SNP-SNP interactions as risk factors for aggressive prostate cancer

Vaidyanathan, Venkatesh; Naidu, Vijay; Karunasinghe, Nishi; Jabed, Anower; Pallati, Radha; Marlow, Gareth; Ferguson, Lynnette R.

doi:10.12688/f1000research.11027.1

Cited by 10 publications

(2 citation statements)

References 35 publications

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“…Lumbar disc herniation is determined by multiple genetic and environmental interactions. Single nucleotide polymorphisms (SNPs) are increasingly becoming candidate biomarkers for determining susceptibility to complex diseases (Vaidyanathan et al, 2017). A single SNP in a single gene may not be enough to affect overall cancer risk.…”

Section: Discussionmentioning

confidence: 99%

Association of GSDMC polymorphisms with lumbar disc herniation among Chinese Han population

Sun

Xiong

et al. 2020

Int J Immunogenetics

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Lumbar disc herniation (LDH) is a relatively common spinal disease, but its pathogenesis is still unknown. Numerous studies have shown that LDH is closely correlated with inflammation, and it has been found to be related to some single nucleotide polymorphisms (SNPs). Our purpose is to explore the correlation between gene polymorphisms of GSDMC and LDH risk, which is of great significance for the study of the pathogenesis of LDH. DNA was extracted from 508 LDH patients and 508 controls. We select SNPs with minor allele frequency >5% in GSDMC gene from 1,000 genome project (http://www.internationalgenome.org/). Then, genotyping was performed using Agena MassARRAY. We used unconditional logistic regression analysis to calculate odds ratios (ORs) and 95% confidence intervals (CIs). The haplotype construction and analysis in GSDMC were applied to detect the association. We identified that rs77681114 in the GSDMC gene was significantly associated with a decreased risk of LDH in the alleles model (OR = 0.81, 95% CI = 0.66–0.99, p = .049) and the log‐additive model (OR = 0.81, 95% CI = 0.65–0.99, p = .049) adjusted by age and gender. The haplotype “AG” constructed by rs77681114 and rs4285452 (OR = 1.24, 95% CI = 1.01–1.53, p = .039) was associated with increased risk of LDH. After age and gender stratification, rs77681114 protected LDH risk at age 49 or older in allelic model (p = .010), co‐dominant model (p = .006), dominant model (p = .029), recessive model (p = .011) and log‐additive model (p = .005). Rs77681114 had protective effect on female LDH risk in both co‐dominant models (p = .033) and recessive models (p = .043). These studies indicated that genetic polymorphisms of GSDMC can relatively reduce the risk of LDH.

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Section: Discussionmentioning

confidence: 99%

Association of GSDMC polymorphisms with lumbar disc herniation among Chinese Han population

Sun

Xiong

et al. 2020

Int J Immunogenetics

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“…Furthermore, it has been shown that mutations and GVs involved in cell expansion interact in an organized manner in prostate cancer, implying that GVs can work with mutations as "tumor co-suppressors" or "co-oncogenes" [66,67]. Aggressive forms of prostate cancer, for instance, have been found in individuals with SNPs-SNPs communication with variants such as MMP16, CSF1, EGFR, and more [68,69]. Besides, the consequences are even more complex to predict because GVs affect risk at the epigenetic level [70] and are affected by additional environmental factors [71].…”

Section: Prostate Cancer (Pc)mentioning

confidence: 99%

Polygenic and Network-based studies in risk identification and demystification of cancer

Hadi

Ayoub

Bachir

et al. 2022

Expert Review of Molecular Diagnostics

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Introduction: Diseases were initially thought to be the consequence of a single gene mutation. Advances in DNA sequencing tools and our understanding of gene behavior have revealed that complex diseases, such as cancer, are the product of genes cooperating with each other and with their environment in orchestrated communication networks. Seeing that the function of individual genes is still used to analyze cancer, the shift to using functionally interacting groups of genes as a new unit of study holds promise for demystifying cancer. Areas Covered:The literature search focused on three types of cancer, namely breast, lung, and prostate, but arguments from other cancers were also included. The aim was to prove that multigene analyses can accurately predict and prognosticate cancer risk, subtype cancer for more personalized and effective treatments, and discover anti-cancer therapies. Computational intelligence is being harnessed to analyze this type of data and is proving indispensable to scientific progress.Expert Opinion: In the future, comprehensive profiling of all kinds of patient data (e.g., serum molecules, environmental exposures) can be used to build universal networks that should help us elucidate the molecular mechanisms underlying diseases and provide appropriate preventive measures, ensuring lifelong health and longevity. Article highlights:• Diseases were originally thought to be the result of a single gene mutation, but advances in DNA sequencing have proven otherwise.• Methods for classifying genetic variants are evolving, and they all show that genetic variants need to be studied in a more robust manner.• Complex diseases occur when the right environmental factors and SNPs exist. The latter are accumulating without understanding their significance, requiring integration into multiomic studies.• Gene networks are dominated by universal laws, proving they are credible to consider as the new "units of study" instead of single genes.• Network and polygenic studies allow for more accurate prediction and prognosis of cancer risk, treatment-useful cancer subtyping, and the discovery of interesting cancer therapies.• Comprehensive network studies integrating all types of data (e.g. transcriptomics, blood serum omics, and environmental agents) are the future of medical care.

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Genome plasticity and endocrine diseases

Wang

Tan

et al. 2020

Genome Plasticity in Health and Disease

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SNP-SNP interactions as risk factors for aggressive prostate cancer

Cited by 10 publications

References 35 publications

Association of GSDMC polymorphisms with lumbar disc herniation among Chinese Han population

Association of GSDMC polymorphisms with lumbar disc herniation among Chinese Han population

Polygenic and Network-based studies in risk identification and demystification of cancer

Genome plasticity and endocrine diseases

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