Harnessing the human myeloid system to improve surgical recovery

The National Institute of General Medical Sciences awarded The Leland Stanford Junior University $431,200 for a Project Grant (R35GM161298) on March 15, 2026, to develop predictive biomarkers and therapeutic targets for improved surgical recovery by analyzing immune mechanisms in patients undergoing surgery.

The research harnesses high-dimensional immune monitoring technologies to characterize the human myeloid system—including monocytes, macrophages, neutrophils, and their subsets—at both local and peripheral sites. The work builds on prior findings linking peripheral myeloid system dysfunction to surgical site infections following gastrointestinal surgery. The funded activities include investigating the contribution of local myeloid immune responses to the pathophysiology of surgical site infections and determining the relationship between the local immune microenvironment and peripheral immune responses to surgery. Prior work by the research team developed single-cell mass cytometry assays for functional and epigenetic monitoring of immune response to surgery and pharmacological interventions, characterized a myeloid cellular program predicting surgical site infections, and built machine learning frameworks for predictive biomarker modeling.

The award funds work performed at Stanford University in Palo Alto, California, with a period of performance extending from March 15, 2026, through February 28, 2031. The funding program, Biomedical Research and Research Training (CFDA 93.859), supports basic research that advances understanding of biological processes and foundations for disease diagnosis, treatment, and prevention.

Abstract

Harnessing the human myeloid system to improve surgical recovery annually, 30 million patients undergo major surgery in the US, with 20-30% experiencing delayed surgical recovery. However, existing tools for predicting surgical recovery perform poorly. An effective immune response to surgical trauma is necessary for most biological processes driving surgical recovery, including infection control, functional recovery, and pain resolution. As such, in-depth analysis of local (i.e., at the surgical site) and peripheral immune mechanisms in patients undergoing surgery is an essential step for identifying accurate predictive biomarkers of surgical recovery and novel therapeutic targets. The human myeloid system (HMS), including monocytes, macrophages, neutrophils, and their subsets, plays a pivotal role in initiating and coordinating the immune response to surgical trauma. Initially focused on the peripheral HMS, our research uses high-dimensional immune monitoring technologies to identify modifiable mechanisms that predict a patient's recovery. Over the past five years, we have: 1) developed single-cell mass cytometry assays for the functional and epigenetic monitoring of patients' immune response to surgery and of pharmacological interventions (NAT. Commun., 2020; ANN. Surg, 2023); 2) characterized an HMS cellular program predicting surgical site infections (ssis, ANN. Surg., 2022); 3) developed a machine learning framework for predictive modeling and selection of reliable biomarkers of surgical outcomes (NAT. Biotech., 2024). This mira program builds on our recent studies highlighting the role of the peripheral HMS in the pathogenesis of ssis after GI surgery. We will first investigate the contribution of the local HMS to the pathophysiology of ssis and determine the relationship between the local immune microenvironment and the peripheral HMS responses to surgery. Second, we will take an integrative approach to build and validate a predictive model of ssis combining the single-cell assessment of immune signaling and epigenetic states in patient blood and tissue samples collected before and during surgery. Third, we will implement a drug repurposing strategy to identify novel immune-modulatory properties of FDA-approved drugs that can be leveraged in clinical trials to prevent ssis. We will employ innovative, multidisciplinary approaches: 1) imaging mass cytometry for the 50-plex analysis of local HMS spatial and functional cellular organization in surgical tissue; 2) sparse machine learning methods for integrative analysis of mass cytometry, plasma proteomic and clinical data; 3) high-throughput mass tag barcoding immunoassay for selection of promising drug candidate targeting selective HMS responses. With a focus on the HMS and key clinical determinants of surgical recovery (infection), our mira research will identify reliable biomarkers and selective drug candidates for future testing in biomarker-guided clinical trials. Our work will also yield an extensive single-cell data repository, that can be shared with the scientific community and expanded to include other immunological dimensions (adaptive system), omic modalities (microbiome, metabolome, and transcriptome) and trauma-related outcomes (sepsis, organ damage, and cognitive decline).