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Principal Investigator: FRANK S HODI
Organization: DANA-FARBER CANCER INST
Fiscal Year: 2024
Award: $1,838,130
Funding agency: National Cancer Institute
Summary
Because cancer immunotherapy constitutes one of the most transformative therapeutic movements over the
history of cancer treatment, there are now hundreds, if not thousands, of ongoing clinical trials in this field.
Despite the remarkable success for a subset of patients, there are substantial gaps in our knowledge. No more
than 30% of patients respond to immune checkpoint blockade and related therapies, many responding patients
develop therapeutic resistance, and many responding and non-responding patients suffer from immune-related
toxicities. There is a clear need to identify critical biomarkers of response, resistance, and toxicity. To improve
our ability to meet this challenge, the NCI-sponsored Cancer Immune Monitoring and Analysis Center (CIMAC)
program was created to enable consistent and comparable interrogation of patient biospecimens across multiple
clinical trials. The program has successfully established a common set of assays harmonized across the four
CIMACs, augmented this basic set with more specialized tests that may be CIMAC-specific but are still
accessible across institutions, deployed these tools across dozens of phase I/II immunotherapy trials, and
generated a pool of standardized data to facilitate inter-trial comparisons. The CIMAC created at Dana-Farber
Cancer Institute (DFCI) built on the existing Center of Immuno-Oncology (CIO) and the long-standing
collaboration with the Broad Institute of MIT and Harvard. The DFCI/Broad CIMAC, joining with the other
CIMACS, now proposes to continue the network mission to compare tumor and immune response features of
individual cancer types treated by multiple immunotherapeutic modalities and multiple cancer types treated by a
single immunotherapeutic modality in order to dissect common and individualized mechanisms of action. One
driving motivation for this renewal application is that the power to identify biomarkers increases with the number
of clinical trials analyzed. Thus, Aim 1 focuses on deploying the suite of assays established over the past five
years to biospecimens collected from additional innovative immunotherapy clinical trials to standardize biomarker
analysis and interpretation. To broaden the scope of parameters being examined, Aim 2 proposes to develop
and verify performance for novel and more complex assays to expand the network capabilities and advance
discovery. Of particular value will be methods that improve multiomic single cell profiling, multiomic spatial
analysis, and immunopeptidome characterization. Aim 3 addresses the challenge of integrating multiomic data
across an increasing number of clinical trials by building novel computational tools that can efficiently process
massive amounts of data and generate interpretable representations of the results. Altogether, these efforts will
support the role of immuno-oncology in the personalized treatment of cancer because only by the analyses of
large well-annotated datasets can we identify links between biology, molecular markers and clinical response.
Terms: <Acceleration><Address><Adoptive Cell Transfers><Allogenic><Antigenic Determinants><Antigens><Assay><Automobile Driving><Binding Determinants><Bioassay><Biological><Biological Assay><Biological Markers><Biology><Blood><Blood Reticuloendothelial System><Blood Sample><Blood specimen><Body Tissues><CAR T cells><CAR modified T cells><CAR-T><CAR-Ts><CTEP><Cancer Therapy Evaluation Program><Cancer Treatment><Cancers><Cell Body><Cells><Clinical><Clinical Trials><Clone Cells><Collaborations><Communication><Complex><Computational toolkit><Coupled><DF/HCC><Dana-Farber Cancer Institute><Data><Data Analyses><Data Analysis><Data Set><Detection><Development><Epitopes><Evaluation><Fostering><Genomics><Germ Lines><Goals><History><Immune><Immune Monitoring><Immune mediated therapy><Immune response><Immunes><Immunologic Monitoring><Immunological Monitoring><Immunological response><Immunologically Directed Therapy><Immunomonitoring><Immunooncology><Immunotherapeutic agent><Immunotherapy><Individual><Institution><Knowledge><Laboratories><Learning><Life><Link><MHC Receptor><Machine Learning><Major Histocompatibility Complex Receptor><Malignant Cell><Malignant Neoplasm Therapy><Malignant Neoplasm Treatment><Malignant Neoplasms><Malignant Tumor><Methods><Mission><Modality><Monitor><Motivation><Movement><Multiomic Data><NIH><National Institutes of Health><Oncolytic viruses><Patients><Performance><Peripheral><Phase><Phenotype><Population><Principal Investigator><Process><Progenitor Cell Transplantation><Protocol><Protocols documentation><Radiation therapy><Radiotherapeutics><Radiotherapy><Recording of previous events><Research><Research Resources><Research Specimen><Resistance><Resources><Role><Series><Site><Specimen><Staining method><Stains><Standardization><Stem Cell Transplantation><Stem cell transplant><T Cell Specificity><T cells for CAR><T-Cell Antigen Receptors><T-Cell Immunologic Specificity><T-Cell Receptor><T-Cells><T-Lymphocyte><T-cell receptor repertoire><TCR repertoire><Testing><Therapeutic><Tissue Sample><Tissues><Toxic effect><Toxicities><United States National Institutes of Health><VAC-TX><Vaccine Therapy><Validation><Variant><Variation><Work><Writing><adoptive cell therapy><adoptive cellular therapy><anti-cancer immunotherapy><anti-cancer therapy><anticancer immunotherapy><bio-informatics tool><bio-markers><bioinformatics tool><biologic><biologic marker><biomarker><biomarker identification><body movement><cancer cell><cancer immunotherapy><cancer microenvironment><cancer therapy><cancer type><cancer-directed therapy><check point blockade><checkpoint blockade><chimeric antigen T cell receptor><chimeric antigen receptor (CAR) T cells><chimeric antigen receptor T cells><chimeric antigen receptor fusion protein T-cells><chimeric antigen receptor modified T cells><computational toolbox><computational tools><computational toolset><computerized data processing><computerized tools><data integration><data interpretation><data processing><data standardization><data standards><design><designing><developmental><driving><flexibility><flexible><high dimensionality><histories><host response><identification of biomarkers><identification of new biomarkers><image-based method><imaging method><imaging modality><immune check point blockade><immune checkpoint blockade><immune drugs><immune microenvironment><immune system response><immune therapeutic approach><immune therapeutic interventions><immune therapeutic regimens><immune therapeutic strategy><immune therapy><immune-based cancer therapies><immune-based therapeutics><immune-based therapies><immune-based treatments><immune-oncology><immuno oncology><immuno therapy><immunogen><immunologic therapeutics><immunology oncology><immunoresponse><immunosuppressive microenvironment><immunosuppressive tumor microenvironment><immunotherapeutics><immunotherapy agent><immunotherapy clinical trials><immunotherapy for cancer><immunotherapy of 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therapy><response><response biomarker><response markers><response to therapy><response to treatment><single cell analysis><social role><standard of care><stem and progenitor cell transplantations><success><therapeutic resistance><therapeutic response><therapeutic vaccination><therapy resistant><therapy response><thymus derived lymphocyte><tool><tool development><transcriptomics><treatment resistance><treatment response><treatment responsiveness><treatment with radiation><tumor><tumor immune microenvironment><tumor microenvironment><tumor-immune system interactions><validations><wasting>