CURRENT FUNDING OPPORTUNITIES

Strategic Partnering to Evaluate Cancer Signatures (SPECS II) (U01)

Program Announcement:

PAR-11-151
Expiration Date: June 16, 2012

Contact:
Tracy Lively, Ph.D.
301-496-1591
livelyt@mail.nih.gov

The NCI invites investigators to form NEW strategic partnerships that will bring together the multi-disciplinary expertise and resources needed to determine how the information derived from comprehensive molecular analyses can be used to improve patient care and, ultimately, patient outcomes. The SPECS II Funding Opportunity Announcement (FOA) encourages the submission of grant applications for support of the clinical application of multi-analyte molecular signatures derived from comprehensive molecular annotation of tumors.

Correlative Studies Using Specimens from Multi-Site Trials (R01/R21)

Program Announcements:

PA-12-013 (R01)
Expiration Date: January 8, 2015

PA-12-014 (R21)
Expiration Date: January 8, 2015

Contact:
Magdalena Thurin, Ph.D.
301-496-1591
thurinm@mail.nih.gov

This funding opportunity encourages the submission of applications to perform validation of the clinical usefulness of new molecular diagnostics that are becoming critical components for determining prognosis or predicting response to therapy for cancer. Advances in cancer biology and powerful technologies are providing increased opportunities for analyzing aberrations in genes, proteins, and molecular profiles and for developing more effective therapeutics and prognostic and predictive markers to inform their use for individual patients. However, prior to clinical laboratory implementation, the technical and analytical performance characteristics (stability, accuracy, and reproducibility) of the assay for the marker need to be established. Secondly, determining clinical utility of a molecular diagnostic--the evidence that the marker separates two subgroups of patients with different outcomes within a large population--requires correlation of laboratory test results with clinical parameters. Therefore, access to clinically-annotated specimens collected from multi-institutional, well-controlled clinical studies is absolutely essential for assessing the clinical usefulness of the test. The ultimate goal of this FOA is to evaluate the clinical utility of analytically validated molecular diagnostic tests to improve clinical decision-making in the care of cancer patients.

Developmental Research in Cancer Prognosis and Prediction (R21/R33)

Program Announcements:

PA-09-158 (R21)
Expiration Date: May 8, 2012

PA-09-159 (R33)
Expiration Date: May 8, 2012

Contacts:
Tracy Lively, Ph.D.
301-435-9007
livelyt@mail.nih.gov

Magdalena Thurin, Ph.D.
301-496-1591
thurinm@mail.nih.gov

An increasing number of publications have described new molecules, new patterns of gene expression, and new aspects of tumor-cell growth that seem to be correlated with known prognostic factors. However, studies that go beyond the exploratory stage of developing a new diagnostic test require large numbers of patient samples with associated clini­cal data. They also need an efficient assay technique and a great deal of statistical input. Such tools could improve clinical decision making in the care of cancer patients.

This CDP-sponsored program is accelerating the translation of new discoveries into clinical practice by allowing investigators to use new diagnostic strategies to solve clinical problems. By providing up to two years of support for a first-phase grant (R21) for technical development and a second-phase grant (R33) for up to an additional three years of support for application and evaluation in a clinical setting, CDP will enable investigators to evaluate the utility and pilot the application of new strategies for determining prognosis or predicting response to therapy.

Validation of Molecular Diagnostics to Predict Patient Outcomes Using Specimens from Multi-Site Cancer Trials (R01/R21)

Program Announcements:

PA-12-013 (R01)
Expiration Date: January 8, 2015

PA-12-014 (R21)
Expiration Date: January 8, 2015

Contact:
Magdalena Thurin, Ph.D.
301-496-1591
thurinm@mail.nih.gov

Minkyung (Min) H. Song, Ph.D.
301-496-8866
songm@mail.nih.gov

In recent years, NCI has sponsored more than 1,500 clinical trials, including cancer treatment and prevention trials. More than 200,000 cancer patients have participated in these trials. Many of these trials have accumulated a large number of tumor specimens with well-annotated demographic and clinical information including diagnosis, treatment, and follow-up data. These tumor specimens provide valuable resource to study molecular diagnostic, prognostic and predictive biomarkers. The objective of this Program Announcements (PAs) is to promote validation studies for molecular diagnostics to prove their clinical usefulness to improve cancer patients’ outcome.

The R01 mechanism is expected to engage investigators into fully developed validation research projects including training and independent validation set analyses resulting in clinically valid diagnostics with a potential for clinical application. Well-annotated tumor and other biospecimen cohorts collected retrospectively during multi-institutional treatment trials are especially suitable for these studies. R21s are considered pilot projects and should be designed to determine whether an assay is analytically valid and/or its results are associated with a clinical endpoint using retrospective tissue collections.

Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01/R21)

Program Announcements:

PA-10-025 (R01)
Expiration Date: January 8, 2013

PA-10-026 (R21)
Expiration Date: January 8, 2013

Contact:
J. Milburn Jessup, M.D.
301-435-9010
jessupj@mail.nih.gov

The purpose of these FOAs for R01 or R21 applications is to encourage clinicians, epidemiologists, geneticists, statisticians, and translational cancer control and prevention researchers to improve existing models for cancer risk, prognosis, or response to therapy by developing innovative research projects that use existing data to develop new models for cancer risk and prognosis and/or validate new models and evaluate their utility in research and clinic settings.

These funding announcements are designed to provide a mechanism under which investigators can address two major challenges in model development: integrating diverse types of data (clinical, demographic, pathologic, environmental, epidemiologic, outcomes, and genetic data from varied data marts or warehouses), and ensuring adequate validation (using multiple separate populations to define sensitivity, specificity, and positive and negative predictive values).