Maximilian Sabayev

All Publications

• Immune Modulation by Personalized vs Standard Prehabilitation Before Major Surgery: A Randomized Clinical Trial. JAMA surgery Cambriel, A., Tsai, A., Choisy, B., Sabayev, M., Hedou, J., Shelton, E., Singh, K., Amar, J., Badea, V., Bruckman, S., Ganio, E., Einhaus, J., Feyaerts, D., Stelzer, I., Sato, M., Langeron, O., Bonham, T. A., Gaudillière, D., Shelton, A., Kin, C., Gaudillière, B., Verdonk, F. 2025

  Abstract

  Prehabilitation programs are increasingly recognized for their potential to improve surgical outcomes. However, their efficacy remains debated, largely due to a lack of pathophysiologically driven implementation and limited personalization.To determine the impact of personalized vs standard prehabilitation on preoperative physical, cognitive, and immune function and postoperative outcomes.In this prospective, single-blinded, randomized interventional trial conducted from June 2020 to September 2022 in a single academic medical center, 58 patients undergoing major elective surgery were randomized to standard (n = 30) or personalized prehabilitation (n = 28) using block randomization. Those with contraindication to exercise, an American Society of Anesthesiologists score 4 or higher, in palliative care, less than 14 days between screening and surgery were excluded. Data were analyzed from April 2023 to May 2025.The personalized group received 2 weekly one-on-one remote coaching sessions tailored to individual progress in 4 domains (physical activity, nutrition, cognitive training, and mindfulness), whereas the standard group followed a paper-based program, including the same domains, without individualized support.Primary clinical outcomes included cognitive assessments and physical performance measures, including the wall squat test, timed-up-and-go test, and 6-minute walk test (6MWT). The primary immunological outcomes included major innate and adaptive immune cell frequencies and intracellular signaling responses measured using a 47-plex mass cytometry immunoassay.Of 58 patients (median [IQR] age, 57 [45-67] years; 31 [57%] female) enrolled, 54 completed the study (n = 27 per group). The personalized group exhibited significant improvements in physical measures (eg, median [IQR] 6MWT: 496 [340-619] minutes before prehab versus 546 [350-728] minutes after; P = .03) and fewer moderate-to-severe postoperative complications (4 vs 11 Clavien-Dindo grade >1; P = .04). Multivariable modeling identified profound and cell-type specific immune alterations postprehabilitation compared to baseline (area under the receiver operating characteristic curve [AUROC], 0.88; 0.79-0.97; P < .001; leave-one-out cross-validation), including dampened phosphorylated protein kinase R-like endoplasmic reticulum kinase 1/2 signaling in classical monocytes and myeloid-derived suppressor cells after interleukin 2, 4, and 6 stimulation, and reduced phosphorylated cyclic adenosine monophosphate response-element binding protein signaling in Th1 cells. In contrast, the standard group showed only moderate clinical improvements and no immune changes (AUROC = 0.63; 95% CI, 0.48-0.78; P = .12).In this study, personalized prehabilitation significantly altered the immunome before surgery, dampening inflammatory signaling responses previously implicated in the pathophysiology of key surgical outcomes, including surgical site infections and postoperative neurocognitive decline. These changes were accompanied by improved physical and cognitive function before surgery and decreased postoperative complications. These findings support the use of personalized prehabilitation and provide an avenue for biologically driven monitoring of prehabilitation efficacy, and individual tailoring of programs to optimize surgical readiness and recovery.ClinicalTrials.gov Identifier: NCT04498208.

  View details for DOI 10.1001/jamasurg.2025.4917

  View details for PubMedID 41222945

• Single-cell-level digital twins for preterm birth prevention strategies. bioRxiv : the preprint server for biology Einhaus, J., Neidlinger, P., Fondeur, O., Sato, M., Anronikov, A., Miyazaki, K., Amar, J. N., Ando, K., Badea, V., Gaudilliere, D. K., Sabayev, M., Feyaerts, D., Diop, M., Tsai, A. S., Cambriel, A., Ganio, E. A., Lagarde, R., O'Kelly, E., Stelzer, I. A., Hedou, J., Wong, R. J., Blumenfeld, Y. J., Lyell, D. J., Shaw, G. M., Oskotsky, T. T., Sirota, M., Giudice, L., Stevenson, D. K., Aghaeepour, N., Gaudilliere, B. 2025

  Abstract

  Digital twin models can accelerate therapeutic development by enabling low-risk testing of candidate interventions. In preterm labor (PTL), a major pregnancy complication where clinical trials face unique ethical and financial barriers, digital twins are especially valuable for evaluating new therapies targeting immune dysfunctions driving PTL. Yet, current models lack single-cell resolution, limiting detection of cell-type-specific mechanisms, off-target effects, and the design of personalized interventions. We present Simulated Immunome Modeling of Clinical Outcomes (SIMCO), a single-cell-level digital twin framework that models immunomodulatory treatment effects on the timing of labor using immunome-wide, single-cell simulations. SIMCO's digital twins are trained and validated on a newly generated mass cytometry atlas of the pregnant immunome exposed to nine candidate drugs preselected for PTL prevention. Applying SIMCO to an independent cohort of pregnant individuals, we simulate treatment effects on gestational length, screening for candidate drugs that delay labor timing and providing system-level mechanistic insight for each drug candidate. Tetrahydrofolate, maprotiline, and the combination of aspirin and lansoprazole emerged as top candidates for PTL prevention, delaying labor onset primarily through enhanced mTOR signaling in innate immune cells and attenuated JAK/STAT signaling in naïve CD4+ T cells. The codebase is available at https://github.com/ofondeur/SIMCO/.

  View details for DOI 10.1101/2025.09.29.679252

  View details for PubMedID 41256687

  View details for PubMedCentralID PMC12621756

• Systemic Immune Dysregulation Induced by Preeclampsia Persists Years After Delivery Sabayev, M., Feyaerts, D., Edward, G. A., Ina, S., Sato, M., Cambriel, A., Bonham, T., Mihalic, Z. N., Diop, M., Iyer, P., Sedan, O., Aghaeepour, N., Angst, M., Shaw, G. M., Stevenson, D. K., Hlatky, M. A., Winn, V. D., Gaudilliere, B. SPRINGER HEIDELBERG. 2025: 98A-99A

  View details for Web of Science ID 001609923000151

• Infusion of young donor plasma components in older patients modifies the immune and inflammatory response to surgical tissue injury: a randomized clinical trial. Journal of translational medicine Gaudilliere, B., Xue, L., Tsai, A. S., Gao, X., McAllister, T. N., Tingle, M., Porras, G., Feinstein, I., Feyaerts, D., Verdonk, F., Sabayev, M., Hedou, J., Ganio, E. A., Berson, E., Becker, M., Espinosa, C., Kim, Y., Lehallier, B., Rawner, E., Feng, C., Amanatullah, D. F., Huddleston, J. I., Goodman, S. B., Aghaeepour, N., Angst, M. S. 2025; 23 (1): 183

  Abstract

  Preclinical evidence suggests that young plasma has beneficial effects on multiple organ systems in aged mice. Whether young plasma exerts beneficial effects in an aging human population remains highly controversial. Despite lacking data, young donor plasma infusions have been promoted for age-related conditions. Given the preclinical evidence that young plasma exerts beneficial effects by attenuating inflammation, this study examined whether administering a young plasma protein fraction to an elderly population would exert anti-inflammatory and immune modulating effects in humans, using surgery as a tissue injury model.This double-blind, placebo-controlled study enrolled and randomized 38 patients undergoing major joint replacement surgery. Patients received four separate infusions of a plasma protein fraction derived from young donors, or placebo one day before surgery, before and after surgery on the day of surgery, and one day after surgery. Blood specimens for proteomic and immunological analyses were collected before each infusion. Based on the high-content assessment of circulating plasma proteins with single-cell analyses of peripheral immune cells, proteomic signatures and cell-type-specific signaling responses that separated the treatment groups were derived with regression models.Elastic net regression models revealed that administration a young plasma protein fraction significantly altered the proteomic (AUC = 0.796, p = 0.002) and the cellular immune response (AUC 0.904, p < 0.001) to surgical trauma resulting in signaling pathway- and cell type-specific anti-inflammatory immune modulation. Affected proteomic pathways regulating inflammation included JAK-STAT, NF-kappa B, and MAPK (p < 0.001). These findings were confirmed at the cellular level as the MAPK and JAK/STAT signaling responses were diminished and IkB, the negative regulator of NFkB, was elevated in adaptive immune cells.Reported findings provide a first proof of principle in humans that a young plasma protein fraction actively regulates inflammatory and immune responses in an elderly population. They provide a solid rationale for elucidating active principles in young plasma that may be of therapeutic benefits for a range of age-related pathologies.ClinicalTrials.gov, NCT03981419.

  View details for DOI 10.1186/s12967-025-06215-w

  View details for PubMedID 39953524

  View details for PubMedCentralID 6764071

• An immune signature of postoperative cognitive decline: A prospective cohort study. International journal of surgery (London, England) Verdonk, F., Cambriel, A., Hedou, J., Ganio, E., Bellan, G., Gaudilliere, D., Einhaus, J., Sabayev, M., Stelzer, I. A., Feyaerts, D., Bonham, A. T., Ando, K., Choisy, B., Drover, D., Heifets, B., Chretien, F., Aghaeepour, N., Angst, M. S., Molliex, S., Sharshar, T., Gaillard, R., Gaudilliere, B. 2024

  Abstract

  Postoperative cognitive decline (POCD) is the predominant complication affecting patients over 60 years old following major surgery, yet its prediction and prevention remain challenging. Understanding the biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This study aimed to provide a comprehensive analysis of immune cell trajectories differentiating patients with and without POCD and to derive a predictive score enabling the identification of high-risk patients during the preoperative period.Twenty-six patients aged 60 years old and older undergoing elective major orthopedic surgery were enrolled in a prospective longitudinal study, and the occurrence of POCD was assessed seven days after surgery. Serial samples collected before surgery, and one, seven, and 90 days after surgery were analyzed using a combined single-cell mass cytometry and plasma proteomic approach. Unsupervised clustering of the high-dimensional mass cytometry data was employed to characterize time-dependent trajectories of all major innate and adaptive immune cell frequencies and signaling responses. Sparse machine learning coupled with data-driven feature selection was applied to the pre-surgery immunological dataset to classify patients at risk for POCD.The analysis identified cell-type and signaling-specific immune trajectories differentiating patients with and without POCD. The most prominent trajectory features revealed early exacerbation of JAK/STAT and dampening of inhibitory κB and nuclear factor-κB immune signaling responses in patients with POCD. Further analyses integrating immunological and clinical data collected before surgery identified a preoperative predictive model comprising one plasma protein and ten immune cell features that classified patients at risk for POCD with excellent accuracy (AUC=0.80, P=2.21e-02 U-test).Immune system-wide monitoring of patients over 60 years old undergoing surgery unveiled a peripheral immune signature of POCD. A predictive model built on immunological data collected before surgery demonstrated greater accuracy in predicting POCD compared to known clinical preoperative risk factors, offering a concise list of biomarker candidates to personalize perioperative management.

  View details for DOI 10.1097/JS9.0000000000002118

  View details for PubMedID 39411891

• Discovery of sparse, reliable omic biomarkers with Stabl. Nature biotechnology Hédou, J., Marić, I., Bellan, G., Einhaus, J., Gaudillière, D. K., Ladant, F. X., Verdonk, F., Stelzer, I. A., Feyaerts, D., Tsai, A. S., Ganio, E. A., Sabayev, M., Gillard, J., Amar, J., Cambriel, A., Oskotsky, T. T., Roldan, A., Golob, J. L., Sirota, M., Bonham, T. A., Sato, M., Diop, M., Durand, X., Angst, M. S., Stevenson, D. K., Aghaeepour, N., Montanari, A., Gaudillière, B. 2024

  Abstract

  Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .

  View details for DOI 10.1038/s41587-023-02033-x

  View details for PubMedID 38168992

  View details for PubMedCentralID 7003173

• Spatial subsetting enables integrative modeling of oral squamous cell carcinoma multiplex imaging data. iScience Einhaus, J., Gaudilliere, D. K., Hedou, J., Feyaerts, D., Ozawa, M. G., Sato, M., Ganio, E. A., Tsai, A. S., Stelzer, I. A., Bruckman, K. C., Amar, J. N., Sabayev, M., Bonham, T. A., Gillard, J., Diop, M., Cambriel, A., Mihalic, Z. N., Valdez, T., Liu, S. Y., Feirrera, L., Lam, D. K., Sunwoo, J. B., Schürch, C. M., Gaudilliere, B., Han, X. 2023; 26 (12): 108486

  Abstract

  Oral squamous cell carcinoma (OSCC), a prevalent and aggressive neoplasm, poses a significant challenge due to poor prognosis and limited prognostic biomarkers. Leveraging highly multiplexed imaging mass cytometry, we investigated the tumor immune microenvironment (TIME) in OSCC biopsies, characterizing immune cell distribution and signaling activity at the tumor-invasive front. Our spatial subsetting approach standardized cellular populations by tissue zone, improving feature reproducibility and revealing TIME patterns accompanying loss-of-differentiation. Employing a machine-learning pipeline combining reliable feature selection with multivariable modeling, we achieved accurate histological grade classification (AUC = 0.88). Three model features correlated with clinical outcomes in an independent cohort: granulocyte MAPKAPK2 signaling at the tumor front, stromal CD4+ memory T cell size, and the distance of fibroblasts from the tumor border. This study establishes a robust modeling framework for distilling complex imaging data, uncovering sentinel characteristics of the OSCC TIME to facilitate prognostic biomarkers discovery for recurrence risk stratification and immunomodulatory therapy development.

  View details for DOI 10.1016/j.isci.2023.108486

  View details for PubMedID 38125025

  View details for PubMedCentralID PMC10730356