Variants of the hK2 protein gene (KLK2) are associated with serum hK2 levels and predict the presence of prostate cancer at biopsy

Construction of a prognostic risk model for clear cell renal cell carcinomas based on centrosome amplification-related genes

Clear cell renal cell carcinoma (ccRCC) is the urological malignancy with the highest incidence, centrosome amplification-associated genes (CARGs) have been suggested to be associated with carcinogenesis, but their roles in ccRCC are still incompletely understood. This study utilizes bioinformatics to explore the role of CARGs in the pathogenesis of ccRCC and to establish a prognostic model for ccRCC related to CARGs. Based on publicly available ccRCC datasets, 2312 differentially expressed genes (DEGs) were identified (control vs. ccRCC). Disease samples were classified into high and low scoring groups based on CARG scores and analysed for differences to obtain 345 DEGs associated with CARG scores (S-DEGs). 137 candidate genes were obtained by taking the intersection of DEGs and S-DEGs. Six prognostic genes (PCP4, SLN, PI3, PROX1, VAT1L, and KLK2) were then screened by univariate Cox, LASSO, and multifactorial Cox regression. These genes exhibit a high degree of enrichment in ribosome-associated pathways. Both risk score and age were independent prognostic factors, and the Nomogram constructed based on them had a good predictive performance (AUC > 0.7). In addition, immunological analyses identified 6 different immune cells and 23 immune checkpoints between the high- and low-risk groups, whereas mutational analyses identified frequent VHL mutations in both high- and low-risk groups. Finally, 93 potentially sensitive drugs were identified. In conclusion, this study identified six CARGs as prognostic genes for ccRCC and established a risk model with predictive value. These findings provide insights for prognostic prediction of ccRCC, optimisation of clinical management and development of targeted therapeutic strategies.

Genetic polymorphisms at 19q13.33 are associated with [-2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer

BACKGROUND

Prostate health index (phi), a derivative of [-2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility.

METHODS

We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index.

RESULTS

We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (P_combined  = 5.73 × 10^-9 ), was also associated with phi values (P_combined  = 3.20 × 10^-6 ). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p < .01).

CONCLUSION

Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.

Transcriptional landscape of PTEN loss in primary prostate cancer

BACKGROUND

PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. In this study, we highlight the transcriptional changes associated with PTEN loss in PCa.

METHODS

Using a meta-analysis approach, we leveraged two large PCa cohorts with experimentally validated PTEN and ERG status by Immunohistochemistry (IHC), to derive a transcriptomic signature of PTEN loss, while also accounting for potential confounders due to ERG rearrangements. This signature was expanded to lncRNAs using the TCGA quantifications from the FC-R2 expression atlas.

RESULTS

The signatures indicate a strong activation of both innate and adaptive immune systems upon PTEN loss, as well as an expected activation of cell-cycle genes. Moreover, we made use of our recently developed FC-R2 expression atlas to expand this signature to include many non-coding RNAs recently annotated by the FANTOM consortium. Highlighting potential novel lncRNAs associated with PTEN loss and PCa progression.

CONCLUSION

We created a PCa specific signature of the transcriptional landscape of PTEN loss that comprises both the coding and an extensive non-coding counterpart, highlighting potential new players in PCa progression. We also show that contrary to what is observed in other cancers, PTEN loss in PCa leads to increased activation of the immune system. These findings can help the development of new biomarkers and help guide therapy choices.

Identification of potential biomarkers and pivotal biological pathways for prostate cancer using bioinformatics analysis methods

Background

Prostate cancer (PCa) is a common urinary malignancy, whose molecular mechanism has not been fully elucidated. We aimed to screen for key genes and biological pathways related to PCa using bioinformatics method.

Methods

Differentially expressed genes (DEGs) were filtered out from the GSE103512 dataset and subjected to the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein–protein interactions (PPI) network was constructed, following by the identification of hub genes. The results of former studies were compared with ours. The relative expression levels of hub genes were examined in The Cancer Genome Atlas (TCGA) and Oncomine public databases. The University of California Santa Cruz Xena online tools were used to study whether the expression of hub genes was correlated with the survival of PCa patients from TCGA cohorts.

Results

Totally, 252 (186 upregulated and 66 downregulated) DEGs were identified. GO analysis enriched mainly in “oxidation-reduction process” and “positive regulation of transcription from RNA polymerase II promoter”; KEGG pathway analysis enriched mostly in “metabolic pathways” and “protein digestion and absorption.” Kallikrein-related peptidase 3, cadherin 1 (CDH1), Kallikrein-related peptidase 2 (KLK2), forkhead box A1 (FOXA1), and epithelial cell adhesion molecule (EPCAM) were identified as hub genes from the PPI network. CDH1, FOXA1, and EPCAM were validated by other relevant gene expression omnibus datasets. All hub genes were validated by both TCGA and Oncomine except KLK2. Two additional top DEGs (ABCC4 and SLPI) were found to be associated with the prognosis of PCa patients.

Conclusions

This study excavated the key genes and pathways in PCa, which might be biomarkers for diagnosis, prognosis, and potential therapeutic targets.

Pan-cancer analysis of clinical relevance of alternative splicing events in 31 human cancers

Alternative splicing represents a critical posttranscriptional regulation of gene expression, which contributes to the protein complexity and mRNA processing. Defects of alternative splicing including genetic alteration and/or altered expression of both pre-mRNA and trans-acting factors give rise to many cancers. By integrally analyzing clinical data and splicing data from TCGA and SpliceSeq databases, a number of splicing events were found clinically relevant in tumor samples. Alternative splicing of KLK2 (KLK2_51239) was found as a potential inducement of nonsense-mediated mRNA decay and associated with poor survival in prostate cancer. Consensus K-means clustering analysis indicated that alternative splicing events could be potentially used for molecular subtype classification of cancers. By random forest survival algorithm, prognostic prediction signatures with well performances were constructed for 31 cancers by using survival-associated alternative splicing events. Furthermore, an online tool for visualization of Kaplan-Meier plots of splicing events in 31 cancers was explored. Briefly, alternative splicing was found of significant clinical relevance with cancers.

Epidemiology of Prostate Cancer

Prostate cancer is the second most frequent cancer diagnosis made in men and the fifth leading cause of death worldwide. Prostate cancer may be asymptomatic at the early stage and often has an indolent course that may require only active surveillance. Based on GLOBOCAN 2018 estimates, 1,276,106 new cases of prostate cancer were reported worldwide in 2018, with higher prevalence in the developed countries. Differences in the incidence rates worldwide reflect differences in the use of diagnostic testing. Prostate cancer incidence and mortality rates are strongly related to the age with the highest incidence being seen in elderly men (> 65 years of age). African-American men have the highest incidence rates and more aggressive type of prostate cancer compared to White men. There is no evidence yet on how to prevent prostate cancer; however, it is possible to lower the risk by limiting high-fat foods, increasing the intake of vegetables and fruits and performing more exercise. Screening is highly recommended at age 45 for men with familial history and African-American men. Up-to-date statistics on prostate cancer occurrence and outcomes along with a better understanding of the etiology and causative risk factors are essential for the primary prevention of this disease.

Involvement of Kallikrein-Related Peptidases in Normal and Pathologic Processes

Human kallikrein-related peptidases (KLKs) are a subgroup of serine proteases that participate in proteolytic pathways and control protein levels in normal physiology as well as in several pathological conditions. Their complex network of stimulatory and inhibitory interactions may induce inflammatory and immune responses and contribute to the neoplastic phenotype through the regulation of several cellular processes, such as proliferation, survival, migration, and invasion. This family of proteases, which includes one of the most useful cancer biomarkers, kallikrein-related peptidase 3 or PSA, also has a protective effect against cancer promoting apoptosis or counteracting angiogenesis and cell proliferation. Therefore, they represent attractive therapeutic targets and may have important applications in clinical oncology. Despite being intensively studied, many gaps in our knowledge on several molecular aspects of KLK functions still exist. This review aims to summarize recent data on their involvement in different processes related to health and disease, in particular those directly or indirectly linked to the neoplastic process.

A genetic-based approach to personalized prostate cancer screening and treatment

PURPOSE OF REVIEW

Recent advances in sequencing technologies have allowed for the identification of genetic variants within germline DNA that can explain a significant portion of the genetic underpinnings of prostate cancer. Despite evidence suggesting that these genetic variants can be used for improved risk stratification, they have not yet been routinely incorporated into routine clinical practice. This review highlights their potential utility in prostate cancer screening.

RECENT FINDINGS

There are now almost 100 genetic variants, called single nucleotide polymorphisms (SNPs) that have been recently found to be associated with the risk of developing prostate cancer. In addition, some of these prostate cancer risk SNPs have also been found to influence prostate specific antigen (PSA) expression levels and potentially aggressive disease.

SUMMARY

Incorporation of panels of prostate cancer risk SNPs into clinical practice offers potential to provide improvements in patient selection for prostate cancer screening; PSA interpretation (e.g. by correcting for the presence of SNPs that influence PSA expression levels; decision for biopsy (using prostate cancer risk SNPs); and possibly the decision for treatment. A proposed clinical algorithm incorporating these prostate cancer risk SNPs is discussed.

Trp(250) -hK2 is defective in intracellular trafficking and activates the unfolded protein response

hK2, a member of the kallikrein protease family encoded by KLK2, is expressed exclusively in prostate and is a putative adjunct tumor marker for prostate cancer screening. The T allele of rs198977, a single nucleotide polymorphism in exon 5 of KLK2, codes for W-hK2 and is associated with lower serum hK2 levels and higher risk of prostate cancer than the C allele encoding R-hK2. To elucidate the mechanism that underlies this SNP's function, we transfected plasmids expressing R-hK2 or W-hK2 into PC3, HeLa and HEK293A cells and measured the hK2 level in cell lysates and conditioned media. The level of W-hK2 was lower than R-hK2 in conditioned media but was not different from R-hK2 in cell lysates. W-hK2 was hardly colocalized with Golgi-targeted fluorescent protein whereas R-hK2 colocalized. Reporter assays related to the unfolded protein response (UPR) and phospho-eIF2α immunoblot showed that W-hK2 increased UPR activity more than R-hK2. These results indicated that W-hK2 had a defect in cellular trafficking from the ER to the Golgi complex due to its misfolding and that it activated the UPR, suggesting a mechanism to explain the association of the T allele with higher prostate cancer risk.

Human kallikrein-2 gene and protein expression predicts prostate cancer at repeat biopsy

Purpose

The human kallikrein-2 (hK2) protein and two single nucleotide polymorphism (SNPs) (rs2664155, rs198977) of the gene are associated with prostate cancer risk. We examined whether hK2 protein and gene SNPs predict prostate cancer at the time of repeat biopsy.

Methods

We prospectively offered a repeat biopsy to men with a negative prostate biopsy performed for a PSA >4.0 ng/mL or abnormal Digital Rectal Exam (DRE) between 2001–2005. We genotyped and measured serum hK2 levels in 941 men who underwent a repeat prostate biopsy. Logistic regression analyses were conducted to determine the significance of KLK2 SNPs and hK2 levels for predicting cancer at repeat biopsy.

Results

Of the 941 patients, 180 (19.1%) were found to have cancer. The rs198977 SNP was positively associated with cancer at repeat biopsy (OR variant T allele = 1.8, 95% CI: 1.04-3.13, p = 0.049). When combined, the odds ratio for prostate cancer for patients with high hK2 levels and the variant T-allele of rs198977 was 3.77 (95% CI: 1.94-7.32, p < 0.0001), compared to patients with low hK2 levels and the C-allele. The addition of hK2 levels and KLK2 rs198977 to the baseline predictive model did not significantly increase the area under the curve from a baseline model of 0.67 to 0.69 (p = 0.6).

Conclusions

The KLK2 SNP rs198977 was positively associated with hK2 levels and predicts prostate cancer at the time of repeat prostate biopsy. Further characterization of the KLK2 gene will be needed to determine its clinical utility.

Genetic variation in KLK2 and KLK3 is associated with concentrations of hK2 and PSA in serum and seminal plasma in young men

BACKGROUND

Genetic variants in KLK2 and KLK3 have been associated with increased serum concentrations of their encoded proteins, human kallikrein-related peptidase 2 (hK2) and prostate-specific antigen (PSA), and with prostate cancer in older men. Low PSA concentrations in seminal plasma (SP) have been associated with low sperm motility. To evaluate whether KLK2 and KLK3 genetic variants affect physiological prostatic secretion, we studied the association of SNPs with hK2 and PSA concentrations in SP and serum of young, healthy men.

METHODS

Leukocyte DNA was extracted from 303 male military conscripts (median age 18.1 years). Nine SNPs across KLK2-KLK3 were genotyped. We measured PSA and hK2 in SP and serum using immunofluorometric assays. The association of genotype frequencies with hK2 and PSA concentrations was tested with the Kruskal-Wallis test.

RESULTS

Four KLK2 SNPs (rs198972, rs198977, rs198978, and rs80050017) were strongly associated with hK2 concentrations in SP and serum, with individuals homozygous for the major alleles having 3- to 7-fold higher concentrations than the intermediate concentrations found in other homozygotes and heterozygotes (all P < 0.001). Three of these SNPs were significantly associated with percentage of free PSA (%fPSA) in serum (all P < 0.007). Three KLK3 SNPs showed associations with PSA in SP, and the rs1058205 SNP was associated with total PSA in serum (P = 0.001) and %fPSA (P = 0.015).

CONCLUSIONS

Associations observed in young, healthy men between the SP and serum concentrations of hK2 and PSA and several genetic variants in KLK2 and KLK3 could be useful to refine models of PSA cutoff values in prostate cancer testing.

Genome-wide association study identifies loci at ATF7IP and KLK2 associated with percentage of circulating free PSA

BACKGROUND

Percentage of free-to-total prostate-specific antigen (%fPSA) is an independent predictor of risk for prostate cancer among men with modestly elevated level of total PSA (tPSA) in blood. Physiological and pathological factors have been shown to influence the %fPSA value and diagnostic accuracy.

MATERIALS/METHODS

To evaluate genetic determinants of %fPSA, we conducted a genome-wide association study of serum %fPSA by genotyping 642,584 single nucleotide polymorphisms (SNPs) in 3192 men of European ancestry, each with a tPSA level of 2.5 to 10 ng/ml, that were recruited in the REduction by DUtasteride of Prostate Cancer Events study. Single nucleotide polymorphisms (SNPs) with P < 10(-5) were further evaluated among the controls of a population-based case-control study in Sweden (2899 prostate cancer cases and 1722 male controls), including 464 controls having tPSA levels of 2.5 to 10 ng/ml.

RESULTS

We identified two loci that were associated with %fPSA at a genome-wide significance level (P <5 x 10(-8)). The first associated SNP was rs3213764 (P = 6.45 x 10(-10)), a nonsynonymous variant (K530R) in the ATF7IP gene at 12p13. This variant was also nominally associated with tPSA (P = .015). The second locus was rs1354774 (P = 1.25 x 10(-12)), near KLK2 at 19q13, which was not associated with tPSA levels, and is separate from the rs17632542 locus at KLK3 that was previously associated with tPSA levels and prostate cancer risk. Neither rs3213764 nor rs1354774 was associated with prostate cancer risk or aggressiveness.

CONCLUSIONS

These findings demonstrate that genetic variants at ATF7IP and KLK2 contribute to the variance of %fPSA.

Genome-wide association study identifies genetic determinants of urine PCA3 levels in men

Prostate cancer gene 3 (PCA3) is a non-coding gene specifically overexpressed in prostate cancer (PCa) that has great potential as a clinical biomarker for predicting prostate biopsy outcome. However, genetic determinants of PCA3 expression level remain unknown. To investigate the association between genetic variants and PCA3 mRNA level, a genome-wide association study was conducted in 1371 men of European descent in the REduction by DUtasteride of prostate Cancer Events trial. First-voided urine specimens containing prostate cells were obtained after digital rectal examination. The PROGENSA PCA3 assay was used to determine PCA3 score in the urinary samples. A linear regression model was used to detect the associations between (single nucleotide polymorphisms) SNPs and PCA3 score under an additive genetic model, adjusting for age and population stratification. Two SNPs, rs10993994 in β-microseminoprotein at 10q11.23 and rs10424878 in kallikrein-related peptidase 2 at 19q13.33, were associated with PCA3 score at genome-wide significance level (P = 1.22 x 10(-9) and 1.06 x 10(-8), respectively). Men carrying the rs10993994 "T" allele or rs10424878 "A" allele had higher PCA3 score compared with men carrying rs10993994 "C" allele or rs10424878 "G" allele (β = 1.25 and 1.24, respectively). This is the first comprehensive search for genetic determinants of PCA3 score. The novel loci identified may provide insight into the molecular mechanisms of PCA3 expression as a potential marker of PCa.

Association of Polymorphism rs198977 in Human Kallikrein-2 Gene (KLK2) with Susceptibility of Prostate Cancer: A Meta-Analysis

OBJECTIVES

To assess the association of polymorphism rs198977 in the human kallikrein-2 gene (KLK2) and risk of prostate cancer (PCa).

METHODS

Two investigators independently searched the PubMed, Elsevier, EMBASE, Web of Science, Wiley Online Library and Chinese National Knowledge Infrastructure (CNKI). Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) for rs198977 and PCa were calculated in a fixed-effects model (the Mantel-Haenszel method) and a random-effects model (the DerSimonian and Laird method) when appropriate.

RESULTS

Six studies met the inclusion criteria in this meta-analysis, which included 5859 PCa cases and 4867 controls. Overall, rs198977 was associated with the PCa risk (TT+CT vs. CC, pooled OR = 1.163, 95% CI = 1.076-1.258, P-value <0.0001). When stratified by ethnicity, significant association was observed in Caucasian samples under both allele comparison (T vs. C, pooled OR = 1.152, 95% CI = 1.079-1.229, P-value <0.0001) and dominant model (TT+CT vs. CC, pooled OR = 1.197, 95% CI = 1.104-1.297, P-value <0.0001). In the overall analysis, a comparably significant increase in the frequency of allele T for rs198977 was detected between cases and controls in Caucasian.

CONCLUSION

This meta-analysis suggests that rs198977 of KLK2 was associated with susceptibility of PCa in Caucasian and the allele T might increase the risk of PCa in Caucasian.

Genetic predisposition to early recurrence in clinically localized prostate cancer

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Currently available nomograms to predict preoperative risk of early biochemical recurrence (EBCR) after radical prostatectomy are solely based on classic clinicopathological variables. Despite providing useful predictions, these models are not perfect. Indeed, most researchers agree that nomograms can be improved by incorporating novel biomarkers. In the last few years, several single nucleotide polymorphisms (SNPs) have been associated with prostate cancer, but little is known about their impact on disease recurrence. We have identified four SNPs associated with EBCR. The addition of SNPs to classic nomograms resulted in a significant improvement in terms of discrimination and calibration. The new nomogram, which combines clinicopathological and genetic variables, will help to improve prediction of prostate cancer recurrence.

OBJECTIVES

To evaluate genetic susceptibility to early biochemical recurrence (EBCR) after radical prostatectomy (RP), as a prognostic factor for early systemic dissemination. To build a preoperative nomogram to predict EBCR combining genetic and clinicopathological factors.

PATIENTS AND METHODS

We evaluated 670 patients from six University Hospitals who underwent RP for clinically localized prostate cancer (PCa), and were followed-up for at least 5 years or until biochemical recurrence. EBCR was defined as a level prostate-specific antigen >0.4 ng/mL within 1 year of RP; preoperative variables studied were: age, prostate-specific antigen, clinical stage, biopsy Gleason score, and the genotype of 83 PCa-related single nucleotide polymorphisms (SNPs). Univariate allele association tests and multivariate logistic regression were used to generate predictive models for EBCR, with clinicopathological factors and adding SNPs. We internally validated the models by bootstrapping and compared their accuracy using the area under the curve (AUC), net reclassification improvement, integrated discrimination improvement, calibration plots and Vickers' decision curves.

RESULTS

Four common SNPs at KLK3, KLK2, SULT1A1 and BGLAP genes were independently associated with EBCR. A significant increase in AUC was observed when SNPs were added to the model: AUC (95% confidence interval) 0.728 (0.674-0.784) vs 0.763 (0.708-0.817). Net reclassification improvement showed a significant increase in probability for events of 60.7% and a decrease for non-events of 63.5%. Integrated discrimination improvement and decision curves confirmed the superiority of the new model.

CONCLUSIONS

Four SNPs associated with EBCR significantly improved the accuracy of clinicopathological factors. We present a nomogram for preoperative prediction of EBCR after RP.

The physiology and pathobiology of human kallikrein-related peptidase 6 (KLK6)

The human kallikrein-related peptidase 6 (KLK6) gene belongs to the 15-member kallikrein (KLK) gene family mapping to chromosome 19q13.3-13.4. Encoding for an enzyme with trypsin-like properties, KLK6 can degrade components of the extracellular matrix. The successful utilisation of another KLK member (KLK3/PSA) for prostate cancer diagnosis has led many to evaluate KLK6 as a potential biomarker for other cancer and diseased states. The observed dysregulated expression in cancers, neurodegenerative diseases and skin conditions has led to the discovery that KLK6 participates in other cellular pathways including inflammation, receptor activation and regulation of apoptosis. Moreover, the improvements in high-throughput genomics have not only enabled the identification of sequence polymorphisms, but of transcript variants, whose functional significances have yet to be realised. This comprehensive review will summarise the current findings of KLK6 pathophysiology and discuss its potential as a viable biomarker.

Genetic association study of a single nucleotide polymorphism of kallikrein-related peptidase 2 with male infertility

Objective

To investigate a kallikrein-related peptidase 2 (KLK2) single nucleotide polymorphism (SNP) in relation to male infertility because of its role in semen processing. We investigated the genetic association of the KLK2+255G>A genotype with male infertility.

Methods

We genotyped the SNP site located in intron 1 (+255G>A, rs2664155) of KLK2 from 218 men with male infertility (cases) and 220 fertile males (controls). Pyrosequencing analysis was performed for the genotyping.

Results

The SNP of the KLK2 gene had a statistically significant association with male infertility (p<0.05). The odds ratio for the minor allele (+255A) in the pooled sample was 0.47 (95% confidence intervals, 0.26-0.85) for rs2664155.

Conclusion

The relationship of KLK2 SNP to male infertility is statistically significant, especially within the non-azoospermia group. Further study is needed to understand the mechanisms associated with male infertility.

Mechanisms of prostate cancer initiation and progression

Prostate cancer is a major health problem as it continues to be the most frequently diagnosed cancer in men in the Western world. While improved early detection significantly decreased mortality, prostate cancer still remains the second leading cause of cancer-related death in Western men. Understanding the mechanisms of prostate cancer initiation and progression should have a significant impact on development of novel therapeutic approaches that can help to combat this disease. The recent explosion of novel high-throughput genetic technologies together with studies in animal models and human tissues allowed a comprehensive analysis and functional validation of the molecular changes. This chapter will summarize and discuss recently identified critical genetic and epigenetic changes that drive prostate cancer initiation and progression. These discoveries should help concentrate the efforts of drug development on key pathways and molecules, and finally translate the knowledge that is gained from mechanistic studies into effective treatments.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms

PURPOSE

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy.

MATERIALS AND METHODS

We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index.

RESULTS

The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities.

CONCLUSIONS

Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information.

Blood biomarker levels to aid discovery of cancer-related single-nucleotide polymorphisms: kallikreins and prostate cancer

Polymorphisms associated with prostate cancer include those in three genes encoding major secretory products of the prostate: KLK2 (encoding kallikrein-related peptidase 2; hK2), KLK3 (encoding prostate-specific antigen; PSA), and MSMB (encoding beta-microseminoprotein). PSA and hK2, members of the kallikrein family, are elevated in sera of men with prostate cancer. In a comprehensive analysis that included sequencing of all coding, flanking, and 2 kb of putative promoter regions of all 15 kallikrein (KLK) genes spanning approximately 280 kb on chromosome 19q, we identified novel single-nucleotide polymorphisms (SNP) and genotyped 104 SNPs in 1,419 cancer cases and 736 controls in Cancer Prostate in Sweden 1, with independent replication in 1,267 cases and 901 controls in Cancer Prostate in Sweden 2. This verified prior associations of SNPs in KLK2 and in MSMB (but not in KLK3) with prostate cancer. Twelve SNPs in KLK2 and KLK3 were associated with levels of PSA forms or hK2 in plasma of control subjects. Based on our comprehensive approach, this is likely to represent all common KLK variants associated with these phenotypes. A T allele at rs198977 in KLK2 was associated with increased cancer risk and a striking decrease of hK2 levels in blood. We also found a strong interaction between rs198977 genotype and hK2 levels in blood in predicting cancer risk. Based on this strong association, we developed a model for predicting prostate cancer risk from standard biomarkers, rs198977 genotype, and rs198977 x hK2 interaction; this model had greater accuracy than did biomarkers alone (area under the receiver operating characteristic curve, 0.874 versus 0.866), providing proof in principle to clinical application for our findings.

Utility of kallikrein-related peptidases (KLKs) as cancer biomarkers

BACKGROUND

The human kallikrein-related peptidase (KLK) family consists of 15 highly conserved serine proteases, which are encoded by the largest uninterrupted cluster of protease genes in the human genome. To date, several members of the family have been reported as potential cancer biomarkers. Although primarily known for their biomarker value in prostate, ovarian, and breast cancers, more recent data suggest analogous roles of KLKs in several other cancers, including gastrointestinal, head and neck, lung, and brain malignancies. Among the proposed KLK cancer biomarkers, prostate-specific antigen (also known as KLK3) is the most widely recognized member in urologic oncology.

CONTENT

Despite substantial progress in the understanding of the biomarker utility of individual KLKs, the current challenge lies in devising biomarker panels to increase the accuracy of prognosis, prediction of therapy, and diagnosis. To date, multiparametric KLK panels have been proposed for prostate, ovarian, and lung cancers. In addition to their biomarker utility, emerging evidence has revealed a number of critical functional roles for KLKs in the pathogenesis of cancer and their potential use as therapeutic targets.

SUMMARY

KLKs have biomarker utility in many cancer types but individually lack sufficient specificity or sensitivity to be used in clinical practice; however, groups of KLKs and other candidate biomarkers may offer improved performance.

A genome-wide association screen identifies regions on chromosomes 1q25 and 7p21 as risk loci for sporadic prostate cancer

We conducted a genome-wide association study of 3090 sporadic prostate cancer patients and controls using the Affymetrix 10 000 SNP GeneChip. Initial screening of 40 prostate cancer cases and 40 non-cancer controls revealed 237 SNPs to be associated with prostate cancer (P<0.05). Among these SNPs, 33 were selected for further association analysis of 2069 men who had undergone a cancer-screening prostate biopsy. Results identified five loci as being significantly associated with increased prostate cancer risk in this larger sample (rs 1930293, OR=1.7, P=0.03; rs 717809-2p12, OR=1.3, P=0.03; rs 494770-4q34, OR=1.3, P=0.01; rs 2348763-7p21, OR=1.5, P=0.01; rs 1552895-9p22, OR=1.5, P=0.002). To validate these association data, 61 additional HapMap tagSNPs spanning the latter five loci were genotyped in this subject cohort and an additional 1021 men (total subject number=3090). This analysis revealed tag SNP rs 4568789 (chromosome 1q25) and tag SNP rs 13225697 (chromosome 7p21) to be significantly associated with prostate cancer (P-values 0.009 and 0.008, respectively). Haplotype analysis revealed significant associations of prostate cancer with two allele risk haplotypes on both chromosome 1q25 (adjusted OR of 2.7 for prostate cancer, P=0.0003) and chromosome 7p21 (adjusted OR of 1.3, P=0.0004). As linkage data have identified a putative prostate cancer gene on chromosome 1q25 (HPC1), and microarray data have revealed the ETV1 oncogene to be overexpressed in prostate cancer tissue, it appears that chromosome 1q25 and 7p21 may be sites of gene variants conferring risk for sporadic and inherited forms of prostate cancer.

A consolidated catalogue and graphical annotation of dbSNP polymorphisms in the human tissue kallikrein (KLK) locus

The human tissue kallikreins, 15 secreted serine proteases, may play diverse roles in pathophysiology. The National Center for Biotechnology Information's dbSNP was mined for polymorphisms located within the kallikrein (KLK) locus using custom-designed "ParSNPs" and "LocusAnnotator" software tools. Using "ParSNPs", a filterable catalogue of 1856 KLK polymorphisms (1023 validated) was generated. "LocusAnnotator" was used to annotate the KLK locus sequence with gene and polymorphism features. A second locus was examined to validate the use of both programs on a non-kallikrein locus. This report may assist in the informed selection of KLK polymorphisms for future association and biochemical studies in relation to disease. Furthermore, "ParSNPs" and "LocusAnnotator" are available at no cost from our website (www.acdcLab.org/annotations) to examine other loci.

Tagging SNPs in the kallikrein genes 3 and 2 on 19q13 and their associations with prostate cancer in men of European origin

Two of the classical kallikrein genes KLK3 and KLK2 on 19q13.4 are plausible candidates in prostate cancer susceptibility. They are expressed almost exclusively in prostate tissue. We have performed a comprehensive analysis of association of variants in these two genes with prostate cancer among men of European descent using a tagging SNP approach. Thirteen SNPs selected from the HapMap database were analyzed in a sample of 596 histologically verified prostate cancer cases and 567 ethnically matched controls. Five SNPs showed significant association at single marker level. Linkage disequilibrium (LD) analysis revealed four LD blocks. We performed a haplotype analysis within each LD block. A major haplotype in block 1 that contains the first two significantly associated SNPs was significantly underrepresented in the prostate cancer cases; a second haplotype in block 3 also showed significant frequency differences between cases and controls. Four of the studied SNPs show positive associations with serum PSA levels. A structure analysis revealed no population stratification in our samples that could have confounded the association results. These findings suggest a plausible role of kallikrein gene variants in the etiology of prostate cancer among men of European ancestry.