Methylation Makers for D Detection of Endometrial i f E d i l - PowerPoint PPT Presentation

Methylation Makers for D Detection of Endometrial i f E d i l Carcinoma Carcinoma Nicolas Wentzensen M.D., Ph.D., M.S. Senior Investigator Hormonal and Reproductive Epidemiology Branch p p gy Division of Cancer Epidemiology and Genetics Advances in Endometrial Cancer Epidemiology and Biology Advances in Endometrial Cancer Epidemiology and Biology Boston, March 17-18, 2014

Endometrial cancer survival • Good prognosis when detected early, but 25% of cancers present at advanced stage and have poor survival • About 80% of endometrial cancer deaths occur due to advanced stage type 1 cancers Adenocarcinoma of the Corpus Uteri: Relative Survival Rate (%) by AJCC Stage (SEER modified 3rd edition), Ages 20+, 12 SEER Areas, 1988-2001

Promise of early detection y o Most common gynecological cancer in the US: 49,560 cases and 8,190 deaths in 2013 o Well defined high risk populations: Women g p p with high BMI, postmenopausal bleeding, endometrial hyperplasia yp p o 1-2 million office visits each year in the US related to postmenopausal bleeding related to postmenopausal bleeding o No uniform management of women at increased risk of endometrial cancer

Methylation profiling of endometrial cancers Discovery Polish Endometrial Cancer Case- Benign Reproductive Tissue Study I: Control Study: 25 normal tissues 148 cancers Replication Endometrial Hyperplasia Study: Benign Reproductive Tissue Study II: 69 cancers 43 normal tissues o Endometrial tissues from three population-based studies o DNA was extracted from paraffin-embedded tissue DNA was extracted from paraffin embedded tissue o Methylation analysis on Illumina Golden Gate platform, covering >800 cancer related genes g o Finding markers of etiologic heterogeneity and for early detection

Methylation patterns show etiologic heterogeneity Endometrial carcinomas Normal endometrium Low % of MSI Low % of MSI High % of MSI High % of MSI Samples in columns Genes in rows Red: higher methylation 25% most variable probes o Two major cancer clusters: One cluster with high prevalence of microsatellite instability (MSI) o Comparison of cancer and normal tissue: Over 300 sites with p<0.001; PTEN pathway was most significantly methylated

Genes with different methylation levels between endometrial cancer and normal endometrial tissue endometrial cancer and normal endometrial tissue Methylation y Gene control case difference p-value ASCL2 0.12 0.78 0.66 < 10 -7 HTR1B 0.10 0.75 0.65 < 10 -7 HS3ST2 0.19 0.78 0.59 < 10 -7 SOX1 0.20 0.76 0.56 < 10 -7 MME 0.06 0.61 0.55 < 10 -7 ADCYAP1 0.09 0.61 0.52 < 10 -7 < 10 -7 NPY 0.17 0.68 0.51 CDH13 0.14 0.54 0.40 1.8x10 -6 o Top eight candidate genes with high methylation differences, low methylation in controls (probes averaged for each gene) controls (probes averaged for each gene) Wentzensen et al. IJC in press

Replication of eight candidate genes in the validation study

Prediction of endometrial carcinomas using methylation markers methylation markers o Two classifiers based on (1) top 8 genes and (2) all 800 genes included on the array were successfully replicated in independent samples

Replication of methylation markers in TCGA Endometrioid Carcinomas Serous Carcinomas Normal Cases Cases Gene tissues p-value AUC p-value AUC (n=358) (n=86) (n=43) ADCYAP1 ADCYAP1 0 07 0.07 0.60 0 60 <0.0001 0 0001 0.97 0 97 0 28 0.28 <0.0001 0 0001 0.77 0 77 ASCL2 0.12 0.55 0.0001 0.79 0.08 0.28 0.44 CDH13 0.16 0.54 <0.0001 0.95 0.18 0.83 0.51 HS3ST2 HS3ST2 0 12 0.12 0 55 0.55 <0 0001 <0.0001 0.95 0 95 0 24 0.24 0.0005 0 0005 0 69 0.69 HTR1B 0.12 0.56 <0.0001 0.99 0.27 0.0001 0.96 MME 0.20 0.48 <0.0001 0.85 0.22 0.19 0.57 NPY NPY 0 10 0.10 0 57 0.57 <0 0001 <0.0001 0.92 0 92 0 20 0.20 0 02 0.02 0 63 0.63 SOX1 0.14 0.60 <0.0001 0.99 0.45 <0.0001 0.96 o All eight markers replicate in endometrioid cancers from TCGA o All eight markers replicate in endometrioid cancers from TCGA o Four (to five) markers replicate in serous cancers from TCGA

Evaluation of candidate markers in lower genital t tract samples t l 1. Tao brush: Sampling from 2. Tampon: Collecting blood and complete uterine epithelium discharge from the vaginal pool o Pilot study with Mayo Clinic: Collection of lower genital tract samples from 40 women with cancer and 40 women without cancer

Replication of candidates in lower genital tract specimens specimens Odds ratio o 5/5 candidates were successfully replicated in Tao brush samples 5/5 did t f ll li t d i T b h l o 4/5 candidates were successfully replicated in Tampon samples Wentzensen et al. IJC in press; Bakkum-Gamez, Wentzensen et al. submitted

NPY methylation in cases and controls NPY 80 60 40 0 20 0 Primary EC Tao Brush EC Tampon EC Tao Brush Control Tampon Control Pos. 1 Methylation (%) Pos. 2 Methylation (%) o Increasing dilution of methylation signal o Good discrimination of case-control status

Performance of markers in Tao brush samples

Performance of the combined analysis of 11 CpG sites in Tampon samples 11 CpG sites in Tampon samples • The AUC of the combined model is 0.85 • At a cutoff of 1 or more hypermethylated sites, the assay has 83% sensitivity and 83% specificity

How can the risk stratification of methylation markers be used clinically? • Refer women to treatment Refer women to treatment • Refer women for further diagnostic evaluation • Reassure women that no further • Reassure women that no further evaluation is necessary

A study to evaluate methylation markers for detection of endometrial carcinoma • 1,000 women 45 years or older presenting at Mayo Clinic – Evaluation of abnormal endometrial bleeding, discharge, thickening of endometrial stripe • At least 5% estimated prevalence for atypical hyperplasia as well as cancer ll • Collection of Tampon and Tao brush samples, blood, tissue from endometrial biopsies and surgery RF data tissue from endometrial biopsies and surgery, RF data • 2-year follow-up of women without endometrial cancer

Risk stratification for prediction of endometrial cancer cancer Risk of 100% endometrial cancer 40% 40% Methylation + 10% Women at increased risk of endometrial cancer Methylation - Methylation 2% 0% o Possibility of self-sampling o Integration of clinical symptoms and methylation markers into risk prediction models models o Evaluation of methylation markers in endometrial hyperplasia Wentzensen and Wacholder Cancer Discovery 2013

Collaborators Collaborators Magee Women’s Hospital NCI-DCEG Lori d’Ambrosio Clara Bodelon Richard Guido Mayo Clinic Louise Brinton Jamie Bakkum Jamie Bakkum Ashley Felix Cancer Center, Warsaw Karl Podratz Mark Greene Jolanta Lissowska Viji Sridhar Patricia Luhn Ruth Pfeiffer Kaiser Permanente Northwest NCI-CCR Joshua Sampson Andrew Glass Stephen Hewitt Hannah Yang Kathy Pearson Keith Killian Keith Killian NCI-DCP Brenda Rush Paul Meltzer Mark Sherman City of Hope Jim Lacey