An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

Wu, Lang; Yang, Yaohua; Guo, Xingyi; Shu, Xiao Ou; Cai, Qiuyin; Li, Bingshan; Tao, Ran; Wu, Chong; Nikas, Jason B.; Sun, Yanfa; Zhu, Jingjing; Roobol, Monique J.; Giles, Graham G.; Brenner, Hermann; John, Esther M.; Clements, Judith A.; Grindedal, Eli Marie; Park, Jong Y.; Stanford, Janet L.; Kóte-Jarai, Zsofia; Haiman, Christopher A.; Eeles, Rosalind; Wang, Zheng; Long, Jirong

doi:10.1038/s41467-020-17673-9

Cited by 37 publications

(32 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This step has led to the evaluation of the genomic alterations in cancers as a global network of molecular events, generating a huge amount of data from single cancer specimens [ 1 ]. Moreover, together with advances in genomics, many other ‘‐omics’ techniques have emerged and have been made available, allowing the generation of multidimensional datasets (genomes, transcriptomes, proteomes, phosphoproteomes, metabolomes) from individuals [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. This global approach might be regarded as capturing any aspect of the biology of cancer, but also implies a shift in our ability to interpret data and to generalize evidence derived from a single patient to a multitude of individuals with the same disease.…”

Section: Global Genomic Profiling: From the Tcga To The Igcg‐argo Projectsmentioning

confidence: 99%

Global mapping of cancers: The Cancer Genome Atlas and beyond

et al. 2021

View full text Add to dashboard Cite

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The

show abstract

Section: Global Genomic Profiling: From the Tcga To The Igcg‐argo Projectsmentioning

confidence: 99%

Global mapping of cancers: The Cancer Genome Atlas and beyond

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The prostate cancer GWAS summary statistics data were generated from 79,194 prostate cancer cases and 61,112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL. [31][32][33] Using the OncoArray platform, 46,939 prostate cancer cases and 27,910 controls were genotyped comprising 570,000 SNPs (http://epi.grants.cancer.gov/oncoarray/). The remaining included participants were from several GWAS, namely, BPC3, CaPS 1 and CaPS 2, iCOGS, NCI PEGASUS, and UK stage 1 and stage 2.…”

Section: Association Analysis Between Genetically Predicted N-glycan Levels and Prostate Cancer Riskmentioning

confidence: 99%

Associations Between Genetically Predicted Plasma N-Glycans and Prostate Cancer Risk: Analysis of Over 140,000 European Descendants

Liu

Zhu

Zhao

et al. 2021

PGPM

Self Cite

View full text Add to dashboard Cite

Background Previous studies suggest a potential link between glycosylation and prostate cancer. To better characterize the relationship between the two, we performed a study to comprehensively evaluate the associations between genetically predicted blood plasma N-glycan levels and prostate cancer risk. Methods Using genetic variants associated with N-glycan levels as instruments, we evaluated the associations between levels of 138 plasma N-glycans and prostate cancer risk. We analyzed data of 79,194 cases and 61,112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL. Results We identified three N-glycans with genetically predicted levels in plasma to be associated with prostate cancer risk after Bonferroni correction. The estimated odds ratios (95% confidence intervals) were 1.29 (1.20–1.40), 0.80 (0.74–0.88), and 0.79 (0.72–0.87) for PGP18, PGP33, and PGP109, respectively, per every one standard deviation increase in genetically predicted levels of N-glycan. However, the instruments for these N-glycans only involved one to two variants. The proportions of variations that can be explained by the instruments range from 1.58% to 2.95% for these three N-glycans. Conclusion We observed associations between genetically predicted levels of three N-glycans PGP18, PGP33, and PGP109 and prostate cancer risk. Given the correlated nature of the N-glycans and that many N-glycans share genetic loci, pleiotropy is a major concern. Future work is warranted to better characterize the relationship between N-glycans and prostate cancer.

show abstract

“…Out of those, 42 CpG sites were also correlated with altered expression of 28 target genes, 11 of which were subsequently validated in the TCGA cohort. Among the most promising genes altered, as a result of the CpG methylation, were nuclear ubiquitous casein and cyclin-dependent kinases substrate [NUCKS1; odds ratio (OR) of 1.35; p = 3.59 × 10 −5 ], complement C4B gene (OR of 0.79; p = 2.18 × 10 −4 ), cilia and flagella associated protein 44 (CFAP44; OR of 1.91; p = 9.11 × 10 −14 ) [38]. Yet, validation of the above methylation targets in the appropriate clinical setting is required to demonstrate potential value as markers for PCa risk.…”

Section: Commercially Available Omics-driven Biomarker Tests With Diagnostic Potentialmentioning

confidence: 99%

Omics Derived Biomarkers and Novel Drug Targets for Improved Intervention in Advanced Prostate Cancer

et al. 2020

View full text Add to dashboard Cite

Prostate cancer (PCa) is one of the most frequently diagnosed malignancies, and the fifth leading cause of cancer related mortality in men. For advanced PCa, radical prostatectomy, radiotherapy, and/or long-term androgen deprivation therapy are the recommended treatment options. However, subsequent progression to metastatic disease after initial therapy results in low 5-year survival rates (29%). Omics technologies enable the acquisition of high-resolution large datasets that can provide insights into molecular mechanisms underlying PCa pathology. For the purpose of this article, a systematic literature search was conducted through the Web of Science Database to critically evaluate recent omics-driven studies that were performed towards: (a) Biomarker development and (b) characterization of novel molecular-based therapeutic targets. The results indicate that multiple omics-based biomarkers with prognostic and predictive value have been validated in the context of PCa, with several of those being also available for commercial use. At the same time, omics-driven potential drug targets have been investigated in pre-clinical settings and even in clinical trials, holding the promise for improved clinical management of advanced PCa, as part of personalized medicine pipelines.

show abstract

An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

Cited by 37 publications

References 71 publications

Global mapping of cancers: The Cancer Genome Atlas and beyond

Global mapping of cancers: The Cancer Genome Atlas and beyond

Associations Between Genetically Predicted Plasma N-Glycans and Prostate Cancer Risk: Analysis of Over 140,000 European Descendants

Omics Derived Biomarkers and Novel Drug Targets for Improved Intervention in Advanced Prostate Cancer

Contact Info

Product

Resources

About