Greg obtained his PhD from the University of California, Los Angeles in the laboratory of Drs. Pedro Lowenstein and Maria Castro where he studied mechanisms of glioblastoma (GBM) brain tumor invasion and immune evasion. Prior to this, he received his doctorate in pharmacy (PharmD) from the University of Rhode Island. Greg is now an American Cancer Society Postdoctoral Fellow and Trainee of the Ludwig Center at Harvard Medical School working in the laboratory of Dr. Peter Sorger. His work aims to synthesize an integrated and time-resolved comprehension of GBM’s influence over the cells, cytokines, and network-level architectures of the systemic immune system to ultimately determine whether, and how, immunotherapy can be leveraged against the disease.

Since becoming an affliate of the Laboratory of Systems Pharmacology (LSP) in the Fall of 2015, Greg has employed mouse models in the development of an extensible in vivo screening platform designed to holistically determine how GBM affects host cellular immune organization. Using a 12-color optimized multicolor immunofluorescence panel (OMIP), Greg is able to immunophenotype major mouse leukocyte lineages throughout multiple lymphoid tissues. This approached has allowed him to contextualize and temporally resolve known aspects of GBM immuno-oncology while identifiying novel network-level signatures of tumor-induced immune suppression. His flow-based immunoprofiling strategy has already provided novel insight into how these tumors influence global leukocyte composition; however, an expected transition to cytometry by time-of-flight (CyTOF) as an alternative single-cell analysis technique should dramatically enhance immunoprofiling resolution, allowing Greg to concomitantly measure over 50 cell surface markers and intracellular proteins of interest.

Greg is now applying his screening platform to better understand how immunotherapy targeting the PD-1/PD-L1 immune checkpoint axis acts to alleviate tumor-induced immunosuppression in GBM and other solid cancers. Here the platform is being exploited to achieve three goals: (1) identify immune signatures that correlate with response or resistance to therapy, (2) infer mechanisms of drug action, and (3) identify immune cell subsets of novel prognostic value.

He next aims to collect both cytokine and mRNA transcript data across multiple immune cell subsets over the course of tumor progression. This information—together with previously collected data on system-wide leukocyte composition—will be used to assemble data-driven, network-level influence diagrams. These diagrams will help guide downstream hypotheses and permit cellular dynamics inferencing. Also on the horizon is the incorporation of genetically-induced tumor models; the study of these systems will allow Greg to interrogate the immunosuppressive influence of clinically-relevant GBM oncogenes.