCs. Both HIF‑1α and HIF‑2α may contribute to the regulation of cellular adaptation to hypoxia and resistance to cancer therapies. This review provides an overview of the roles of HIFs in CSCs. HIF‑1α and HIF‑2α have significant prognostic and predictive value in the clinic and the concept of personalized medicine should be applied in designing clinical trials for HIF inhibitors.

Hypoxia and renal cell carcinoma: The influence of HIF1A+1772C/T functional genetic polymorphism on prognosis

OBJECTIVES

Hypoxia-inducible factor (HIF-1) is a key regulator of the genes involved in the cellular response to hypoxia. Overexpression of HIF-1 has been implicated in the pathogenesis of renal cell carcinoma (RCC), and functional polymorphisms of the HIF1A gene may confer susceptibility to RCC. Our purpose was to assess the influence of HIF1A+1772C/T (rs11549465) polymorphism on RCC prognosis.

MATERIAL AND METHODS

This study evaluated the associations of the HIF1A+1772C/T (rs11549465) polymorphism with clinicopathologic prognostic factors, recurrence/progression, and survival in a cohort of 179 patients with RCC treated at Portuguese Oncology Institute of Porto. Genotyping analysis, using DNA extracted from peripheral blood, was performed by real-time polymerase chain reaction allelic discrimination. The genotype associations with clinicopathologic parameters and recurrence/progression were analyzed by the chi-square or Fisher tests. Genotypes influencing cancer-specific survival were compared using Cox proportional hazard regression, Kaplan-Meier curves, and Breslow test.

RESULTS

None of the genotypes (CC, CT, or TT) were significantly associated with clinicopathologic prognostic factors. The TT genotype and T allele were associated with recurrence/progression (P = 0.042 and P = 0.02, respectively). Patients with CT and CT+TT genotypes tend to have an increased risk to RCC-related death (hazard ratio = 2.79; 95% CI: 0.88-8.82; P = 0.08 and hazard ratio = 2.76; 95% CI: 0.93-8.22; P = 0.07, respectively) and showed worse cancer-specific survival curves than those with the CC genotype (P = 0.012 and P = 0.018, respectively).

CONCLUSIONS

These results suggest that HIF1A+1772C/T (rs11549465) polymorphism may have effects on RCC recurrence/progression and survival.

Lymphatic metastasis of gallbladder cancer: Present and future

Lymphatic metastasis is the most common way of metastasis in gallbladder cancer (GBC), and it is also one of the important factors influencing prognosis. Therefore, it is important to elucidate the lymphatic drainage pathways, group the metastatic lymph nodes, assess the extent of lymphadenectomy, and identify relevant predictors of lymphatic metastasis. The development of lymph node tracer technique has greatly improved the surgical procedure, and exploration of the molecular mechanisms of lymphatic metastases may provide new therapeutic targets. In the current review, we discuss the lymphatic drainage pathways as well as the substation, predictors, tracers and mechanisms of lymphatic metastasis of GBC.

Molecular signatures of ovarian diseases: Insights from network medicine perspective

Dysfunctions and disorders in the ovary lead to a host of diseases including ovarian cancer, ovarian endometriosis, and polycystic ovarian syndrome (PCOS). Understanding the molecular mechanisms behind ovarian diseases is a great challenge. In the present study, we performed a meta-analysis of transcriptome data for ovarian cancer, ovarian endometriosis, and PCOS, and integrated the information gained from statistical analysis with genome-scale biological networks (protein-protein interaction, transcriptional regulatory, and metabolic). Comparative and integrative analyses yielded reporter biomolecules (genes, proteins, metabolites, transcription factors, and micro-RNAs), and unique or common signatures at protein, metabolism, and transcription regulation levels, which might be beneficial to uncovering the underlying biological mechanisms behind the diseases. These signatures were mostly associated with formation or initiation of cancer development, and pointed out the potential tendency of PCOS and endometriosis to tumorigenesis. Molecules and pathways related to MAPK signaling, cell cycle, and apoptosis were the mutual determinants in the pathogenesis of all three diseases. To our knowledge, this is the first report that screens these diseases from a network medicine perspective. This study provides signatures which could be considered as potential therapeutic targets and/or as medical prognostic biomarkers in further experimental and clinical studies. Abbreviations DAVID: Database for Annotation, Visualization and Integrated Discovery; DEGs: differentially expressed genes; GEO: Gene Expression Omnibus; KEGG: Kyoto Encyclopedia of Genes and Genomes; LIMMA: Linear Models for Microarray Data; MBRole: Metabolite Biological Role; miRNA: micro-RNA; PCOS: polycystic ovarian syndrome; PPI: protein-protein interaction; RMA: Robust Multi-Array Average; TF: transcription factor.