Insulin and Metabolic Pathways yin Endometrial Cancer

Marc J. Gunter, PhDReader/Associate ProfessorDepartment of Epidemiology and BiostatisticsDepartment of Epidemiology and BiostatisticsImperial College, London

International Variation in Age-Standardized Endometrial Cancer Incidence Rates, 2012,

Globocan, 2012

Obesity and Cancer Risk

Renehan et al., 2008

Trends in Overweight and Obesity

70%

80%

60%

eigh

t

50%

ropo

rtio

n ov

erw

e

USAEngland

Canada

40%

P Spain

Austria

Australia

Italy

30% France

Australia

Korea

20%1970 1980 1990 2000 2010 2020

Year

WHO, 2010

Obesity and Endometrial Cancer: Mechanisms

Exposures ObesityDiet Physicalactivity

Mechanisms Growth factors

Adipokines Inflammation

Steroid hormones

Insulin resistance

?Biomarkers

Insulin

C P tid

Estrogen

P t

Leptin

CRPIGF-1

IGFBP 3

?C-Peptide

HbA1c

Progesterone

SHBG

CRP

TNF-αIGFBP-3

Free IGF-I

Endometrial CancerEndpoint

Insulin and IGF-I Signalling

E i t l d tExperimental data support a cancer-promoting effect of insulin and IGF-I

Are circulating levels of insulin and IGF-I

i t d ithassociated with future endometrial cancer risk?

Women’s Health Initiative

• Case-Cohort Study of Insulin/IGF-I Axis in WHI-OS (93,676 postmenopausal women; 77 months of follow-up):postmenopausal women; 77 months of follow up):

– Breast Cancer (900 cases) C l t l C (500 )

(Gunter et al., JNCI, 101(1):48-60)

– Colorectal Cancer (500 cases)– Endometrial Cancer (300 cases) – Representative Sub-cohort (900 subjects)

(Gunter et al., Cancer Res, 68(1):329-37)

(Gunter et al., CEBP, 17(1):921-9)

– Prospectively assess the association of insulin/IGF-axis components with these cancers while controlling for endogenous p g gestrogen levels.

– Fasting insulin glucose Total IGF-I Free IGF-I IGFBP-3Fasting insulin, glucose, Total IGF I, Free IGF I, IGFBP 3, estradiol

Circulating Insulin, Free IGF-I, Estradiol and Endometrial Cancer Risk in the Women’s Health do et a Ca ce s t e o e s ea t

Initiative

RR P<0.001

OestradiolP 0 01

Hazard Ratio

P=0.02

Ptrend = 0.01

IGF-IPtrend = 0.10trend =

P=0.01

Quartile of Serologic ParameterQuartile of Serologic Factor

Metabolic Subtypes in Obesity

Not all obesity is the same-is this relevant for cancer?

Metabolically-defined Obesity Subtypes and E d t i l C Ri kEndometrial Cancer Risk

WHI +EPIC (950 cases, 950 controls)

BMI<25 + HOMA Q1-2

BMI<25 + HOMA Q4

BMI>25 + HOMA Q1-2

BMI>25 + HOMA Q4

Insulin and IGF-I and Endometrial Cancer• Significant positive association between fasting insulin levels and

endometrial cancer riskRi k ti t ll ff t d b dj t t f BMI t di l f IGF– Risk estimates generally unaffected by adjustment for BMI, estradiol, free IGF suggesting independent pathway

– Generally consistent with data from other cohort studies (EPIC, NYUWHS)y ( , )

– Insulin resistance in the absence of obesity may be a significant risk factor for endometrial cancer

• Free IGF-I levels inversely related to endometrial cancer risk– Unexpected but consistent with cross-sectional data

• What is going on at the tissue level?– Lack of data on expression of insulin/IGF pathways in different endometrial

tissues (normal, malignant)– Serum versus local levels? Circulating IGF-I is regulated by GH and mainly

hepatic in origin; Uterine IGF-I regulated by estrogen

Molecular Pathologic Study of Insulin/IGF SignalingSignaling

• Normal Endometrium (hysterectomy samples)• Premenopausal women (n=80)• Premenopausal women (n=80)• Postmenopausal women (n=56)

• Hyperplasias (n=67)

• Endometrioid Adenocarcinomas (n=1,230)( , )• Stage I (n=78)• Stage II (n=408)• Stage III (n=598)• Stage IV (n=146)

• FFPE, fresh frozen tissue, serum, risk factor data

• BRTE (NCI); Albert Einstein College of Medicine (New York); Hammersmith, Charing Cross Hospitals, (London); GOG-0210

Insulin and IGF-I Signalling

1. Comparison of expression acrossacross endometrial tissues

2. Impact of EC2. Impact of EC Risk factors

3. Understand circulatingcirculating versus local levels

IR-IGF-P Receptor Insulin Receptor

Secretory Secretory

Proliferative Proliferative

Insulin Receptor Expression in Endometrial Tissues

40

Endometrial TissuesP <0.001

30

35

20

25

Tran

scrip

ts

X 1

0-6

ansc

ripts

X

10-6

10

15

Tra

0

5

Tiss e T peTissue Type

Secretory Proliferative CAH Type I-II EC Type III-IV EC

*Normalized to 18s rRNA

Role of Sex Hormone and Insulin/IGF Axes in Endometrial Cancer Prognosis

• Nested cohort study of 900 stage II-IV EA patients recruited to GOG-0210

•Serum (obtained prior to surgery)

•Insulin, IGF-I, IGF-II, IGFBP-1, -3

•Estrogens, Progesterone, SHBG

• Fresh Frozen Tissue

•Gene expression (mRNA)-IGF-I, IGF-II, IGFBP-1, IGFBP-3, IR, IGF-IR, ER, PR, Akt, PTEN, , , ,

•Tumor Microarrays

•Immunohistochemical expression of IGF-IR, IR, Phospho-IGF-IR, Phospho-Akt, PTEN, ER, PR

Insulin, IGF-I, IGFBP-3 and Progression Free Survival in GOG-0210og ess o ee Su a GOG 0 0

(287 recurrences to date)

RR

OestradiolP 0 01

Hazard Ratio

Ptrend = 0.01

IGF-IPtrend = 0.10

P<0.001

trend =

Quartile of Serologic ParameterQuartile of Serologic Factor

Multivariate model includes age, stage,

grade, BMI

Metabolite Profiling and Endometrial Cancer•Hyperinsulinemia is associated with increased risk of endometrial cancer suggesting this pathway is important for endometrial tumorigenesis but:

• Complex relationship with IGF-I for both risk and prognosis• Predictive value of hyperinsulinemia is likely not high (common)

• Are there biochemical pathways specific for endometrial cancer development that increase a woman’s risk?

• Example: Panel of 4 amino acids (Leu, Val, Phe, Ile) shown to be predictive of DM-II risk beyond traditional risk factors and insulin resistance (Wang et al., Nat Med. 2011; 17(4):448–453)

• Case-control (n=250) study of metabolomic profiling and ( ) y p gendometrial cancer reported significant association with stearic acid and acylcarnitines (Gaudet et al., J Clin Endocrinol Metab. 2012 97(9):3216-23)

Metabolomic Profiling and Endometrial Cancer Risk

•To investigate the association of metabolomic proflies with endometrial cancer

• Profile 1 500 incident cases and 1 500 matched controls (2 stage design)• Profile 1,500 incident cases and 1,500 matched controls (2-stage design)• E2C2: NHS, EPIC, CPS-II, NYUWHS, MEC• Metabolomic platform at Broad Institute (>600 characterised metabolites;

unannotated peak data)• Proportion of cases/controls with existing hormonal data (insulin, IGF-I,

steroid hormones)

T th i ti f d t i l i k f t ith•To assess the association of endometrial cancer risk factors with metabolite profiles

• Anthropometric parameters• Genetic loci• Genetic loci• Hormone profiles• Ethnicity

•To explore the extent to which metabolites explain the association of endometrial cancer with its risk factors (mediation analyses)

INTERCEPT

WeightWeight loss

Serum markers

• Insulin/IGF• Inflammation• Metabolomics

Tissue k

• Cancer associated molecular or morphologicalmarkers morphological changes in tissue

Collaboration with Professor Jane Wardle (UCL); CR-UK Funded

INTERCEPT

~300 obese subjects enrolled

Blood, urine, stool, colon biopsies banked

Endometrial Tissue?

Intensive Weight Loss (VLCD)

General Dietary AdviceLoss (VLCD)

(10-20%)Advice

(1-2%)

9-12 months

Blood, urine, stool, colon biopsies banked

(i) Insulin/IGF/mTOR (ii) Metabolomic Profiling

Acknowledgements/CollaboratorsImperial College

Elio Riboli

Others:

Herbert Yu (University of Hawaii)Hector KeunMelissa MerrittMaria Kyrgiou

( y )JoAnn Manson (Harvard)Garnet Anderson (Fred Hutchinson Cancer Research Center)M k Sh (NCI)Hani Gabra

Albert Einstein College of Medicine

Mark Sherman (NCI)Louise Brinton (NCI)Hannah Yang (NCI)Mia Gaudet (ACS)Medicine

Howard StricklerGloria Huang

Mia Gaudet (ACS)Jane Wardle (UCL)Immaculata DeVivo (Harvard)Sara Olson (MSKCC)Gloria Huang

Tom RohanXiaonan XueGloria Ho

Sara Olson (MSKCC)Anne Zelenuich-Jacquotte (NYU)

Mark Einstein Funding Sources Grants R01-CA93881 (H. Strickler); R01-CA133010 (M. Gunter); CR-UK; OCA(M. Gunter)