Genome-wide association studies (GWAS) have identified rs11672691 at 19q13 associated with aggressive prostate cancer (PCa). Here, we independently confirmed the finding in a cohort of 2,738 PCa ...patients and discovered the biological mechanism underlying this association. We found an association of the aggressive PCa-associated allele G of rs11672691 with elevated transcript levels of two biologically plausible candidate genes, PCAT19 and CEACAM21, implicated in PCa cell growth and tumor progression. Mechanistically, rs11672691 resides in an enhancer element and alters the binding site of HOXA2, a novel oncogenic transcription factor with prognostic potential in PCa. Remarkably, CRISPR/Cas9-mediated single-nucleotide editing showed the direct effect of rs11672691 on PCAT19 and CEACAM21 expression and PCa cellular aggressive phenotype. Clinical data demonstrated synergistic effects of rs11672691 genotype and PCAT19/CEACAM21 gene expression on PCa prognosis. These results provide a plausible mechanism for rs11672691 associated with aggressive PCa and thus lay the ground work for translating this finding to the clinic.
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•SNP rs11672691 at 19q13 associates with aggressive PCa, PCAT19, and CEACAM21 expression•rs11672691 G empowers prognostic factor HOXA2 to elevate its eQTL gene expression•rs11672691 directly impacts gene regulation, PCa cellular phenotype, and progression•rs11672691 genotype and PCAT19 or CEACAM21 expression synergize in PCa prognosis
A non-coding risk allele associated with aggressive prostate cancer creates a transcription factor binding site that in turn promotes oncogenesis by impacting expression of nearby genes.
Motivation Annotation of large amounts of generated sequencing data is a demanding task. Most of the currently available robust annotation tools, like ANNOVAR, are command-line based tools which ...require a certain degree of programming skills. User-friendly tools for variant annotation of sequencing data with graphical interface are under-represented. Results We have developed an interactive application, which harnesses the easy usability of R Shiny and combines it with the versatile annotation features of ANNOVAR. This application is easy to use and gives comprehensive annotations for user supplied vcf files using multiples databases. The output table contains the list of variants and their corresponding annotation presented within the graphical interface. In addition, the annotation results are downloadable as text file.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Prostate cancer is globally the second most commonly diagnosed cancer type in men. Recent studies suggest that mutations in DNA repair genes are associated with aggressive forms of prostate cancer ...and castration resistance. Prostate cancer with DNA repair defects may be vulnerable to therapeutic targeting by Poly(ADP-ribose) polymerase (PARP) inhibitors. PARP enzymes modify target proteins with ADP-ribose in a process called PARylation and are in particular involved in single strand break repair. The rationale behind the clinical trials that led to the current use of PARP inhibitors to treat cancer was to target the dependence of BRCA-mutant cancer cells on the PARP-associated repair pathway due to deficiency in homologous recombination. However, recent studies have proposed therapeutic potential for PARP inhibitors in tumors with a variety of vulnerabilities generating dependence on PARP beyond the synthetic lethal targeting of BRCA1/BRCA2 mutated tumors, suggesting a wider potential than initially thought. Importantly, PARP-associated DNA repair pathways are also closely connected to androgen receptor (AR) signaling, which is a key regulator of tumor growth and a central therapeutic target in prostate cancer. In this review, we provide an extensive overview of published and ongoing trials exploring PARP inhibitors in treatment of prostate cancer and discuss the underlying biology. Several clinical trials are currently studying PARP inhibitor mono- and combination therapies in the treatment of prostate cancer. Integration of drugs targeting DNA repair pathways in prostate cancer treatment modalities allows developing of more personalized care taking also into account the genetic makeup of individual tumors.
Distinguishing aggressive prostate cancer from indolent disease improves personalized treatment. Although only few genetic variants are known to predispose to aggressive prostate cancer, synergistic ...interactions of
G84E high-risk prostate cancer susceptibility mutation with other genetic loci remain unknown. The purpose of this study was to examine the interplay of
rs138213197 (G84E) and
rs2278911 (R229Q) germline variants on prostate cancer risk.
Genotyping was done in Finnish discovery cohort (
= 2,738) and validated in Swedish (
= 3,132) and independent Finnish (
= 1,155) prostate cancer cohorts. Expression pattern analysis was followed by functional studies in prostate cancer cell models.
Interplay of
(G84E) and
(R229Q) variants results in highest observed inherited prostate cancer risk (OR, 21.1;
= 0.000024). In addition, this synergism indicates a significant association of
T and
T dual carriers with elevated risk for high Gleason score (OR, 2.3;
= 0.025) and worse prostate cancer-specific life expectancy (HR, 3.9;
= 0.048), and it is linked with high PSA at diagnosis (OR, 3.30;
= 0.028). Furthermore, combined high expression of
correlates with earlier biochemical recurrence. Finally, functional experiments showed that ectopic expression of variants stimulates prostate cancer cell growth and migration. In addition, we observed strong chromatin binding of HOXB13 at
locus and revealed that
functionally promotes
transcription. The study is limited to retrospective Nordic cohorts.
Simultaneous presence of
T and
T alleles confers for high prostate cancer risk and aggressiveness of disease, earlier biochemical relapse, and lower disease-specific life expectancy. HOXB13 protein binds to
gene and functionally promotes
transcription.
Prostate cancer (PrCa) is one of the most common cancers in men, but little is known about factors affecting its clinical outcomes. Genome-wide association studies have identified more than 170 ...germline susceptibility loci, but most of them are not associated with aggressive disease. We performed a genome-wide analysis of 185,478 SNPs in Finnish samples (2738 cases, 2400 controls) from the international Collaborative Oncological Gene-Environment Study (iCOGS) to find underlying PrCa risk variants. We identified a total of 21 common, low-penetrance susceptibility loci, including 10 novel variants independently associated with PrCa risk. Novel risk loci were located in the 8q24 (CASC8 rs16902147, OR 1.86, p
= 3.53 × 10
and rs58809953, OR 1.71, p
= 4.00 × 10
; intergenic rs79012498, OR 1.81, p
= 4.26 × 10
), 17q21 (SP6 rs2074187, OR 1.66, p
= 3.75 × 10
), 11q13 (rs12795301, OR 1.42, p
= 2.89 × 10
) and 8p21 (rs995432, OR 1.38, p
= 3.00 × 10
) regions. Here, we describe SP6, a transcription factor gene, as a new, potentially high-risk gene for PrCa. The intronic variant rs2074187 in SP6 was associated not only with overall susceptibility to PrCa (OR 1.66) but also with a higher odds ratio for aggressive PrCa (OR 1.89) and lower odds for non-aggressive PrCa (OR 1.43). Furthermore, the new intergenic variant rs79012498 at 8q24 conferred risk for aggressive PrCa. Our findings highlighted the power of a population-stratified approach to identify novel, clinically actionable germline PrCa risk loci and strongly suggested SP6 as a new PrCa candidate gene that may be involved in the pathogenesis of PrCa.
Pharmacogenomic biomarker availability of Hungarian Summaries of Product Characteristics (SmPC) was assembled and compared with the information in US Food and Drug Administration (FDA) drug labels of ...the same active substance (July 2019). The level of action of these biomarkers was assessed from The Pharmacogenomics Knowledgebase database. From the identified 264 FDA approved drugs with pharmacogenomic biomarkers in drug label, 195 are available in Hungary. From them, 165 drugs include pharmacogenomic data disposing 222 biomarkers. Most of them are metabolizing enzymes (46%) and pharmacological targets (41%). The most frequent therapeutic area is oncology (37%), followed by infectious diseases (12%) and psychiatry (9%) (p < 0.00001). Most common biomarkers in Hungarian SmPCs are CYP2D6, CYP2C19, estrogen and progesterone hormone receptor (ESR, PGS). Importantly, US labels present more specific pharmacogenomic subheadings, the level of action has a different prominence, and offer more applicable dose modifications than Hungarians (5% vs 3%). However, Hungarian SmPCs are at 9 oncology drugs stricter than FDA, testing is obligatory before treatment. Out of the biomarkers available in US drug labels, 62 are missing completely from Hungarian SmPCs (p < 0.00001). Most of these belong to oncology (42%) and in case of 11% of missing biomarkers testing is required before treatment. In conclusion, more factual, clear, clinically relevant pharmacogenomic information in Hungarian SmPCs would reinforce implementation of pharmacogenetics. Underpinning future perspective is to support regulatory stakeholders to enhance inclusion of pharmacogenomic biomarkers into Hungarian drug labels and consequently enhance personalized medicine in Hungary.
BioCPR–A Tool for Correlation Plots Fey, Vidal; Jambulingam, Dhanaprakash; Sara, Henri ...
Data (Basel),
09/2021, Letnik:
6, Številka:
9
Journal Article
Recenzirano
Odprti dostop
A gene is a sequence of DNA bases through which genetic information is passed on to the next generation. Most genes encode for proteins that ultimately control cellular function. Understanding the ...interrelation between genes without the application of statistical methods can be a daunting task. Correlation analysis is a powerful approach to determine the strength of association between two variables (e.g., gene-wise expression). Moreover, it becomes essential to visualize this data to establish patterns and derive insight. The most common method for gene expression visualization is to use correlation heatmaps in which the colors of the plot represent strength of co-expression. In order to address this requirement, we developed a visualization tool called BioCPR: Biological Correlation Plots in R. This tool performs both correlation analysis and subsequent visualization in the form of an interactive heatmap, improving both usability and interpretation of the data. BioCPR is an R Shiny-based application and can be run locally in Rstudio or a web browser.
Pairs of related bladder cancer cases who belong to pedigrees with an excess of bladder cancer were sequenced to identify rare, shared variants as candidate predisposition variants. Candidate ...variants were tested for association with bladder cancer risk. A validated variant was assayed for segregation to other related cancer cases, and the predicted protein structure of this variant was analyzed. This study of affected bladder cancer relative pairs from high-risk pedigrees identified 152 bladder cancer predisposition candidate variants. One variant in
(ETS Repressing Factor) was significantly associated with bladder cancer risk in an independent population, was observed to segregate with bladder and prostate cancer in relatives, and showed evidence for altering the function of the associated protein. This finding of a rare variant in
that is strongly associated with bladder and prostate cancer risk in an extended pedigree both validates
as a cancer predisposition gene and shows the continuing value of analyzing affected members of high-risk pedigrees to identify and validate rare cancer predisposition variants.
The RTK/ERK signaling pathway has been implicated in prostate cancer progression. However, the genetic relevance of this pathway to aggressive prostate cancer at the SNP level remains undefined. Here ...we performed a SNP and gene-based association analysis of the RTK/ERK pathway with aggressive prostate cancer in a cohort comprising 956 aggressive and 347 non-aggressive cases. We identified several loci including rs3217869/CCND2 within the pathway shown to be significantly associated with aggressive prostate cancer. Our functional analysis revealed a statistically significant relationship between rs3217869 risk genotype and decreased CCND2 expression levels in a collection of 119 prostate cancer patient samples. Reduced expression of CCND2 promoted cell proliferation and its overexpression inhibited cell growth of prostate cancer. Strikingly, CCND2 downregulation was consistently observed in the advanced prostate cancer in 18 available clinical data sets with a total amount of 1,095 prostate samples. Furthermore, the lower expression levels of CCND2 markedly correlated with prostate tumor progression to high Gleason score and elevated PSA levels, and served as an independent predictor of biochemical relapse and overall survival in a large cohort of prostate cancer patients. Together, we have identified an association of genetic variants and genes in the RTK/ERK pathway with prostate cancer aggressiveness, and highlighted the potential importance of CCND2 in prostate cancer susceptibility and tumor progression to metastasis.
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