The modern research on molecular basis of prostate cancer (PCa) development includes studies aiming to identify potential genetic markers which could be used in diagnostics and/or monitoring of PCa. Genome-wide association studies (GWASs) have identified over 75 variants associated with PCa risk. One of the major PCa-related regions identified through GWASs is found to be a segment of 8q24. Other important PCa-susceptibility regions are 17q12, 17q24, 10q11, and 19q13. Candidate-gene based approach has also provided evidence of association between PCa risk and genetic variants located in functionally significant genes (both protein-coding and noncoding RNA genes) involved in normal prostatic cell growth, malignant transformation, or in the development of metastases. Nevertheless, the success of these studies is questionable, since numerous candidates for PCa-susceptibility variants were identified, but these results failed to replicate. The main aim of both types of genetic association studies on PCa is the identification of potential PCa genetic markers which could be used for constructing reliable algorithms for evaluating the risk for PCa development and/or PCa progression.
- prostate cancer
- association study
- candidate gene
- validation study
- replication study
Alarming statistics on prostate cancer (PCa) incidence and mortality, as well as the results of epidemiological studies, have led to focusing research efforts on discovering molecular mechanisms underlying its onset and progression . Still, molecular basis of PCa pathogenesis remains largely unknown, while the results of studies in this area of research suggest that PCa is one of the most genetically and molecularly heterogeneous malignant tumors . Among PCa cases, most are sporadic, while a significantly smaller percent represents familial type, including hereditary cases. High-penetrability PCa-related loci are not common in populations and are found to be associated with hereditary PCa. Since PCa represents a multifactorial disease with polygenic basis, and sporadic cases are much more frequently diagnosed, most of the research in the area of PCa molecular genetics has focused on genetic variants with low penetrability .
The modern research on molecular basis of PCa development includes studies aiming to identify potential genetic markers which could be used in diagnostics and/or monitoring of PCa . This is of utmost importance, since one of the major issues in clinical practice related to PCa is a large percent of latent PCa among newly diagnosed . The overdiagnosis of PCa in early diagnosed cases, due to indolent forms, leads to unnecessary morbidity because of application of invasive therapeutic procedures . This led to focusing the research efforts on discovering genetic markers that could be used for assessing the biological potential of early diagnosed PCa. Therefore, the use of these genetic markers, together with standard prognostic parameters of PCa progression, which include initial serum PSA level, Gleason score, and clinical stage, could greatly improve the current clinical protocols by being implemented in algorithms for evaluating the patient’s risk of PCa and/or PCa aggressiveness .
Studies aiming to identify potential PCa-related loci are designed as case-control or case-only studies, which evaluate the differences in genotype distributions between cases and controls, as well as between different groups of patients, classified according to clinical characteristics. The most validated loci associated with PCa risk were identified through Genome-wide association studies (GWAS) . Nevertheless, numerous PCa-related genetic variants were found in studies based on selected candidate genes .
2. Linkage analyses and high-penetrability loci
Linkage analyses have led to identification of the first high-penetrability PCa susceptibility loci . These studies were based on analyses in hereditary PCa, which is a less frequent type of PCa, and yielded high or moderate-penetrability loci, such as HPC1 (eng.
3. Genome-wide association studies
To date (February 2016), GWASs have identified over 75 variants associated with prostate cancer risk, predominantly in populations of European ancestry (Figure 1) [15, 16]. The first GWASs were conducted in 2007, for which a large collection of samples were obtained from PCa patients and healthy controls, as well as databases that included clinical data of patients were constructed [17–19]. The necessity of a large number of subjects for this type of study was obvious even in this early period of conducting GWASs.
As in other complex diseases, PCa GWASs are usually designed in a multistage manner, with the whole set of tag-single nucleotide polymorphisms (tag-SNPs) being evaluated in the first phase, and only subsets of the most significant SNP being replicated in much larger groups of patients and controls in next phases [20, 21]. Thus, repeating the tests yields the most significant results .
The results of initial GWASs showed that most of the PCa-associated genetic variants are located in so-called “gene-deserts”. The lack of protein-coding genes in these regions was explained by the supposed presence of regulatory sequences of major proto-oncogenes and tumor-suppressive genes [22, 23]. Today, another explanation is also the presence of genes encoding regulatory RNA molecules within PCa-risk regions .
3.1. 8q24 region
One of the major PCa-related regions was found to be 8q24. Within approximately 1 million base pairs segment of 8q24 reside multiple variants associated with PCa . This region was first identified as associated with PCa susceptibility in a genome-wide linkage study conducted in Icelandic population . Later on, the association of genetic variants within this region with PCa risk was shown in initial GWASs from 2007. Gudmunsson et al., Haiman et al. and Yeager et al. have shown the association between previously reported rs1447295 and PCa risk [17–19]. Also, these first GWASs identified other PCa susceptibility variants within 8q24, rs6983267, and rs16901979. Afterward, GWASs have provided evidence for association of other single-nucleotide genetic variants (SNVs) from 8q24 with PCa risk, such as rs4242382, rs7017300, and rs7837688 [27, 28]. In the recent years, by implementing clinical data and by using case-only design, both GWASs and validation studies have provided evidence for an association of several loci within 8q24 with PCa aggressiveness or survival [29–32].
PCa-susceptibility region within 8q24 was defined as
17q12 is another PCa susceptibility region identified through initial GWAS. Two of the genetic variants located in 17q12, rs7501939 and rs3760511, were found to be associated with the risk of developing PCa in the study by Gudmundsson et al. conducted in 2007 . In this GWAS, minor alleles of these two single nucleotide genetic variants were found to confer the increased risk of PCa in cohorts of participants from Iceland, Netherlands, and the USA, while in the group of Hispanics this genetic association was not shown . The results of this GWAS were further validated in multiple populations, mostly of European origin [36–43]. Validation studies were even conducted in Africans in which genetic association studies on PCa are scarce [37, 44–47]. The most recent meta-analysis of both GWASs and validation studies has also shown the association of these genetic variants with PCa risk .
SNVs rs7501939 and rs3760511 are located in the first intron of the hepatocyte nuclear factor 1 β(
Another PCa-susceptibility region on chromosome 17 is 17q24. Genetic variants located within this region which were found to be associated with PCa are intergenic variants. Similar to 8q24 genetic variants, those located in 17q24 are found in a gene desert, probably harboring multiple regulatory sequences controlling the expression of surrounding genes . One of the most proximal genes is
Two out of the three GWASs, which were published in 2008 in the same issue of
Region 19q13 harboring kallikrein genes
Another subregion associated with PCa risk is 19q13.4 in which a GWASs hit is in strong LD in Chinese population with germline deletion affecting
4. Candidate gene-based approaches
Even before GWASs, the necessity of conducting association studies in order to identify low and moderate penetrability genetic variants that contribute to PCa risk was obvious. Therefore, numerous candidate genes were analyzed for genetic variants associated with PCa, with questionable success due to false discoveries and the lack of replication . Candidates were selected based on their potential functional significance in normal prostatic cell growth, malignant transformation, or in the development of metastases. Therefore, among these candidate genes are those encoding proteins involved in androgen signaling, cell-cycle control mechanisms, major tumor-suppressors, or proto-oncogenes, as well as those involved in cellular adhesion or communication with surrounding cellular or matrix components of prostate epithelium [62, 63]. This implies the need for previous knowledge when designing case-control studies using candidate gene approach .
Even though these studies were common before GWASs, they are still conducted in numerous populations, aiming to confirm previously found associations, or to identify new ones by analyzing other candidates, selected by using modern research results, such as those involved in regulatory functions of non-coding RNAs .
4.1. Protein-coding genes
4.1.1. Androgen signaling
Since androgen signaling is essential for growth and survival of prostate epithelial cells, genes involved in androgen biosynthesis, signal reception and transduction, as well as in androgen metabolism have emerged as candidates for case–control studies . Most of these studies involved Androgen receptor (AR), as the major component of androgen signaling and regulation of expression of androgen-responding genes. Among these studies, major percentage relied on analyzing the potential association of the length of CAG repeat string with exon 1 which encodes a poly-glutamine tract of AR with PCa risk . This homopolymeric tract is located in N-terminal domain of AR, which possesses transactivational properties and its length is inversely correlated with transactivation function . Even though initial results were promising, the supposed association was not confirmed in a large percentage of later studies, and the effect sizes were not large enough to support the substantial biological role. Therefore, the association of this genetic variant with PCa risk remains controversial [68–70].
Another three-nucleotide (GGN) repeat string, encoding polyglycine tract in AR, was analyzed for potential association between its length and PCa risk. This repeat string is also located in exon 1, but less studied than the CAG repeat tract, possibly due to technical problems in amplifying GC-rich DNA regions . The effect of the length of GGN repeat string on transactivational properties of AR is still unclear, and the other proposed mechanism of potential functional significance is the effect on AR translation . Studies on the potential association of this microsatellite on PCa risk and progression yielded contrasting results [73–79].
Mixed results were also found for
4.1.2. Carcinogen metabolism
Among genes involved in cell detoxification, those encoding glutathione-S-transferases have been mostly analyzed. Nevertheless, most of these studies yielded insignificant results on association with PCa risk . Other frequently analyzed genes involved in metabolism of carcinogens are
Two genetic variants within
The most commonly analyzed SNVs in
The results obtained for genetic variants in
4.1.3. DNA repair, cell cycle control, and apoptosis
Dysfunctions of DNA repair pathway, apoptosis regulation, and cell cycle control mechanisms alter the cells response to DNA damage and lead to uncontrolled proliferation, progression and metastasis of malignant diseases. Also, genetic variants in genes involved in these processes could potentially attribute to cancer susceptibility and/or progression risk .
Among the genes analyzed for association between genetic variants and prostate cancer risk or aggressiveness are
The most common SNVs in
A recent study conducted in Spain showed the association of rs11615 in
Among genetic variants located in
Numerous studies conducted on a potential association between
The most extensively analyzed SNV located in
4.1.4. Vitamin D signaling
Vitamin D signaling in PCa has stimulatory effect on apoptosis, as well as inhibitory effect on the progression of cell cycle. Therefore, multiple genetic variants within the gene encoding the receptor for vitamin D (
Even though the initial results on these loci were promising, in multiple populations, they were not replicated [113, 115]. The association of these genetic variants with PCa progression parameters and the disease outcome also remains inconclusive [113, 116].
4.1.5. Chronic inflammation and angiogenesis
Numerous genes involved in chronic inflammation have been studies for association of genetic variants that reside within them with PCa risk and/or progression . Also, the importance of vascular support to cancer growth stimulated the association studies on PCa analyzing genetic variants located in angiogenesis-related genes . Since these processes are codependent, numerous genes primarily found to be involved in chronic inflammation are also discussed as angiogenesis-related genes, and vice versa.
Among the most important factors of chronic inflammation are
There have been various PCa case–control studies involving
Candidates for this type of studies were also genes encoding transcription factors which regulate the expression of
Some of the key regulators of angiogenesis are also fibroblast growth factors (
Among the most extensively analyzed candidate genes in PCa-related case-control studies are
Angiogenesis process and tumor invasion also require degradation of extracellular matrix and basal membranes, which are catalyzed by matrix metalloproteinases. Among the genes encoding this class of enzymes,
4.1.6. Cellular adhesion
Among genes involved in cellular adhesion,
Only few studies also included genetic variants in genes encoding intercellular adhesion molecules (ICAMs), proteins involved in cellular adhesion and signaling. The analyzed genetic variants are those located in
4.2. Long noncoding RNA genes
The potential involvement of long noncoding RNAs (lncRNAs) in prostate carcinogenesis was suggested not only by the results of expression analyses that showed several known oncogenic and/or tumor-suppressive lcnRNAs to be aberrantly expressed in malignant prostatic tissue or plasma samples from patients with PCa but also by the identification of several PCa-specific lncRNAs [163, 164].
Several SNVs in lncRNA genes were identified as PCa susceptibility variants in case–control studies on PCa. In their study published in 2011, Jin et al. have stated that eight SNVs identified to that time through GWAS are located in lncRNA intervals . They also identified a SNV in a putative lncRNA which was not later experimentally confirmed as a PCa-susceptibility variants . In a study published in 2013, Xue et al. have shown the association between two tag-SNPs in Prostate cancer gene expression marker 1 (
Dysregulation of diverse regulatory mechanisms based on microRNA activity has been implicated in prostate carcinogenesis. Therefore, possibly functional genetic variants located in
MicroRNA genetic variants have been analyzed for their potential association with PCa in only a few studies conducted in Asian populations and in a single population of European origin. These studies have provided discordant results on the effects of genetic variants in rs2910164 in
Another SNV, rs895819 located in a gene encoding miR-27a, which is androgen-regulated and stimulates the androgen signalization in a positive feedback loop, was found to be associated with PCa risk, as well as with the development of distant metastases. Nevertheless, these results are derived from a single study on PCa risk and rs895819 conducted relatively recent and needs further validation .
5. Replication, validation studies, and Meta-analyses
Differences in genetic backgrounds are an important issue in genetic association studies. Therefore, interpretation of data requires discussing the potential differences between populations. Therefore, in order to analyze such differences, multiple validation analyses are conducted in various population and ethnicities. These studies are designed so that they resemble as much as possible to the original study that yielded genetic associations, or the lack of it. The ratio for conducting such studies is the possible lack of association between identified PCa-susceptibility variants with PCa risk in certain populations, or the differences in effect sizes . Replication studies, conducted in confirmation group of participants from the same population in which the initial results were found, is a method of checking reproducibility and evaluating possible false positives and effect overestimation [179, 180].
Currently, replications and validations are conducted for both GWASs results, as well as for results from candidate gene-based studies. Of utmost importance is conducting replication and validation analyses of hits from studies with relatively small sample sizes, as well as with poorly clinically characterized cases with the lack of data on possible confounders, or questionable recruitment of controls . Also, an important issue in case–control studies on PCa is the type of control group, which is in some cases healthy controls, while in others group of patients with benign prostatic hyperplasia (BPH). Furthermore, classification systems for patients with PCa which are used for evaluating potential genetic associations with PCa progression differ between studies, which together with small sizes of patient groups, calls for replication of acquired statistically significant data.
All of these issues are a potential reason for the opposing results on the association of the most of genetic variants analyzed in multiple studies with PCa risk and progression. Therefore, in order to elucidate the effect of these genetic variants, meta-analyses of eligible studies are frequently conducted. Combining the results from smaller studies through data synthesis in meta-analysis could result in increased statistical power . Therefore, meta-analyses could provide more precise estimations, as well as the insight in the potential effect of confounders , such as ethnicity, participant recruitment strategy, or study size.
6. Future perspectives
The main aim of genetic association studies on PCa is the identification of potential PCa genetic markers which could be used for constructing reliable algorithms for evaluating the risk for PCa development and/or PCa progression . Therefore, it is important not only to identify these PCa-related genetic variants, but also to precisely characterize their effect sizes. In order to do that, ethnic differences need to be taken into account . Other important issues in interpreting results of association studies are gene–gene and gene-environment interactions. Therefore, future research and designing such algorithms require integration of knowledge on genetic associations, cellular pathways, and statistical epistasis in which real biological interaction could be reflected.
Since the major problem in clinical practice related to PCa is the overdiagnosis and monitoring of patients , additional studies on PCa aggressiveness with clinically well characterized groups of PCa patients are needed to identify genetic variants associated with PCa progression risk. The later implementation of algorithms based on these genetic variants could greatly improve clinical protocols in monitoring and treating PCa.
The efforts for improving clinical protocols in PCa diagnostics, monitoring and treatment resulted in conducting genetic association studies on PCa. These studies aim to identify potential PCa genetic markers and characterize their association with PCa risk and/or progression through measuring effect sizes. The identified and validated genetic markers could then be used for constructing reliable algorithms for evaluating the risk for PCa development and, more importantly, for PCa progression. Implementing such algorithms in clinical practice is expected to improve the distinction between early diagnosed PCa cases that require aggressive treatment and latent PCa cases which remain indolent during patient’s lifetime.
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