Abstract

Although the causes of prostate cancer are still unknown, numerous studies support the role of genetic factors in the development and progression of this disease. Single nucleotide polymorphisms (SNPs) in key angiogenesis genes have been studied in prostate cancer. In this review, we provide an overview of the current knowledge of the role of genetic variants in the angiogenesis pathway in prostate cancer risk and progression. Of the 17 prostate cancer genome-wide association studies (GWAS) conducted to date, only one identified disease-associated SNPs in a region of an angiogenesis pathway gene. An association was observed between aggressive disease and three intergenic SNPs (rs11199874, rs10749408 and rs10788165) in a region on chromosome 10q26 that encompasses FGFR2 . The majority (27/32, 84.4%) of primary candidate gene studies reviewed had a small ( n < 800, 20/32, 62.5%) to medium sample size ( n = 800–2000, 7/32, 21.9%), whereas only five (15.6%) had a large sample size ( n ≥ 2000). Results from the large studies revealed associations with risk and aggressive disease for SNPs in NOS2A , NOS3 and MMP-2 and risk for HIF1-α . Meta-analyses have so far been conducted on FGFR2, TGF-β , TNF-α, HIF1-α and IL10 and the results reveal an association with risk for SNPs in FGFR2 and TGF-β and aggressive disease for SNPs in IL-10 . Thus, existing evidence from GWAS and large candidate gene studies indicates that SNPs from a limited number of angiogenesis pathway genes are associated with prostate cancer risk and progression.

Introduction

Prostate cancer is the most common non-skin malignancy among men worldwide. In the USA, an estimated 240 890 new cases and 33 720 deaths are expected in 2011 ( 1 ). Although the causes of prostate cancer are still unknown, family history of the disease is one of the strongest risk factors. Twin studies suggest that ∼42% of the disease risk may be attributed to heritable factors ( 2 ). Furthermore, recent genome-wide association studies (GWAS) have identified susceptibility variants ( 3–5 ), providing evidence in support of the role of genetic susceptibility in the development of prostate cancer.

Angiogenesis is a biological process that involves the division and migration of endothelial cells, resulting in microvasculature formation ( 6 , 7 ). The formation of blood vessels is important for organ development during embryogenesis and continues to contribute to organ growth after birth, but during adulthood, most blood vessels remain quiescent and angiogenesis is limited to the cycling ovary and in the placenta during pregnancy ( 6–8 ). Nonetheless, endothelial cells maintain their ability to divide rapidly into blood vessels in response to physiological stimuli, such as hypoxia, and angiogenesis is reactivated during wound healing and repair ( 6 , 7 , 9 ). The process of post-natal angiogenesis is regulated by a continuous interplay (that establishes a balance) of stimulators such as vascular endothelial growth factor (VEGF), basic fibroblast growth factor, epidermal growth factor (EGF), interleukins (ILs), nitric oxide synthase (NOS), transforming growth factor beta (TGF-β), tumor necrosis factor alpha (TNF-α), platelet derived growth factor and matrix metalloproteinases (MMPs) and inhibitors such as endostatin, platelet factor-4, tumastin, thrombospondin-1, plasminogen activator inhibitor-1 and angiostatin ( 6–10 ) ( Figure 1 ). However, in many disorders including cancer, the balance between stimulators and inhibitors is tilted to favor stimulators, resulting in an ‘angiogenic switch’ ( 11 , 12 ).

Fig. 1.

The role of angiogenesis in tumor progression. Post-natal angiogenesis is regulated by a balanced and continuous interplay of factors that act as pro-angiogenic (VEGFs, FGF, EGF, HIF, TGF-β and TNF-α), anti-angiogenic (endostatin and IFN) or both pro-/anti-angiogenic (MMPs and ILs). However, a growing tumor can tilt the balance toward pro-angiogenic factors to promote vascular growth and facilitate tumor invasion, regional lymph node and distant metastasis.

Fig. 1.

The role of angiogenesis in tumor progression. Post-natal angiogenesis is regulated by a balanced and continuous interplay of factors that act as pro-angiogenic (VEGFs, FGF, EGF, HIF, TGF-β and TNF-α), anti-angiogenic (endostatin and IFN) or both pro-/anti-angiogenic (MMPs and ILs). However, a growing tumor can tilt the balance toward pro-angiogenic factors to promote vascular growth and facilitate tumor invasion, regional lymph node and distant metastasis.

The so-called ‘angiogenic switch’ may result from changes in the expression levels of genes in the angiogenesis pathway. Single nucleotide polymorphisms (SNPs) may alter gene expression and influence the process of angiogenesis. Indeed, several SNPs in angiogenesis genes that affect gene expression have been identified. These variants may potentially contribute to interindividual variation in the risk and progression of tumors ( 13 ) and have thus been studied in this context for various cancers, including prostate cancer. However, GWAS have so far only identified three intergenic SNPs in a region encompassing FGFR2 and SNPs in FGF10 and IL-16 that are not directly involved in angiogenesis. The majority (27/32, 84.4%) of primary candidate gene studies conducted to date have a small ( n < 800, 20/32, 62.5%) to medium sample size ( n = 800–2000, 7/32, 21.9%) and may be underpowered. Only a small number (5/32, 15.6%, n ≥ 2000) of large studies and meta-analyses have been conducted so far and very few SNPs have been identified. In this review, we provide an overview of the current knowledge of the role of genetic variants in the angiogenesis pathway in prostate cancer risk and progression.

The role of angiogenesis in prostate cancer

Angiogenesis is an important pathway for tumor progression ( 6 , 7 , 9 , 10 ) ( Figure 1 ). A tumor can grow up to a diameter of 2–3 mm by diffusion of nutrients from existing blood vessels. Angiogenesis is therefore inevitable in tumor progression and metastasis since tumor growth requires the development and remodeling of blood vessels to ensure the supply of oxygen and nutrients ( 6 , 7 ). Similar to other solid tumors, progressive growth and metastasis of prostate cancer are dependent on angiogenesis and existing evidence supports a role for angiogenesis in prostate cancer. For instance, microvessel density is correlated with prostate cancer progression and the expression of angiogenic factors is altered in prostate cancer and associated with clinical stage, Gleason score, tumor stage, progression, metastasis and survival ( 14–17 ).

Genetic variants in the angiogenesis pathway and prostate cancer

Angiogenesis is a complex multifactorial process that reflects a finely tuned balance between a variety of angiogenic factors that act as activators or inhibitors ( 8 ). Several key pro-angiogenic and anti-angiogenic factors have been implicated in prostate cancer and SNPs in these genes may alter expression and influence the process of angiogenesis, potentially leading to interindividual variation in the risk and progression of this disease. However, prostate cancer GWAS have directly or indirectly identified few SNPs in angiogenesis genes so far and SNPs in only a few angiogenesis genes have been studied in relation to prostate cancer risk and progression in candidate gene studies.

Genome-wide association studies

A search of the GWAS catalogue of the National Human Genome Research Institute of the National Institute of Health indicated that 17 GWAS ( 18–34 ) have been published on prostate cancer as of 6 February 2012 ( http://www.genome.gov/gwastudies/index.cfm ). Most studies investigated subjects with European ancestry background except two studies, which reported on Asians ( 32 ) and African Americans ( 25 ). Thomas et al. ( 33 ) observed that the homozygous minor allele of a non-synonymous SNP (rs4072111) that changes a serine to proline in IL-16 was significantly ( P = 1.19 × 10 −5 ) associated with an increased risk of aggressive cancer. Another study using a screening cohort and biopsy-proven controls observed significant associations ( P = 6.0 × 10 −7 to 3.0 × 10 −10 ) between aggressive prostate cancer and three intergenic SNPs (rs11199874, rs10749408 and rs10788165) that span a 590-kb region on chromosome 10q26 that encompasses FGFR2 , an angiogenesis gene ( 28 ). Only one GWAS has so far observed a prostate cancer susceptibility SNP [rs2121875; odds ratio (OR) = 1.05, 95% confidence interval (CI) = 1.02–1.08; P = 4 x 10 −8 ] and it was found in the intron of FGF10 , which is not directly involved in angiogenesis ( 26 ). Penney ( 29 ) observed associations with mortality for SNPs in IL-18 (rs360729, P = 2.1 × 10 −4 ; rs243908, P = 3.0 × 10 −4 ) and IL-11 (rs12709950, P = 5.3 × 10 −4 ) in their stage one scan, but none of them was replicated in stage 2.

So far GWAS have directly or indirectly identified very few SNPs in angiogenesis genes and this limited evidence suggests that SNPs in the angiogenesis pathway may modify disease risk and also the risk of developing an aggressive disease.

Candidate gene studies

Several candidate gene studies have been conducted on angiogenesis genes and prostate cancer risk or progression. However, the majority of the studies are small ( n < 800, 62.5%) to medium ( n = 800–2000, 21.9%) sized, and only a few (15.6%) are large studies ( n ≥ 2000). Moreover, only a few genes or variants in the angiogenesis pathway have been studied. The most commonly studied angiogenesis genes are VEGF , MMPs , ILs , NOS , FGF , TGF-β and TNF-α and COL18A1 (endostatin). Table I--III summarizes the candidate genetic association studies conducted so far on angiogenesis genes. The genes are broadly categorized as main pro-angiogenesis ( VEGF and FGF - Table I), other pro-angiogenesis ( TGF-β , TNF-α , NOS , EGF , HIF-1α and ACE -Table II), pro-/anti- and anti-angiogenesis ( MMPs and ILs and COL18A1 - Table III). MMPs and ILs are categorized as pro-/anti-angiogenesis because certain family members are pro-angiogenesis, whereas others are anti-angiogenesis.

Table I.

Summary of epidemiologic studies of polymorphisms in main pro-angiogenesis genes and prostate cancer risk and progression

Gene SNP rsID Alias Case/control Country Outcome  OR/HR (95% CI) a / P -value  Reference 
VEGF rs1570360 −1154  238/263 b UK Risk (GG versus AA) 0.45 (0.24–0.86)  ( 35 )  
238 c  Survival (AA versus GG) 0.49 (0.19–1.26) 
VEGF rs1570360 −1154 101/100 Tunisia Risk (GG versus AA) 0.27 (0.08–0.83)  ( 36 )  
30/71 d  Advanced stage (GG versus AA)  0.002 e 
rs2010963 −634 101/100  Risk (GG versus GC/CC) 1.95 (1.04–3.65) 
30/71 d  Advanced stage (GG versus GC/CC)  0.03 e 
rs3025039 +936 101/100  Risk (CC versus TT) 1.82 (0.13–51.93) 
30/71 d  Advanced stage (CC versus TT)  >0.05 e 
VEGF rs1570360 −1154 1158/1172 USA Risk (per A allele) 1.02 (0.90–1.15)  ( 37 )  
458/1172   Aggressive f (per A allele)  1.06 (0.90–1.24) 
rs3025039 +936 1163  Risk (per T allele) 0.98 (0.83–1.15) 
1163   Aggressive f (per T allele)  0.91 (0.73–1.14) 
rs699947 −2578 1165/1177  Risk (per A allele) 0.96 (0.86–1.08) 
460/1177   Aggressive f (per A allele)  1.05 (0.90–1.22) 
rs25648  1142/1161  Risk (per T allele) 0.96 (0.82–1.12) 
450/1161   Aggressive f (per T allele)  1.04 (0.85–1.27) 
rs2010963 −634 1138/1158  Risk (per A allele) 0.92 (0.81–1.04) 
446/1158   Aggressive f (per A allele)  0.85 (0.71–1.00) 
VEGF rs699947 −2578 702/702 Austria Risk (frequency of A allele)  0.60 e  ( 38 )  
−2489 702/702  Risk (frequency of T allele)  0.95 e 
rs833061 −460 702/702  Risk (frequency of T allele)  0.92 e 
rs2010963 −634 702/702  Risk (frequency of C allele)  0.36 e 
rs25648 −7 702/702  Risk (frequency of T allele)  0.39 e 
rs3025039 +936 702/702  Risk (frequency of T allele)  0.15 e 
+1612 702/702  Risk (frequency of A allele)  0.53 e 
VEGF rs833061 −460 96/119 Taiwan Risk (per T allele) 2.2 (1.3–3.8)  ( 39 )  
53/43 d  Advanced stage  0.76 e 
58/38 d  High grade  0.88 e 
VEGF rs833061 −460 270/252 Japan Risk (TT versus CC) 0.98 (0.72–1.04)  ( 40 )  
113/157 d  Advanced stage (TT versus CC) 1.04 (0.67–1.61) 
163/105 g  High grade (TT versus CC) 1.16 (0.75–1.79) 
95 c  Recurrence (TT versus TC/CC) 2.46 (1.23–4.93) 
99 c  Survival (TT versus TC + CC) 2.98 (1.36–6.49) 
VEGF rs833061 −460 133/157 Turkey Risk (CC versus TT) 1.28 (0.51–3.20)  ( 41 )  
26/157  Advanced stage (CC versus CT/TT) 2.23 (1.01–4.93) 
52/157  High grade (CC versus CT/TT) 2.23 (0.70–6.28) 
VEGF rs3025040 +2482 193/666 USA Risk (CC versus TT) 0.72 (0.12–4.30)  ( 42 )  
rs699947 +2578 20/666  Progression (CC versus CT/TT) 3.12 (1.23–7.92) 
193/666  Risk (AA versus CC) 1.44 (0.52–3.99) 
VEGFR rs2305948 +889 193/666 USA Risk (GG versus AA) 0.98 (0.38–2.53)  ( 42 )  
rs1870377 +1416 193/666  Risk (TT versus TA/AA) 0.54 (0.28–1.05) 
rs1531289 IVS25–92 193/666  Risk (GG versus AA) 1.44 (0.77–2.71) 
rs7692791 IVS6+54 193/666  Risk (CC versus TT) 0.73 (0.38–1.40) 
FGFR rs351855   244 c USA Recurrence (GlyGly versus ArgGly/ArgArg)  0.02 e  ( 43 )  
FGFR rs2011077  492/179 Japan Risk (AA versus GG) 6.26 (3.15–12.43)  ( 44 )  
167/325  Advanced stage (AA versus GG) 5.55 (3.02–10.21) 
197/228  High grade (AA versus GG) 1.76 (0.96–1.02) 
FGFR    USA    ( 45 )  
rs1966265 1189/1254 White Risk (GG versus AA) 1.05 (0.74–1.49) 
 147/80 Black Risk (GG versus GA) 0.77 (0.31–1.93) 
rs376618 1238/1245 White Risk (AA versus GG) 0.92 (0.67–1.25) 
 145/80 Black Risk (AA versus GG) 2.46 (0.81–9.28) 
rs7708357 1258/1254 White Risk (GG versus AA) 1.03 (0.81–1.32) 
 146/78 Black Risk (GG versus AA) 0.60 (0.23–1.50) 
FGFR rs351855 G388R 2618/1992 Meta-analysis Risk (Arg versus Gly) 1.17 (1.07–1.29)  ( 46 )  
FGFR rs351855 G388R 2618/2305 Meta-analysis Risk (Arg versus Gly) 1.17 (1.07–1.29)  ( 47 )  
1542/677  Advanced stage (Arg versus Gly) 1.18 (0.96–1.44) 
1935/1787 Caucasian Risk (Arg versus Gly) 1.21 (1.00–1.47) 
492/344 Asian Risk (Arg versus Gly) 1.24 (1.02–1.51) 
191/174 African Risk (Arg versus Gly) 1.15 (0.73–1.82) 
Gene SNP rsID Alias Case/control Country Outcome  OR/HR (95% CI) a / P -value  Reference 
VEGF rs1570360 −1154  238/263 b UK Risk (GG versus AA) 0.45 (0.24–0.86)  ( 35 )  
238 c  Survival (AA versus GG) 0.49 (0.19–1.26) 
VEGF rs1570360 −1154 101/100 Tunisia Risk (GG versus AA) 0.27 (0.08–0.83)  ( 36 )  
30/71 d  Advanced stage (GG versus AA)  0.002 e 
rs2010963 −634 101/100  Risk (GG versus GC/CC) 1.95 (1.04–3.65) 
30/71 d  Advanced stage (GG versus GC/CC)  0.03 e 
rs3025039 +936 101/100  Risk (CC versus TT) 1.82 (0.13–51.93) 
30/71 d  Advanced stage (CC versus TT)  >0.05 e 
VEGF rs1570360 −1154 1158/1172 USA Risk (per A allele) 1.02 (0.90–1.15)  ( 37 )  
458/1172   Aggressive f (per A allele)  1.06 (0.90–1.24) 
rs3025039 +936 1163  Risk (per T allele) 0.98 (0.83–1.15) 
1163   Aggressive f (per T allele)  0.91 (0.73–1.14) 
rs699947 −2578 1165/1177  Risk (per A allele) 0.96 (0.86–1.08) 
460/1177   Aggressive f (per A allele)  1.05 (0.90–1.22) 
rs25648  1142/1161  Risk (per T allele) 0.96 (0.82–1.12) 
450/1161   Aggressive f (per T allele)  1.04 (0.85–1.27) 
rs2010963 −634 1138/1158  Risk (per A allele) 0.92 (0.81–1.04) 
446/1158   Aggressive f (per A allele)  0.85 (0.71–1.00) 
VEGF rs699947 −2578 702/702 Austria Risk (frequency of A allele)  0.60 e  ( 38 )  
−2489 702/702  Risk (frequency of T allele)  0.95 e 
rs833061 −460 702/702  Risk (frequency of T allele)  0.92 e 
rs2010963 −634 702/702  Risk (frequency of C allele)  0.36 e 
rs25648 −7 702/702  Risk (frequency of T allele)  0.39 e 
rs3025039 +936 702/702  Risk (frequency of T allele)  0.15 e 
+1612 702/702  Risk (frequency of A allele)  0.53 e 
VEGF rs833061 −460 96/119 Taiwan Risk (per T allele) 2.2 (1.3–3.8)  ( 39 )  
53/43 d  Advanced stage  0.76 e 
58/38 d  High grade  0.88 e 
VEGF rs833061 −460 270/252 Japan Risk (TT versus CC) 0.98 (0.72–1.04)  ( 40 )  
113/157 d  Advanced stage (TT versus CC) 1.04 (0.67–1.61) 
163/105 g  High grade (TT versus CC) 1.16 (0.75–1.79) 
95 c  Recurrence (TT versus TC/CC) 2.46 (1.23–4.93) 
99 c  Survival (TT versus TC + CC) 2.98 (1.36–6.49) 
VEGF rs833061 −460 133/157 Turkey Risk (CC versus TT) 1.28 (0.51–3.20)  ( 41 )  
26/157  Advanced stage (CC versus CT/TT) 2.23 (1.01–4.93) 
52/157  High grade (CC versus CT/TT) 2.23 (0.70–6.28) 
VEGF rs3025040 +2482 193/666 USA Risk (CC versus TT) 0.72 (0.12–4.30)  ( 42 )  
rs699947 +2578 20/666  Progression (CC versus CT/TT) 3.12 (1.23–7.92) 
193/666  Risk (AA versus CC) 1.44 (0.52–3.99) 
VEGFR rs2305948 +889 193/666 USA Risk (GG versus AA) 0.98 (0.38–2.53)  ( 42 )  
rs1870377 +1416 193/666  Risk (TT versus TA/AA) 0.54 (0.28–1.05) 
rs1531289 IVS25–92 193/666  Risk (GG versus AA) 1.44 (0.77–2.71) 
rs7692791 IVS6+54 193/666  Risk (CC versus TT) 0.73 (0.38–1.40) 
FGFR rs351855   244 c USA Recurrence (GlyGly versus ArgGly/ArgArg)  0.02 e  ( 43 )  
FGFR rs2011077  492/179 Japan Risk (AA versus GG) 6.26 (3.15–12.43)  ( 44 )  
167/325  Advanced stage (AA versus GG) 5.55 (3.02–10.21) 
197/228  High grade (AA versus GG) 1.76 (0.96–1.02) 
FGFR    USA    ( 45 )  
rs1966265 1189/1254 White Risk (GG versus AA) 1.05 (0.74–1.49) 
 147/80 Black Risk (GG versus GA) 0.77 (0.31–1.93) 
rs376618 1238/1245 White Risk (AA versus GG) 0.92 (0.67–1.25) 
 145/80 Black Risk (AA versus GG) 2.46 (0.81–9.28) 
rs7708357 1258/1254 White Risk (GG versus AA) 1.03 (0.81–1.32) 
 146/78 Black Risk (GG versus AA) 0.60 (0.23–1.50) 
FGFR rs351855 G388R 2618/1992 Meta-analysis Risk (Arg versus Gly) 1.17 (1.07–1.29)  ( 46 )  
FGFR rs351855 G388R 2618/2305 Meta-analysis Risk (Arg versus Gly) 1.17 (1.07–1.29)  ( 47 )  
1542/677  Advanced stage (Arg versus Gly) 1.18 (0.96–1.44) 
1935/1787 Caucasian Risk (Arg versus Gly) 1.21 (1.00–1.47) 
492/344 Asian Risk (Arg versus Gly) 1.24 (1.02–1.51) 
191/174 African Risk (Arg versus Gly) 1.15 (0.73–1.82) 

Note: The table includes results for meta-analysis (where at least one exists), but not results for the individual studies included in the meta-analysis.

a

HR, hazard ratio.

b

Controls included females.

c

Cases only.

d

Localized/advanced.

e

P -value.

f

A combination of stage and grade.

g

Low grade/high grade.

Table II.

Summary of epidemiologic studies of polymorphisms in other pro-angiogenesis genes and prostate cancer risk and progression

Gene SNP rsID Alias Case/control Country Outcome  OR/HR (95% CI) a / P -value  Reference 
TGF-β1 rs16949649 −509 492/492 USA Risk (CC versus TT) 1.23 (0.80–1.87)  ( 69 )  
157/157  Advanced stage (CC versus TT) 2.36 (1.03–5.43) 
133/133  High grade (CC versus TT) 1.34 (0.60–3.00) 
TGFβ1 rs16949649 −509  USA    ( 70 )  
  653/1476 All Risk (CC versus TT) 1.04 (0.76–1.42) 
  233/289  High grade (CC versus TT) 0.48 (0.27–0.85) 
  111/379  Prognosis (CC versus TT) 0.49 (0.24–1.00) 
  440/829  NHW b Risk (CC versus TT) 1.06 (0.71–1.59) 
  145/195  High grade (CC versus TT) 0.31 (0.15–0.68) 
  67/249  Prognosis (CC versus TT) 0.30 (0.10–0.89) 
  165/408  HW c Risk (CC versus TT) 1.21 (0.71–2.06) 
  73/70  High grade (CC versus TT) 0.93 (0.37–2.33) 
  39/96  Prognosis (CC versus TT) 0.96 (0.32–2.87) 
  48/239 Black Risk (CC versus TT) 1.15 (0.58–2.31) 
  15/24  High grade (CC versus TT) 1.62 (0.40–6.63) 
  5/34  Prognosis (CC versus CT) 1.74 (0.23–13.41) 
TGF-β1 rs1800470 +29 2605/3129 Meta-analysis Risk (CC/CT versus TT) 1.24 (1.02–1.52)  ( 75 )  
TNF-α   75/418 USA    ( 86 )  
rs1799724 −857 71/407 White  Aggressive d (CC versus TT)  0.75 (0.32–1.74) 
  12/56 Black  Aggressive d (CC versus TT)   NC e 
rs361525 −238 75/438 White  Aggressive d (CC versus TT)  0.90 (0.36–2.25) 
  12/56 Black  Aggressive d (CC versus TT)  1.40 (0.13–15.75) 
TNF-α rs1800629 −308 4238/4403 Meta-analysis Risk (AA versus GG) 0.89 (0.67–1.17)  ( 79 )  
TNF-α rs1799964 −1031 197/256 India Risk (TT versus CC) 2.01 (1.16–3.42)  ( 82 )  
   140/57 f  High grade (TT versus TC/CC) 1.82 (1.07–3.07) 
  87/110  Metastasis (TT versus TC/CC) 1.82 (1.07–3.07) 
rs1800630 −863 197/256  Risk (CC versus AA) 0.93 (0.45–1.89) 
   140/57 f  High grade (TT versus TC/CC)  >0.05 g 
  87/110  Metastasis (TT versus TC/CC) 1.89 (1.10–3.25) 
rs1799724 −857 197/256  Risk (CC versus TT) 0.87 (0.15–4.94) 
   140/57 f  High grade (TC/CC versus TT)  >0.05 g 
  87/110  Metastasis (TC/CC versus TT)  >0.05 g 
NOS2A  S608L  USA    ( 57 )  
rs2297518  1252/1254 All Risk (CC versus TT) 0.98 (0.66–1.46) 
  536/1254   Aggressive d (CC versus CT/TT)  1.13 (0.91–1.39) 
  715/1254  Non-aggressive (CC versus CT/TT) 1.02 (0.85–1.24) 
  1149/1373 White Risk (CC versus TT) 0.97 (0.65–1.45) 
  103/93 Black Risk (CC versus TT) 1.21 (0.13–11.7) 
rs9282801  1353/1787 All Risk (GT versus TT) 1.25 (1.06–1.46) 
  536/1787   Aggressive d (GG versus GT/TT)  1.26 (1.03–1.55) 
  716/1787  Non-aggressive (GG versus GT/TT) 1.20 (0.99–1.43) 
  1150/1393 White Risk (GT versus TT) 1.20 (1.01–1.42) 
  103/394 Black Risk (GT versus TT) 1.64 (1.02–2.66) 
rs944722  1237/1750 All Risk 0.77 (0.61–0.97) 
  530/1750   Aggressive d (AA versus AG/GG)  0.71 (0.58–0.87) 
  706/1750  Non-aggressive (AA versus AG/GG) 0.83 (0.69–1.01) 
  1137/1365 White Risk (AA versus GG) 0.79 (0.63–1.01) 
  100/385 Black Risk (AA versus GG) 0.59 (0.22–1.62) 
NOS2A rs2297518 S608L 1166/1178 USA Risk (per T allele) 1.11 (0.96–1.29)  ( 37 )  
459/1178  Aggressive d 1.03 (0.84–1.25) 
NOS3 rs2070744 −786T/C  NC e USA Risk (per C allele)  NC e  ( 37 )  
527/553   Aggressive d 0.90 (0.76–1.07) 
rs1799983 D298E 1420/1446  Risk (per T allele) 0.95 (0.82–1.10) 
556/1446   Aggressive d 0.96 (0.86–1.07) 
NOS3 rs1007311 E298D  USA    ( 57 )  
1247/1772 All Risk (AA versus GG) 1.33 (1.07–1.64) 
532/1772   Aggressive d (AA versus GG)  1.48 (1.11–1.95) 
714/1772  Non-aggressive (AA versus GG) 1.21 (0.93–1.56) 
1144/1377 White Risk (AA versus GG) 1.28 (1.02–1.61) 
102/395 Black Risk (AA versus GG) 1.85 (0.93–3.68) 
NOS3 rs1007311 E298D 125/153 Portugal Risk (GT/TT versus GG) 1.59 (0.96–2.63)  ( 59 )  
74/153 Progression 0.63 (0.29–1.39) 
EGF rs4444903 +61 1163/1178 USA Risk (per allele) 0.98 (0.87–1.10)  ( 37 )  
458/1178   Aggressive d (per allele)  0.98 (0.84–1.15) 
EGF rs4444903 +61 123/152 Portugal Risk (AA versus AG + GG) 1.94 (0.99–3.79)  ( 88 )  
67/152  High grade (AA versus AG + GG) 3.37 (1.47–7.73) 
36/152  Metastasis (AA versus AG + GG) 2.61 (1.03–6.60) 
123 h  Survival (AA versus AG + GG)  0.018 i 
HIF-1α rs11549465 +1772 1420/1450 USA Risk (CC versus TT) 0.41 (0.21–0.82)  ( 37 )  
455/1450   Aggressive d (per allele)  0.53 (0.22–1.29) 
HIF-1α rs11549465 +1772 196/196 USA Metastasis  0.024 i  ( 90 )  
ACE rs4646994  324 Meta-analysis Risk (DD versus II) 0.77 (0.64–0.92)  ( 94 )  
ACE rs4646994  189/290 China Risk (DD versus ID/II) 0.32 (0.20–0.51)  ( 98 )  
108/80 f  Advanced stage (DD versus ID/II) 2.21 (1.17–4.19) 
33/143 g  High grade (DD versus ID/II) 1.07 (0.46–2.50) 
Gene SNP rsID Alias Case/control Country Outcome  OR/HR (95% CI) a / P -value  Reference 
TGF-β1 rs16949649 −509 492/492 USA Risk (CC versus TT) 1.23 (0.80–1.87)  ( 69 )  
157/157  Advanced stage (CC versus TT) 2.36 (1.03–5.43) 
133/133  High grade (CC versus TT) 1.34 (0.60–3.00) 
TGFβ1 rs16949649 −509  USA    ( 70 )  
  653/1476 All Risk (CC versus TT) 1.04 (0.76–1.42) 
  233/289  High grade (CC versus TT) 0.48 (0.27–0.85) 
  111/379  Prognosis (CC versus TT) 0.49 (0.24–1.00) 
  440/829  NHW b Risk (CC versus TT) 1.06 (0.71–1.59) 
  145/195  High grade (CC versus TT) 0.31 (0.15–0.68) 
  67/249  Prognosis (CC versus TT) 0.30 (0.10–0.89) 
  165/408  HW c Risk (CC versus TT) 1.21 (0.71–2.06) 
  73/70  High grade (CC versus TT) 0.93 (0.37–2.33) 
  39/96  Prognosis (CC versus TT) 0.96 (0.32–2.87) 
  48/239 Black Risk (CC versus TT) 1.15 (0.58–2.31) 
  15/24  High grade (CC versus TT) 1.62 (0.40–6.63) 
  5/34  Prognosis (CC versus CT) 1.74 (0.23–13.41) 
TGF-β1 rs1800470 +29 2605/3129 Meta-analysis Risk (CC/CT versus TT) 1.24 (1.02–1.52)  ( 75 )  
TNF-α   75/418 USA    ( 86 )  
rs1799724 −857 71/407 White  Aggressive d (CC versus TT)  0.75 (0.32–1.74) 
  12/56 Black  Aggressive d (CC versus TT)   NC e 
rs361525 −238 75/438 White  Aggressive d (CC versus TT)  0.90 (0.36–2.25) 
  12/56 Black  Aggressive d (CC versus TT)  1.40 (0.13–15.75) 
TNF-α rs1800629 −308 4238/4403 Meta-analysis Risk (AA versus GG) 0.89 (0.67–1.17)  ( 79 )  
TNF-α rs1799964 −1031 197/256 India Risk (TT versus CC) 2.01 (1.16–3.42)  ( 82 )  
   140/57 f  High grade (TT versus TC/CC) 1.82 (1.07–3.07) 
  87/110  Metastasis (TT versus TC/CC) 1.82 (1.07–3.07) 
rs1800630 −863 197/256  Risk (CC versus AA) 0.93 (0.45–1.89) 
   140/57 f  High grade (TT versus TC/CC)  >0.05 g 
  87/110  Metastasis (TT versus TC/CC) 1.89 (1.10–3.25) 
rs1799724 −857 197/256  Risk (CC versus TT) 0.87 (0.15–4.94) 
   140/57 f  High grade (TC/CC versus TT)  >0.05 g 
  87/110  Metastasis (TC/CC versus TT)  >0.05 g 
NOS2A  S608L  USA    ( 57 )  
rs2297518  1252/1254 All Risk (CC versus TT) 0.98 (0.66–1.46) 
  536/1254   Aggressive d (CC versus CT/TT)  1.13 (0.91–1.39) 
  715/1254  Non-aggressive (CC versus CT/TT) 1.02 (0.85–1.24) 
  1149/1373 White Risk (CC versus TT) 0.97 (0.65–1.45) 
  103/93 Black Risk (CC versus TT) 1.21 (0.13–11.7) 
rs9282801  1353/1787 All Risk (GT versus TT) 1.25 (1.06–1.46) 
  536/1787   Aggressive d (GG versus GT/TT)  1.26 (1.03–1.55) 
  716/1787  Non-aggressive (GG versus GT/TT) 1.20 (0.99–1.43) 
  1150/1393 White Risk (GT versus TT) 1.20 (1.01–1.42) 
  103/394 Black Risk (GT versus TT) 1.64 (1.02–2.66) 
rs944722  1237/1750 All Risk 0.77 (0.61–0.97) 
  530/1750   Aggressive d (AA versus AG/GG)  0.71 (0.58–0.87) 
  706/1750  Non-aggressive (AA versus AG/GG) 0.83 (0.69–1.01) 
  1137/1365 White Risk (AA versus GG) 0.79 (0.63–1.01) 
  100/385 Black Risk (AA versus GG) 0.59 (0.22–1.62) 
NOS2A rs2297518 S608L 1166/1178 USA Risk (per T allele) 1.11 (0.96–1.29)  ( 37 )  
459/1178  Aggressive d 1.03 (0.84–1.25) 
NOS3 rs2070744 −786T/C  NC e USA Risk (per C allele)  NC e  ( 37 )  
527/553   Aggressive d 0.90 (0.76–1.07) 
rs1799983 D298E 1420/1446  Risk (per T allele) 0.95 (0.82–1.10) 
556/1446   Aggressive d 0.96 (0.86–1.07) 
NOS3 rs1007311 E298D  USA    ( 57 )  
1247/1772 All Risk (AA versus GG) 1.33 (1.07–1.64) 
532/1772   Aggressive d (AA versus GG)  1.48 (1.11–1.95) 
714/1772  Non-aggressive (AA versus GG) 1.21 (0.93–1.56) 
1144/1377 White Risk (AA versus GG) 1.28 (1.02–1.61) 
102/395 Black Risk (AA versus GG) 1.85 (0.93–3.68) 
NOS3 rs1007311 E298D 125/153 Portugal Risk (GT/TT versus GG) 1.59 (0.96–2.63)  ( 59 )  
74/153 Progression 0.63 (0.29–1.39) 
EGF rs4444903 +61 1163/1178 USA Risk (per allele) 0.98 (0.87–1.10)  ( 37 )  
458/1178   Aggressive d (per allele)  0.98 (0.84–1.15) 
EGF rs4444903 +61 123/152 Portugal Risk (AA versus AG + GG) 1.94 (0.99–3.79)  ( 88 )  
67/152  High grade (AA versus AG + GG) 3.37 (1.47–7.73) 
36/152  Metastasis (AA versus AG + GG) 2.61 (1.03–6.60) 
123 h  Survival (AA versus AG + GG)  0.018 i 
HIF-1α rs11549465 +1772 1420/1450 USA Risk (CC versus TT) 0.41 (0.21–0.82)  ( 37 )  
455/1450   Aggressive d (per allele)  0.53 (0.22–1.29) 
HIF-1α rs11549465 +1772 196/196 USA Metastasis  0.024 i  ( 90 )  
ACE rs4646994  324 Meta-analysis Risk (DD versus II) 0.77 (0.64–0.92)  ( 94 )  
ACE rs4646994  189/290 China Risk (DD versus ID/II) 0.32 (0.20–0.51)  ( 98 )  
108/80 f  Advanced stage (DD versus ID/II) 2.21 (1.17–4.19) 
33/143 g  High grade (DD versus ID/II) 1.07 (0.46–2.50) 

Note: The table includes results for meta-analysis (where at least one exists), but not results for the individual studies included in the meta-analysis.

a

HR, hazard ratio.

b

Non-Hispanic White.

c

Hispanic White.

d

A combination of stage and grade.

e

Not calculated in the manuscript due to small numbers.

f

Localized/advanced.

g

Low grade/high grade.

h

Cases only.

i

P -value.

Table III.

Summary of epidemiologic studies of polymorphisms in pro-/anti- and anti-angiogenesis genes and prostate cancer risk and progression

Gene SNP rsID Alias Case/control Country Outcome  OR/HR (95% CI) a / P -value  Reference 
Pro-/anti-angiogenesis 
MMP-1 rs1799750 −1602 283/251 Japan Risk (1G1G versus 1G2G/2G/2G) 1.04 (0.62–1.74)  ( 104 )  
158/251  Advanced Stage (1G1G versus 1G2G/2G/2G) 1.42 (0.70–2.89) 
210/251  High Grade (1G1G versus 1G2G/2G2G) 1.47 (0.62–3.50) 
MMP-2 rs1477017  1417/1450 USA Risk (AA versus GG) 1.30 (1.04–1.64)  ( 37 )  
556/1450   Aggressive b (AA versus GG)  1.36 (1.00–1.86) 
rs17301608 1414/1441  Risk (CC versus TT) 1.33 (1.06–1.67) 
557/1441   Aggressive b (CC versus TT)  1.47 (1.08–2.00) 
rs11639960 1410/1439  Risk (AA versus GG) 1.24 (0.97–1.58) 
554/1439   Aggressive b (AA versus GG)  1.21 (0.86–1.70) 
MMP-9 rs17576  521/549 USA  Aggressive b (per minor allele)  1.03 (0.86–1.22)  ( 37 )  
rs3918256  522/548   Aggressive b (per minor allele)  0.94 (0.79–1.12) 
rs2250889  527/553   Aggressive b (per minor allele)  1.09 (0.88–1.34) 
rs3787268 R574P 1415/1441  Risk (per minor allele) 0.95 (0.75–1.20) 
  555/1441   Aggressive b (per minor allele)  0.81 (0.58–1.13) 
rs2274756 R668Q 525/550   Aggressive b (per minor allele)  0.93 (0.73–1.18) 
MMP-9 rs3918242 −1562 101/109 Tunisia Risk (CC versus CT/TT) 2.86 (1.28–6.45)  ( 106 )  
55/106  High grade (CC versus CT/TT) 3.21 (1.29–8.06) 
71/106  Advanced stage (CC versus CT/TT) 2.47 (1.02–6.00) 
IL-1 rs16944 −511 247/263 UK Risk (CC versus TT)  >0.05 c  ( 35 )  
238 d  Survival (CC versus TT) 0.77 (0.33–1.76) 
IL-1    USA    ( 86 )  
rs16944 −511  74/418 e White  Aggressive b (CC versus TT)  0.99 (0.42–2.31) 
   13/58 e Black  Aggressive b (CC versus TT)  6.55 (0.59–72.35) 
rs1143627 −31  74/417 e White  Aggressive b (TT versus CC)  1.25 (0.55–2.86) 
   13/57 e Black  Aggressive b (TT versus CC)  6.64 (0.60–73.78) 
rs1143634 +3954  75/413 e White  Aggressive b (CC versus TT)  3.11 (1.20–8.06) 
   13/58 e Black  Aggressive b (CC versus TT)  3.07 (0.22–43.40) 
IL-1 rs16944 −511 473/607 USA Risk (CC versus TT)   ( 109 )  
  124/607  Advanced stage (CC versus TT) 0.80 (0.54–1.20) 
  359/607  Early stage (CC versus TT) 1.03 (0.53–2.01) 
rs1143634 −31 486/614  Risk (CC versus TT) 0.74 (0.48 (1.16) 
  124/614  Advanced stage (CC versus TT) 1.22 (0.70–2.12) 
  359/614  Early stage (CC versus TT) 1.54 (0.64–3.68) 
  473/607  Risk (CC versus TT) 0.91 (0.69–1.21) 
IL-6    USA    ( 86 )  
rs1800797 −598  70/383 e White  Aggressive b (GG versus GA)  1.19 (0.66–2.14) 
   4/22 e Black  Aggressive b (GG versus GA)  1.19 (0.18–7.7) 
rs2069832 +180  66/176 e White  Aggressive b (GG versus GA)  1.08 (0.59–1.97) 
   12/79 e Black  Aggressive b (GG versus GA)  1.71 (0.25–11.57) 
rs1800795 −174  74/401 e White  Aggressive b (CC versus GG)  0.77 (0.39–1.52) 
   15/57 e Black  Aggressive b (CC versus GG)  0.38 (0.05–3.13) 
IL-6 rs1800795 −174 484/613 USA Risk (CC versus TT) 1.18 (0.82–1.69)  ( 109 )  
  124/613  Advanced stage (CC versus TT) 1.00 (0.55–1.83) 
  359/613  Early stage (CC versus TT) 1.21 (0.82–1.80) 
IL-6 rs1800795 −236 1053/1053 Finland Risk (CC versus GG) 0.87 (0.67–1.13)  ( 81 )  
rs2069832 IVS2 + 180 1053/1053  Risk (AA versus GG) 0.92 (0.71–1.20) 
rs2069849 Ex5 + 132 1053/1053  Risk (CC versus CT) 1.17 (0.68–2.01) 
IL-8 rs4073 −251 247/263 UK Risk (AA versus TT) 0.66 (0.44–0.99)  ( 35 )  
   238 d  Survival (TT versus AA) 1.26 (0.59–2.67) 
IL-8    USA    ( 86 )  
rs2227307 +230  71/393 e White  Aggressive b (GG versus TT)  1.10 (0.57–2.13) 
   12/55 e Black  Aggressive b (GG versus TT)  0.43 (0.05–3.65) 
 −47  71/387 e White  Aggressive b (CC versus TT)  1.29 (0.14–11.67) 
   13/56 e Black  Aggressive b (CC versus TT)  5.10 (0.32–81.48) 
rs4073 −251  65/353 e White  Aggressive b (TT versus AA)  0.78 (0.39–1.56) 
   11/48 e Black  Aggressive b (TT versus AA)  1.44 (0.10–19.95) 
IL-8 rs4073 −251 484/613 USA Risk (GG versus CC) 0.91 (0.65–1.29)  ( 109 )  
  124/613  Advanced stage (GG versus CC) 0.64 (0.36–1.13) 
  359/613  Early stage (GG versus CC) 1.02 (0.70–1.48) 
IL-8 rs4073 −251 584/584 Finland Risk (TT versus AA) 1.2 (0.8–1.8)  ( 110 )  
IL-10 rs1800896 −1082 3385/4311 Meta-analysis Risk (G versus A) 0.94 (0.83–1.06)  ( 117 )  
rs1800871 −819 2827/3685  Risk (T versus C) 0.95 (0.83–1.09) 
   1076/708 f  Advanced stage (C versus T) 1.16 (1.04–1.31) 
rs1800872 −592 2243/2508  Risk (A versus C) 1.02 (0.96–1.08) 
   1424/1064 f  Advanced stage (C versus A) 1.13 (1.01–1.26) 
IL-10 rs1800896 −1082 4846/5244 Meta-analysis  Risk ( G versus A)  1.00 (0.91–1.10)  ( 118 )  
rs1800871 −819 2939/3899 Risk (T versus C) 0.96 (0.85–1.08) 
rs1800872 −592 3741/3507 Risk (A versus C) 1.03 (0.96–1.11) 
IL-10 rs1800871 −819  116 d Taiwan Recurrence (AA versus AG/GG) 2.97 (1.07–8.23)  ( 119 )  
IL-18 rs187237 −137 265/280 China Risk (GG versus CC) 2.18 (1.03–4.60)  ( 120 )  
rs1946518 −607 265/280 Risk (CC versus AA) 1.20 (0.74–1.96) 
Anti-angiogenesis 
COL18A1 rs1248337 D104N 1841/198 Brazil Risk (DN versus DD) 2.4 (1.4–4.2)  ( 126 )  
COL18A1 rs1248337 D104N  USA    ( 127 )  
  253/190 White Progression (DN versus DD) 0.87 (0.51–1.49) 
  136/162 Black Progression (DN versus DD) 0.46 (0.05–4.47) 
COL18A1 rs1248337 D104N 544/678 USA Risk (NN/DN versus DD) 1.2 (0.9–1.6)  ( 129 )  
147/678  Advanced stage (NN/DN versus DD) 0.8 (0.5–1.4) 
223/678  High grade (NN/DN versus DD) 1.0 (0.7–1.5) 
129 d  Progression (NN/DN versus DD) 1.2 (0.7–1.8) 
Gene SNP rsID Alias Case/control Country Outcome  OR/HR (95% CI) a / P -value  Reference 
Pro-/anti-angiogenesis 
MMP-1 rs1799750 −1602 283/251 Japan Risk (1G1G versus 1G2G/2G/2G) 1.04 (0.62–1.74)  ( 104 )  
158/251  Advanced Stage (1G1G versus 1G2G/2G/2G) 1.42 (0.70–2.89) 
210/251  High Grade (1G1G versus 1G2G/2G2G) 1.47 (0.62–3.50) 
MMP-2 rs1477017  1417/1450 USA Risk (AA versus GG) 1.30 (1.04–1.64)  ( 37 )  
556/1450   Aggressive b (AA versus GG)  1.36 (1.00–1.86) 
rs17301608 1414/1441  Risk (CC versus TT) 1.33 (1.06–1.67) 
557/1441   Aggressive b (CC versus TT)  1.47 (1.08–2.00) 
rs11639960 1410/1439  Risk (AA versus GG) 1.24 (0.97–1.58) 
554/1439   Aggressive b (AA versus GG)  1.21 (0.86–1.70) 
MMP-9 rs17576  521/549 USA  Aggressive b (per minor allele)  1.03 (0.86–1.22)  ( 37 )  
rs3918256  522/548   Aggressive b (per minor allele)  0.94 (0.79–1.12) 
rs2250889  527/553   Aggressive b (per minor allele)  1.09 (0.88–1.34) 
rs3787268 R574P 1415/1441  Risk (per minor allele) 0.95 (0.75–1.20) 
  555/1441   Aggressive b (per minor allele)  0.81 (0.58–1.13) 
rs2274756 R668Q 525/550   Aggressive b (per minor allele)  0.93 (0.73–1.18) 
MMP-9 rs3918242 −1562 101/109 Tunisia Risk (CC versus CT/TT) 2.86 (1.28–6.45)  ( 106 )  
55/106  High grade (CC versus CT/TT) 3.21 (1.29–8.06) 
71/106  Advanced stage (CC versus CT/TT) 2.47 (1.02–6.00) 
IL-1 rs16944 −511 247/263 UK Risk (CC versus TT)  >0.05 c  ( 35 )  
238 d  Survival (CC versus TT) 0.77 (0.33–1.76) 
IL-1    USA    ( 86 )  
rs16944 −511  74/418 e White  Aggressive b (CC versus TT)  0.99 (0.42–2.31) 
   13/58 e Black  Aggressive b (CC versus TT)  6.55 (0.59–72.35) 
rs1143627 −31  74/417 e White  Aggressive b (TT versus CC)  1.25 (0.55–2.86) 
   13/57 e Black  Aggressive b (TT versus CC)  6.64 (0.60–73.78) 
rs1143634 +3954  75/413 e White  Aggressive b (CC versus TT)  3.11 (1.20–8.06) 
   13/58 e Black  Aggressive b (CC versus TT)  3.07 (0.22–43.40) 
IL-1 rs16944 −511 473/607 USA Risk (CC versus TT)   ( 109 )  
  124/607  Advanced stage (CC versus TT) 0.80 (0.54–1.20) 
  359/607  Early stage (CC versus TT) 1.03 (0.53–2.01) 
rs1143634 −31 486/614  Risk (CC versus TT) 0.74 (0.48 (1.16) 
  124/614  Advanced stage (CC versus TT) 1.22 (0.70–2.12) 
  359/614  Early stage (CC versus TT) 1.54 (0.64–3.68) 
  473/607  Risk (CC versus TT) 0.91 (0.69–1.21) 
IL-6    USA    ( 86 )  
rs1800797 −598  70/383 e White  Aggressive b (GG versus GA)  1.19 (0.66–2.14) 
   4/22 e Black  Aggressive b (GG versus GA)  1.19 (0.18–7.7) 
rs2069832 +180  66/176 e White  Aggressive b (GG versus GA)  1.08 (0.59–1.97) 
   12/79 e Black  Aggressive b (GG versus GA)  1.71 (0.25–11.57) 
rs1800795 −174  74/401 e White  Aggressive b (CC versus GG)  0.77 (0.39–1.52) 
   15/57 e Black  Aggressive b (CC versus GG)  0.38 (0.05–3.13) 
IL-6 rs1800795 −174 484/613 USA Risk (CC versus TT) 1.18 (0.82–1.69)  ( 109 )  
  124/613  Advanced stage (CC versus TT) 1.00 (0.55–1.83) 
  359/613  Early stage (CC versus TT) 1.21 (0.82–1.80) 
IL-6 rs1800795 −236 1053/1053 Finland Risk (CC versus GG) 0.87 (0.67–1.13)  ( 81 )  
rs2069832 IVS2 + 180 1053/1053  Risk (AA versus GG) 0.92 (0.71–1.20) 
rs2069849 Ex5 + 132 1053/1053  Risk (CC versus CT) 1.17 (0.68–2.01) 
IL-8 rs4073 −251 247/263 UK Risk (AA versus TT) 0.66 (0.44–0.99)  ( 35 )  
   238 d  Survival (TT versus AA) 1.26 (0.59–2.67) 
IL-8    USA    ( 86 )  
rs2227307 +230  71/393 e White  Aggressive b (GG versus TT)  1.10 (0.57–2.13) 
   12/55 e Black  Aggressive b (GG versus TT)  0.43 (0.05–3.65) 
 −47  71/387 e White  Aggressive b (CC versus TT)  1.29 (0.14–11.67) 
   13/56 e Black  Aggressive b (CC versus TT)  5.10 (0.32–81.48) 
rs4073 −251  65/353 e White  Aggressive b (TT versus AA)  0.78 (0.39–1.56) 
   11/48 e Black  Aggressive b (TT versus AA)  1.44 (0.10–19.95) 
IL-8 rs4073 −251 484/613 USA Risk (GG versus CC) 0.91 (0.65–1.29)  ( 109 )  
  124/613  Advanced stage (GG versus CC) 0.64 (0.36–1.13) 
  359/613  Early stage (GG versus CC) 1.02 (0.70–1.48) 
IL-8 rs4073 −251 584/584 Finland Risk (TT versus AA) 1.2 (0.8–1.8)  ( 110 )  
IL-10 rs1800896 −1082 3385/4311 Meta-analysis Risk (G versus A) 0.94 (0.83–1.06)  ( 117 )  
rs1800871 −819 2827/3685  Risk (T versus C) 0.95 (0.83–1.09) 
   1076/708 f  Advanced stage (C versus T) 1.16 (1.04–1.31) 
rs1800872 −592 2243/2508  Risk (A versus C) 1.02 (0.96–1.08) 
   1424/1064 f  Advanced stage (C versus A) 1.13 (1.01–1.26) 
IL-10 rs1800896 −1082 4846/5244 Meta-analysis  Risk ( G versus A)  1.00 (0.91–1.10)  ( 118 )  
rs1800871 −819 2939/3899 Risk (T versus C) 0.96 (0.85–1.08) 
rs1800872 −592 3741/3507 Risk (A versus C) 1.03 (0.96–1.11) 
IL-10 rs1800871 −819  116 d Taiwan Recurrence (AA versus AG/GG) 2.97 (1.07–8.23)  ( 119 )  
IL-18 rs187237 −137 265/280 China Risk (GG versus CC) 2.18 (1.03–4.60)  ( 120 )  
rs1946518 −607 265/280 Risk (CC versus AA) 1.20 (0.74–1.96) 
Anti-angiogenesis 
COL18A1 rs1248337 D104N 1841/198 Brazil Risk (DN versus DD) 2.4 (1.4–4.2)  ( 126 )  
COL18A1 rs1248337 D104N  USA    ( 127 )  
  253/190 White Progression (DN versus DD) 0.87 (0.51–1.49) 
  136/162 Black Progression (DN versus DD) 0.46 (0.05–4.47) 
COL18A1 rs1248337 D104N 544/678 USA Risk (NN/DN versus DD) 1.2 (0.9–1.6)  ( 129 )  
147/678  Advanced stage (NN/DN versus DD) 0.8 (0.5–1.4) 
223/678  High grade (NN/DN versus DD) 1.0 (0.7–1.5) 
129 d  Progression (NN/DN versus DD) 1.2 (0.7–1.8) 

Note: The table includes results for meta-analysis (where at least one exists), but not results for the individual studies included in the meta-analysis.

a

HR, hazard ratio.

b

A combination of stage and grade.

c

P -value.

d

Cases only.

e

High aggressive/low + intermediate aggressive.

f

Localized/advanced.

Pro-angiogenesis genes

Vascular endothelial growth factor

VEGF is the most important regulator of angiogenesis and plays a critical role in both the development and metastasis of tumors. It has a mitogenic effect on endothelial cells and promotes their migration and invasion and also facilitates metastasis by increasing vascular permeability to tumor cells ( 48 ). It is one of a family of six protein isoforms expressed in different tissues including the prostate. The expression of VEGF is positively associated with microvessel density, tumor stage, Gleason score and disease-specific survival in prostate cancer patients ( 49 ). Furthermore, plasma VEGF is higher in patients with localized prostate cancer than in healthy controls ( 50 ).

VEGF is highly polymorphic and SNPs, particularly at −1154 (A/G), −634 (G/C) and −460 (C/T) in the promoter region, shown to affect its expression ( 51 ) have been studied in relation to prostate cancer risk and progression. The AA genotype at −1154 has been associated with low expression of VEGF and two previous independent studies have shown that carriers of the A allele have a reduced risk (OR = 0.27–0.45) of prostate cancer ( 35 , 36 ). Though this finding is intriguing, both studies were relatively small and in one of the studies ( 35 ), almost half of the controls (124 of 263) were females. In a large study, Jacobs et al. ( 37 ) did not observe an association for this variant (per A allele or comparing GG to AA) or other variants in the promoter (rs699947), 3′ untranslated region (rs3025039) or exon 1 (rs25648 and rs2010963) with risk or advanced disease, albeit rs2010963 was associated with a borderline statistically ( P = 0.05) reduced risk of advanced disease.

An increased risk of prostate cancer and an aggressive phenotype for homozygous and heterozygous carriers of the C allele at VEGF −634 (GC + CC) have been reported in a small study ( 36 ). However, in a medium-sized study (702 cases and 702 controls) that examined seven SNPs in the promoter, coding or untranslated regions of VEGF , none of the SNPs (all P ≥ 0.15), including −634, was associated with the risk for prostate cancer ( 38 ). Furthermore, this study did not find an association at any of the SNPs with stage, histological grade, prostate-specific antigen level at the time of diagnosis, age at diagnosis or VEGF plasma level ( 38 ). Studies on VEGF −460 polymorphism have also produced inconsistent results. One small study observed that the T allele of VEGF −460 polymorphism was associated with an increased risk of prostate cancer, but not with clinical stage ( P = 0.76) or grade ( P = 0.88) ( 39 ). Two subsequent small studies did not confirm this finding ( 40 , 41 ), but an association between this SNP with biochemical recurrence after radical prostatectomy and survival was observed in one of the studies ( 40 ). Other SNPs in the promoter region of VEGF or in the VEGF receptor are not associated with prostate cancer ( 38 , 42 ).

Investigation of VEGF variants with risk or progression of prostate cancer has been largely limited to SNPs in the promoter region and the results have been inconsistent. The role of VEGF variants in prostate cancer therefore remains inconclusive.

Nitric oxide synthase

Nitric oxide (NO) has a dual yet opposing role in carcinogenesis. It promotes carcinogenesis through induction of angiogenesis, whereas it inhibits carcinogenesis through induction of cell death ( 52 ). NOS is the enzyme that synthesizes NO in the cell. It has multiple isoforms: neuronal NOS (NOS1), inducible NOS (NOS2) and endothelial NOS (NOS3) ( 53 ). NOS2 (gene for NOS2 is NOS2A ) is over expressed in prostate tumor tissues ( 54 , 55 ) and NOS3 protects prostate cancer cells from apoptosis ( 56 ). A large nested case–control study in the screening arm of the Prostate Lung Colon and Ovary (PLCO) cohort screening Trial found that polymorphisms in NOS2A (rs9282801 and rs944722) and NOS3 (rs1007311) were generally associated with aggressive cancer (stage III–IV or Gleason score ≥7) ( 57 ). The authors attempted to confirm their results in Cancer Genetic Markers of Susceptibility (CGEMS), which included ∼72% of the subjects in the PLCO study. Only one SNP ( NOS2A rs2297518) overlapped between the PLCO and CGEMs studies and this SNP was not associated with prostate cancer in both studies. One NOS2A SNP (rs944722) that showed an association in the PLCO study was in high linkage disequilibrium ( r2 = 0.96) with an SNP (rs2274894) in CGEMS that showed association in the same direction as that of rs944722, albeit marginally statistically significant ( P = 0.10). In this study, one SNP in NOS2A (rs9282801) showed a statistical interaction ( Pinteraction = 0.01) with antioxidant vitamin intake and was associated with aggressive prostate cancer among subjects with a high antioxidant intake (OR = 1.61, 95% CI = 1.18–2.19), but not among subjects with low antioxidant intake (OR = 1.06, 95% CI = 0.76–1.48). This potential interaction is intriguing because of the potential role of NO as a reactive oxygen species scavenger that protects tumors from reactive oxygen species-induced apoptosis ( 58 ) and therefore warrants further investigation.

A 27-bp repeat polymorphism in intron 4 of NOS3 was associated with prostate cancer risk and a non-synonymous codon 298 polymorphism of this gene was associated with advanced prostate cancer and bone metastasis in a small ( N = 278) case–control study ( 59 ). In a larger study, Jacobs et al. ( 37 ) did not observe an association between NOS2 and NOS3 polymorphisms and prostate cancer risk or advanced disease. Therefore, evidence for an association between NOS polymorphisms and prostate cancer remains inconclusive.

Fibroblast growth factor receptor

Fibroblast growth factors (FGFs), along with VEGF, are key players in tumor angiogenesis and their inhibition represses tumor growth. Aberrant expression of multiple FGF family members and their cognate receptors are found in multiple cancers, including prostate cancer ( 60 ). Normal prostate stromal cells produce several FGFs, whereas prostate epithelial cells express corresponding FGF receptors (FGFR). The FGF/FGFR family members act as mediators of communication between the epithelium and the stroma (reviewed in ( 61 )). FGFR4 is the only member of the FGF/FGFR family that has been investigated in several studies to examine association of its genetic variants with prostate cancer risk and progression. The most studied polymorphism contains either glycine (Gly) or arginine (Arg) at codon 388 [ FGFR4 Gly388Arg (G388R) or rs351855] in the transmembrane domain of the receptor. This polymorphism has been associated with tumor aggressiveness or patients' survival in several cancers ( 62 , 63 ). However, results for studies of prostate cancer risk have been inconsistent with some studies reporting an association ( 43 , 44 ) or no association ( 45 , 64 ). Two meta-analyses of the same four studies concluded that the Arg(388) allele of FGFR4 Gly388Arg is associated with a modest increased risk (OR = 1.17, 95% CI = 1.07–1.29) of prostate cancer ( 46 , 47 ) for all ethnicities combined. One of the meta-analysis ( 47 ) found that the increased risk was more prominent in Caucasians (OR = 1.21, 95% CI = 1.00–1.47) and Asians (OR = 1.24, 95% CI = 1.02–1.51), but not African-Americans (OR = 1.15, 95% CI = 0.73–1.82). Furthermore, prostate cancer patients with the Arg/Arg genotype had an increased risk of advanced and metastatic disease compared with those with Gly/Gly + Gly/Arg genotypes ( 47 ). One study that was part of the meta-analysis found an association between this SNP and biochemical recurrence ( 43 ). An intron 11 SNP (rs2011077) in FGFR was associated with increased risk of prostate cancer and advanced stage disease ( 44 ), but other SNPs (rs1966265, rs376618 and rs7708357) have shown no association with risk ( 45 ).

There are some data to suggest that FGFR4 388 polymorphism is associated with increased risk of prostate cancer and advanced disease, particularly in Caucasians and Asians ( 46 , 47 ), but limited data exist on other polymorphisms in this gene.

Transforming growth factor beta

TGF-β is a family of potent regulators of cellular proliferation, differentiation and morphogenesis, as well as extracellular matrix formation, extracellular proteolysis, and inflammation. Alterations in gene expression, secretion and regulation of TGF-β may lead to a favorable environment for tumor development by angiogenesis stimulation and immune system suppression ( 65 ). Of the TGF-βs, TGF-β1 is highly expressed in prostate cancer and leads to tumor promotion and metastasis ( 66 ). Several polymorphisms in TGF-β1 gene have been identified, and two variants in strong linkage disequilibrium, C−509T and T+29C, are associated with increased serum levels ( 67 , 68 ).

A nested case–control study within the Physicians Health Study observed that the T allele of TGF-β1 C-509T was associated with advanced disease, but not with risk or high-grade prostate cancer ( 69 ). However, in a larger study, the TT genotype of TGF-β1 C-509T was associated with decreased risk of high-grade prostate cancer and poor prognosis among non-Hispanic White men, but no association for Hispanic White men or Black men ( 70 ).

The polymorphism at +29 of TGF-β1 is non-synonymous and changes a leucine to a proline. A meta-analysis of different cancers, including five prostate cancer studies ( 69 , 71–74 ), stratified by cancer type concluded there was a modest increased risk (OR = 1.24, 95% CI = 1.02–1.52) of prostate cancer among carriers of the C allele of T+29C polymorphism ( 75 ). Interestingly, the frequency of the C allele differed among the six studies from 0.29 in Europeans in Brazil ( 71 ) to 0.54 among Europeans in Germany ( 74 ). Thus, findings to date for TGF-β1 C-509T are inconsistent, but TGF-β1 T+29C may be associated with a modest increased risk of prostate cancer.

Tumor necrosis factor alpha

TNF-α is a multifunctional cytokine with a key role in angiogenesis. It facilitates angiogenesis by directly stimulating proliferation of endothelial cells or by indirectly regulating the expression of pro-angiogenic factors ( 76–78 ). A number of studies have been conducted to examine the association between TNF-α polymorphisms and prostate cancer risk. Wang et al. ( 79 ) recently performed a meta-analysis including 30 case–control studies with a total number of 16 507 cases and 19 749 controls to derive a precise estimation of the association between the most studied TNF-α polymorphism, TNF-α-308 A/G (rs1800629), and the risk of four common cancers, including prostate cancer. A subgroup analysis on prostate cancer that included six studies ( 80–85 ) consisting of 4238 cases and 4403 controls revealed that rs1800629 was not associated with prostate cancer risk (OR = 0.89, 95% CI = 0.67–1.17).

Other polymorphisms in TNF-α , such as −1031T>C, −857 C>T and −238, that alter expression are less studied. Increased risk of prostate cancer has been reported for the CC genotype at −1031 and −1031 C and −857 T alleles are associated with higher tumor grade and an increased risk of tumor progression and metastasis ( 82 ). However, Zabaleta et al. ( 86 ) did not observe an association with aggressive (using a combination of Gleason score and clinical stage) disease for the −857 polymorphism.

The association between TNF-α −308 variants and prostate cancer is null and the association with advanced disease for other variants is inconsistent.

Other pro-angiogenesis genes

Epidermal growth factor (EGF) activates several pro-oncogenic intracellular pathways inducing proliferation, differentiation and tumorigenesis in epithelial cells by binding to the EGF receptor. Although EGF can have direct effects on tumor cells, it also promotes angiogenesis, predominantly through a mitogenic effect on endothelial cells ( 87 ). In a small study comparing prostate cancer patients treated with androgen blockade therapy ( N = 123) to healthy controls ( N = 152), an association was observed between a functional EGF SNP at +61G/A (rs4444903) and high Gleason (≥7) score, metastatic disease and survival ( 88 ). In a larger (1425 cases and 1453 controls) and more comprehensive (16 SNPs in EGF ) study, Jacobs et al. ( 37 ) did not observe an association with EGF polymorphisms, including +61G/A, and prostate cancer risk or advanced disease.

The hypoxia-inducible factor-1 (HIF-1) is a transcription factor that regulates the expression of genes involved in various cellular functions, including angiogenesis, in response to hypoxia ( 89 ). HIF-1 binds to DNA as a heterodimer consisting of HIF-1α and HIF-1β. Unlike HIF-1β which is ubiquitously expressed, HIF-1α expression is tightly regulated by oxygen tension ( 89 ). Two non-synonymous polymorphisms (C1772T and G1790A) in exon 12 within the oxygen-dependent degradation region of HIF-1α that may result in overexpression and enhanced stability of the protein has been described. In a small study of androgen-independent prostate cancer (AIPC) patients ( N = 196) and healthy controls ( N = 196), the C1772T polymorphism was associated with AIPC, but the frequency of the G1790A polymorphism was low (AIPC = 3.1% and controls = 1.5%) and no definitive conclusion could be reached ( 90 ). Li et al. ( 91 ) did not observe a direct association with prostate cancer risk for the two variants but observed that men with the CC genotype of HIF-1α C1772T and higher IGFBP-3 serum levels had a lower risk of aggressive prostate cancer. Recently, Foley et al. ( 92 ) observed that heterozygous carriers of the C1772T polymorphism of HIF-1α have an increased risk for clinically localized prostate cancer, though the CT genotype did not modulate HIF-1α protein expression in hypoxia in vitro . Jacobs et al. ( 37 ) did not observe an association between HIF-1 polymorphisms and prostate cancer risk or aggressive disease.

Angiotensin II (Ang II) is a main effector in the renin–angiotensin system and plays a critical role in cell proliferation and angiogenesis ( 93 ). Angiotensin-converting enzyme (ACE) generates Ang II from its precursor. ACE is synthesized by the prostate and an insertion (I)/deletion (D) polymorphism in the ACE gene has been described, with the highest levels of circulating and tissue ACE activity found in carriers of the DD genotype ( 94 ). In a recent meta-analysis, including three studies ( 95–97 ), a lower risk of prostate cancer was observed for carriers of the II genotype compared with the DD genotype ( 94 ). A similar finding was recently observed among Han Chinese where the II genotype and I allele, compared with the DD genotype and D allele, were associated with a decreased risk of prostate cancer ( 98 ), suggesting that this genotype may influence the behavior of human prostate cancer.

Pro-/anti-angiogenesis genes

Matrix metalloproteinases

MMPs are a multifarious family of proteolytic enzymes involved in tumor growth, invasion and metastasis through the breakdown of extracellular matrix and release of pro-angiogenic factors ( 99 ). MMPs were initially recognized as pro-angiogenic, but recent evidence suggests that individual MMPs can exhibit pro- or anti-angiogenesis properties depending on the type and stage of development of a particular cancer ( 100 , 101 ). The family of mammalian MMPs includes 24 members, but only polymorphisms in MMP-1 , -2 and -9 have been studied in relation to prostate cancer.

An insertion/deletion SNP 2G/1G (−1602) in the promoter region of MMP-1 has been described ( 102 , 103 ). This polymorphic site usually has one guanine (1G) and the insertion of an additional guanine at the site (2G) enhances the expression of MMP-1 ( 102 , 103 ). The presence of the second G allele of the MMP-1 promoter polymorphism was not associated with susceptibility or progression of prostate cancer ( 104 , 105 ). Associations between three correlated intronic SNPs (rs1477017, rs17301608 and rs11639960) among 13 genotyped SNPs in MMP-2 and prostate cancer risk and advanced disease were reported in the Cancer Prevention Study II Nutrition Cohort ( 37 ). However, associations for two (rs17301608 and rs11639960) of the three SNPs were not confirmed in an independent dataset using cases from the CGEMS GWAS and controls from the PLCO study cohort. The other SNP was not genotyped in CGEMS.

Sfar et al. ( 106 ) observed that subjects carrying at least one copy of the MMP-9 T allele of a functional genetic variant of MMP-9 (−1562 C/T, rs3918242) had an increased risk of developing a high-grade tumor and advanced disease, but preliminary results from a recent study did not detect an association between −1562 C/T ( P = 0.91) or other polymorphisms (Q279R and R574P) in MMP-9 and prostate cancer aggressiveness ( 107 ). However, the recent study was based on only 97 patients and only 32 showed a positive biopsy for prostate cancer. In a large study, Jacobs et al. ( 37 ) did not observe an association with prostate cancer risk or advanced disease for five SNPs (including R574P) in MMP-9 . Therefore, the evidence to date suggests that MMP SNPs are not likely to be associated with prostate cancer risk or progression.

Interleukins

Chronic inflammation is one of several factors associated with the development of prostate cancer. ILs are a group of cytokines and variants in cytokine genes have been associated with increased inflammation and cytokine production. Murphy et al. ( 17 ) observed that expression of IL-8 correlates with Gleason score, tumor stage and microvessel density. Lehrer et al. ( 108 ) reported an elevation of serum IL-8 in prostate cancer patients with bone metastases, when compared with men with localized prostate cancer.

Few studies have been conducted on IL , except for IL-10 , variants in the context of prostate cancer. One polymorphism (rs16944) in IL-1 is associated with aggressive disease among Caucasians ( 86 ) and the interaction between IL-1 and IL-10 is associated with increased risk (OR = 3.38, 95% CI = 1.70–6.71) of prostate cancer among this group ( 83 ). Presently, no association with risk or survival has been observed for this variant or other IL-1 variants ( 35 , 109 ). IL-6 variants have not been associated with risk or aggressive disease ( 81 , 109 ). Association with IL-8 has been inconsistent with one study reporting a reduction in risk associated with the TT genotype of IL-8– 251 ( 35 ), whereas other studies have reported no association with risk or aggressive disease for this polymorphism ( 86 , 110 ).

IL-10 is the most studied IL in the context of IL variants and prostate cancer. IL-10 is a pleiotropic cytokine that inhibits tumor-induced angiogenesis and inflammation. The anti-angiogenesis effect of IL-10 reduces tumor growth, whereas its anti-inflammatory effect promotes tumorigenesis by enabling tumor cells to escape immune surveillance ( 111 , 112 ). Reduced levels of IL-10 expression have been associated with polymorphisms in its promoter region ( IL-10 −1082, −819 and −592) and several studies have examined the association between these polymorphisms and prostate cancer. However, the results have been inconsistent with some studies reporting an increased ( 35 , 80 , 83 , 86 , 113–115 ), decreased ( 83 ) or no association ( 115 , 116 ) with risk or progression.

To derive a more precise estimation of the association between IL-10 gene polymorphisms and prostate cancer, two meta-analyses have been recently performed. In one meta-analysis including 10 studies (4107 cases and 5274 controls), there were no significant associations between prostate cancer risk and IL-10 −1082 A>G (rs1800896), −819 C>T (rs1800871) or −592 C>A (rs1800872) polymorphisms and the results were similar for Asians and Caucasians ( 117 ). However, the meta-analysis suggested that rs1800871 and rs1800872 polymorphisms might be modestly associated with advanced disease and might therefore impact disease progression. Controls in some of the studies that are included in this meta-analysis deviated from Hardy–Weinberg and also had benign prostatic hyperplasia, which could potentially bias the summary estimate. A second larger meta-analysis including 5503 cases and 6078 controls from 12 studies (including 10 in the previous meta-analysis) also did not observe associations between IL-10 rs1800896, rs1800871 and rs1800872 polymorphisms and prostate cancer risk and the findings were similar for Asians and Caucasians ( 118 ). This finding provides additional evidence that these polymorphisms may not be associated with prostate cancer risk.

To date, only one study has examined polymorphisms in ILs with biochemical recurrence of prostate cancer after radical prostatectomy ( 119 ). This study observed that the AA genotype of IL-10 rs1800871 was independently associated with a higher risk of prostate-specific antigen recurrence compared with the A/G + G/G genotypes, suggesting that the IL-10 polymorphism may be a prognostic factor for prostate-specific antigen recurrence after radical prostatectomy ( 119 ). However, this study included only 116 cases and the finding needs to be replicated in an independent larger study. Analysis of two SNPs (−137 G/C and −607 C/A) in the IL-18 gene promoter in a Chinese population observed that −137 GC and CC genotypes and the −137C/−607A haplotype were associated with a significantly increased risk of prostate cancer compared with the −137 GG genotypes or the −137G/−607C haplotype ( 120 ).

So far, the association between SNPs in ILs and prostate cancer risk is generally null, but the available evidence suggests that IL variants may be associated with advanced disease and potentially recurrence of the disease.

Anti-angiogenesis gene

COL18A1 (endostatin)

Endostatin is a C-terminal cleavage product of the extracellular matrix protein collagen XVIII ( COL18A1 ). It inhibits endothelial cell proliferation in vitro and tumor angiogenesis and growth in vivo ( 121 ). Endostatin is an important inhibitory molecule which mediates the sequential steps involved in angiogenesis. Higher serum levels of endostatin in animal models result in regression of solid tumors ( 122–124 ). Furthermore, the lower incidence of tumors in Down syndrome patients who have higher serum levels of endostatin provides further evidence for the tumor suppressive role of endostatin ( 125 ).

A non-synonymous polymorphism in the endostatin gene ( COL18A1 ) occurs at codon 104, which results in the change of aspartic acid to asparagine (D104N, rs1248337). Though this polymorphism does not appear to affect expression, structural modeling suggests it may impair binding to other molecules that could decrease its potential to inhibit angiogenesis ( 126 ). The D104N polymorphism has been associated with increased risk, but not aggressiveness, of prostate cancer, among Caucasians and Blacks in Brazil ( 126 ). However, the study had only 61 and 11 classified Caucasian and Black cases, respectively, and only one unclassified participant aged ≥65 years was homozygous for the N allele in the study. Macpherson et al. ( 127 ) did not observe an association with this polymorphism and AIPC or survival. In another study, endostatin D104N polymorphism was not associated with aggressiveness or disease-free survival ( 128 ). In a recent larger prospective study (544 incident cases and 678 matched controls) within the Physicians' Health Study, no overall association was observed between carriage of the N allele of endostatin D104N and prostate cancer risk or cancer-specific mortality ( 129 ). However, an analysis stratified by body mass index (BMI) revealed that among men homozygous for the D allele, overweight and obese (BMI ≥25 kg/m 2 ) men had a twofold increased risk of prostate cancer, prostate cancer death or metastasis. In contrast, healthy weight (BMI <25 kg/m 2 ) men who had at least one copy of the N allele had a higher prostate cancer risk and a worse prognosis. These findings suggest that BMI may interact with this polymorphism in prostate cancer development and progression.

The evidence to date suggests that endostatin is not associated with prostate cancer risk or progression but may interact with BMI to impact risk and outcome. However, this interaction has been examined in only one study and future studies are warranted to confirm this finding.

Multiple angiogenesis genes and gene–gene interactions

Few studies have examined multiple angiogenesis genes or the interaction between angiogenesis genes and prostate cancer risk or progression. A recent study evaluated the association between prostate cancer and variants in IL-10 , TGF-β1 , VEGF , their receptors and the joint modifying effects of these variants in a case–control study consisting of African American men ( 42 ). The study did not observe main effects for any of the SNPs but observed that the presence of VEG F 2482T combined with VEGFR IVS 6 + 54 loci was associated ( P = 0.04) with the risk of prostate cancer. A combined effect of EGF + 61G>A and TGF-β1 + 869T>C functional polymorphisms have been shown to be associated with risk ( P = 0.004) and time to androgen independence ( P = 0.039) in prostate cancer ( 130 ). In a similar study, the combination of VEGF −1154G/A; VEGF −634G/C; MMP9 −1562C/T and TSP1 −8831A/G yielded a significant gene dosage effect for increasing numbers of potential high-risk genotypes, where individuals with one and three high-risk genotypes had increasingly elevated risks of prostate cancer ( 131 ). Jacobs et al. examined associations between SNPs in nine angiogenesis-related candidate genes ( EGF , LTA , HIF1A , HIF1AN , MMP2 , MMP9 , NOS2A , NOS3 and VEGF ) and risk of overall and advanced prostate cancer. They observed initial associations at SNPs in only HIF1A and MMP2 , but almost all the associations did not replicate in an independent dataset ( 37 ). These preliminary findings suggest that interaction of angiogenesis gene polymorphisms may be associated with prostate cancer but replication in larger studies is needed.

Conclusions

Strong biological evidence exists for the involvement of angiogenesis in prostate cancer development and progression. However, the evidence that links polymorphic variants in key genes within this pathway with prostate cancer progression and prognosis is limited to just a few genes. For most of the variants, the data are inconsistent. Although the exact basis for the inconsistent results is unknown, potential explanations include differences in study design, populations and relatively small sample sizes. More importantly, investigation of few SNPs in candidate genes may not be an optimal approach for an association study. Most of the studied SNPs are in promoter regions and have been studied because of their potential effect on expression. Since gene expression may be affected by either SNPs in the promoter regions or DNA methylation, it is conceivable that DNA methylation may be involved in the complex angiogenesis pathway. Therefore, future studies should incorporate the methylation status of genes in the angiogenesis pathway in relation to prostate cancer risk and progression.

Funding

This research was supported in part by a cancer prevention fellowship (EKA) supported by the National Cancer Institute grant (R25TCA147832; PI: Egan, K) and (R01CA128813; PI: Park, JY).

Abbreviations

    Abbreviations
  • ACE

    angiotensin-converting enzyme

  • AIPC

    androgen-independent prostate cancer

  • CGEMS

    Cancer Genetic Markers of Susceptibility

  • CI

    confidence interval

  • EGF

    epidermal growth factor

  • FGF

    fibroblast growth factor

  • FGFR

    fibroblast growth factor receptor

  • GWAS

    genome-wide association studies

  • HIF-1

    hypoxia-inducible factor-1

  • ILs

    interleukins

  • MMPs

    matrix metalloproteinases

  • NOS

    nitric oxide synthase

  • OR

    odds ratio

  • PLCO

    Prostate Lung Colon and Ovary

  • SNPs

    single nucleotide polymorphisms

  • TGF-β

    transforming growth factor beta

  • TNF-α

    tumor necrosis factor alpha

  • VEGF

    vascular endothelial growth factor

We are grateful to Donald Buchanan and Veronica Nemeth for excellent graphic design of manuscript.

Conflict of Interest Statement: None declared.

References

1.
Siegel
R
et al
Cancer statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths
CA Cancer J. Clin.
 
2011
61
212
236
2.
Lichtenstein
P
et al
Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark, and Finland
N. Engl. J. Med.
 
2000
343
78
85
3.
Hindorff
LA
et al
Genetic architecture of cancer and other complex diseases: lessons learned and future directions
Carcinogenesis
 
2011
32
945
954
4.
Wiklund
F
Prostate cancer genomics: can we distinguish between indolent and fatal disease using genetic markers?
Genome Med.
 
2010
2
45
5.
Varghese
JS
et al
Genome-wide association studies in common cancers—what have we learnt?
Curr. Opin. Genet. Dev.
 
2010
20
201
209
6.
Weis
SM
et al
Tumor angiogenesis: molecular pathways and therapeutic targets
Nat. Med.
 
2011
17
1359
1370
7.
Carmeliet
P
et al
Molecular mechanisms and clinical applications of angiogenesis
Nature
 
2011
473
298
307
8.
Carmeliet
P
Angiogenesis in life, disease and medicine
Nature
 
2005
438
932
936
9.
Potente
M
et al
Basic and therapeutic aspects of angiogenesis
Cell
 
2011
146
873
887
10.
Folkman
J
Angiogenesis: an organizing principle for drug discovery?
Nat. Rev. Drug Discov.
 
2007
6
273
286
11.
De Bock
K
et al
Antiangiogenic therapy, hypoxia, and metastasis: risky liaisons, or not?
Nat. Rev. Clin. Oncol.
 
2011
8
393
404
12.
Hanahan
D
et al
Transgenic mouse models of tumour angiogenesis: the angiogenic switch, its molecular controls, and prospects for preclinical therapeutic models
Eur. J. Cancer
 
1996
32A
2386
2393
13.
Jain
L
et al
The role of vascular endothelial growth factor SNPs as predictive and prognostic markers for major solid tumors
Mol. Cancer Ther.
 
2009
8
2496
2508
14.
Tomic
TT
et al
Castration resistant prostate cancer is associated with increased blood vessel stabilization and elevated levels of VEGF and Ang-2
Prostate
 
2011
72
705
712
15.
Bono
AV
et al
Microvessel density in prostate carcinoma
Prostate Cancer Prostatic Dis.
 
2002
5
123
127
16.
Borre
M
et al
Microvessel density predicts survival in prostate cancer patients subjected to watchful waiting
Br. J. Cancer
 
1998
78
940
944
17.
Murphy
C
et al
Nonapical and cytoplasmic expression of interleukin-8, CXCR1, and CXCR2 correlates with cell proliferation and microvessel density in prostate cancer
Clin. Cancer Res.
 
2005
11
4117
4127
18.
Duggan
D
et al
Two genome-wide association studies of aggressive prostate cancer implicate putative prostate tumor suppressor gene DAB2IP
J. Natl Cancer Inst.
 
2007
99
1836
1844
19.
Eeles
RA
et al
Identification of seven new prostate cancer susceptibility loci through a genome-wide association study
Nat. Genet.
 
2009
41
1116
1121
20.
Eeles
RA
et al
Multiple newly identified loci associated with prostate cancer susceptibility
Nat. Genet.
 
2008
40
316
321
21.
FitzGerald
LM
et al
Genome-wide association study identifies a genetic variant associated with risk for more aggressive prostate cancer
Cancer Epidemiol. Biomarkers Prev.
 
2011
20
1196
1203
22.
Gudmundsson
J
et al
Genome-wide association and replication studies identify four variants associated with prostate cancer susceptibility
Nat. Genet.
 
2009
41
1122
1126
23.
Gudmundsson
J
et al
Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24
Nat. Genet.
 
2007
39
631
637
24.
Gudmundsson
J
et al
Common sequence variants on 2p.15 and Xp11.22 confer susceptibility to prostate cancer
Nat. Genet.
 
2008
40
281
283
25.
Haiman
CA
et al
Genome-wide association study of prostate cancer in men of African ancestry identifies a susceptibility locus at 17q21
Nat. Genet.
 
2011
43
570
573
26.
Kote-Jarai
Z
et al
Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study
Nat. Genet.
 
2011
43
785
791
27.
Murabito
JM
et al
A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study
BMC Med. Genet.
 
2007
8
suppl. 1
S6
28.
Nam
RK
et al
New variants at 10q26 and 15q21 are associated with aggressive prostate cancer in a genome-wide association study from a prostate biopsy screening cohort
Cancer Biol. Ther.
 
2011
12
997
1004
29.
Penney
KL
et al
Genome-wide association study of prostate cancer mortality
Cancer Epidemiol. Biomarkers Prev.
 
2010
19
2869
2876
30.
Schumacher
FR
et al
Genome-wide association study identifies new prostate cancer susceptibility loci
Hum. Mol. Genet.
 
2011
20
3867
3875
31.
Sun
J
et al
Sequence variants at 22q13 are associated with prostate cancer risk
Cancer Res.
 
2009
69
10
15
32.
Takata
R
et al
Genome-wide association study identifies five new susceptibility loci for prostate cancer in the Japanese population
Nat. Genet.
 
2010
42
751
754
33.
Thomas
G
et al
Multiple loci identified in a genome-wide association study of prostate cancer
Nat. Genet.
 
2008
40
310
315
34.
Yeager
M
et al
Genome-wide association study of prostate cancer identifies a second risk locus at 8q24
Nat. Genet.
 
2007
39
645
649
35.
McCarron
SL
et al
Influence of cytokine gene polymorphisms on the development of prostate cancer
Cancer Res.
 
2002
62
3369
3372
36.
Sfar
S
et al
Association of VEGF genetic polymorphisms with prostate carcinoma risk and clinical outcome
Cytokine
 
2006
35
21
28
37.
Jacobs
EJ
et al
Polymorphisms in angiogenesis-related genes and prostate cancer
Cancer Epidemiol. Biomarkers Prev.
 
2008
17
972
977
38.
Langsenlehner
T
et al
Single nucleotide polymorphisms and haplotypes in the gene for vascular endothelial growth factor and risk of prostate cancer
Eur. J. Cancer
 
2008
44
1572
1576
39.
Lin
CC
et al
Vascular endothelial growth factor gene-460 C/T polymorphism is a biomarker for prostate cancer
Urology
 
2003
62
374
377
40.
Fukuda
H
et al
Clinical implication of vascular endothelial growth factor T-460C polymorphism in the risk and progression of prostate cancer
Oncol. Rep.
 
2007
18
1155
1163
41.
Onen
IH
et al
No association between polymorphism in the vascular endothelial growth factor gene at position -460 and sporadic prostate cancer in the Turkish population
Mol. Biol. Rep.
 
2008
35
17
22
42.
VanCleave
TT
et al
Interaction among variant vascular endothelial growth factor (VEGF) and its receptor in relation to prostate cancer risk
Prostate
 
2010
70
341
352
43.
Wang
J
et al
The fibroblast growth factor receptor-4 Arg388 allele is associated with prostate cancer initiation and progression
Clin. Cancer Res.
 
2004
10
6169
6178
44.
Ma
Z
et al
Polymorphisms of fibroblast growth factor receptor 4 have association with the development of prostate cancer and benign prostatic hyperplasia and the progression of prostate cancer in a Japanese population
Int. J. Cancer
 
2008
123
2574
2579
45.
FitzGerald
LM
et al
Association of FGFR4 genetic polymorphisms with prostate cancer risk and prognosis
Prostate Cancer Prostatic Dis.
 
2009
12
192
197
46.
Xu
W
et al
FGFR4 transmembrane domain polymorphism and cancer risk: a meta-analysis including 8555 subjects
Eur. J. Cancer
 
2010
46
3332
3338
47.
Xu
B
et al
FGFR4 Gly388Arg polymorphism contributes to prostate cancer development and progression: a meta-analysis of 2618 cases and 2305 controls
BMC Cancer
 
2011
11
84
48.
Veikkola
T
et al
Regulation of angiogenesis via vascular endothelial growth factor receptors
Cancer Res.
 
2000
60
203
212
49.
Borre
M
et al
Association between immunohistochemical expression of vascular endothelial growth factor (VEGF), VEGF-expressing neuroendocrine-differentiated tumor cells, and outcome in prostate cancer patients subjected to watchful waiting
Clin. Cancer Res.
 
2000
6
1882
1890
50.
Botelho
F
et al
VEGF and prostatic cancer: a systematic review
Eur. J. Cancer Prev.
 
2010
19
385
392
51.
Stevens
A
et al
Haplotype analysis of the polymorphic human vascular endothelial growth factor gene promoter
Cancer Res.
 
2003
63
812
816
52.
Lancaster
JR
Jr
et al
Tumors face NO problems?
Cancer Res.
 
2006
66
6459
6462
53.
Mocellin
S
et al
Nitric oxide, a double edged sword in cancer biology: searching for therapeutic opportunities
Med. Res. Rev.
 
2007
27
317
352
54.
Uotila
P
et al
Increased expression of cyclooxygenase-2 and nitric oxide synthase-2 in human prostate cancer
Urol. Res.
 
2001
29
23
28
55.
Klotz
T
et al
Selective expression of inducible nitric oxide synthase in human prostate carcinoma
Cancer
 
1998
82
1897
1903
56.
Tong
X
et al
eNOS protects prostate cancer cells from TRAIL-induced apoptosis
Cancer Lett.
 
2004
210
63
71
57.
Lee
KM
et al
Nitric oxide synthase gene polymorphisms and prostate cancer risk
Carcinogenesis
 
2009
30
621
625
58.
Wartenberg
M
et al
Reactive oxygen species-mediated regulation of eNOS and iNOS expression in multicellular prostate tumor spheroids
Int. J. Cancer
 
2003
104
274
282
59.
Medeiros
RM
et al
Endothelial nitric oxide synthase gene polymorphisms and genetic susceptibility to prostate cancer
Eur. J. Cancer Prev.
 
2002
11
343
350
60.
Ropiquet
F
et al
Increased expression of fibroblast growth factor 6 in human prostatic intraepithelial neoplasia and prostate cancer
Cancer Res.
 
2000
60
4245
4250
61.
Wesche
J
et al
Fibroblast growth factors and their receptors in cancer
Biochem. J.
 
2011
437
199
213
62.
Streit
S
et al
FGFR4 Arg388 allele correlates with tumour thickness and FGFR4 protein expression with survival of melanoma patients
Br. J. Cancer
 
2006
94
1879
1886
63.
Spinola
M
et al
Functional FGFR4 Gly388Arg polymorphism predicts prognosis in lung adenocarcinoma patients
J. Clin. Oncol.
 
2005
23
7307
7311
64.
Ho
CK
et al
FGFR4 Gly388Arg polymorphism and prostate cancer risk in Scottish men
Prostate Cancer Prostatic Dis.
 
2010
13
94
96
65.
Zhu
B
et al
Transforming growth factor beta and prostate cancer
Cancer Treat. Res.
 
2005
126
157
173
66.
Kambhampati
S
et al
Growth factors involved in prostate carcinogenesis
Front. Biosci.
 
2005
10
1355
1367
67.
Yokota
M
et al
Association of a T29-->C polymorphism of the transforming growth factor-beta1 gene with genetic susceptibility to myocardial infarction in Japanese
Circulation
 
2000
101
2783
2787
68.
Grainger
DJ
et al
Genetic control of the circulating concentration of transforming growth factor type beta1
Hum. Mol. Genet.
 
1999
8
93
97
69.
Ewart-Toland
A
et al
A gain of function TGFB1 polymorphism may be associated with late stage prostate cancer
Cancer Epidemiol. Biomarkers Prev.
 
2004
13
759
764
70.
Brand
TC
et al
Association of polymorphisms in TGFB1 and prostate cancer prognosis
J. Urol.
 
2008
179
754
758
71.
Faria
PC
et al
Transforming growth factor-beta 1 gene polymorphisms and expression in the blood of prostate cancer patients
Cancer Invest.
 
2007
25
726
732
72.
Kang
D
et al
Lack of association of transforming growth factor-beta1 polymorphisms and haplotypes with prostate cancer risk in the prostate, lung, colorectal, and ovarian trial
Cancer Epidemiol. Biomarkers Prev.
 
2007
16
1303
1305
73.
Li
Z
et al
Increased risk of prostate cancer and benign prostatic hyperplasia associated with transforming growth factor-beta 1 gene polymorphism at codon10
Carcinogenesis
 
2004
25
237
240
74.
Meyer
A
et al
TGFB1 gene polymorphism Leu10Pro (c.29T>C), prostate cancer incidence and quality of life in patients treated with brachytherapy
World J. Urol.
 
2009
27
371
377
75.
Wei
BB
et al
TGFbeta1 T29C polymorphism and cancer risk: a meta-analysis based on 40 case-control studies
Cancer Genet. Cytogenet.
 
2010
196
68
75
76.
Wu
Y
et al
TNF-alpha/NF-kappaB/Snail pathway in cancer cell migration and invasion
Br. J. Cancer
 
2010
102
639
644
77.
Johnston
DA
et al
TNF induction of jagged-1 in endothelial cells is NFkappaB-dependent
Gene
 
2009
435
36
44
78.
Balkwill
F
Tumour necrosis factor and cancer
Nat. Rev. Cancer
 
2009
9
361
371
79.
Wang
J
et al
Tumour necrosis factor alpha-308G/A polymorphism and risk of the four most frequent cancers: a meta-analysis
Int. J. Immunogenet.
 
2011
38
311
320
80.
Wang
MH
et al
Association of IL10 and other immune response- and obesity-related genes with prostate cancer in CLUE II
Prostate
 
2009
69
874
885
81.
Moore
SC
et al
Adipokine genes and prostate cancer risk
Int. J. Cancer
 
2009
124
869
876
82.
Kesarwani
P
et al
Polymorphisms in tumor necrosis factor-A gene and prostate cancer risk in North Indian cohort
J. Urol.
 
2009
182
2938
2943
83.
Zabaleta
J
et al
Interactions of cytokine gene polymorphisms in prostate cancer risk
Carcinogenesis
 
2008
29
573
578
84.
Danforth
KN
et al
TNF polymorphisms and prostate cancer risk
Prostate
 
2008
68
400
407
85.
Wu
HC
et al
p.53 gene codon 72 polymorphism but not tumor necrosis factor-alpha gene is associated with prostate cancer
Urol. Int.
 
2004
73
41
46
86.
Zabaleta
J
et al
Cytokine genetic polymorphisms and prostate cancer aggressiveness
Carcinogenesis
 
2009
30
1358
1362
87.
Dunn
IF
et al
Growth factors in glioma angiogenesis: FGFs, PDGF, EGF, and TGFs
J. Neurooncol.
 
2000
50
121
137
88.
Teixeira
AL
et al
Genetic polymorphism in EGF is associated with prostate cancer aggressiveness and progression-free interval in androgen blockade-treated patients
Clin. Cancer Res.
 
2008
14
3367
3371
89.
Majmundar
AJ
et al
Hypoxia-inducible factors and the response to hypoxic stress
Mol. Cell
 
2010
40
294
309
90.
Chau
CH
et al
Polymorphism in the hypoxia-inducible factor 1alpha gene may confer susceptibility to androgen-independent prostate cancer
Cancer Biol. Ther.
 
2005
4
1222
1225
91.
Li
H
et al
Hypoxia-inducible factor-1alpha (HIF-1alpha) gene polymorphisms, circulating insulin-like growth factor binding protein (IGFBP)-3 levels and prostate cancer
Prostate
 
2007
67
1354
1361
92.
Foley
R
et al
The HIF-1alpha C1772T polymorphism may be associated with susceptibility to clinically localised prostate cancer but not with elevated expression of hypoxic biomarkers
Cancer Biol. Ther.
 
2009
8
118
124
93.
Willis
LM
et al
Angiotensin receptor blockers and angiogenesis: clinical and experimental evidence
Clin Sci (Lond)
 
2011
120
307
319
94.
Ruiter
R
et al
The ACE insertion/deletion polymorphism and risk of cancer, a review and meta-analysis of the literature
Curr. Cancer Drug Targets
 
2011
11
421
430
95.
Sierra Diaz
E
et al
Angiotensin-converting enzyme insertion/deletion and angiotensin type 1 receptor A1166C polymorphisms as genetic risk factors in benign prostatic hyperplasia and prostate cancer
J. Renin Angiotensin Aldosterone Syst.
 
2009
10
241
246
96.
van der Knaap
R
et al
Renin-angiotensin system inhibitors, angiotensin I-converting enzyme gene insertion/deletion polymorphism, and cancer: the Rotterdam Study
Cancer
 
2008
112
748
757
97.
Yigit
B
et al
Effects of ACE I/D polymorphism on prostate cancer risk, tumor grade and metastatis
Anticancer Res.
 
2007
27
933
936
98.
Wang
X
et al
Angiotensin-converting enzyme insertion/deletion polymorphism and the risk of prostate cancer in the Han population of China
Med. Oncol.
 
2011
[Published online ahead of print 28 Aug 2011] http://www.ncbi.nlm.nih.gov/pubmed/21874567 (12 September 2011, date last accessed).
99.
Rundhaug
JE
Matrix metalloproteinases and angiogenesis
J. Cell. Mol. Med.
 
2005
9
267
285
100.
Deryugina
EI
et al
Pleiotropic roles of matrix metalloproteinases in tumor angiogenesis: contrasting, overlapping and compensatory functions
Biochim. Biophys. Acta.
 
2010
1803
103
120
101.
Martin
MD
et al
The other side of MMPs: protective roles in tumor progression
Cancer Metastasis Rev.
 
2007
26
717
724
102.
Tower
GB
et al
The 2G single nucleotide polymorphism (SNP) in the MMP-1 promoter contributes to high levels of MMP-1 transcription in MCF-7/ADR breast cancer cells
Breast Cancer Res. Treat.
 
2003
82
75
82
103.
Rutter
JL
et al
A single nucleotide polymorphism in the matrix metalloproteinase-1 promoter creates an Ets binding site and augments transcription
Cancer Res.
 
1998
58
5321
5325
104.
Tsuchiya
N
et al
Clinical significance of a single nucleotide polymorphism and allelic imbalance of matrix metalloproteinase-1 promoter region in prostate cancer
Oncol. Rep.
 
2009
22
493
499
105.
Albayrak
S
et al
Role of MMP-1 1G/2G promoter gene polymorphism on the development of prostate cancer in the Turkish population
Urol. Int.
 
2007
79
312
315
106.
Sfar
S
et al
TSP1 and MMP9 genetic variants in sporadic prostate cancer
Cancer Genet. Cytogenet.
 
2007
172
38
44
107.
Gil Ugarteburu
R
et al
Matrix metalloproteinase-9 polymorphisms in the diagnosis of prostate cancer. A preliminary experience
Arch. Esp. Urol.
 
2010
63
125
132
108.
Lehrer
S
et al
Serum interleukin-8 is elevated in men with prostate cancer and bone metastases
Technol. Cancer Res. Treat.
 
2004
3
411
109.
Michaud
DS
et al
Genetic polymorphisms of interleukin-1B (IL-1B), IL-6, IL-8, and IL-10 and risk of prostate cancer
Cancer Res.
 
2006
66
4525
4530
110.
Yang
HP
et al
Genetic variation in interleukin 8 and its receptor genes and its influence on the risk and prognosis of prostate cancer among Finnish men in a large cancer prevention trial
Eur. J. Cancer Prev.
 
2006
15
249
253
111.
Kalkunte
S
et al
Vascular IL-10: a protective role in preeclampsia
J. Reprod. Immunol.
 
2011
88
165
169
112.
Mosser
DM
et al
Interleukin-10: new perspectives on an old cytokine
Immunol. Rev.
 
2008
226
205
218
113.
Kesarwani
P
et al
IL-10 -1082 G>A: a risk for prostate cancer but may be protective against progression of prostate cancer in North Indian cohort
World J. Urol.
 
2009
27
389
396
114.
Faupel-Badger
JM
et al
Association of IL-10 polymorphisms with prostate cancer risk and grade of disease
Cancer Causes Control
 
2008
19
119
124
115.
Liu
J
et al
Association of genetic polymorphisms in the interleukin-10 promoter with risk of prostate cancer in Chinese
BMC Cancer
 
2010
10
456
116.
Eder
T
et al
Interleukin-10 [ATA] promoter haplotype and prostate cancer risk: a population-based study
Eur. J. Cancer
 
2007
43
472
475
117.
Shao
N
et al
IL-10 polymorphisms and prostate cancer risk: a meta-analysis
Prostate Cancer Prostatic Dis.
 
2011
14
129
135
118.
Zou
YF
et al
Lack of association of IL-10 gene polymorphisms with prostate cancer: evidence from 11,581 subjects
Eur. J. Cancer
 
2011
47
1072
1079
119.
Lin
HC
et al
Influence of cytokine gene polymorphisms on prostate-specific antigen recurrence in prostate cancer after radical prostatectomy
Urol. Int.
 
2009
83
463
470
120.
Liu
Y
et al
Genetic polymorphisms of the interleukin-18 gene and risk of prostate cancer
DNA Cell Biol.
 
2007
26
613
618
121.
O'Reilly
MS
et al
Endostatin: an endogenous inhibitor of angiogenesis and tumor growth
Cell
 
1997
88
277
285
122.
Yokoyama
Y
et al
Effect of endostatin on spontaneous tumorigenesis of mammary adenocarcinoma in a transgenic mouse model
Cancer Res.
 
2000
60
4362
4365
123.
Perletti
G
et al
Antitumor activity of endostatin against carcinogen-induced rat primary mammary tumors
Cancer Res.
 
2000
60
1793
1796
124.
Yoon
SS
et al
Mouse endostatin inhibits the formation of lung and liver metastases
Cancer Res.
 
1999
59
6251
6256
125.
Hasle
H
et al
Risks of leukaemia and solid tumours in individuals with Down's syndrome
Lancet
 
2000
355
165
169
126.
Iughetti
P
et al
A polymorphism in endostatin, an angiogenesis inhibitor, predisposes for the development of prostatic adenocarcinoma
Cancer Res.
 
2001
61
7375
7378
127.
Macpherson
GR
et al
Genotyping and functional analysis of the D104N variant of human endostatin
Cancer Biol. Ther.
 
2004
3
1298
1303
128.
Li
HC
et al
Endostatin polymorphism 4349G/A(D104N) is not associated with aggressiveness of disease in prostate [corrected] cancer
Dis. Markers
 
2005
21
37
41
129.
Mucci
LA
et al
Polymorphism in endostatin, an angiogenesis inhibitor, and prostate cancer risk and survival: a prospective study
Int. J. Cancer
 
2009
125
1143
1146
130.
Teixeira
AL
et al
Combined analysis of EGF+61G>A and TGFB1+869T>C functional polymorphisms in the time to androgen independence and prostate cancer susceptibility
Pharmacogenomics J.
 
2009
9
341
346
131.
Sfar
S
et al
Combined effects of the angiogenic genes polymorphisms on prostate cancer susceptibility and aggressiveness
Mol. Biol. Rep.
 
2009
36
37
45