Abbreviated Name

GLNE 007

Lead Investigator

Bresalier, Bob — The University of Texas MD Anderson Cancer Center

Coordinating Investigator

Zheng, Yingye — Fred Hutchinson Cancer Center

Involved Investigators

• Rowland Jr., Kendrith — Carle Cancer Center
• — University of Michigan
• McGills, Sarah — University of North Carolina
• Syngal, Sapna — Dana Farber Cancer Institute-BWH
• Zaghiyan, Karen — Cedars Sinai Medical Center
• Crockett, Seth — Oregon Health Science University
• Stoffel, Elena — University of Michigan
• Ruffin, IV, Mack T. — Hershey-Penn State Medical Center
• Grady UW, William — University of Washington
• Bresalier, Bob — The University of Texas MD Anderson Cancer Center
• Symonds, Erin — Flinders Centre for Innovation in Cancer
• Young, Graeme — Lab – Flinders Centre for Innovation in Cancer
• McConnell, Daniel S. — University of Michigan
• Teshima, Christopher — St Michael's Hospital
• Shaukat , Aasma — University of Minnesota
• Shaukat, Aasma — NYU Langone
• Zheng, Yingye — Fred Hutchinson Cancer Center

Abstract

As part of the National Cancer Institute-funded Early Detection Research Network (EDRN), the Great Lakes-New England Clinical Epidemiological Center (GLNE CEC) proposes a research study that validates potential molecular markers (“biomarkers”) for the detection of precancerous and cancerous conditions and cancer risk assessment. Although examples of such biomarkers are currently in clinical use (i.e. CEA, CA-125), there are limitations to all of them. Our consortium focuses on gastrointestinal neoplasia.

Aims

1.   Assessment of the utility of individual stool-based, and serum-based biomarkers for discriminating between 1) patients with adenocarcinomas, 2)patients with adenomas with high grade dysplasia, 3) patients with advanced adenomas defined as adenoma histology of any combination (including sessile serrated adenoma, tubulovillous adenoma, villous adenoma, sessile serrated polyp/adenoma, traditional serrated adenoma OR any adenoma ≥1 cm OR three or more adenomas), 4)patients with adenomas that are not advanced, and 5) colonoscopy with no neoplasia in subjects both at average and higher risk for developing colon cancer. 2.   Construction of a panel of markers from those considered in Objective 1 to discriminate, under a number of assumptions concerning prevalence and cost of misclassification, between: a.   (Primary) Subjects with non-neoplastic endoscopic findings or non-advanced adenomas versus patients with cancers; b.   (Secondary) Subjects with non-neoplastic endoscopic findings versus patients with cancers. 3.   Comparison of the characteristics of individual markers and panels as discriminators to those of the established current standard, fecal immunochemical test (FIT). 4.   Continued support of a renewal of a bank of stool samples linked to serum, tissue, and clinical data from patients with colorectal cancer, adenomas and normal controls for validation of stool- based markers that may be developed in the future.

Analytic Method

Assessment of the utility of individual biomarkers for discriminating between patients with adenocarcinomas, patients with adenomas, patients without adenomas and normal subjects. For markers measured on a continuous scale, the within-stratum, or within-class (e.g. SRN as a class), distributions of the marker values will be assessed by graphical means (e.g., q-q plots). Maximum likelihood estimates of distribution parameters will be calculated. For markers measured on a dichotomous scale, the proportions of positive tests in each class will be determined. For each marker, non-parametric (via SAS PROC LOGISTIC) and fully parametric ROC curves will be constructed for: Stratum 4 versus all others except SRN-adenomas (define as adenoma ≥1 cm or adenoma with high grade dysplasia or sessile serrated polyp ≥1 cm) (primary comparison); Stratum 4 versus Strata 1 and 2 (secondary comparison); and other exploratory comparisons: Stratum 4 versus Stratum 1; Stratum 4 and SRN-adenomas in Strata 3 versus Strata 1 and 2 and non-SRN adenoma; Strata 2, 3 and 4 versus Stratum 1. While the non-parametric ROCs are generally preferred, decision rules for population screens may require very high specificity, which will require accurate estimation in the distribution tails; parametric ROC curves may be better for this application. The area under each ROC curve (AUC) for each comparison will be determined.

Publications

• No publications available at this time for this protocol.

Biomarkers

• BCAT1
• Circulating methylated genes BCAT1/IKZF1 (Clinical Genomics)
• galectin-3 ligand
• Hypomethylated LINE1 from circulating cell free DNA (VolitionRx)
• IKZF1
• TIMP1

Data Collections

• No data collections available at this time for this protocol.

Start Date

Apr 25 2019

Estimated Finish Date

Mar 31 2021

Protocol ID

456

Protocol Type

Collaboration

Fields of Research

• Proteomics

Collaborative Group

G.I. and Other Associated Cancers Research Group

Cancer Types

• Malignant neoplasm of colon

Phased Status

1