DNA Analysis of Tumor Tissue Samples From Young Patients With Acute Lymphoblastic Leukemia

August 12, 2022 updated by: Children's Oncology Group

Single Nucleotide Polymorphisms and Relapse Risk in Standard Risk ALL

This laboratory study is looking at DNA in tumor tissue samples from young patients with acute lymphoblastic leukemia. DNA analysis of tumor tissue may help doctors predict how well patients will respond to treatment

Study Overview

Detailed Description

PRIMARY OBJECTIVE:

I. To validate significant associations between SNPs and treatment outcome and toxicity on Children's Cancer Group (CCG)-1891 on an independent sample set from a successor CCG study for standard risk acute lymphoblastic leukemia (ALL), CCG-1952.

II. To evaluate the role of SNPs in drug metabolizing enzymes and the development of veno-occlusive disease in patients on CCG-1952.

III. To evaluate interactions among genotypes and other risk factors for treatment response in a combined data set of CCG-1891 and CCG-1952 with recently developed analytic tools for high dimensional data.

IV. To develop predictive models utilizing genetic information obtained in Aim 1.1 and clinical data to predict treatment response and toxicity.

OUTLINE:

Tumor tissue samples undergo genotype assessment on the Pyrosequencing platform. Contingency tables and X^2 test performs a univariate analysis of the risk of relapse and genotype, and multivariable analyses using logistic regression. Cox proportional hazards evaluate the risk of relapse given genotype and other confounders. Genotype patterning, classification and regression trees, and multifactor dimensionality reduction evaluates for patterns of single nucleotide polymorphisms associated with toxicity and relapse risk.

Study Type

Observational

Enrollment (Actual)

520

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Pennsylvania
      • Philadelphia, Pennsylvania, United States, 19104
        • Childrens Oncology Group

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

No older than 18 years (Child, Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Description

Inclusion Criteria:

  • Enrolled in clinical trial CCG-1891 or CCG-1952 with pediatric ALL

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Ancillary-Correlative (genotype assessment)
Tumor tissue samples undergo genotype assessment on the Pyrosequencing platform. Contingency tables and X^2 test performs a univariate analysis of the risk of relapse and genotype, and multivariable analyses using logistic regression. Cox proportional hazards evaluate the risk of relapse given genotype and other confounders. Genotype patterning, classification and regression trees, and multifactor dimensionality reduction evaluates for patterns of single nucleotide polymorphisms associated with toxicity and relapse risk.
Correlative studies

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Leukemia Relapse
Time Frame: Day 7
Contingency tables will be used to tabulate the relationship between relapse and genotype, race, leukemia cytogenetics, day 7 bone marrow status, and treatment arm
Day 7
Development of veno-occlusive disease in patients on CCG-1952
Time Frame: Day 28
Classification and Regression Trees (CART), genotype patterning, Multifactor Dimensionality Reduction (MDR) techniques will be used to identify SNP combinations associated with risk of relapse and VOD
Day 28
Development of a predictive model of leukemia relapse
Time Frame: Day 28
Predictive models will be developed utilizing genetic information obtained in Aim 1.1 and clinical data to predict treatment response
Day 28
Development of a predictive model of leukemia toxicity
Time Frame: Day 28
Predictive models will be developed utilizing genetic information obtained in Aim 1.1 and clinical data to predict treatment toxicity.
Day 28

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Development of grade III/IV toxicity as defined by the CCG toxicity criteria
Time Frame: Day 28
Contingency tables will be used to tabulate categorical toxicities and toxicity severity grade.
Day 28

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Richard Aplenc, Children's Oncology Group

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 13, 2004

Primary Completion (Actual)

May 5, 2016

Study Registration Dates

First Submitted

May 9, 2009

First Submitted That Met QC Criteria

May 9, 2009

First Posted (Estimate)

May 12, 2009

Study Record Updates

Last Update Posted (Actual)

August 15, 2022

Last Update Submitted That Met QC Criteria

August 12, 2022

Last Verified

October 1, 2017

More Information

Terms related to this study

Other Study ID Numbers

  • AALL04B2 (Other Identifier: CTEP)
  • U10CA098543 (U.S. NIH Grant/Contract)
  • NCI-2009-00309 (Registry Identifier: CTRP (Clinical Trial Reporting Program))
  • CDR0000371580
  • COG-AALL04B2

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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