Insulin and Metabolic Pathways in Endometrial Cancer

Insulin and Metabolic Pathways in Endometrial Cancer Marc J. Gunter, PhD Reader/Associate Professor Department of Epidemiology and Biostatistics Imperial College, London

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

Obesity and Cancer Risk Renehan et al., 2008

80% Trends in Overweight and Obesity 70% roportion overwe eight P 60% 50% USA Spain England Canada 40% Austria Italy Australia 30% France Korea 20% 1970 1980 1990 Year 2000 2010 2020 WHO, 2010

Obesity and Endometrial Cancer: Mechanisms Exposures Diet Obesity Physical activity Mechanisms Growth factors Insulin resistance Adipokines Inflammation Steroid hormones? Biomarkers IGF-1 IGFBP-3 Insulin C-Peptide Leptin CRP Estrogen Progesterone Free IGF-I HbA1c TNF-α SHBG Endpoint Endometrial Cancer

Insulin and IGF-I Signalling Experimental data support a cancerpromoting effect of insulin and IGF-I Are circulating levels of insulin and IGF-I associated 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): Breast Cancer (900 cases) Colorectal l Cancer (500 cases) Endometrial Cancer (300 cases) Representative Sub-cohort (900 subjects) (Gunter et al., JNCI, 101(1):48-60) (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 estrogen levels. Fasting insulin glucose Total IGF-I Free IGF-I IGFBP-3 Fasting 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 Initiative RR P<0.001 Hazard Ratio P=0.02 P=0.01 Oestradiol P trend = 001 0.01 IGF-I P trend = 0.10 trend = Quartile of Serologic Factor Quartile of Serologic Parameter

Metabolic Subtypes in Obesity Not all obesity is the same-is this relevant for cancer?

Metabolically-defined Obesity Subtypes and Endometrial 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 risk Risk estimates t generally unaffected by adjustment t for BMI, estradiol, free IGF suggesting independent pathway Generally consistent with data from other cohort studies (EPIC, NYUWHS) 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 Signaling Normal Endometrium (hysterectomy samples) 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 across endometrial tissues 2. Impact of EC Risk factors 3. Understand circulating versus local levels

IR-IGF-P Receptor Insulin Receptor Secretory Secretory Proliferative Proliferative

Insulin Receptor Expression in Endometrial Tissues 40 P <0.001 35 30 Tra Transcripts X X 10 10-6 -6 25 20 15 10 5 0 Tissue 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 o Free Survival in GOG-0210 0 (287 recurrences to date) RR Hazard Ratio Oestradiol P trend = 001 0.01 P<0.001 IGF-I P trend = 0.10 trend = Quartile of Serologic Factor Quartile of Serologic Parameter 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 g endometrial 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) 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) To assess the association of endometrial cancer risk factors with metabolite profiles Anthropometric parameters 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 Weight loss Serum markers Insulin/IGF Inflammation Metabolomics Tissue markers Cancer associated molecular or 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) (10-20%) General Dietary Advice (1-2%) 9-12 months Blood, urine, stool, colon biopsies banked (i) Insulin/IGF/mTOR (ii) Metabolomic Profiling

Acknowledgements/Collaborators Imperial College Elio Riboli Hector Keun Melissa Merritt Maria Kyrgiou Hani Gabra Albert Einstein College of Medicine Howard Strickler Gloria Huang Tom Rohan Xiaonan Xue Gloria Ho Mark Einstein Others: Herbert Yu (University of Hawaii) JoAnn Manson (Harvard) Garnet Anderson (Fred Hutchinson Cancer Research Center) Mark Sherman (NCI) Louise Brinton (NCI) Hannah Yang (NCI) Mia Gaudet (ACS) Jane Wardle (UCL) Immaculata DeVivo (Harvard) Sara Olson (MSKCC) Anne Zelenuich-Jacquotte (NYU) Funding Sources Grants R01-CA93881 (H. Strickler); R01-CA133010 (M. Gunter); CR- UK; OCA(M. Gunter)