UH3CA207101
Cooperative Agreement
Overview
Grant Description
Colorectal Cancer Molecular Subtype Assay Development and Validation - Abstract
Stage III colorectal cancer (CRC) demonstrates substantial variability in tumor biology and clinical outcomes. There is a need to understand prognosis for patients in order to gauge risk benefit for chemotherapy and intensity of chemotherapy administration. These features are not well recapitulated by the current biomarkers in use in the clinic, majority of them are DNA based mutation assays.
RNA expression patterns have been described by various investigators and may more fully recapitulate tumor biology. The clinical utility of these findings has been limited by the apparent conflicting subgrouping efforts and lack of a validated gene expression signature as a clinical grade assay applicable on formalin fixed paraffin embedded (FFPE) tissue.
In our international collaboration with several academic leaders who have previously published in this field, we have identified a robust consensus subgroup classification based on clustering approaches independent of clinical outcomes. Remarkably, this classification system, termed Consensus Molecular Subtypes (CMS), identified 4 subgroups that provide novel insights into the classification of CRC. One subgroup with mesenchymal, TGF-β, and angiogenic features (CMS4) is associated with a hazard ratio for death of 2.26 (95% CI of 1.41 to 3.61, P=.001), significantly higher than other subgroups, in a multivariate model inclusive of current clinical and pathologic risk factors and genetic signature (Oncotype DX).
We hypothesize that a gene expression signature classifier can be developed and validated for determining the CMS in FFPE tissues, and that this classifier can be implemented to improve prognostication of stage III CRC by classifying them in CMS 4 vs. other subtypes. We have developed a support-vector-machine classifier with very high accuracy for classification based on an Affymetrix array from fresh frozen specimens. We have demonstrated good classification accuracy (>90%) using customized NanoString codesets on FFPE tumor samples of 85 patients with stage III CRC. We have also demonstrated good technical reproducibility in six of those 85 samples.
In this application, we will transfer the assay using the NanoString codeset to fresh frozen (FF) and FFPE using a set of paired samples, while maintaining classifier performance. We will then pursue technical and analytic validation of the assay, including precision in repeatability, reproducibility between sample types, inter-lab reproducibility, and impact of RNA quality/quantity.
In the UH3 portion of the grant, we will clinically validate the prognostic utility of the gene expression signature assay in a single-institution cohort, and then in a completed prospective study of FOLFOX chemotherapy (NRG/NSABPC-08), in a CLIA certified laboratory. Additional data will be used in predicting response to various standard of care therapeutics, which represents a series of future potential applications of the assay.
By utilizing an assay developed to classify CRC by its tumor biology, we anticipate development of an enduring tool that will be of greater use than traditional fit-for-purpose tests.
Stage III colorectal cancer (CRC) demonstrates substantial variability in tumor biology and clinical outcomes. There is a need to understand prognosis for patients in order to gauge risk benefit for chemotherapy and intensity of chemotherapy administration. These features are not well recapitulated by the current biomarkers in use in the clinic, majority of them are DNA based mutation assays.
RNA expression patterns have been described by various investigators and may more fully recapitulate tumor biology. The clinical utility of these findings has been limited by the apparent conflicting subgrouping efforts and lack of a validated gene expression signature as a clinical grade assay applicable on formalin fixed paraffin embedded (FFPE) tissue.
In our international collaboration with several academic leaders who have previously published in this field, we have identified a robust consensus subgroup classification based on clustering approaches independent of clinical outcomes. Remarkably, this classification system, termed Consensus Molecular Subtypes (CMS), identified 4 subgroups that provide novel insights into the classification of CRC. One subgroup with mesenchymal, TGF-β, and angiogenic features (CMS4) is associated with a hazard ratio for death of 2.26 (95% CI of 1.41 to 3.61, P=.001), significantly higher than other subgroups, in a multivariate model inclusive of current clinical and pathologic risk factors and genetic signature (Oncotype DX).
We hypothesize that a gene expression signature classifier can be developed and validated for determining the CMS in FFPE tissues, and that this classifier can be implemented to improve prognostication of stage III CRC by classifying them in CMS 4 vs. other subtypes. We have developed a support-vector-machine classifier with very high accuracy for classification based on an Affymetrix array from fresh frozen specimens. We have demonstrated good classification accuracy (>90%) using customized NanoString codesets on FFPE tumor samples of 85 patients with stage III CRC. We have also demonstrated good technical reproducibility in six of those 85 samples.
In this application, we will transfer the assay using the NanoString codeset to fresh frozen (FF) and FFPE using a set of paired samples, while maintaining classifier performance. We will then pursue technical and analytic validation of the assay, including precision in repeatability, reproducibility between sample types, inter-lab reproducibility, and impact of RNA quality/quantity.
In the UH3 portion of the grant, we will clinically validate the prognostic utility of the gene expression signature assay in a single-institution cohort, and then in a completed prospective study of FOLFOX chemotherapy (NRG/NSABPC-08), in a CLIA certified laboratory. Additional data will be used in predicting response to various standard of care therapeutics, which represents a series of future potential applications of the assay.
By utilizing an assay developed to classify CRC by its tumor biology, we anticipate development of an enduring tool that will be of greater use than traditional fit-for-purpose tests.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Texas
United States
Geographic Scope
State-Wide
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 165% from $297,095 to $787,854.
The Univeristy Of Texas M.D. Anderson Cancer Center was awarded
Colorectal Cancer Molecular Subtype Assay Development and Validation
Cooperative Agreement UH3CA207101
worth $787,854
from National Cancer Institute in September 2018 with work to be completed primarily in Texas United States.
The grant
has a duration of 6 years and
was awarded through assistance program 93.394 Cancer Detection and Diagnosis Research.
The Cooperative Agreement was awarded through grant opportunity Assay Validation For High Quality Markers For NCI-Supported Clinical Trials (UH2/UH3).
Status
(Complete)
Last Modified 7/5/24
Period of Performance
9/21/18
Start Date
8/31/24
End Date
Funding Split
$787.9K
Federal Obligation
$0.0
Non-Federal Obligation
$787.9K
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for UH3CA207101
Transaction History
Modifications to UH3CA207101
Additional Detail
Award ID FAIN
UH3CA207101
SAI Number
UH3CA207101-926813735
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75NC00 NIH NATIONAL CANCER INSTITUTE
Funding Office
75NC00 NIH NATIONAL CANCER INSTITUTE
Awardee UEI
S3GMKS8ELA16
Awardee CAGE
0KD38
Performance District
TX-90
Senators
John Cornyn
Ted Cruz
Ted Cruz
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
National Cancer Institute, National Institutes of Health, Health and Human Services (075-0849) | Health research and training | Grants, subsidies, and contributions (41.0) | $490,759 | 100% |
Modified: 7/5/24