Chimeric antigen receptors (CARs) link an antigen recognition domain to intracellular signaling domains to redirect T cell specificity and function. T cells expressing CARs with CD28/CD3ζ or 4-1BB/CD3ζ signaling domains are effective at treating refractory B cell malignancies but exhibit differences in effector function, clinical efficacy, and toxicity that are assumed to result from the activation of divergent signaling cascades. We analyzed stimulation-induced phosphorylation events in primary human CD8 CD28/CD3ζ and 4-1BB/CD3ζ CAR T cells by mass spectrometry and found that both CAR constructs activated similar signaling intermediates. Stimulation of CD28/CD3ζ CARs activated faster and larger-magnitude changes in protein phosphorylation, which correlated with an effector T cell-like phenotype and function. In contrast, 4-1BB/CD3ζ CAR T cells preferentially expressed T cell memory-associated genes and exhibited sustained antitumor activity against established tumors in vivo. Mutagenesis of the CAR CD28 signaling domain demonstrated that the increased CD28/CD3ζ CAR signal intensity was partly related to constitutive association of Lck with this domain in CAR complexes. Our data show that CAR signaling pathways cannot be predicted solely by the domains used to construct the receptor and that signal strength is a key determinant of T cell fate. Thus, tailoring CAR design based on signal strength may lead to improved clinical efficacy and reduced toxicity.

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.