An epistatic interaction between the PAX8 and STK17B genes in papillary thyroid cancer susceptibility

Inositol 1,4,5-trisphosphate receptor gene variants are related to the risk of breast cancer in a Chinese population

BACKGROUND

Mammalian inositol 1,4,5-trisphosphate receptor (ITPR) genes encode ubiquitously expressed endoplasmic reticulum Ca²⁺ channels that have recently been shown to be closely linked to the pathogenesis of several cancers. However, few studies to date have explored associations between ITPR gene family single nucleotide polymorphisms (SNPs) and breast cancer risk.

METHODS

In the present case-control study, 12 SNPs in the potential functional regions of the ITPR1, ITPR2, and ITPR3 genes were genotyped using an Illumina Infinium® Beadchip in 2095 Chinese women (1032 cases and 1063 controls).

RESULTS

Multivariate logistic regression analyses indicated that a missense SNP in the ITPR3 coding region (rs2229642) was significantly related to breast cancer risk when using an additive model in this study (rs2229642-adjusted odds ratio = 1.40, 95% confidence interval = 1.12-1.74, p = 2.97 × 10^-3 ). Expression quantitative trait loci analyses indicated that the SNP rs2229642 was associated with reduced ITPR3 expression levels (p = 3.2 × 10^-7 ) and with marked reductions in the expressions of several proximal genes, including BAK1, GRM4, HLA-DOB, and UQCC2 (p = 0.013, 0.018, 3.4 × 10^-3 , 3.8 × 10^-5 ), suggesting that it may further regulate other genes associated with oncogenic susceptibility. Kaplan-Meier analyses indicated that the patients with higher ITPR3 expression exhibited significantly poorer outcomes compared to the patients with lower expression of this gene (hazard ratio = 1.11, 95% confidence interval = 1-1.23, p = 0.046).

CONCLUSIONS

The results indicated that genetic variant in the coding region of ITPR3 gene may regulate the expressions of its host and some other cancer-related genes, as well as act as potential predictive biomarker for susceptibility to breast cancer in the Chinese population.

Genetic interactions effects for cancer disease identification using computational models: a review

Genome-wide association studies (GWAS) provide clear insight into understanding genetic variations and environmental influences responsible for various human diseases. Cancer identification through genetic interactions (epistasis) is one of the significant ongoing researches in GWAS. The growth of the cancer cell emerges from multi-locus as well as complex genetic interaction. It is impractical for the physician to detect cancer via manual examination of SNPs interaction. Due to its importance, several computational approaches have been modeled to infer epistasis effects. This article includes a comprehensive and multifaceted review of all relevant genetic studies published between 2001 and 2020. In this contemporary review, various computational methods are as follows: multifactor dimensionality reduction-based approaches, statistical strategies, machine learning, and optimization-based techniques are carefully reviewed and presented with their evaluation results. Moreover, these computational approaches' strengths and limitations are described. The issues behind the computational methods for identifying the cancer disease through genetic interactions and the various evaluation parameters used by researchers have been analyzed. This review is highly beneficial for researchers and medical professionals to learn techniques adapted to discover the epistasis and aids to design novel automatic epistasis detection systems with strong robustness and maximum efficiency to address the different research problems in finding practical solutions effectively.

Thyroid Cancer: The Quest for Genetic Susceptibility Involving DNA Repair Genes

The incidence of thyroid cancer (TC), particularly well-differentiated forms (DTC), has been rising and remains the highest among endocrine malignancies. Although ionizing radiation (IR) is well established on DTC aetiology, other environmental and genetic factors may also be involved. DNA repair single nucleotide polymorphisms (SNPs) could be among the former, helping in explaining the high incidence. To further clarify the role of DNA repair SNPs in DTC susceptibility, we analyzed 36 SNPs in 27 DNA repair genes in a population of 106 DTCs and corresponding controls with the aim of interpreting joint data from previously studied isolated SNPs in DNA repair genes. Significant associations with DTC susceptibility were observed for XRCC3 rs861539, XPC rs2228001, CCNH rs2230641, MSH6 rs1042821 and ERCC5 rs2227869 and for a haplotype block on chromosome 5q. From 595 SNP-SNP combinations tested and 114 showing relevance, 15 significant SNP combinations (p < 0.01) were detected on paired SNP analysis, most of which involving CCNH rs2230641 and mismatch repair variants. Overall, a gene-dosage effect between the number of risk genotypes and DTC predisposition was observed. In spite of the volume of data presented, new studies are sought to provide an interpretability of the role of SNPs in DNA repair genes and their combinations in DTC susceptibility.

Mismatch repair single nucleotide polymorphisms and thyroid cancer susceptibility

Thyroid cancer (TC) is the most common endocrine malignancy and its incidence continues to rise worldwide. Ionizing radiation exposure is the best established etiological factor. Heritability is high; however, despite valuable contribution from recent genome-wide association studies, the current understanding of genetic susceptibility to TC remains limited. Several studies suggest that altered function or expression of the DNA mismatch repair (MMR) system may contribute to TC pathogenesis. Therefore, the present study aimed to evaluate the potential role of a panel of MMR single nucleotide polymorphisms (SNPs) on the individual susceptibility to well-differentiated TC (DTC). A case-control study was performed involving 106 DTC patients and 212 age- and gender-matched controls, who were all Caucasian Portuguese. Six SNPs present in distinct MMR genes (MLH1 rs1799977, MSH3 rs26279, MSH4 rs5745325, PMS1 rs5742933, MLH3 rs175080 and MSH6 rs1042821) were genotyped through TaqMan^® assays and genotype-associated risk estimates were calculated. An increased risk was observed in MSH6 rs1042821 variant homozygotes [adjusted odds ratio (OR)=3.42, 95% CI: 1.04-11.24, P=0.04, under the co-dominant model; adjusted OR=3.84, 95% CI: 1.18-12.44, P=0.03, under the recessive model]. The association was especially evident for the follicular histotype and female sex. The association was also apparent when MSH6 was analysed in combination with other MMR SNPs such as MSH3 rs26279. Interestingly, two other SNP combinations, both containing the MSH6 heterozygous genotype, were associated with a risk reduction, suggesting a protective effect for these genotype combinations. These data support the idea that MMR SNPs such as MSH6 rs1042821, alone or in combination, may contribute to DTC susceptibility. This is coherent with the limited evidence available. Nevertheless, further studies are needed to validate these findings and to establish the usefulness of these SNPs as genetic susceptibility biomarkers for DTC so that, in the near future, cancer prevention policies may be optimized under a personalized medicine perspective.

Eigen-Epistasis for detecting gene-gene interactions

BACKGROUND

A large amount of research has been devoted to the detection and investigation of epistatic interactions in genome-wide association studies (GWASs). Most of the literature focuses on low-order interactions between single-nucleotide polymorphisms (SNPs) with significant main effects.

RESULTS

In this paper we propose an original approach for detecting epistasis at the gene level, without systematically filtering on significant genes. We first compute interaction variables for each gene pair by finding its Eigen-Epistasis component, defined as the linear combination of Gene SNPs having the highest correlation with the phenotype. The selection of significant effects is done using a penalized regression method based on Group Lasso controlling the False Discovery Rate.

CONCLUSION

The method is tested against two recent alternative proposals from the literature using synthetic data, and shows good performances in different settings. We demonstrate the power of our approach by detecting new gene-gene interactions on three genome-wide association studies.

ENDOCRINE TUMOURS: Advances in the molecular pathogenesis of thyroid cancer: lessons from the cancer genome

Thyroid cancer is the most common endocrine malignancy giving rise to one of the most indolent solid cancers, but also one of the most lethal. In recent years, systematic studies of the cancer genome, most importantly those derived from The Cancer Genome Altas (TCGA), have catalogued aberrations in the DNA, chromatin, and RNA of the genomes of thousands of tumors relative to matched normal cellular genomes and have analyzed their epigenetic and protein consequences. Cancer genomics is therefore providing new information on cancer development and behavior, as well as new insights into genetic alterations and molecular pathways. From this genomic perspective, we will review the main advances concerning some essential aspects of the molecular pathogenesis of thyroid cancer such as mutational mechanisms, new cancer genes implicated in tumor initiation and progression, the role of non-coding RNA, and the advent of new susceptibility genes in thyroid cancer predisposition. This look across these genomic and cellular alterations results in the reshaping of the multistep development of thyroid tumors and offers new tools and opportunities for further research and clinical development of novel treatment strategies.

Thyroid cancer GWAS identifies 10q26.12 and 6q14.1 as novel susceptibility loci and reveals genetic heterogeneity among populations

Thyroid cancer is the most heritable cancer of all those not displaying typical Mendelian inheritance. However, most of the genetic factors that would explain the high heritability remain unknown. Our aim was to identify additional common genetic variants associated with susceptibility to this disease. In order to do so, we performed a genome-wide association study in a series of 398 cases and 502 controls from Spain, followed by a replication in four well-defined Southern European case-control collections contributing a total of 1,422 cases and 1,908 controls. The association between the variation at the 9q22 locus near FOXE1 and thyroid cancer risk was consistent across all series, with several SNPs identified (rs7028661: OR = 1.64, p = 1.0 × 10(-22) , rs7037324: OR = 1.54, p = 1.2 × 10(-17) ). Moreover, the rare alleles of three SNPs (rs2997312, rs10788123 and rs1254167) at 10q26.12 showed suggestive evidence of association with higher risk of the disease (OR = 1.35, p = 1.2 × 10(-04) , OR = 1.26, p = 5.2 × 10(-04) and OR = 1.38, p = 5.9 × 10(-05) , respectively). Finally, the rare allele of rs4075570 at 6q14.1 conferred protection in the series studied (OR = 0.82, p = 2.0 × 10(-04) ). This study suggests that heterogeneity in genetic susceptibility between populations is a key feature to take into account when exploring genetic risk factors related to this disease.

Thyroid transcription factors in development, differentiation and disease

Identification of the thyroid transcription factors (TTFs), NKX2-1, FOXE1, PAX8 and HHEX, has considerably advanced our understanding of thyroid development, congenital thyroid disorders and thyroid cancer. The TTFs are fundamental to proper formation of the thyroid gland and for maintaining the functional differentiated state of the adult thyroid; however, they are not individually required for precursor cell commitment to a thyroid fate. Although knowledge of the mechanisms involved in thyroid development has increased, the full complement of genes involved in thyroid gland specification and the signals that trigger expression of the genes that encode the TTFs remain unknown. The mechanisms involved in thyroid organogenesis and differentiation have provided clues to identifying the genes that are involved in human congenital thyroid disorders and thyroid cancer. Mutations in the genes that encode the TTFs, as well as polymorphisms and epigenetic modifications, have been associated with thyroid pathologies. Here, we summarize the roles of the TTFs in thyroid development and the mechanisms by which they regulate expression of the genes involved in thyroid differentiation. We also address the implications of mutations in TTFs in thyroid diseases and in diseases not related to the thyroid gland.