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 b...