R01CA268287
Project Grant
Overview
Grant Description
Prognostic and Predictive Digital Tissue Image Assay for Prostate Cancer - Project Summary:
There were >34,000 PCA-related deaths in 2020 in the US alone. Definitive treatment includes radical prostatectomy (RP) or radiotherapy (RT) with long-term androgen-suppression therapy (ADT). These have been shown to be effective treatments for organ-confined PCA and have been demonstrated to reduce the risk of death from PCA.
In 38-52% of cases, however, advanced disease with potentially poor prognosis is found on tissue pathology. A number of recent clinical trials have shown the benefit of adjuvant therapy in select PCA patients post-RP or RT. However, it is critical to identify those PCA patients who, following definitive therapy (surgery or radiation), are at high risk for recurrence or metastasis and thus will benefit from adjuvant therapy versus patients who will not and hence may be spared the morbidity and cost of therapy.
Recognizing the significance of this unmet clinical need, in 2018 the NCCN guidelines for PCA were modified to include the Decipher score, a prognostic molecular gene-based test to identify the likelihood of metastasis following surgery. We have developed our own "Integrated Risk Score" (IRIS) image classifier that (NPJ Precision Oncology, in press14) combines computer-extracted morphologic glandular features from H&E tissue slides of the tumor.
IRIS stratified PCA patients (N>900, 6 sites) based on their time to biochemical recurrence (BCR) into low- and high-risk groups (P<0.001; HR=2.44). Further, IRIS when combined with pre-op PSA and Gleason grade outperformed Decipher in predicting BCR in N=173 patients (P<0.001; HR=3.23 vs HR=2.76).
In this R01, we will validate IRIS as (1) prognostic of BCR and risk of metastasis as well as (2) predictive of the added benefit of additional chemotherapy following definitive therapy (surgery or radiation) in PCA. In a recent paper in Clinical Cancer Research, we identified IRIS-specific prognostic features for African American (AA) men with PCA. We will build on these findings to develop population-specific IRIS models for PCA.
We will also further optimize IRIS by including (1) features of stromal and cribriform morphology, (2) develop population-specific IRIS models for different ethnic groups, and (3) complement IRIS with clinico-pathological features.
To validate IRIS as predictive of the benefit of adjuvant therapy, we need access to randomized clinical trial tissue slide images involving PCA patients treated with definitive therapy alone (surgery or ADT+radiation) and definitive therapy+adj. chemo. The STAMPEDE and RTOG-0521 trials fit these criteria; we have secured approval to access tissue slide images from these trials.
To make the tool widely available, IRIS will be integrated into PathPresenter, a digital pathology viewer and management platform currently in use in 178 countries. This partnership will combine expertise in (a) computational pathology of the Madabhushi group, (2) clinical, pathological, and biomarker expertise of PCA from the University of Pennsylvania (Drs. Priti Lal), and (3) GU medical oncology expertise from the Cleveland Clinic (Dr. Shilpa Gupta) to translate IRIS as the first tissue non-destructive prognostic and predictive affordable precision medicine (APM) solution for PCA.
There were >34,000 PCA-related deaths in 2020 in the US alone. Definitive treatment includes radical prostatectomy (RP) or radiotherapy (RT) with long-term androgen-suppression therapy (ADT). These have been shown to be effective treatments for organ-confined PCA and have been demonstrated to reduce the risk of death from PCA.
In 38-52% of cases, however, advanced disease with potentially poor prognosis is found on tissue pathology. A number of recent clinical trials have shown the benefit of adjuvant therapy in select PCA patients post-RP or RT. However, it is critical to identify those PCA patients who, following definitive therapy (surgery or radiation), are at high risk for recurrence or metastasis and thus will benefit from adjuvant therapy versus patients who will not and hence may be spared the morbidity and cost of therapy.
Recognizing the significance of this unmet clinical need, in 2018 the NCCN guidelines for PCA were modified to include the Decipher score, a prognostic molecular gene-based test to identify the likelihood of metastasis following surgery. We have developed our own "Integrated Risk Score" (IRIS) image classifier that (NPJ Precision Oncology, in press14) combines computer-extracted morphologic glandular features from H&E tissue slides of the tumor.
IRIS stratified PCA patients (N>900, 6 sites) based on their time to biochemical recurrence (BCR) into low- and high-risk groups (P<0.001; HR=2.44). Further, IRIS when combined with pre-op PSA and Gleason grade outperformed Decipher in predicting BCR in N=173 patients (P<0.001; HR=3.23 vs HR=2.76).
In this R01, we will validate IRIS as (1) prognostic of BCR and risk of metastasis as well as (2) predictive of the added benefit of additional chemotherapy following definitive therapy (surgery or radiation) in PCA. In a recent paper in Clinical Cancer Research, we identified IRIS-specific prognostic features for African American (AA) men with PCA. We will build on these findings to develop population-specific IRIS models for PCA.
We will also further optimize IRIS by including (1) features of stromal and cribriform morphology, (2) develop population-specific IRIS models for different ethnic groups, and (3) complement IRIS with clinico-pathological features.
To validate IRIS as predictive of the benefit of adjuvant therapy, we need access to randomized clinical trial tissue slide images involving PCA patients treated with definitive therapy alone (surgery or ADT+radiation) and definitive therapy+adj. chemo. The STAMPEDE and RTOG-0521 trials fit these criteria; we have secured approval to access tissue slide images from these trials.
To make the tool widely available, IRIS will be integrated into PathPresenter, a digital pathology viewer and management platform currently in use in 178 countries. This partnership will combine expertise in (a) computational pathology of the Madabhushi group, (2) clinical, pathological, and biomarker expertise of PCA from the University of Pennsylvania (Drs. Priti Lal), and (3) GU medical oncology expertise from the Cleveland Clinic (Dr. Shilpa Gupta) to translate IRIS as the first tissue non-destructive prognostic and predictive affordable precision medicine (APM) solution for PCA.
Awardee
Funding Goals
TO IMPROVE SCREENING AND EARLY DETECTION STRATEGIES AND TO DEVELOP ACCURATE DIAGNOSTIC TECHNIQUES AND METHODS FOR PREDICTING THE COURSE OF DISEASE IN CANCER PATIENTS. SCREENING AND EARLY DETECTION RESEARCH INCLUDES DEVELOPMENT OF STRATEGIES TO DECREASE CANCER MORTALITY BY FINDING TUMORS EARLY WHEN THEY ARE MORE AMENABLE TO TREATMENT. DIAGNOSIS RESEARCH FOCUSES ON METHODS TO DETERMINE THE PRESENCE OF A SPECIFIC TYPE OF CANCER, TO PREDICT ITS COURSE AND RESPONSE TO THERAPY, BOTH A PARTICULAR THERAPY OR A CLASS OF AGENTS, AND TO MONITOR THE EFFECT OF THE THERAPY AND THE APPEARANCE OF DISEASE RECURRENCE. THESE METHODS INCLUDE DIAGNOSTIC IMAGING AND DIRECT ANALYSES OF SPECIMENS FROM TUMOR OR OTHER TISSUES. SUPPORT IS ALSO PROVIDED FOR ESTABLISHING AND MAINTAINING RESOURCES OF HUMAN TISSUE TO FACILITATE RESEARCH. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Atlanta,
Georgia
303221007
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 342% from $679,964 to $3,008,190.
Emory University was awarded
Precision Prostate Cancer Tissue Image Assay Improved Treatment Decisions
Project Grant R01CA268287
worth $3,008,190
from National Cancer Institute in September 2022 with work to be completed primarily in Atlanta Georgia United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.394 Cancer Detection and Diagnosis Research.
The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 9/24/25
Period of Performance
9/5/22
Start Date
8/31/27
End Date
Funding Split
$3.0M
Federal Obligation
$0.0
Non-Federal Obligation
$3.0M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01CA268287
Additional Detail
Award ID FAIN
R01CA268287
SAI Number
R01CA268287-3212095817
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75NC00 NIH National Cancer Institute
Funding Office
75NC00 NIH National Cancer Institute
Awardee UEI
S352L5PJLMP8
Awardee CAGE
2K291
Performance District
GA-05
Senators
Jon Ossoff
Raphael Warnock
Raphael Warnock
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) | $1,307,609 | 100% |
Modified: 9/24/25