Absence of association between TLR4 Thr399Ile polymorphism and cervical cancer susceptibility

Human Papillomavirus Infections and the Role Played by Cervical and Cervico-Vaginal Microbiota-Evidence from Next-Generation Sequencing Studies

This comprehensive review encompasses studies examining changes in the cervical and cervico-vaginal microbiota (CM and CVM) in relation to human papillomavirus (HPV) using next-generation sequencing (NGS) technology. HPV infection remains a prominent global health concern, with a spectrum of manifestations, from benign lesions to life-threatening cervical cancers. The CM and CVM, a unique collection of microorganisms inhabiting the cervix/vagina, has emerged as a critical player in cervical health. Recent research has indicated that disruptions in the CM and CVM, characterized by a decrease in Lactobacillus and the overgrowth of other bacteria, might increase the risk of HPV persistence and the progression of cervical abnormalities. This alteration in the CM or CVM has been linked to a higher likelihood of HPV infection and cervical dysplasia. NGS technology has revolutionized the study of the cervical microbiome, providing insights into microbial diversity, dynamics, and taxonomic classifications. Bacterial 16S rRNA gene sequencing, has proven invaluable in characterizing the cervical microbiome, shedding light on its role in HPV infections and paving the way for more tailored strategies to combat cervical diseases. NGS-based studies offer personalized insights into an individual's cervical microbiome. This knowledge holds promise for the development of novel diagnostic tools, targeted therapies, and preventive interventions for cervix-related conditions, including cervical cancer.

Association of TLR4 gene 2026A/G (rs1927914), 896A/G (rs4986790), and 1196C/T (rs4986791) polymorphisms and cancer susceptibility: Meta-analysis and trial sequential analysis

BACKGROUND

This study was performed to assess the association of TLR4 gene 2026A/G (rs1927914), 896A/G (rs4986790), and 1196C/T (rs4986791) polymorphisms and cancer susceptibility based on published case-control studies.

METHODS

Web of Science, PubMed, Embase, CBM, WanFang Data, CNKI, and VIP database were used for article retrieving. Then, these articles were screened according to the study inclusion and exclusion criteria. The data was extracted, and the study quality was evaluated according to the principle of Newcastle-Ottawa Scale. Meta-analysis was performed by RevMan 5.4 and Stata MP-17 software. Trial sequential analysis was performed by TSA 0.9.5.10 Beta software.

RESULTS

Eighty-seven case-control studies including 25,969 cases and 32,119 controls were included in the meta-analysis. The diseases involved in case groups include prostate cancer, lung cancer, gastric cancer, hepatocellular carcinoma, colorectal cancer, etc. A versus G model of rs1927914, A versus G model of rs4986790 and C versus T model of rs4986791 showed that odds ratio (OR) = 1.08, OR = 0.85, and OR = 0.74 respectively. All the 3 comparisons were statistically significant. Sensitivity analysis showed that the results were stable. Publication bias analysis and trial sequential analysis showed that no significant publication bias was found in the results of the meta-analysis, and the probability of false positives was small.

CONCLUSION

People with A allele of rs1927914, G allele of rs4986790, or T allele of rs4986791 have higher risks of cancer. The results of meta-analysis are stable and have less probability of false positives.

A review of methods for detecting single-nucleotide polymorphisms in the Toll-like receptor gene family

The Toll-like receptors play an essential role in immunity through targeting the pathogen-associated molecular patterns. Nucleotide variations in TLR genes, especially single-nucleotide polymorphisms, have been shown to alter host immune susceptibility to several infections and diseases. Since TLR genes' polymorphisms can be a promising biomarker, ongoing investigations aim to develop, optimize and validate SNP detection methods. This review discusses various TLR SNP detection methods, either used extensively or occasionally, but having a vast potential in high-throughput settings. Methods such as PCR-restriction fragment length polymorphism, TaqMan^® assay, direct sequencing and matrix-assisted laser desorption ionization - time of flight mass spectroscopy MS are frequently used methods whereas Illumina GoldenGate^® assay, reverse hybridization technology, PCR-confronting two-pair primers, KBiosciences KASPar^® SNP assay, SNP stream^®, PCR-fluorescence hybridization and SNaPshot^® are powerful but sporadically used methods. We suggest that, for individual laboratories, the detection method of choice depends on a combination of factors such as throughput volume, reproducibility, feasibility and cost-effectiveness.

TLR4 Polymorphisms and Expression in Solid Cancers

Toll-like receptors (TLRs) are a type of pattern-recognition receptor (PRR) that are part of the innate immune system known to recognize pathogen-associated molecular patterns and thereby play a crucial role in host immune response. Among the various known TLRs, TLR4 is one of the most extensively studied PRRs expressed by immune, certain nonimmune, and tumor cells. When TLR4 binds with the bacterial lipopolysaccharide, it induces production of proinflammatory cytokines, chemokines, and effector molecules as part of the immune response. Continuous exposure to pathogens and TLR4 signaling results in chronic inflammation that may further lead to malignant transformation. TLR4 is a highly polymorphic gene, and genetic variations are known to influence host immune response, leading to dysregulation of signaling pathway, which may affect an individual's susceptibility to various diseases, including cancer. Furthermore, TLR4 expression in different tumor types may also serve as a marker for tumor proliferation, differentiation, metastasis, prognosis, and patient survival. This review aims to summarize various reports related to TLR4 polymorphisms and expression patterns and their influences on different cancer types with a special focus on solid tumors.