Alea Christine Delmastro

All Publications

• The immunometabolic topography of tuberculosis granulomas governs cellular organization and bacterial control. bioRxiv : the preprint server for biology McCaffrey, E. F., Delmastro, A. C., Fitzhugh, I., Ranek, J. S., Douglas, S., Peters, J. M., Fullaway, C. C., Bosse, M., Liu, C. C., Gillen, C., Greenwald, N. F., Anzick, S., Martens, C., Winfree, S., Bai, Y., Sowers, C., Goldston, M., Kong, A., Boonrat, P., Bigbee, C. L., Venugopalan, R., Maiello, P., Klein, E., Rodgers, M. A., Scanga, C. A., Lin, P. L., Kirschner, D., Fortune, S., Bryson, B. D., Butler, J. R., Mattila, J. T., Flynn, J. L., Angelo, M. 2025

  Abstract

  Despite being heavily infiltrated by immune cells, tuberculosis (TB) granulomas often subvert the host response to Mycobacterium tuberculosis (Mtb) infection and support bacterial persistence. We previously discovered that human TB granulomas are enriched for immunosuppressive factors typically associated with tumor-immune evasion, raising the intriguing possibility that they promote tolerance to infection. In this study, our goal was to identify the prime drivers for establishing this tolerogenic niche and to determine if the magnitude of this response correlates with bacterial persistence. To do this, we conducted a multimodal spatial analysis of 52 granulomas from 16 non-human primates (NHP) who were infected with low dose Mtb for 9-12 weeks. Notably, each granuloma's bacterial burden was individually quantified allowing us to directly ask how granuloma spatial structure and function relate to infection control. We found that a universal feature of TB granulomas was partitioning of the myeloid core into two distinct metabolic environments, one of which is hypoxic. This hypoxic environment associated with pathologic immune cell states, dysfunctional cellular organization of the granuloma, and a near-complete blockade of lymphocyte infiltration that would be required for a successful host response. The extent of these hypoxia-associated features correlated with worsened bacterial burden. We conclude that hypoxia governs immune cell state and organization within granulomas and is a potent driver of subverted immunity during TB.

  View details for DOI 10.1101/2025.02.18.638923

  View details for PubMedID 40027668

  View details for PubMedCentralID PMC11870603

• Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition. bioRxiv : the preprint server for biology Greenwald, N. F., Nederlof, I., Sowers, C., Ding, D. Y., Park, S., Kong, A., Houlahan, K. E., Varra, S. R., de Graaf, M., Geurts, V., Liu, C. C., Ranek, J. S., Voorwerk, L., de Maaker, M., Kagel, A., McCaffrey, E., Khan, A., Yeh, C. Y., Fullaway, C. C., Khair, Z., Bai, Y., Piyadasa, H., Risom, T., Delmastro, A., Hartmann, F. J., Mangiante, L., Sotomayor-Vivas, C., Schumacher, T. N., Ma, Z., Bosse, M., van de Vijver, M. J., Tibshirani, R., Horlings, H. M., Curtis, C., Kok, M., Angelo, M. 2025

  Abstract

  Immune checkpoint inhibition (ICI) has fundamentally changed cancer treatment. However, only a minority of patients with metastatic triple negative breast cancer (TNBC) benefit from ICI, and the determinants of response remain largely unknown. To better understand the factors influencing patient outcome, we assembled a longitudinal cohort with tissue from multiple timepoints, including primary tumor, pre-treatment metastatic tumor, and on-treatment metastatic tumor from 117 patients treated with ICI (nivolumab) in the phase II TONIC trial. We used highly multiplexed imaging to quantify the subcellular localization of 37 proteins in each tumor. To extract meaningful information from the imaging data, we developed SpaceCat, a computational pipeline that quantifies features from imaging data such as cell density, cell diversity, spatial structure, and functional marker expression. We applied SpaceCat to 678 images from 294 tumors, generating more than 800 distinct features per tumor. Spatial features were more predictive of patient outcome, including features like the degree of mixing between cancer and immune cells, the diversity of the neighboring immune cells surrounding cancer cells, and the degree of T cell infiltration at the tumor border. Non-spatial features, including the ratio between T cell subsets and cancer cells and PD-L1 levels on myeloid cells, were also associated with patient outcome. Surprisingly, we did not identify robust predictors of response in the primary tumors. In contrast, the metastatic tumors had numerous features which predicted response. Some of these features, such as the cellular diversity at the tumor border, were shared across timepoints, but many of the features, such as T cell infiltration at the tumor border, were predictive of response at only a single timepoint. We trained multivariate models on all of the features in the dataset, finding that we could accurately predict patient outcome from the pre-treatment metastatic tumors, with improved performance using the on-treatment tumors. We validated our findings in matched bulk RNA-seq data, finding the most informative features from the on-treatment samples. Our study highlights the importance of profiling sequential tumor biopsies to understand the evolution of the tumor microenvironment, elucidating the temporal and spatial dynamics underlying patient responses and underscoring the need for further research on the prognostic role of metastatic tissue and its utility in stratifying patients for ICI.

  View details for DOI 10.1101/2025.01.26.634557

  View details for PubMedID 39975273

  View details for PubMedCentralID PMC11838242

• Malaria-specific Type 1 regulatory T cells are more abundant in first pregnancies and associated with placental malaria. EBioMedicine Kirosingh, A. S., Delmastro, A., Kakuru, A., van der Ploeg, K., Bhattacharya, S., Press, K. D., Ty, M., Parte, L., Kizza, J., Muhindo, M., Devachanne, S., Gamain, B., Nankya, F., Musinguzi, K., Rosenthal, P. J., Feeney, M. E., Kamya, M., Dorsey, G., Jagannathan, P. 2023; 95: 104772

  Abstract

  Malaria in pregnancy (MIP) causes higher morbidity in primigravid compared to multigravid women; however, the correlates and mechanisms underlying this gravidity-dependent protection remain incompletely understood. We aimed to compare the cellular immune response between primigravid and multigravid women living in a malaria-endemic region and assess for correlates of protection against MIP.We characterised the second trimester cellular immune response among 203 primigravid and multigravid pregnant women enrolled in two clinical trials of chemoprevention in eastern Uganda, utilizing RNA sequencing, flow cytometry, and functional assays. We compared responses across gravidity and determined associations with parasitaemia during pregnancy and placental malaria.Using whole blood RNA sequencing, no significant differentially expressed genes were identified between primigravid (n = 12) and multigravid (n = 11) women overall (log 2(FC) > 2, FDR < 0.1). However, primigravid (n = 49) women had higher percentages of malaria-specific, non-naïve CD4+ T cells that co-expressed IL-10 and IFNγ compared with multigravid (n = 85) women (p = 0.000023), and higher percentages of these CD4+ T cells were associated with greater risks of parasitaemia in pregnancy (Rs = 0.49, p = 0.001) and placental malaria (p = 0.0073). These IL-10 and IFNγ co-producing CD4+ T cells had a genomic signature of Tr1 cells, including expression of transcription factors cMAF and BATF and cell surface makers CTLA4 and LAG-3.Malaria-specific Tr1 cells were highly prevalent in primigravid Ugandan women, and their presence correlated with a higher risk of malaria in pregnancy. Understanding whether suppression of Tr1 cells plays a role in naturally acquired gravidity-dependent immunity may aid the development of new vaccines or treatments for MIP.This work was funded by NIH (PO1 HD059454, U01 AI141308, U19 AI089674, U01 AI155325, U01 AI150741), the March of Dimes (Basil O'Connor award), and the Bill and Melinda Gates Foundation (OPP 1113682).

  View details for DOI 10.1016/j.ebiom.2023.104772

  View details for PubMedID 37634385

• Embedding Azobenzene-Functionalized Carbon Nanotubes into a Polymer Matrix for Stretchable, Composite Solar Thermal Devices JOURNAL OF PHYSICAL CHEMISTRY C Colburn, T. W., Delmastro, A. C., Figueroa, M., Lopez, F., Cooper, C. B. 2022

  View details for DOI 10.1021/acs.jpcc.2c03865

  View details for Web of Science ID 000853650400001

• The immunoregulatory landscape of human tuberculosis granulomas. Nature immunology McCaffrey, E. F., Donato, M., Keren, L., Chen, Z., Delmastro, A., Fitzpatrick, M. B., Gupta, S., Greenwald, N. F., Baranski, A., Graf, W., Kumar, R., Bosse, M., Fullaway, C. C., Ramdial, P. K., Forgó, E., Jojic, V., Van Valen, D., Mehra, S., Khader, S. A., Bendall, S. C., van de Rijn, M., Kalman, D., Kaushal, D., Hunter, R. L., Banaei, N., Steyn, A. J., Khatri, P., Angelo, M. 2022

  Abstract

  Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-β, regulatory T cells and IDO1+ PD-L1+ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.

  View details for DOI 10.1038/s41590-021-01121-x

  View details for PubMedID 35058616

• Rhesus Macaque CODEX Multiplexed Immunohistochemistry Panel for Studying Immune Responses During Ebola Infection FRONTIERS IN IMMUNOLOGY Jiang, S., Mukherjee, N., Bennett, R. S., Chen, H., Logue, J., Dighero-Kemp, B., Kurtz, J. R., Adams, R., Phillips, D., Schuerch, C. M., Goltsev, Y., Hickey, J. W., McCaffrey, E. F., Delmastro, A., Chu, P., Reader, J., Keesler, R., Galvan, J. A., Zlobec, I., Van Rompay, K. K. A., Liu, D. X., Hensley, L. E., Nolan, G. P., McIlwain, D. R. 2021; 12: 729845

  Abstract

  Non-human primate (NHP) animal models are an integral part of the drug research and development process. For some biothreat pathogens, animal model challenge studies may offer the only possibility to evaluate medical countermeasure efficacy. A thorough understanding of host immune responses in such NHP models is therefore vital. However, applying antibody-based immune characterization techniques to NHP models requires extensive reagent development for species compatibility. In the case of studies involving high consequence pathogens, further optimization for use of inactivated samples may be required. Here, we describe the first optimized CO-Detection by indEXing (CODEX) multiplexed tissue imaging antibody panel for deep profiling of spatially resolved single-cell immune responses in rhesus macaques. This 21-marker panel is composed of a set of 18 antibodies that stratify major immune cell types along with a set three Ebola virus (EBOV)-specific antibodies. We validated these two sets of markers using immunohistochemistry and CODEX in fully inactivated Formalin-Fixed Paraffin-Embedded (FFPE) tissues from mock and EBOV challenged macaques respectively and provide an efficient framework for orthogonal validation of multiple antibody clones using CODEX multiplexed tissue imaging. We also provide the antibody clones and oligonucleotide tag sequences as a valuable resource for other researchers to recreate this reagent set for future studies of tissue immune responses to EBOV infection and other diseases.

  View details for DOI 10.3389/fimmu.2021.729845

  View details for Web of Science ID 000732063400001

  View details for PubMedID 34938283

  View details for PubMedCentralID PMC8685521