Mark M. Davis, PhD Publications

Director, Stanford Institute for Immunity, Transplantation and Infection and the Burt and Marion Avery Family Professor


  • Adoptively Transferred, In Vitro-Generated Alloantigen-Specific Type 1 Regulatory T (Tr1) Cells Persist Long-Term In Vivo Cepika, A., Chen, P. P., Agarwal, R., Saini, G., Louis, D. M., Amaya-Hernandez, L. C., Xu, L., Shiraz, P., Tate, K. M., Margittai, D., Bhatia, N., Meyer, E., Bertaina, A., Davis, M. M., Bacchetta, R., Roncarolo, M. CELL PRESS. 2021: 73
  • CRIPSR/Cas9 Technology: Hypoimmunogenic Pluripotent Stem Cells Evade Immune Rejection in Fully Immunocompetent Allogeneic Recipients Hu, X., Deuse, T., Gravina, A., Wang, D., Tediashvili, G., Reichenspurner, H., Davis, M. M., Lanier, L. L., Schrepfer, S. ELSEVIER SCIENCE INC. 2021: S28–S29
  • Learning from HIV-1 to predict the immunogenicity of T cell epitopes in SARS-COV-2. iScience Gao, A., Chen, Z., Amitai, A., Doelger, J., Mallajosyula, V., Sundquist, E., Segal, F. P., Carrington, M., Davis, M. M., Streeck, H., Chakraborty, A. K., Julg, B. 2021: 102311


    We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic-T-Lymphocyte (CTL) epitopes derived from diverse pathogens including SARS-CoV-2. The model was trained and optimized on the relative immunodominance of CTL epitopes in Human Immunodeficiency Virus infection. Its accuracy was tested against experimental data from COVID-19 patients. Our model predicts that only some SARS-CoV-2 epitopes predicted to bind to HLA molecules are immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but those from the SARS-CoV-2 spike protein alone are unlikely to do so. Our model also predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to seasonal coronaviruses circulating in the population and such cross-reactive CD8+ T cells can indeed be detected in prepandemic blood donors, suggesting that some level of CTL immunity against COVID-19 may be present in some individuals prior to SARS-CoV-2 infection.

    View details for DOI 10.1016/j.isci.2021.102311

    View details for PubMedID 33748696

  • Aging and CMV discordance are associated with increased immune diversity between monozygotic twins. Immunity & ageing : I & A Yan, Z., Maecker, H. T., Brodin, P., Nygaard, U. C., Lyu, S. C., Davis, M. M., Nadeau, K. C., Andorf, S. 2021; 18 (1): 5


    BACKGROUND: Broadly, much of variance in immune system phenotype has been linked to the influence of non-heritable factors rather than genetics. In particular, two non-heritable factors: aging and human cytolomegavirus (CMV) infection, have been known to account for significant inter-individual immune variance. However, many specific relationships between them and immune composition remain unclear, especially between individuals over narrower age ranges. Further exploration of these relationships may be useful for informing personalized intervention development.RESULTS: To address this need, we evaluated 41 different cell type frequencies by mass cytometry and identified their relationships with aging and CMV seropositivity. Analyses were done using 60 healthy individuals, including 23 monozygotic twin pairs, categorized into young (12-31years) and middle-aged (42-59years). Aging and CMV discordance were associated with increased immune diversity between monozygotic twins overall, and particularly strongly in various T cell populations. Notably, we identified 17 and 11 cell subset frequencies as relatively influenced and uninfluenced by non-heritable factors, respectively, with results that largely matched those from studies on older-aged cohorts. Next, CD4+ T cell frequency was shown to diverge with age in twins, but with lower slope than in demographically similar non-twins, suggesting that much inter-individual variance in this cell type can be attributed to interactions between genetic and environmental factors. Several cell frequencies previously associated with memory inflation, such as CD27- CD8+ T cells and CD161+ CD4+ T cells, were positively correlated with CMV seropositivity, supporting findings that CMV infection may incur rapid aging of the immune system.CONCLUSIONS: Our study confirms previous findings that aging, even within a relatively small age range and by mid-adulthood, and CMV seropositivity, both contribute significantly to inter-individual immune diversity. Notably, we identify several key immune cell subsets that vary considerably with aging, as well as others associated with memory inflation which correlate with CMV seropositivity.

    View details for DOI 10.1186/s12979-021-00216-1

    View details for PubMedID 33461563

  • SIMON: Open-Source Knowledge Discovery Platform. Patterns (New York, N.Y.) Tomic, A., Tomic, I., Waldron, L., Geistlinger, L., Kuhn, M., Spreng, R. L., Dahora, L. C., Seaton, K. E., Tomaras, G., Hill, J., Duggal, N. A., Pollock, R. D., Lazarus, N. R., Harridge, S. D., Lord, J. M., Khatri, P., Pollard, A. J., Davis, M. M. 2021; 2 (1): 100178


    Data analysis and knowledge discovery has become more and more important in biology and medicine with the increasing complexity of biological datasets, but the necessarily sophisticated programming skills and in-depth understanding of algorithms needed pose barriers to most biologists and clinicians to perform such research. We have developed a modular open-source software, SIMON, to facilitate the application of 180+ state-of-the-art machine-learning algorithms to high-dimensional biomedical data. With an easy-to-use graphical user interface, standardized pipelines, and automated approach for machine learning and other statistical analysis methods, SIMON helps to identify optimal algorithms and provides a resource that empowers non-technical and technical researchers to identify crucial patterns in biomedical data.

    View details for DOI 10.1016/j.patter.2020.100178

    View details for PubMedID 33511368

  • Antigen-specific T Cell Activation Distinguishes Between Recent and Remote Tuberculosis Infection. American journal of respiratory and critical care medicine Mpande, C. A., Musvosvi, M., Rozot, V., Mosito, B., Reid, T. D., Schreuder, C., Lloyd, T., Bilek, N., Huang, H., Obermoser, G., Davis, M. M., Ruhwald, M., Hatherill, M., Scriba, T. J., Nemes, E., ACS Study Team 2021


    RATIONALE: Current diagnostic tests fail to identify individuals at higher risk of progression to tuberculosis disease, such as those with recent Mycobacterium tuberculosis infection, who should be prioritized for targeted preventive treatment.OBJECTIVES: To define a blood-based biomarker, measured with a simple flow cytometry assay, that can stratify different stages of tuberculosis infection to infer risk of disease.METHODS: South African adolescents were serially tested with QuantiFERON-TB Gold to define recent (QuantiFERON-TB conversion <6 months) and persistent (QuantiFERON-TB+ for >1 year) infection. We defined the DeltaHLA-DR median fluorescence intensity biomarker as the difference in HLA-DR expression between IFN-gamma+TNF+ Mycobacterium tuberculosis-specific and total CD3+ T cells. Biomarker performance was assessed by blinded prediction in untouched test cohorts with recent versus persistent infection or tuberculosis disease, and unblinded analysis of asymptomatic adolescents with tuberculosis infection who remained healthy (non-progressors) or who progressed to microbiologically-confirmed disease (progressors).MEASUREMENTS AND MAIN RESULTS: In the test cohorts, frequencies of Mycobacterium tuberculosis-specific T cells differentiated between QuantiFERON-TB- (n=25) and QuantiFERON-TB+ (n=47) individuals (area under the ROC curve and 95% confidence intervals: 0.94; 0.87-1.00). DeltaHLA-DR significantly discriminated between recent (n=20) and persistent (n=22) QuantiFERON-TB+ (0.91; 0.83-1.00); persistent QuantiFERON-TB+ and newly diagnosed tuberculosis (n=19, 0.99; 0.96-1.00); and tuberculosis progressors (n=22) and non-progressors (n=34, 0.75; 0.63-0.87). However, DeltaHLA-DR MFI could not discriminate between recent QuantiFERON-TB+ and tuberculosis (0.67; 0.50-0.84).CONCLUSION: The DeltaHLA-DR biomarker can identify individuals with recent QuantiFERON-TB conversion and those with disease progression, allowing targeted provision of preventive treatment to those at highest risk of tuberculosis. Further validation studies of this novel immune biomarker in various settings and populations at risk are warranted.

    View details for DOI 10.1164/rccm.202007-2686OC

    View details for PubMedID 33406011

  • Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery. Immunity Chiou, S. H., Tseng, D. n., Reuben, A. n., Mallajosyula, V. n., Molina, I. S., Conley, S. n., Wilhelmy, J. n., McSween, A. M., Yang, X. n., Nishimiya, D. n., Sinha, R. n., Nabet, B. Y., Wang, C. n., Shrager, J. B., Berry, M. F., Backhus, L. n., Lui, N. S., Wakelee, H. A., Neal, J. W., Padda, S. K., Berry, G. J., Delaidelli, A. n., Sorensen, P. H., Sotillo, E. n., Tran, P. n., Benson, J. A., Richards, R. n., Labanieh, L. n., Klysz, D. D., Louis, D. M., Feldman, S. A., Diehn, M. n., Weissman, I. L., Zhang, J. n., Wistuba, I. I., Futreal, P. A., Heymach, J. V., Garcia, K. C., Mackall, C. L., Davis, M. M. 2021; 54 (3): 586–602.e8


    To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRβ chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A∗02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli. Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

    View details for DOI 10.1016/j.immuni.2021.02.014

    View details for PubMedID 33691136

  • Signatures of immune dysfunction in HIV and HCV infection share features with chronic inflammation in aging and persist after viral reduction or elimination. Proceedings of the National Academy of Sciences of the United States of America Lopez Angel, C. J., Pham, E. A., Du, H. n., Vallania, F. n., Fram, B. J., Perez, K. n., Nguyen, T. n., Rosenberg-Hasson, Y. n., Ahmed, A. n., Dekker, C. L., Grant, P. M., Khatri, P. n., Maecker, H. T., Glenn, J. S., Davis, M. M., Furman, D. n. 2021; 118 (14)


    Chronic inflammation is thought to be a major cause of morbidity and mortality in aging, but whether similar mechanisms underlie dysfunction in infection-associated chronic inflammation is unclear. Here, we profiled the immune proteome, and cellular composition and signaling states in a cohort of aging individuals versus a set of HIV patients on long-term antiretroviral therapy therapy or hepatitis C virus (HCV) patients before and after sofosbuvir treatment. We found shared alterations in aging-associated and infection-associated chronic inflammation including T cell memory inflation, up-regulation of intracellular signaling pathways of inflammation, and diminished sensitivity to cytokines in lymphocytes and myeloid cells. In the HIV cohort, these dysregulations were evident despite viral suppression for over 10 y. Viral clearance in the HCV cohort partially restored cellular sensitivity to interferon-α, but many immune system alterations persisted for at least 1 y posttreatment. Our findings indicate that in the HIV and HCV cohorts, a broad remodeling and degradation of the immune system can persist for a year or more, even after the removal or drastic reduction of the pathogen load and that this shares some features of chronic inflammation in aging.

    View details for DOI 10.1073/pnas.2022928118

    View details for PubMedID 33811141

  • Modeling human adaptive immune responses with tonsil organoids. Nature medicine Wagar, L. E., Salahudeen, A. n., Constantz, C. M., Wendel, B. S., Lyons, M. M., Mallajosyula, V. n., Jatt, L. P., Adamska, J. Z., Blum, L. K., Gupta, N. n., Jackson, K. J., Yang, F. n., Röltgen, K. n., Roskin, K. M., Blaine, K. M., Meister, K. D., Ahmad, I. N., Cortese, M. n., Dora, E. G., Tucker, S. N., Sperling, A. I., Jain, A. n., Davies, D. H., Felgner, P. L., Hammer, G. B., Kim, P. S., Robinson, W. H., Boyd, S. D., Kuo, C. J., Davis, M. M. 2021


    Most of what we know about adaptive immunity has come from inbred mouse studies, using methods that are often difficult or impossible to confirm in humans. In addition, vaccine responses in mice are often poorly predictive of responses to those same vaccines in humans. Here we use human tonsils, readily available lymphoid organs, to develop a functional organotypic system that recapitulates key germinal center features in vitro, including the production of antigen-specific antibodies, somatic hypermutation and affinity maturation, plasmablast differentiation and class-switch recombination. We use this system to define the essential cellular components necessary to produce an influenza vaccine response. We also show that it can be used to evaluate humoral immune responses to two priming antigens, rabies vaccine and an adenovirus-based severe acute respiratory syndrome coronavirus 2 vaccine, and to assess the effects of different adjuvants. This system should prove useful for studying critical mechanisms underlying adaptive immunity in much greater depth than previously possible and to rapidly test vaccine candidates and adjuvants in an entirely human system.

    View details for DOI 10.1038/s41591-020-01145-0

    View details for PubMedID 33432170

  • Mass Cytometry Defines Virus-Specific CD4+ T Cells in Influenza Vaccination. ImmunoHorizons Subrahmanyam, P. B., Holmes, T. H., Lin, D., Su, L. F., Obermoser, G., Banchereau, J., Pascual, V., Garcia-Sastre, A., Albrecht, R. A., Palucka, K., Davis, M. M., Maecker, H. T. 2020; 4 (12): 774–88


    The antiviral response to influenza virus is complex and multifaceted, involving many immune cell subsets. There is an urgent need to understand the role of CD4+ T cells, which orchestrate an effective antiviral response, to improve vaccine design strategies. In this study, we analyzed PBMCs from human participants immunized with influenza vaccine, using high-dimensional single-cell proteomic immune profiling by mass cytometry. Data were analyzed using a novel clustering algorithm, denoised ragged pruning, to define possible influenza virus-specific clusters of CD4+ T cells. Denoised ragged pruning identified six clusters of cells. Among these, one cluster (Cluster 3) was found to increase in abundance following stimulation with influenza virus peptide ex vivo. A separate cluster (Cluster 4) was found to expand in abundance between days 0 and 7 postvaccination, indicating that it is vaccine responsive. We examined the expression profiles of all six clusters to characterize their lineage, functionality, and possible role in the response to influenza vaccine. Clusters 3 and 4 consisted of effector memory cells, with high CD154 expression. Cluster 3 expressed cytokines like IL-2, IFN-gamma, and TNF-alpha, whereas Cluster 4 expressed IL-17. Interestingly, some participants had low abundance of Clusters 3 and 4, whereas others had higher abundance of one of these clusters compared with the other. Taken together, we present an approach for identifying novel influenza virus-reactive CD4+ T cell subsets, a method that could help advance understanding of the immune response to influenza, predict responsiveness to vaccines, and aid in better vaccine design.

    View details for DOI 10.4049/immunohorizons.1900097

    View details for PubMedID 33310880

  • Progenitor identification and SARS-CoV-2 infection in human distal lung organoids. Nature Salahudeen, A. A., Choi, S. S., Rustagi, A., Zhu, J., van Unen, V., de la O, S. M., Flynn, R. A., Margalef-Catala, M., Santos, A. J., Ju, J., Batish, A., Usui, T., Zheng, G. X., Edwards, C. E., Wagar, L. E., Luca, V., Anchang, B., Nagendran, M., Nguyen, K., Hart, D. J., Terry, J. M., Belgrader, P., Ziraldo, S. B., Mikkelsen, T. S., Harbury, P. B., Glenn, J. S., Garcia, K. C., Davis, M. M., Baric, R. S., Sabatti, C., Amieva, M. R., Blish, C. A., Desai, T. J., Kuo, C. J. 2020


    The distal lung contains terminal bronchioles and alveoli that facilitate gas exchange. Three-dimensional in vitro human distal lung culture systems would strongly facilitate investigation of pathologies including interstitial lung disease, cancer, and SARS-CoV-2-associated COVID-19 pneumonia. We generated long-term feeder-free, chemically defined culture of distal lung progenitors as organoids derived from single adult human alveolar epithelial type II (AT2) or KRT5+ basal cells. AT2 organoids exhibited AT1 transdifferentiation potential while basal cell organoids developed lumens lined by differentiated club and ciliated cells. Single cell analysis of basal organoid KRT5+ cells revealed a distinct ITGA6+ITGB4+ mitotic population whose proliferation further segregated to a TNFRSF12Ahi subfraction comprising ~10% of KRT5+ basal cells, residing in clusters within terminal bronchioles and exhibiting enriched clonogenic organoid growth activity. Distal lung organoids were created with apical-out polarity to display ACE2 on the exposed external surface, facilitating SARS-CoV-2 infection of AT2 and basal cultures and identifying club cells as a novel target population. This long-term, feeder-free organoid culture of human distal lung, coupled with single cell analysis, identifies unsuspected basal cell functional heterogeneity and establishes a facile in vitro organoid model for human distal lung infections including COVID-19-associated pneumonia.

    View details for DOI 10.1038/s41586-020-3014-1

    View details for PubMedID 33238290

  • Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19. Cell Su, Y., Chen, D., Yuan, D., Lausted, C., Choi, J., Dai, C. L., Voillet, V., Duvvuri, V. R., Scherler, K., Troisch, P., Baloni, P., Qin, G., Smith, B., Kornilov, S. A., Rostomily, C., Xu, A., Li, J., Dong, S., Rothchild, A., Zhou, J., Murray, K., Edmark, R., Hong, S., Heath, J. E., Earls, J., Zhang, R., Xie, J., Li, S., Roper, R., Jones, L., Zhou, Y., Rowen, L., Liu, R., Mackay, S., O'Mahony, D. S., Dale, C. R., Wallick, J. A., Algren, H. A., Zager, M. A., ISB-Swedish COVID19 Biobanking Unit, Wei, W., Price, N. D., Huang, S., Subramanian, N., Wang, K., Magis, A. T., Hadlock, J. J., Hood, L., Aderem, A., Bluestone, J. A., Lanier, L. L., Greenberg, P. D., Gottardo, R., Davis, M. M., Goldman, J. D., Heath, J. R. 2020


    We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.

    View details for DOI 10.1016/j.cell.2020.10.037

    View details for PubMedID 33171100

  • Bifidobacterium alters the gut microbiota and modulates the functional metabolism of T regulatory cells in the context of immune checkpoint blockade. Proceedings of the National Academy of Sciences of the United States of America Sun, S., Luo, L., Liang, W., Yin, Q., Guo, J., Rush, A. M., Lv, Z., Liang, Q., Fischbach, M. A., Sonnenburg, J. L., Dodd, D., Davis, M. M., Wang, F. 2020


    Immune checkpoint-blocking antibodies that attenuate immune tolerance have been used to effectively treat cancer, but they can also trigger severe immune-related adverse events. Previously, we found that Bifidobacterium could mitigate intestinal immunopathology in the context of CTLA-4 blockade in mice. Here we examined the mechanism underlying this process. We found that Bifidobacterium altered the composition of the gut microbiota systematically in a regulatory T cell (Treg)-dependent manner. Moreover, this altered commensal community enhanced both the mitochondrial fitness and the IL-10-mediated suppressive functions of intestinal Tregs, contributing to the amelioration of colitis during immune checkpoint blockade.

    View details for DOI 10.1073/pnas.1921223117

    View details for PubMedID 33077598

  • The Power of Single Cell Technologies; from T Cell Receptor to Antigen(s) in Multiple Sclerosis Saligrama, N., Fernandes, R. A., Pai, J., Oksenberg, J., Satpathy, A., Davis, M. M. WILEY. 2020: S198
  • The science and medicine of human immunology. Science (New York, N.Y.) Pulendran, B., Davis, M. M. 2020; 369 (6511)


    Although the development of effective vaccines has saved countless lives from infectious diseases, the basic workings of the human immune system are complex and have required the development of animal models, such as inbred mice, to define mechanisms of immunity. More recently, new strategies and technologies have been developed to directly explore the human immune system with unprecedented precision. We discuss how these approaches are advancing our mechanistic understanding of human immunology and are facilitating the development of vaccines and therapeutics for infection, autoimmune diseases, and cancer.

    View details for DOI 10.1126/science.aay4014

    View details for PubMedID 32973003

  • Immune Profiling and Causal Antigen Discovery in Mouse and Human Models of Immune Checkpoint Inhibitor-induced Myocarditis Zhu, H., Lee, D., Sarah, W., Galdos, F. X., D'Addabbo, J., Fowler, M. B., Reddy, S., Heather, W., Neal, J. W., Witteles, R., Maecker, H. T., Davis, M., Nguyen, P. K., Wu, S. M. LIPPINCOTT WILLIAMS & WILKINS. 2020
  • Systems immunology. Current opinion in immunology Davis, M. M. 2020; 65: 79–82


    Systems biological approaches to immunology have grown exponentially in the past decade, especially as broad approaches to data collection have become more accessible. It is still in its infancy; however, largely descriptive, and looking for the main drivers of particular phenomena, such as vaccination effects or pregnancy. But this lays the ground work for an increasingly sophisticated appreciation of subsystems and interactions and will lead to predictive modeling and a deeper understanding of human diseases and interactions with pathogens.

    View details for DOI 10.1016/j.coi.2020.06.006

    View details for PubMedID 32738786

  • Discovery of a novel shared tumor antigen in human lung cancer. Tseng, D., Chiou, S., Yang, X., Reuben, A., Wilhelmy, J., McSween, A., Conley, S., Sinha, R., Nabet, B., Wang, C., Shrager, J. B., Berry, M. F., Backhus, L., Lui, n., Wakelee, H. A., Neal, J. W., Zhang, J., Garcia, K., Mackall, C., Davis, M. AMER SOC CLINICAL ONCOLOGY. 2020
  • Correction to: Cardiovascular Complications in Patients with COVID-19: Consequences of Viral Toxicities and Host Immune Response. Current cardiology reports Zhu, H., Rhee, J., Cheng, P., Waliany, S., Chang, A., Witteles, R. M., Maecker, H., Davis, M. M., Nguyen, P. K., Wu, S. M. 2020; 22 (5): 36


    It has been pointed out that the second paragraph of the section "Treatments for SARS-CoV-2 Infection" contains an error. The original article has been corrected.

    View details for DOI 10.1007/s11886-020-01302-4

    View details for PubMedID 32405913