Does metformin really reduce prostate cancer risk: an up-to-date comprehensive genome-wide analysis
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ABSTRACT:
SUBMITTER: Zhang X
PROVIDER: S-EPMC11241920 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:The role of metformin in prostate cancer chemoprevention remains unclear. REDUCE, which followed biopsy-negative men with protocol-dictated PSA-independent biopsies at 2- and 4-years, provides an opportunity to evaluate the link between metformin use and prostate cancer diagnosis with minimal confounding from screening biases. In diabetic men from REDUCE, we tested the association between metformin use, use of other antidiabetic medications, versus no antidiabetic medication use, and prostate cancer diagnosis as well as prostate cancer grade (low-grade Gleason 4-6 and high-grade Gleason 7-10) using logistic regression. Of the 540 diabetic men with complete data, 205 (38%) did not report use of any antidiabetic medications, 141 (26%) reported use of at least one antidiabetic medication other than metformin, and 194 (36%) reported use of metformin. During the 4-year study, 122 men (23%) were diagnosed with prostate cancer. After adjusting for various clinical and demographic characteristics, we found that metformin use was not significantly associated with total (OR, 1.19; P = 0.50), low- (OR, 1.01; P = 0.96), or high-grade (OR, 1.83; P = 0.19) prostate cancer diagnosis. Likewise, there was no significant association between the use of non-metformin antidiabetic medications and prostate cancer risk in both crude (OR, 1.02; P = 0.95) and multivariable analysis (OR, 0.85; P = 0.56). Furthermore, the interactions between antidiabetic medication use and BMI, geographic location, coronary artery disease, smoking, and treatment group were not significant (all P > 0.05). Among diabetic men with a negative prestudy biopsy who all underwent biopsies largely independent of PSA, metformin use was not associated with reduced risk of prostate cancer diagnosis.
| S-EPMC4651624 | biostudies-literature
Project description:Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.
| S-EPMC9260602 | biostudies-literature
Project description:Base substitution catalogues represent historical records of mutational processes that have been active in a cell. Such processes can be distinguished by various characteristics, like mutation type, sequence context, transcriptional and replicative strand bias, genomic distribution and association with (epi)-genomic features.We have created MutationalPatterns, an R/Bioconductor package that allows researchers to characterize a broad range of patterns in base substitution catalogues to dissect the underlying molecular mechanisms. Furthermore, it offers an efficient method to quantify the contribution of known mutational signatures within single samples. This analysis can be used to determine whether certain DNA repair mechanisms are perturbed and to further characterize the processes underlying known mutational signatures.MutationalPatterns allows for easy characterization and visualization of mutational patterns. These analyses willsupport fundamental research into mutational mechanisms and may ultimately improve cancer diagnosis and treatment strategies. MutationalPatterns is freely available at http://bioconductor.org/packages/MutationalPatterns .
| S-EPMC5922316 | biostudies-other
Project description:BackgroundNo single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS).ObjectiveTo test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.Design, setting, and participantsSNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.Outcome measurements and statistical analysisOdds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.Results and limitationsA total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.ConclusionsWe did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.Patient summaryWe evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.
| S-EPMC4359641 | biostudies-literature
Project description:Date palms (Phoenix dactylifera) are an important fruit crop of arid regions of the Middle East and North Africa. Despite its importance, few genomic resources exist for date palms, hampering evolutionary genomic studies of this perennial species. Here we report an improved long-read genome assembly for P. dactylifera that is 772.3 Mb in length, with contig N50 of 897.2 Kb, and use this to perform genome-wide association studies (GWAS) of the sex determining region and 21 fruit traits. We find a fruit color GWAS at the R2R3-MYB transcription factor VIRESCENS gene and identify functional alleles that include a retrotransposon insertion and start codon mutation. We also find a GWAS peak for sugar composition spanning deletion polymorphisms in multiple linked invertase genes. MYB transcription factors and invertase are implicated in fruit color and sugar composition in other crops, demonstrating the importance of parallel evolution in the evolutionary diversification of domesticated species.
| S-EPMC6794320 | biostudies-literature
Project description:Metformin, an oral biguanide used for first-line treatment of type 2 diabetes mellitus, has attracted attention for its anti-proliferative and anti-cancer effects in several solid tumors, including prostate cancer (PCa). Liver kinase B1 (LKB1) and adenosine monophosphate-activated protein kinase (AMPK) activation, inhibition of the mammalian target of rapamycin (mTOR) activity and protein synthesis, induction of apoptosis and autophagy by p53 and p21, and decreased blood insulin level have been suggested as direct anti-cancer mechanisms of metformin. Research has shown that PCa development and progression are associated with metabolic syndrome and its components. Therefore, reduction in the risk of PCa and improvement in survival in metformin users may be the results of the direct anti-cancer mechanisms of the drug or the secondary effects from improvement of metabolic syndrome. In contrast, some research has suggested that there is no association between metformin use and PCa incidence or survival. In this comprehensive review, we summarize updated evidence on the relationship between metformin use and oncological effects in patients with PCa. We also highlight ongoing clinical trials evaluating metformin as an adjuvant therapy in novel drug combinations in various disease settings.
| S-EPMC7698147 | biostudies-literature
Project description:Prostate cancer (PC) is the most common malignancy observed in men. It is evident that genetic factors play some important roles in PC etiology. Recently, genome-wide association studies in diverse ethnic groups have identified more than 40 germline variants of various genes or chromosomal loci that are significantly associated with PC susceptibility, including multiple 8q24 loci, prostate-specific genes, metabolic and hormone-related genes, and many regions where no coding gene is annotated. However, there are only a few variants or genes for which biological significance or functions have been elucidated so far. The greatest challenge related to genome-wide association studies loci in prostate genomics is to understand the functional consequences of these PC-associated loci and their involvement in PC biology and carcinogenesis. There have been attempts to determine PC risk estimations by combining multiple PC-associated variants for clinical tests, and these can identify a very minor population with high risk of PC. However, they cannot distinguish risk of aggressive PC from that of non-aggressive PC. Further identification of PC-susceptibility loci in larger genome-wide association studies cohorts and biological insights gained from such functional analyses have the potential to translate into clinical benefits, including the development of reliable biomarkers, risk estimation, and effective strategies for screening and prevention of PC.
| S-EPMC7659324 | biostudies-literature
Project description:BackgroundOver the last decade, genome-wide association studies (GWAS) have discovered many risk associated single nucleotide polymorphisms (SNPs) of prostate cancer (PCa). However, the majority of the associated PCa SNPs, including those in linkage disequilibrium (LD) blocks, are generally not located in protein coding regions. The systematical investigation of the functional roles of these SNPs, especially the non-coding SNPs, becomes very necessary and helpful to the understanding of the molecular mechanism of PCa.ResultsIn this work, we proposed a comprehensive framework at network level to integrate the SNP annotation, target gene assignment, gene ontology (GO) classification, pathway enrichment analysis and regulatory network reconstruction to illustrate the molecular functions of PCa associated SNPs. By LD expansion, we first identified 1828 LD SNPs using 49 reported GWAS SNPs as a start. We carefully annotated these 1828 LD SNPs via either UCSC known genes, UCSC regulation elements, or expression Quantitative Trait Loci (eQTL) data. As a result, we found 1154 SNPs were functionally annotated and obtained 205 unique PCa genes for further enrichment analysis. The enriched GO biological processes and pathways were found mainly related to regulation of cell death, apoptosis, cell proliferation, and metabolic process, which have been proved essential to cancer development. We constructed PCa genes specific transcription regulatory networks, finding several important genetic regulators for PCa, such as IGF-1/IGF-2 receptors, SP1, CREB1, and androgen receptor (AR).ConclusionsA comprehensive framework was proposed for integrative and systematic analysis of PCa SNPs, the analysis can provide essential information for the understanding of the regulatory function of GWAS SNPs in PCa, and will facilitate the discovery of novel candidate biomarkers for diagnosis and prognosis of PCa.
| S-EPMC4042239 | biostudies-literature
Project description:The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
| S-EPMC10841479 | biostudies-literature
Project description:Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations- we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r^2≥0.5. Greater than 88% of the 727 SNPs fall within putative enhancers, many of which alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid in the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancer regions, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r^2=0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a preliminary step in connecting risk to disease process. ChIP-seq analysis of H3K27Ac in LNCaP charcoal-stripped serum, H3K27Ac in LNCaP charcoal-stripped serum +DHT, TCF7L2 in LNCaP
2014-01-28 | E-GEOD-51621 | biostudies-arrayexpress