Identifying the combination of genetic factors that determine susceptibility to cervical cancer

N-Heterocycle based Degraders (PROTACs) Manifesting Anticancer Efficacy: Recent Advances

Proteolysis Targeting Chimeras (PROTACs) technology has emerged as a promising strategy for the treatment of undruggable therapeutic targets. Researchers have invested a great effort in developing druggable PROTACs; however, the problems associated with PROTACs, including poor solubility, metabolic stability, cell permeability, and pharmacokinetic profile, restrict their clinical utility. Thus, there is a pressing need to expand the size of the armory of PROTACs which will escalate the chances of pinpointing new PROTACs with optimum pharmacokinetic and pharmacodynamics properties. N- heterocycle is a class of organic frameworks that have been widely explored to construct new and novel PROTACs. This review provides an overview of recent efforts of medicinal chemists to develop N-heterocycle-based PROTACs as effective cancer therapeutics. Specifically, the recent endeavors centred on the discovery of PROTACs have been delved into various classes based on the E3 ligase they target (MDM2, IAP, CRBN, and other E3 ligases). Mechanistic insights revealed during the biological assessment of recently furnished Nheterocyclic- based PROTACs constructed via the utilization of ligands for various E3 ligases have been discussed.

Interaction between susceptibility loci in cGAS-STING pathway, MHC gene and HPV infection on the risk of cervical precancerous lesions in Chinese population

Human papillomavirus (HPV) infection is a definite risk factor for cervical cancer. Nevertheless, only some infected individuals actually develop cervical cancer. The cGAS-STING pathway in innate immunity plays an important role in protecting against HPV infection. Chen et al. described that the rs2516448 SNP in the MHC locus may affect susceptibility to cervical cancer, a finding that we attempted to replicate in a Chinese population. To investigate the effects of cGAS, STING and MHC polymorphisms on susceptibility to cervical precancerous lesions, 9 SNPs were analyzed in 164 cervical precancerous lesion cases and 428 controls. Gene-gene and gene-environment interactions were also evaluated. We found a significantly decreased risk of cervical precancerous lesions for the GG genotype of rs311678 in the cGAS gene (ORadjusted = 0.40, 95% CI: 0.16-0.98). Moreover, MDR analysis identified a significant three-locus interaction model, involving HPV infection, age at menarche and rs311678 in cGAS. Additionally, a significant antagonistic interaction between HPV infection and rs311678 was found on an additive scale. In conclusion, our results indicate that the rs311678 polymorphism in the cGAS gene confers genetic susceptibility to cervical precancerous lesions. Moreover, the three-way gene-environment interactions further demonstrate that the rs311678 polymorphism in cGAS can significantly decrease the risk of HPV infection and the elder at menarche.

Association of single nucleotide polymorphisms in tumor necrosis factor-alpha with cervical cancer susceptibility

Tumor necrosis factor-alpha (TNF-α) polymorphisms have been reported to play an important role in the development of cervical cancer. But the results remain inconclusive. We performed this study to provide a comprehensive assessment of the association by means of a meta-analysis in which all published studies were included. The studies investigating the associations between cervical cancer risk and TNF-α polymorphisms were identified through PubMed, Embase, CNKI, and Chinese BioMedical Literature Database. OR and 95% CI (odds ratio and 95% confidence interval) were calculated using either the fixed or random effects model to assess the associations. We eventually included eighteen case-control studies of SNP -308 G>A and nine studies of SNP -238 G>A. Meta-analysis of the former polymorphism suggested significantly increased risk of cervical cancer associated with the A allele (OR 1.19, 95% CI 1.02-1.38). Subgroup analysis according to ethnicity showed similar results in Caucasians (A vs. G: OR 1.25, 95% CI 1.02-1.54; AA vs. GG: OR 1.47, 95% CI 1.04-2.08; AA vs. GA+GG: OR 1.47, 95% CI 1.04-2.08). For SNP -238 G>A, a protective association was observed in overall comparisons (A vs. G: OR 0.64, 95% CI 0.51-0.80; AA+GA vs. GG: OR 0.62, 95% CI 0.49-0.79) and subgroup analysis of Caucasians (A vs. G: OR 0.67, 95% CI 0.53-0.83; AA+GA vs. GG: OR 0.65, 95% CI 0.51-0.82). Our meta-analysis indicates that TNF-α polymorphisms may confer susceptibility to cervical cancer in an ethic-specific fashion.

IL-10 gene promoter and intron polymorphisms as genetic biomarkers of cervical cancer susceptibility among Tunisians

OBJECTIVE

We investigated the association between polymorphisms in the promoter and intron regions of the interleukin-10 (IL-10) gene with the risk of cervical cancer (CC) in Tunisian patients and control women.

METHODS

Study subjects comprised 86 CC cases and 126 control women. Genotyping of IL-10 intron (rs3024491, rs3024490) and promoter (rs1800872, rs1800871, rs1800896) variants was done by real-time PCR, with defined clusters.

RESULTS

The minor allele frequencies of the five tested IL-10 SNPs were not significantly different between cervical cancer cases and control women. However, significantly higher frequencies of homozygous minor allele-carriers in cases was seen for rs3024490 (P=0.023), rs1800872 (P=0.037), and rs1800871 (P=0.028). IL-10 serum levels were significantly reduced in rs3024490 T/T vs. G/G genotype carriers, and in rs1800871 T/T than C/C genotype carriers. While carriage of rs1800872 and rs3024491 minor allele was associated with reduced IL-10 secretion, this was not statistically significant. Haploview analysis demonstrated high linkage disequilibrium (LD) among the IL10 SNPs studied, and only seven haplotypes were common, capturing 98.8% of the total possible haplotypes. Reduced frequency of haplotypes GTCCA (P<0.001) and TGATG (P<0.001) was seen in cervical cancer cases than in control women, thus conferring disease protection nature to these haplotype. This association remained significant for GTCCA (Pc=0.006) and TGATG (P=0.045) after correcting for multiple comparisons.

CONCLUSION

Specific IL-10 variants (rs3024490, rs1800872, and rs1800871) and haplotype (GTCCA and TGATG) may contribute to the development of cervical cancer among Tunisian women.

New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer

Cervical cancer is a complex disease with multiple environmental and genetic determinants. In this study, we sought an association between polymorphisms in immune response genes and cervical cancer using both single-locus and multi-locus analysis approaches. A total of 14 single nucleotide polymorphisms (SNPs) distributed in CD28, CTLA4, ICOS, PDCD1, FAS, TNFA, IL6, IFNG, TGFB1 and IL10 genes were determined in patients and healthy individuals from three independent case/control sets. The first two sets comprised White individuals (one group with 82 cases and 85 controls, the other with 83 cases and 85 controls) and the third was constituted by non-white individuals (64 cases and 75 controls). The multi-locus analysis revealed higher frequencies in cancer patients of three three-genotype combinations [CD28+17(TT)/IFNG+874(AA)/TNFA-308(GG), CD28+17(TT)/IFN+847(AA)/PDCD1+7785(CT), and CD28 +17(TT)/IFNG+874(AA)/ICOS+1564(TT)] (P < 0.01, Monte Carlo simulation). We hypothesized that this two-genotype [CD28(TT) and IFNG(AA)] combination could have a major contribution to the observed association. To address this question, we analyzed the frequency of the CD28(TT), IFNG(AA) genotype combination in the three groups combined, and observed its increase in patients (P = 0.0011 by Fisher's exact test). The contribution of a third polymorphism did not reach statistical significance (P = 0.1). Further analysis suggested that gene-gene interaction between CD28 and IFNG might contribute to susceptibility to cervical cancer. Our results showed an epistatic effect between CD28 and IFNG genes in susceptibility to cervical cancer, a finding that might be relevant for a better understanding of the disease pathogenesis. In addition, the novel analytical approach herein proposed might be useful for increasing the statistical power of future genome-wide multi-locus studies.

Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms

Currently, single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) of >5% are preferentially used in case-control association studies of common human diseases. Recent technological developments enable inexpensive and accurate genotyping of a large number of SNPs in thousands of cases and controls, which can provide adequate statistical power to analyze SNPs with MAF <5%. Our purpose was to determine whether evaluating rare SNPs in case-control association studies could help identify causal SNPs for common diseases. We suggest that slightly deleterious SNPs (sdSNPs) subjected to weak purifying selection are major players in genetic control of susceptibility to common diseases. We compared the distribution of MAFs of synonymous SNPs with that of nonsynonymous SNPs (1) predicted to be benign, (2) predicted to be possibly damaging, and (3) predicted to be probably damaging by PolyPhen. Our sources of data were the International HapMap Project, ENCODE, and the SeattleSNPs project. We found that the MAF distribution of possibly and probably damaging SNPs was shifted toward rare SNPs compared with the MAF distribution of benign and synonymous SNPs that are not likely to be functional. We also found an inverse relationship between MAF and the proportion of nsSNPs predicted to be protein disturbing. On the basis of this relationship, we estimated the joint probability that a SNP is functional and would be detected as significant in a case-control study. Our analysis suggests that including rare SNPs in genotyping platforms will advance identification of causal SNPs in case-control association studies, particularly as sample sizes increase.

Hypermethylation of two consecutive tumor suppressor genes, BLU and RASSF1A, located at 3p21.3 in cervical neoplasias

OBJECTIVES

Although initiated by human papillomavirus (HPV), cervical carcinogenesis demands other cofactors to shape its natural course. Epigenetic effects such as DNA methylation, are considered to contribute to carcinogenesis process.

METHODS

The methylation status of BLU and RASSF1A, as well as the HPV infection status, were assessed in a full spectrum of cervical neoplasia, including 45 low-grade squamous intraepithelial lesions (LSIL), 63 high-grade squamous intraepithelial lesions (HSIL), 107 squamous cell carcinomas (SCC), 23 adenocarcinomas (AC), and 44 normal control tissues.

RESULTS

The BLU was methylated in 76.9% of SCC, 57.4% of HSIL, 20.0% of LSIL and 12.5% of normal tissues (P<0.001). The RASSF1A was methylated in 15% of SCC, 17.5% of HSIL, but not in LSIL or normal tissues (P<0.001). In AC, 43.5% of patients showed BLU methylation and 26.1% RASSF1A methylation, significantly higher than the corresponding control frequencies of 12.5% (P=0.005) and 0% (P=0.001), respectively. There was an insignificant trend toward loss of BLU methylation with advancing clinical stages of SCC (84.8%, 67.7%, and 63.6% in stages I, II, and III/IV, respectively; P=0.08). Patients with LSIL infected with high-risk HPV showed a higher rate of BLU methylation than those without HPV (38.8% vs 9.1%, respectively; P=0.057). The methylation of RASSF1A was inversely related to HPV infection in patients with HSIL/SCC (P=0.003).

CONCLUSIONS

These results suggest that the methylation of BLU and RASSF1A genes is associated with cervical carcinogenesis, which could be clinically important in the future molecular screening of cervical neoplasia.

Identifying SNPs predictive of phenotype using random forests

There has been a great interest and a few successes in the identification of complex disease susceptibility genes in recent years. Association studies, where a large number of single-nucleotide polymorphisms (SNPs) are typed in a sample of cases and controls to determine which genes are associated with a specific disease, provide a powerful approach for complex disease gene mapping. Genes of interest in those studies may contain large numbers of SNPs that classical statistical methods cannot handle simultaneously without requiring prohibitively large sample sizes. By contrast, high-dimensional nonparametric methods thrive on large numbers of predictors. This work explores the application of one such method, random forests, to the problem of identifying SNPs predictive of the phenotype in the case-control study design. A random forest is a collection of classification trees grown on bootstrap samples of observations, using a random subset of predictors to define the best split at each node. The observations left out of the bootstrap samples are used to estimate prediction error. The importance of a predictor is quantified by the increase in misclassification occurring when the values of the predictor are randomly permuted. We extend the concept of importance to pairs of predictors, to capture joint effects, and we explore the behavior of importance measures over a range of two-locus disease models in the presence of a varying number of SNPs unassociated with the phenotype. We illustrate the application of random forests with a data set of asthma cases and unaffected controls genotyped at 42 SNPs in ADAM33, a previously identified asthma susceptibility gene. SNPs and SNP pairs highly associated with asthma tend to have the highest importance index value, but predictive importance and association do not always coincide.

Genetics, statistics and human disease: analytical retooling for complexity

Molecular biologists and geneticists alike now acknowledge that most common human diseases with a genetic component are likely to have complex etiologies. Yet despite this belief, many statistical geneticists continue applying, in slightly new and different ways, methodologies that were developed to dissect much simpler etiologies. In this article, we characterize, with examples, the various factors that can complicate genetic analysis and demonstrate their shared features and how they affect genetic analysis. We describe a variety of approaches that are currently available, revealing methodological gaps and suggesting new directions for method development. Finally, we propose a comprehensive two-step approach to analysis that systemically addresses the different genetic factors that are likely to underlie complex diseases.