The insulin-insulin-like growth factor (IGF) system in ... · Westernisation and prostate cancer...
Transcript of The insulin-insulin-like growth factor (IGF) system in ... · Westernisation and prostate cancer...
The insulin-insulin-like growth factor (IGF) system in
prostate cancer risk and progression
Insights from the ProtecT case-control study
Richard Martin
1
Thanks to….
• Mari-Anne Rowlands
• Supervisors - Jeff Holly, David Gunnell, Kate Tilling
• ProtecT PIs - Jenny Donovan, Freddie Hamdy, David Neal
• ProtecT study group - Athene Lane, Michael Davies, Anya Burton, Becky Gilbert, Chris Metcalfe, Nick Young, George Davey Smith, Simon Collin, John Kemp, Carolina Bonilla
2
Age-standardised incidence and mortality rates for prostate cancer by world regions, 2002 estimates
0 20 40 60 80 100 120 140
Eastern Asia
South Central Asia
Northern Africa
South-Eastern Asia
Western Asia
Eastern Africa
Eastern Europe
Western Africa
Middle Africa
World
Central America
Southern Europe
Southern Africa
South America
Caribbean
Northern Europe
Western Europe
Australia/New Zealand
Northern America
Rate per 100,000
Incidence
Mortality
3
120 x variation in incidence
26 fold variation in mortality
Age range
% Latent Prostate Cancers found at autopsy
Autopsy examination of entire prostate glands from
1056 men, aged 20-80 years, who died of causes other
than prostate cancer between 1993-2004.
Pathology examination of whole mount, step sections.
American men of African ancestry have around 60% higher incidence of clinical prostate cancers and between 2 to 3 fold higher mortality from prostate cancer compared to American men of European continental ancestry.
4
Slide kindly prepared &
lent by Prof Jeff Holly
Prostate cancers are initiated in all men as they age (somatic mutations in oncogenes and tumour suppressor genes)
These only progress to clinical disease in a few men and the risk of this progression depends on where they live in the world
Why – genes or environment?
5
% Cumulative Rate by age 75
Cancer Rates in Migrants Converge to that of Locals (J Peto, Nature 411;2001:390-395)
0
5
10
15
Prostate
Japanese Osaka70-71
Japanese Osaka88-92
JapaneseHawaii88-92
Hawaii Caucasians 68-72
Hawaii Caucasians 88-92
6
Westernisation and prostate cancer risk
Hsing AW and Devesa SS, Epidemiol Rev 2001; Vol 23, No. 1
Lifestyle
factors Westernisation
Americanisation
High intake of meat, animal
fat and simple sugar.
Physical inactivity
Obesity
Abdominal
obesity
Insulin
resistance Hyperinsulinemia
Low intake of protective
factors (soy, green tea,
antioxidants etc.
Genetic
susceptibility
Hormone
pathway
IGF pathway
Androgens
Estrogens
Androgen receptor (AR)
AR coactivators
SHBG
Androgenic Action
Prostate cancer
Common polymorphisms in
hormone-related genes (SRD5A2, HSD17B, HSD3B, CYP17,
CYP19, AR, VDR, INS VNTR, etc)
Highly penetrant genes (HPC1, HPCX etc)
7
Obesity and prostate cancer
MacInnis et al. Cancer Causes & Control 2006 8
RR: 1.12 per
5 kg/m2 increment,
95% CI 1.01–1.23
RR: 0.96 per
5 kg/m2 increment,
95% CI 0.89–1.03
Advanced cases
Localised cases
Insulin and prostate cancer: 5-12 yrs prospective study
P-trend = 0.02
Albanes et al J Natl Cancer Inst (2009) 9
Westernisation and prostate cancer risk
Hsing AW and Devesa SS, Epidemiol Rev 2001; Vol 23, No. 1
Lifestyle
factors Westernisation
Americanisation
High intake of meat, animal
fat and simple sugar.
Physical inactivity
Obesity
Abdominal
obesity
Insulin
resistance Hyperinsulinemia
Low intake of protective
factors (soy, green tea,
antioxidants etc.
Genetic
susceptibility
Hormone
pathway
IGF pathway
Androgens
Estrogens
Androgen receptor (AR)
AR coactivators
SHBG
Androgenic Action
Prostate cancer
Common polymorphisms in
hormone-related genes (SRD5A2, HSD17B, HSD3B, CYP17,
CYP19, AR, VDR, INS VNTR, etc)
Highly penetrant genes (HPC1, HPCX etc)
Gene-environment
interactions
10
IGF system
Within individuals, levels are stable – i.e.
Long-term exposure to high or low levels
Data from Jeff
Holly, Bristol
11
Nutritional and lifestyle regulation of IGFs
Rogers et al, Public Health Nutrition, 2006;
Ngo et al, Cancer Causes & Control, 2003 12
Insulin-IGFs promote cell
growth and survival via
activation of intracellular
kinase cascades
Insulin-IGF signalling
IRS1
PI3K
PIP3
P
P P
IGF-IR
PTEN
Akt
p110
p85
950
1131
1135
1136
1250
1251
β β
α α
Metabolism/Proliferation
IGF-I
α β
IGFBP-3
Integrin
IGFBP
protease
• Anti-apoptosis
• Transformation
• Proliferation
• Adhesion
• Migration
Slide kindly prepared and lent by Prof Jeff Holly 13
0.6
0.8
1
1.2
1.4
1.6
1.8
IGF-I
SBP
DBP
TOTAL CHL
LDL CHL
HDL CHL
TRIGL
Risk of prostate cancer (red) per SD increase in IGF-I* compared with risks of IHD (blue) per SD increase in IGF-I &
classic risk factors**
IGF-I
*data from Renehan et al. Lancet 2004;363: 1346–53
**data from Juul A. Circulation 2002;106:939-944 14
Meta-analysis - IGF-I with prostate cancer risk (42 studies, 7481 cases)
Rowlands M-A et al. Int J Cancer 2009
Pooled relative risk per
SD increase in IGF-I
1.21
(1.07, 1.36)
Heterogeneity between groups: p = 0.000
All studies (fixed effects) (I-squared = 88.4%, p = 0.000)
Zhigang
Chokkalingam
All retrospective studies (random effects)
Harman
Scorilas
Trapeznikova
Lacey
Kanety
Miyata
All retrospective studies (fixed effects) (I-squared = 90.7%, p = 0.000)
Morris
Chan
Shariat
Hernandez
Allen
Wolk
Schaefer
Hill
Kehinde
Stattin
Cutting
Woodson
Author
Marszalek
Nam
Lopez
Prospective studies
Khosravi
Finne
Kurek
Mantzoros
Baffa
All prospective studies (fixed effects) (I-squared = 59.3%, p = 0.002)
Platz
Hazem
Peng
Cohen
Chen
Severi
Oliver
Koliakos
Li
Aksoy
Djavan
All studies (random effects)
All prospective studies (random effects)
Weiss
Janssen
Retrospective studies
Meyer
2007
2001
2000
2003
2004
2001
1993
2003
2006
1998
2002
2007
2007
1998
1998
2000
2005
2004
1999
2003
2005
2005
2004
2001
2000
2000
2007
2000
2005
2002
2002
1993
2005
2006
2004
2000
Year of publication
2003
2004
1999
2007
2004
2005
1.18 (1.14, 1.23)
1.98 (1.68, 2.33)
1.73 (1.21, 2.47)
1.26 (1.05, 1.52)
1.69 (1.05, 2.72)
1.47 (1.19, 1.82)
1.58 (1.01, 2.47)
1.03 (0.66, 1.62)
0.40 (0.13, 1.19)
1.86 (1.30, 2.66)
1.31 (1.24, 1.38)
0.82 (0.70, 0.97)
1.80 (1.29, 2.53)
0.87 (0.61, 1.22)
0.83 (0.56, 1.22)
1.16 (1.01, 1.33)
1.26 (0.93, 1.69)
0.93 (0.69, 1.25)
0.81 (0.48, 1.38)
1.99 (1.20, 3.30)
1.24 (0.95, 1.61)
1.39 (0.90, 2.14)
0.81 (0.61, 1.07)
OR per standard
deviation increase in
IGF-I (95% CI)
1.11 (0.91, 1.36)
1.02 (0.86, 1.20)
0.57 (0.31, 1.05)
1.74 (1.27, 2.38)
0.77 (0.58, 1.03)
0.99 (0.76, 1.30)
1.75 (1.42, 2.18)
0.60 (0.39, 0.91)
1.05 (1.00, 1.12)
1.10 (0.89, 1.37)
0.61 (0.48, 0.78)
4.16 (2.94, 5.88)
1.06 (0.65, 1.74)
0.87 (0.57, 1.32)
1.05 (0.92, 1.19)
1.39 (1.09, 1.78)
1.20 (0.80, 1.79)
1.06 (0.87, 1.29)
1.08 (0.71, 1.63)
5.33 (3.99, 7.13)
1.21 (1.07, 1.36)
1.07 (0.97, 1.18)
1.08 (0.93, 1.24)
0.97 (0.80, 1.18)
1.25 (0.91, 1.71)
100.00
5.66
1.20
0.66
3.38
0.75
0.75
0.12
1.19
52.15
5.43
1.32
1.26
1.01
7.96
1.70
1.74
0.53
0.59
2.12
0.81
1.95
3.86
5.65
0.41
1.55
1.79
2.12
3.26
0.84
47.85
3.21
2.65
1.25
0.62
0.85
9.23
2.47
0.94
3.89
0.88
1.79
7.16
3.95
1.52
1.18 (1.14, 1.23)
1.98 (1.68, 2.33)
1.73 (1.21, 2.47)
1.26 (1.05, 1.52)
1.69 (1.05, 2.72)
1.47 (1.19, 1.82)
1.58 (1.01, 2.47)
1.03 (0.66, 1.62)
0.40 (0.13, 1.19)
1.86 (1.30, 2.66)
1.31 (1.24, 1.38)
0.82 (0.70, 0.97)
1.80 (1.29, 2.53)
0.87 (0.61, 1.22)
0.83 (0.56, 1.22)
1.16 (1.01, 1.33)
1.26 (0.93, 1.69)
0.93 (0.69, 1.25)
0.81 (0.48, 1.38)
1.99 (1.20, 3.30)
1.24 (0.95, 1.61)
1.39 (0.90, 2.14)
0.81 (0.61, 1.07)
1.11 (0.91, 1.36)
1.02 (0.86, 1.20)
0.57 (0.31, 1.05)
1.74 (1.27, 2.38)
0.77 (0.58, 1.03)
0.99 (0.76, 1.30)
1.75 (1.42, 2.18)
0.60 (0.39, 0.91)
1.05 (1.00, 1.12)
1.10 (0.89, 1.37)
0.61 (0.48, 0.78)
4.16 (2.94, 5.88)
1.06 (0.65, 1.74)
0.87 (0.57, 1.32)
1.05 (0.92, 1.19)
1.39 (1.09, 1.78)
1.20 (0.80, 1.79)
1.06 (0.87, 1.29)
1.08 (0.71, 1.63)
5.33 (3.99, 7.13)
1.21 (1.07, 1.36)
1.07 (0.97, 1.18)
1.08 (0.93, 1.24)
0.97 (0.80, 1.18)
1.25 (0.91, 1.71)
100.00
5.66
1.20
0.66
3.38
0.75
0.75
0.12
1.19
52.15
5.43
1.32
1.26
1.01
7.96
1.70
1.74
0.53
0.59
2.12
0.81
1.95
3.86
5.65
0.41
1.55
1.79
2.12
3.26
0.84
47.85
% Weight
(fixed effects)
3.21
2.65
1.25
0.62
0.85
9.23
2.47
0.94
3.89
0.88
1.79
7.16
3.95
1.52
1.2 .5 1 2 5
OR per standard deviation increase in IGF-I
Heterogeneity between groups: p = 0.000
All studies (fixed effects) (I-squared = 88.4%, p = 0.000)
Zhigang
Chokkalingam
All retrospective studies (random effects)
Harman
Scorilas
Trapeznikova
Lacey
Kanety
Miyata
All retrospective studies (fixed effects) (I-squared = 90.7%, p = 0.000)
Morris
Chan
Shariat
Hernandez
Allen
Wolk
Schaefer
Hill
Kehinde
Stattin
Cutting
Woodson
Author
Marszalek
Nam
Lopez
Prospective studies
Khosravi
Finne
Kurek
Mantzoros
Baffa
All prospective studies (fixed effects) (I-squared = 59.3%, p = 0.002)
Platz
Hazem
Peng
Cohen
Chen
Severi
Oliver
Koliakos
Li
Aksoy
Djavan
All studies (random effects)
All prospective studies (random effects)
Weiss
Janssen
Retrospective studies
Meyer
2007
2001
2000
2003
2004
2001
1993
2003
2006
1998
2002
2007
2007
1998
1998
2000
2005
2004
1999
2003
2005
2005
2004
2001
2000
2000
2007
2000
2005
2002
2002
1993
2005
2006
2004
2000
Year of publication
2003
2004
1999
2007
2004
2005
1.18 (1.14, 1.23)
1.98 (1.68, 2.33)
1.73 (1.21, 2.47)
1.26 (1.05, 1.52)
1.69 (1.05, 2.72)
1.47 (1.19, 1.82)
1.58 (1.01, 2.47)
1.03 (0.66, 1.62)
0.40 (0.13, 1.19)
1.86 (1.30, 2.66)
1.31 (1.24, 1.38)
0.82 (0.70, 0.97)
1.80 (1.29, 2.53)
0.87 (0.61, 1.22)
0.83 (0.56, 1.22)
1.16 (1.01, 1.33)
1.26 (0.93, 1.69)
0.93 (0.69, 1.25)
0.81 (0.48, 1.38)
1.99 (1.20, 3.30)
1.24 (0.95, 1.61)
1.39 (0.90, 2.14)
0.81 (0.61, 1.07)
OR per standard
deviation increase in
IGF-I (95% CI)
1.11 (0.91, 1.36)
1.02 (0.86, 1.20)
0.57 (0.31, 1.05)
1.74 (1.27, 2.38)
0.77 (0.58, 1.03)
0.99 (0.76, 1.30)
1.75 (1.42, 2.18)
0.60 (0.39, 0.91)
1.05 (1.00, 1.12)
1.10 (0.89, 1.37)
0.61 (0.48, 0.78)
4.16 (2.94, 5.88)
1.06 (0.65, 1.74)
0.87 (0.57, 1.32)
1.05 (0.92, 1.19)
1.39 (1.09, 1.78)
1.20 (0.80, 1.79)
1.06 (0.87, 1.29)
1.08 (0.71, 1.63)
5.33 (3.99, 7.13)
1.21 (1.07, 1.36)
1.07 (0.97, 1.18)
1.08 (0.93, 1.24)
0.97 (0.80, 1.18)
1.25 (0.91, 1.71)
100.00
5.66
1.20
0.66
3.38
0.75
0.75
0.12
1.19
52.15
5.43
1.32
1.26
1.01
7.96
1.70
1.74
0.53
0.59
2.12
0.81
1.95
3.86
5.65
0.41
1.55
1.79
2.12
3.26
0.84
47.85
3.21
2.65
1.25
0.62
0.85
9.23
2.47
0.94
3.89
0.88
1.79
7.16
3.95
1.52
1.18 (1.14, 1.23)
1.98 (1.68, 2.33)
1.73 (1.21, 2.47)
1.26 (1.05, 1.52)
1.69 (1.05, 2.72)
1.47 (1.19, 1.82)
1.58 (1.01, 2.47)
1.03 (0.66, 1.62)
0.40 (0.13, 1.19)
1.86 (1.30, 2.66)
1.31 (1.24, 1.38)
0.82 (0.70, 0.97)
1.80 (1.29, 2.53)
0.87 (0.61, 1.22)
0.83 (0.56, 1.22)
1.16 (1.01, 1.33)
1.26 (0.93, 1.69)
0.93 (0.69, 1.25)
0.81 (0.48, 1.38)
1.99 (1.20, 3.30)
1.24 (0.95, 1.61)
1.39 (0.90, 2.14)
0.81 (0.61, 1.07)
1.11 (0.91, 1.36)
1.02 (0.86, 1.20)
0.57 (0.31, 1.05)
1.74 (1.27, 2.38)
0.77 (0.58, 1.03)
0.99 (0.76, 1.30)
1.75 (1.42, 2.18)
0.60 (0.39, 0.91)
1.05 (1.00, 1.12)
1.10 (0.89, 1.37)
0.61 (0.48, 0.78)
4.16 (2.94, 5.88)
1.06 (0.65, 1.74)
0.87 (0.57, 1.32)
1.05 (0.92, 1.19)
1.39 (1.09, 1.78)
1.20 (0.80, 1.79)
1.06 (0.87, 1.29)
1.08 (0.71, 1.63)
5.33 (3.99, 7.13)
1.21 (1.07, 1.36)
1.07 (0.97, 1.18)
1.08 (0.93, 1.24)
0.97 (0.80, 1.18)
1.25 (0.91, 1.71)
100.00
5.66
1.20
0.66
3.38
0.75
0.75
0.12
1.19
52.15
5.43
1.32
1.26
1.01
7.96
1.70
1.74
0.53
0.59
2.12
0.81
1.95
3.86
5.65
0.41
1.55
1.79
2.12
3.26
0.84
47.85
% Weight
(fixed effects)
3.21
2.65
1.25
0.62
0.85
9.23
2.47
0.94
3.89
0.88
1.79
7.16
3.95
1.52
1.2 .5 1 2 5
OR per standard deviation increase in IGF-I
Study Design Pooled relative risk
Retrospective (28) 1.26 (1.05-1.52)
Prospective (14) 1.07 (0.96-1.18)
Prostate cancer cases per study:
14 to 727; mean: 180
I2 = 88%
Stage Pooled relative risk
Advanced (4) 1.41 (1.07, 1.85)
Localised (4) 1.10 (0.98, 1.22)
15
IGFBP-2 binds to integrins,
inactivating the tumour suppressor,
PTEN
Intra-celullar kinase cascades that
promote growth and survival are
switched-off by counteracting
phosphatases
Phosphatase PTEN is inactived
in a large proportion of solid tumors,
and is associated with cancer
progression
IGF-II & IGFBP-2
IRS1
PI3K
PIP3
P
P P
IGF-IR
PTEN
Akt
p110
p85
950
1131
1135
1136
1250
1251
β β
α α
Tumor suppression
IGF-II
Tumor progression
α β
IGFBP-2
Integrin
Insulin
Perks CM et al. Oncogene 2007;26:5966
Slide kindly prepared &
lent by Prof Jeff Holly 16
IRS1
PI3K
PIP3
P
P P
IR/IGF-IR
PTEN Akt
p110
p85
950
1131
1135
1136
1250
1251
β β
α α
TUMOUR PROGRESSION
α
IGFBP-2
Integrin Receptor
Insulin IGFBP-3
Prostate Cancer Susceptibility Genetic Loci:
Insulin/IGF-II
ITGA6
NKX3.1
PIK3C2B
PDLIM5
MCM7 / miR-106b~25
FOXA1
IGF-II
β
miR-106b~25
PDLIM2/
mystique ?
ILK MCM7
FOXA1
Slide kindly prepared &
lent by Prof Jeff Holly 17
Aims • To investigate the roles of circulating levels of IGF-I,
IGF-II, IGFBP-2 & IGFBP-3 in PSA-detected prostate cancer and its progression
• 15-fold larger sample size than most previous studies - statistical precision
• Population-based sample & standardised diagnosis – reduces detection bias
• Screen-detected cancers ≈10 years prior to clinical detection - allows inference on role of IGFs in prostate cancer initiation & follow-up for progression
18
Invited to attend: 226,716 men (aged 50-69
years from 300 GP practices across 9 UK cities).
PSA tested: 111,091 men
Have biopsy: >10,000 men – 10 core transrectal ultrasound-guided biopsy.
Have cancer (3,174)
Case control design in ProtecT
Full data on IGF-axis and covariates:
2,686 men with prostate cancer
2,766 matched controls
Stratum match on:
• Age (5 year bands)
• GP practice
• Calendar date
19
Case characteristics
STAGE
Localised T1-T2, NX, M0 2,355 (88%)
Advanced T3-T4, N0-3, M0-1 311 (11%)
Unstaged 20 (1%)
GRADE
Low Gleason score 3-6 1,808 (67%)
Mid Gleason score 7 720 (27%)
High Gleason score 8-10 152 (6%)
20
IGF-I
1
2
3
4
5
IGF-II
1
2
3
4
5
IGFBP-2
1
2
3
4
5
IGFBP-3
1
2
3
4
5
IGF/IGFBP
Quintile of
558/584
566/542
537/557
553/516
550/487
544/413
542/575
544/480
544/533
540/641
550/459
513/539
544/548
548/557
547/561
539/386
535/463
539/521
531/588
535/679
Controls/Cases
1.0
0.91 (0.76, 1.08)
1.03 (0.86, 1.22)
0.96 (0.80, 1.14)
0.96 (0.80, 1.16)
1.0
1.45 (1.21, 1.74)
1.25 (1.03, 1.51)
1.43 (1.18, 1.73)
1.76 (1.43, 2.17)
1.0
1.12 (0.77, 1.63)
1.37 (0.95, 1.99)
1.65 (1.15, 2.37)
1.72 (1.21, 2.45)
1.0
1.31 (1.07, 1.60)
1.45 (1.19, 1.77)
1.67 (1.37, 2.04)
1.99 (1.62, 2.44)
ratio (95% CI)
Odds
<0.001
<0.01
<0.001
<0.001
<0.01
<0.001
1 .75 1 1.5 2.5
Results
Increasing IGF p linear trend = 0.62
Rowlands M-A et al. Cancer Research 2011 21
IGF-I
1
2
3
4
5
IGF-II
1
2
3
4
5
IGFBP-2
1
2
3
4
5
IGFBP-3
1
2
3
4
5
IGF/IGFBP
Quintile of
558/584
566/542
537/557
553/516
550/487
544/413
542/575
544/480
544/533
540/641
550/459
513/539
544/548
548/557
547/561
539/386
535/463
539/521
531/588
535/679
Controls/Cases
1.0
0.91 (0.76, 1.08)
1.03 (0.86, 1.22)
0.96 (0.80, 1.14)
0.96 (0.80, 1.16)
1.0
1.45 (1.21, 1.74)
1.25 (1.03, 1.51)
1.43 (1.18, 1.73)
1.76 (1.43, 2.17)
1.0
1.12 (0.77, 1.63)
1.37 (0.95, 1.99)
1.65 (1.15, 2.37)
1.72 (1.21, 2.45)
1.0
1.31 (1.07, 1.60)
1.45 (1.19, 1.77)
1.67 (1.37, 2.04)
1.99 (1.62, 2.44)
ratio (95% CI)
Odds
<0.01
<0.001
<0.01
<0.001
1 .75 1 1.5 2.5
Results
Increasing IGF p linear trend = 0.62
p linear trend < 0.001
22
IGF-I
1
2
3
4
5
IGF-II
1
2
3
4
5
IGFBP-2
1
2
3
4
5
IGFBP-3
1
2
3
4
5
IGF/IGFBP
Quintile of
558/584
566/542
537/557
553/516
550/487
544/413
542/575
544/480
544/533
540/641
550/459
513/539
544/548
548/557
547/561
539/386
535/463
539/521
531/588
535/679
Controls/Cases
1.0
0.91 (0.76, 1.08)
1.03 (0.86, 1.22)
0.96 (0.80, 1.14)
0.96 (0.80, 1.16)
1.0
1.45 (1.21, 1.74)
1.25 (1.03, 1.51)
1.43 (1.18, 1.73)
1.76 (1.43, 2.17)
1.0
1.12 (0.77, 1.63)
1.37 (0.95, 1.99)
1.65 (1.15, 2.37)
1.72 (1.21, 2.45)
1.0
1.31 (1.07, 1.60)
1.45 (1.19, 1.77)
1.67 (1.37, 2.04)
1.99 (1.62, 2.44)
ratio (95% CI)
Odds
<0.001 <0.001
1 .75 1 1.5 2.5
Results
Increasing IGF p linear trend = 0.62
p linear trend < 0.001
p linear trend < 0.001
23
IGF-I
1
2
3
4
5
IGF-II
1
2
3
4
5
IGFBP-2
1
2
3
4
5
IGFBP-3
1
2
3
4
5
IGF/IGFBP
Quintile of
558/584
566/542
537/557
553/516
550/487
544/413
542/575
544/480
544/533
540/641
550/459
513/539
544/548
548/557
547/561
539/386
535/463
539/521
531/588
535/679
Controls/Cases
1.0
0.91 (0.76, 1.08)
1.03 (0.86, 1.22)
0.96 (0.80, 1.14)
0.96 (0.80, 1.16)
1.0
1.45 (1.21, 1.74)
1.25 (1.03, 1.51)
1.43 (1.18, 1.73)
1.76 (1.43, 2.17)
1.0
1.12 (0.77, 1.63)
1.37 (0.95, 1.99)
1.65 (1.15, 2.37)
1.72 (1.21, 2.45)
1.0
1.31 (1.07, 1.60)
1.45 (1.19, 1.77)
1.67 (1.37, 2.04)
1.99 (1.62, 2.44)
ratio (95% CI)
Odds
1 .75 1 1.5 2.5
Results
Increasing IGF p linear trend = 0.62
p linear trend < 0.001
p linear trend < 0.001
p linear trend < 0.01
24
Heterogeneity between groups: p < 0.001 Fixed effects (I-squared = 87.9%, p < 0.001)
Chen
Random effects
PSA DETECTED, PROSPECTIVE STUDIES
Nam
Fixed effects (I-squared = 0.0%, p = 0.418)
ROUTINELY DETECTED, RETROSPECTIVE STUDIES
Borugian
PSA DETECTED, RETROSPECTIVE STUDIES
Scorilas
Chokkalingam
Li
ROUTINELY DETECTED, PROSPECTIVE STUDIES
Author
Fixed effects (I-squared = 80.6%, p = 0.006)
Aksoy
Mikami
Miyata
Cutting
Hong
Morris
Random effects
Gill
Severi
Janssen
Meyer
Platz
Schaefer
Pina
Safarinejad
Sciarra
Kurek
Lopez
Harman
Baffa
Lacey
Random effects
Cohen
Tajtakova
Koliakos
Fixed effects (I-squared = 56.8%, p = 0.002)
Rowlands
Mucci
Stattin
Zhigang
Kanety
Chan
Random effects
Hernandez
Trapeznikova
Marszalek
Allen
Kim
Khosravi
Shariat Peng
Finne
Weiss
Mantzoros
Hill
Woodson
Oliver
Kehinde
Djavan
Random effects
Wolk
Ismail
Chan
Fixed effects (I-squared = 91.5%, p < 0.001)
Nimptsch
2005
2005
2008
2003
2001
2003
Year
2004
2009
2003
1999
2008
2006
2011
2006
2004
2005
2005
1998
2009
2011
2008
2000
2004
2000
2000
2001
1993
2010
2000
2011
2010
2004
2007
1993
2002
2007
2004
2005
2007
2009
2001
2002 2002
2000
2007
1997
2000
2003
2004
2005
1999
1998
2002
1998
2010
1.09 (1.06, 1.12)
0.87 (0.57, 1.32)
1.02 (0.79, 1.33)
Odds ratio per
1.02 (0.86, 1.20)
1.04 (0.92, 1.17)
1.08 (0.83, 1.42)
1.47 (1.19, 1.82)
1.73 (1.21, 2.47)
1.06 (0.87, 1.29)
IGF-I (95% CI)
0.99 (0.94, 1.05)
1.08 (0.71, 1.63)
0.96 (0.53, 1.73)
1.86 (1.30, 2.66)
1.39 (0.90, 2.14)
0.97 (0.82, 1.16)
0.82 (0.70, 0.97)
1.15 (1.05, 1.25)
1.03 (0.89, 1.20)
1.05 (0.92, 1.19)
0.97 (0.80, 1.18)
1.25 (0.91, 1.71)
1.10 (0.89, 1.37)
0.93 (0.69, 1.25)
0.89 (0.70, 1.14)
0.56 (0.47, 0.67)
1.20 (0.76, 1.87)
0.99 (0.76, 1.30)
0.57 (0.31, 1.05)
1.69 (1.05, 2.72)
0.60 (0.39, 0.91)
1.03 (0.66, 1.62)
1.19 (1.00, 1.41)
1.06 (0.65, 1.74)
1.02 (0.76, 1.38)
1.20 (0.80, 1.79)
1.09 (1.04, 1.14)
0.99 (0.93, 1.04)
0.99 (0.85, 1.17)
1.24 (0.95, 1.61)
1.98 (1.68, 2.33)
0.40 (0.13, 1.19)
1.17 (0.64, 2.15)
1.04 (0.92, 1.17)
0.83 (0.56, 1.22)
1.58 (1.01, 2.47)
1.11 (0.91, 1.36)
1.16 (1.01, 1.33)
0.99 (0.77, 1.27)
1.74 (1.27, 2.38)
0.87 (0.61, 1.22) 4.16 (2.94, 5.88)
0.77 (0.57, 1.03)
1.07 (0.93, 1.24)
1.75 (1.42, 2.18)
0.81 (0.48, 1.38)
0.81 (0.61, 1.07)
1.39 (1.09, 1.78)
1.99 (1.20, 3.30)
5.33 (3.99, 7.13)
1.08 (0.99, 1.17)
1.26 (0.93, 1.69)
0.60 (0.46, 0.77)
1.80 (1.29, 2.53)
SD increase in
1.18 (1.13, 1.24)
1.18 (1.08, 1.28)
100.00
0.43
%
2.88
5.66
1.05
1.72
0.61
1.98
24.48
0.45
0.22
0.61
0.41
2.43
2.76
3.26
4.70
2.01
0.77
1.63
0.89
1.26
2.42
0.38
1.08
0.21
0.34
0.43
0.38
0.32
0.85
0.48
36.86
22.32
2.97
1.08
2.89
0.06
0.21
0.51
0.38
1.97
4.06
1.22
0.79
0.64 0.64
0.90
3.65
1.66
0.27
1.00
1.26
0.30
0.91
0.86
1.15
0.67
Weight
33.00
10.65
Yes
Model
No
No
No
Yes
No
IGFBP3
No
No
No
No
No
No
No
No
No
Yes
Yes
No
No
No
No
No
No
Yes
No
Yes
No
No
No
No
Yes
Yes
No
No
Yes
No
No
No
Yes
Yes
No
No No
Yes
Yes
No
No
Yes
Yes
No
No
Yes
No
Yes
adjusted for
No
1.09 (1.06, 1.12)
0.87 (0.57, 1.32)
1.02 (0.79, 1.33)
Odds ratio per
1.02 (0.86, 1.20)
1.04 (0.92, 1.17)
1.08 (0.83, 1.42)
1.47 (1.19, 1.82)
1.73 (1.21, 2.47)
1.06 (0.87, 1.29)
IGF-I (95% CI)
0.99 (0.94, 1.05)
1.08 (0.71, 1.63)
0.96 (0.53, 1.73)
1.86 (1.30, 2.66)
1.39 (0.90, 2.14)
0.97 (0.82, 1.16)
0.82 (0.70, 0.97)
1.15 (1.05, 1.25)
1.03 (0.89, 1.20)
1.05 (0.92, 1.19)
0.97 (0.80, 1.18)
1.25 (0.91, 1.71)
1.10 (0.89, 1.37)
0.93 (0.69, 1.25)
0.89 (0.70, 1.14)
0.56 (0.47, 0.67)
1.20 (0.76, 1.87)
0.99 (0.76, 1.30)
0.57 (0.31, 1.05)
1.69 (1.05, 2.72)
0.60 (0.39, 0.91)
1.03 (0.66, 1.62)
1.19 (1.00, 1.41)
1.06 (0.65, 1.74)
1.02 (0.76, 1.38)
1.20 (0.80, 1.79)
1.09 (1.04, 1.14)
0.99 (0.93, 1.04)
0.99 (0.85, 1.17)
1.24 (0.95, 1.61)
1.98 (1.68, 2.33)
0.40 (0.13, 1.19)
1.17 (0.64, 2.15)
1.04 (0.92, 1.17)
0.83 (0.56, 1.22)
1.58 (1.01, 2.47)
1.11 (0.91, 1.36)
1.16 (1.01, 1.33)
0.99 (0.77, 1.27)
1.74 (1.27, 2.38)
0.87 (0.61, 1.22) 4.16 (2.94, 5.88)
0.77 (0.57, 1.03)
1.07 (0.93, 1.24)
1.75 (1.42, 2.18)
0.81 (0.48, 1.38)
0.81 (0.61, 1.07)
1.39 (1.09, 1.78)
1.99 (1.20, 3.30)
5.33 (3.99, 7.13)
1.08 (0.99, 1.17)
1.26 (0.93, 1.69)
0.60 (0.46, 0.77)
1.80 (1.29, 2.53)
SD increase in
1.18 (1.13, 1.24)
1.18 (1.08, 1.28)
100.00
0.43
%
2.88
5.66
1.05
1.72
0.61
1.98
(Fixed effects)
24.48
0.45
0.22
0.61
0.41
2.43
2.76
3.26
4.70
2.01
0.77
1.63
0.89
1.26
2.42
0.38
1.08
0.21
0.34
0.43
0.38
0.32
0.85
0.48
36.86
22.32
2.97
1.08
2.89
0.06
0.21
0.51
0.38
1.97
4.06
1.22
0.79
0.64 0.64
0.90
3.65
1.66
0.27
1.00
1.26
0.30
0.91
0.86
1.15
0.67
Weight
33.00
10.65
1 .2 .5 1 2 6
Odds ratio (OR) per 1 standard deviation (SD) increase in IGF-I
Meta-analysis of 55 IGF-I studies stratified by detection method and study design
25
Association of IGF-I with PSA change following diagnosis (active monitoring)
24
68
Pre
dic
ted P
SA
(ng/m
l)
50 55 60 65 70Age(years)
5th 25th 50th 75th 95th
IGF-I
Rapid post-diagnosis PSADT (≤
4 years versus > 4 years) an
indicator of progression
Lines represent the average pattern of increase
in PSA (ng/ml) between ages 50-70, by initial
IGF-I (5th, 25th, 50th, 75th, and 95th centiles)
909 men with PCa & a
mean of 14 follow-up
PSA measures
OR = 1.34 (95% CI:0.98,1.81)
per SD increase in IGF-I.
26
Clinical cohort of 194 men with advanced disease: associations of IGF-I with progression to mortality
Prostate cancer specific mortality (n=60)
All cause mortality (n=104)
OR (95% CI) P-value OR (95% CI) P-value
Model 1 1.22 (0.93, 1.59) 0.1 1.18 (0.95, 1.46) 0.1
Model 2 1.23 (0.94, 1.62) 0.1 1.20 (0.96, 1.49) 0.1
Model 3 1.59 (1.11, 2.28) 0.01 1.68 (1.28, 2.23) <0.001
Adjustments:
Model 1: Adjusted for age
Model 2: Adjusted for age, stage, Gleason, smoking, treatment & PSA
Model 3: Adjusted for age, stage, Gleason, smoking, treatment, PSA & IGFBP-3
Odds ratio (OR) per 1 standard
deviation (SD) increase in IGF-I
Rowlands M-A et al. Cancer Causes & Control 2011 27
0.6
0.8
1
1.2
1.4
1.6
1.8
IGF-I
SBP
DBP
TOTAL CHL
LDL CHL
HDL CHL
TRIGL
Risk of prostate cancer (red) per SD increase in IGF-I* compared with risks of IHD (blue) per SD increase in IGF-I &
classic risk factors**
*data from Renehan et al. Lancet 2004;363: 1346–53
**data from Juul A. Circulation 2002;106:939-944
PSA-detected
ProtecT
(n=2686) Meta-analysis
PSA-
detected
Clinically-
detected
Clinical
Progression (PSADT<4yr)
ProtecT (n=908)
Mortality
Advanced
Cancers
Sheffield
Cohort
(n=194)
IGF-I
28
Summary
• IGF-I may not stimulate initiation (leading to screen-detected disease) but may instead support progression (clinically detected disease)
• IGF-I may be a modifiable mediator of the effect of diet/lifestyle on prostate cancer progression
• Circulating IGF-II, IGFBP-2 and IGFBP-3 associated with increased risk of PSA-detected cancer
• Magnitude of the associations for 5th vs 1st quintile similar to risk conferred by a 1st degree FH of PCa
29
How might the clinical management of PCa change?
• Dietary interventions to alter IGF-I in men with PCa
– e.g. put men with prostate cancer on a dairy-free diet & increase exercise levels
– NIHR funded BRU - Nutrition, Lifestyle, Obesity
• Drug development /trials of inhibitors of IGF-I levels – e.g. IGFBP-3, ligand-specific antibodies and GH antagonists
• Measure IGF-I levels to predict prostate cancer outcomes
• Include IGF-II, IGFBP-2 or IGFBP-3 in a screening panel
31