B-cell-directed CAR-T cell therapy activates CD8+ cytotoxic CARneg bystander T-cells in non-human primates and patients.

CAR-T cells hold promise as a therapy for B-cell-derived malignancies, yet despite their impressive initial response rates, a significant proportion of patients ultimately experience relapse. While recent studies have explored the mechanisms of in vivo CAR-T cell function, little is understood about the activation of surrounding CARneg bystander T-cells and their potential to enhance tumor responses. We performed single-cell RNA-Seq (scRNA-Seq) on non-human primate (NHP) and patient-derived T-cells to identify the phenotypic and transcriptomic hallmarks of bystander activation of CARneg T-cells following B-cell targeted CAR-T cell therapy. Utilizing a highly translatable CD20 CAR NHP model, we observed a distinct population of activated CD8+ CARneg T-cells emerging during CAR-T cell expansion. These bystander CD8+ CARneg T-cells exhibited a unique transcriptional signature with upregulation of NK-cell markers (KIR3DL2, CD160, KLRD1), chemokines and chemokine receptors (CCL5, XCL1, CCR9), and downregulation of naive T-cell-associated genes (SELL, CD28). A transcriptionally similar population was identified in patients following Tisagenlecleucel infusion. Mechanistic studies revealed that IL-2 and IL-15 exposure induced bystander-like CD8+ T-cells in a dose dependent manner. In vitro activated and patient-derived T-cells with the bystander phenotype efficiently killed leukemic cells through a TCR-independent mechanism. Collectively, this dataset provides the first comprehensive identification and profiling of CARneg bystander CD8+ T-cells following B-cell targeting CAR-T cell therapy and suggests a novel mechanism through which CAR-T cell infusion might trigger enhanced anti-leukemic responses.

Alloengraftment without significant toxicity or GVHD in CD45 antibody-drug conjugate conditioned Fanconi anemia mice.

Fanconi anemia (FA) is an inherited DNA repair disorder characterized by bone marrow (BM) failure, developmental abnormalities, myelodysplasia, and leukemia and solid tumor predisposition. Allogeneic hematopoietic stem cell transplantation (allo-HSCT), a mainstay treatment, is limited by conditioning regimen-related toxicity and graft-versus-host disease (GVHD). Antibody-drug-conjugates (ADCs) targeting hematopoietic stem cells (HSCs) can open marrow niches permitting donor stem cell alloengraftment. Here, we report that single dose anti-mouse CD45-targeted-ADC (CD45-ADC) facilitated stable, multilineage chimerism in 3 distinct FA mouse models representing 90% of FA complementation groups. CD45-ADC profoundly depleted host stem cell enriched LineageSca1+cKit+ cells within 48 hours. Fanca-/- recipients of minor-mismatched BM and single dose CD45-ADC had peripheral blood (PB) mean donor chimerism >90%; donor HSCs alloengraftment was verified in secondary recipients. In Fancc-/- and Fancg-/- recipients of fully allogeneic grafts, PB mean donor chimerism was 60-80% and 70-80%, respectively. The mean percent donor chimerism in BM and spleen mirrored PB results. CD45-ADC conditioned mice did not have clinical toxicity. A transient <2.5-fold increase in hepatocellular enzymes and mild-to-moderate histopathological changes were seen. Under GVHD allo-HSCT conditions, wildtype and Fanca-/- recipients of CD45-ADC had markedly reduced GVHD lethality compared to lethal irradiation. Moreover, single dose anti-human CD45-ADC given to rhesus macaque nonhuman primates on days -6 or -10 was at least as myeloablative as lethal irradiation. These data suggest that CD45-ADC can potently promote donor alloengraftment and hematopoiesis without significant toxicity or severe GVHD, as seen with lethal irradiation, providing strong support for clinical trial considerations in highly vulnerable FA patients.

DNA methylation and chromatin accessibility predict age in the domestic dog.

Across mammals, the epigenome is highly predictive of chronological age. These "epigenetic clocks," most of which have been built using DNA methylation (DNAm) profiles, have gained traction as biomarkers of aging and organismal health. While the ability of DNAm to predict chronological age has been repeatedly demonstrated, the ability of other epigenetic features to predict age remains unclear. Here, we use two types of epigenetic information-DNAm, and chromatin accessibility as measured by ATAC-seq-to develop age predictors in peripheral blood mononuclear cells sampled from a population of domesticated dogs. We measured DNAm and ATAC-seq profiles for 71 dogs, building separate predictive clocks from each, as well as the combined dataset. We also use fluorescence-assisted cell sorting to quantify major lymphoid populations for each sample. We found that chromatin accessibility can accurately predict chronological age (R2 ATAC = 26%), though less accurately than the DNAm clock (R2 DNAm = 33%), and the clock built from the combined datasets was comparable to both (R2 combined = 29%). We also observed various populations of CD62L+ T cells significantly correlated with dog age. Finally, we found that all three clocks selected features that were in or near at least two protein-coding genes: BAIAP2 and SCARF2, both previously implicated in processes related to cognitive or neurological impairment. Taken together, these results highlight the potential of chromatin accessibility as a complementary epigenetic resource for modeling and investigating biologic age.

Algorithmically Reconstructed Molecular Pathways as the New Generation of Prognostic Molecular Biomarkers in Human Solid Cancers.

Individual gene expression and molecular pathway activation profiles were shown to be effective biomarkers in many cancers. Here, we used the human interactome model to algorithmically build 7470 molecular pathways centered around individual gene products. We assessed their associations with tumor type and survival in comparison with the previous generation of molecular pathway biomarkers (3022 "classical" pathways) and with the RNA transcripts or proteomic profiles of individual genes, for 8141 and 1117 samples, respectively. For all analytes in RNA and proteomic data, respectively, we found a total of 7441 and 7343 potential biomarker associations for gene-centric pathways, 3020 and 2950 for classical pathways, and 24,349 and 6742 for individual genes. Overall, the percentage of RNA biomarkers was statistically significantly higher for both types of pathways than for individual genes (p < 0.05). In turn, both types of pathways showed comparable performance. The percentage of cancer-type-specific biomarkers was comparable between proteomic and transcriptomic levels, but the proportion of survival biomarkers was dramatically lower for proteomic data. Thus, we conclude that pathway activation level is the advanced type of biomarker for RNA and proteomic data, and momentary algorithmic computer building of pathways is a new credible alternative to time-consuming hypothesis-driven manual pathway curation and reconstruction.

Uniformly shaped harmonization combines human transcriptomic data from different platforms while retaining their biological properties and differential gene expression patterns.

Introduction: Co-normalization of RNA profiles obtained using different experimental platforms and protocols opens avenue for comprehensive comparison of relevant features like differentially expressed genes associated with disease. Currently, most of bioinformatic tools enable normalization in a flexible format that depends on the individual datasets under analysis. Thus, the output data of such normalizations will be poorly compatible with each other. Recently we proposed a new approach to gene expression data normalization termed Shambhala which returns harmonized data in a uniform shape, where every expression profile is transformed into a pre-defined universal format. We previously showed that following shambhalization of human RNA profiles, overall tissue-specific clustering features are strongly retained while platform-specific clustering is dramatically reduced. Methods: Here, we tested Shambhala performance in retention of fold-change gene expression features and other functional characteristics of gene clusters such as pathway activation levels and predicted cancer drug activity scores. Results: Using 6,793 cancer and 11,135 normal tissue gene expression profiles from the literature and experimental datasets, we applied twelve performance criteria for different versions of Shambhala and other methods of transcriptomic harmonization with flexible output data format. Such criteria dealt with the biological type classifiers, hierarchical clustering, correlation/regression properties, stability of drug efficiency scores, and data quality for using machine learning classifiers. Discussion: Shambhala-2 harmonizer demonstrated the best results with the close to 1 correlation and linear regression coefficients for the comparison of training vs validation datasets and more than two times lesser instability for calculation of drug efficiency scores compared to other methods.

Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers.

Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived "healthy" normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min - 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact "differential" expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice.

Notch signaling drives intestinal graft-versus-host disease in mice and nonhuman primates.

Notch signaling promotes T cell pathogenicity and graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation (allo-HCT) in mice, with a dominant role for the Delta-like Notch ligand DLL4. To assess whether Notch's effects are evolutionarily conserved and to identify the mechanisms of Notch signaling inhibition, we studied antibody-mediated DLL4 blockade in a nonhuman primate (NHP) model similar to human allo-HCT. Short-term DLL4 blockade improved posttransplant survival with durable protection from gastrointestinal GVHD in particular. Unlike prior immunosuppressive strategies tested in the NHP GVHD model, anti-DLL4 interfered with a T cell transcriptional program associated with intestinal infiltration. In cross-species investigations, Notch inhibition decreased surface abundance of the gut-homing integrin α4ß7 in conventional T cells while preserving α4ß7 in regulatory T cells, with findings suggesting increased ß1 competition for α4 binding in conventional T cells. Secondary lymphoid organ fibroblastic reticular cells emerged as the critical cellular source of Delta-like Notch ligands for Notch-mediated up-regulation of α4ß7 integrin in T cells after allo-HCT. Together, DLL4-Notch blockade decreased effector T cell infiltration into the gut, with increased regulatory to conventional T cell ratios early after allo-HCT. Our results identify a conserved, biologically unique, and targetable role of DLL4-Notch signaling in intestinal GVHD.

Distinct Traits of Structural and Regulatory Evolutional Conservation of Human Genes with Specific Focus on Major Cancer Molecular Pathways.

The evolution of protein-coding genes has both structural and regulatory components. The first can be assessed by measuring the ratio of non-synonymous to synonymous nucleotide substitutions. The second component can be measured as the normalized proportion of transposable elements that are used as regulatory elements. For the first time, we characterized in parallel the regulatory and structural evolutionary profiles for 10,890 human genes and 2972 molecular pathways. We observed a ~0.1 correlation between the structural and regulatory metrics at the gene level, which appeared much higher (~0.4) at the pathway level. We deposited the data in the publicly available database RetroSpect. We also analyzed the evolutionary dynamics of six cancer pathways of two major axes: Notch/WNT/Hedgehog and AKT/mTOR/EGFR. The Hedgehog pathway had both components slower, whereas the Akt pathway had clearly accelerated structural evolution. In particular, the major hub nodes Akt and beta-catenin showed both components strongly decreased, whereas two major regulators of Akt TCL1 and CTMP had outstandingly high evolutionary rates. We also noticed structural conservation of serine/threonine kinases and the genes related to guanosine metabolism in cancer signaling: GPCRs, G proteins, and small regulatory GTPases (Src, Rac, Ras); however, this was compensated by the accelerated regulatory evolution.

Pan-cancer antagonistic inhibition pattern of ATM-driven G2/M checkpoint pathway vs other DNA repair pathways.

DNA repair mechanisms keep genome integrity and limit tumor-associated alterations and heterogeneity, but on the other hand they promote tumor survival after radiation and genotoxic chemotherapies. We screened pathway activation levels of 38 DNA repair pathways in nine human cancer types (gliomas, breast, colorectal, lung, thyroid, cervical, kidney, gastric, and pancreatic cancers). We took RNAseq profiles of the experimental 51 normal and 408 tumor samples, and from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium databases - of 500/407 normal and 5752/646 tumor samples, and also 573 normal and 984 tumor proteomic profiles from Proteomic Data Commons portal. For all the samplings we observed a congruent trend that all cancer types showed inhibition of G2/M arrest checkpoint pathway compared to the normal samples, and relatively low activities of p53-mediated pathways. In contrast, other DNA repair pathways were upregulated in most of the cancer types. The G2/M checkpoint pathway was statistically significantly downregulated compared to the other DNA repair pathways, and this inhibition was strongly impacted by antagonistic regulation of (i) promitotic genes CCNB and CDK1, and (ii) GADD45 genes promoting G2/M arrest. At the DNA level, we found that ATM, TP53, and CDKN1A genes accumulated loss of function mutations, and cyclin B complex genes - transforming mutations. These findings suggest importance of activation for most of DNA repair pathways in cancer progression, with remarkable exceptions of G2/M checkpoint and p53-related pathways which are downregulated and neutrally activated, respectively.

Chronic GvHD NIH Consensus Project Biology Task Force: evolving path to personalized treatment of chronic GvHD.

Chronic graft-versus-host disease (cGvHD) remains a prominent barrier to allogeneic hematopoietic stem cell transplantion as the leading cause of nonrelapse mortality and significant morbidity. Tremendous progress has been achieved in both the understanding of pathophysiology and the development of new therapies for cGvHD. Although our field has historically approached treatment from an empiric position, research performed at the bedside and bench has elucidated some of the complex pathophysiology of cGvHD. From the clinical perspective, there is significant variability of disease manifestations between individual patients, pointing to diverse biological underpinnings. Capitalizing on progress made to date, the field is now focused on establishing personalized approaches to treatment. The intent of this article is to concisely review recent knowledge gained and formulate a path toward patient-specific cGvHD therapy.

Engineering T cells to suppress acute GVHD and leukemia relapse after allogeneic hematopoietic stem cell transplantation.

Acute graft-versus-host disease (aGVHD) limits the therapeutic benefit of allogeneic hematopoietic stem cell transplantation (allo-HSCT) and requires immunosuppressive prophylaxis that compromises antitumor and antipathogen immunity. OX40 is a costimulatory receptor upregulated on circulating T cells in aGVHD and plays a central role in driving the expansion of alloreactive T cells. Here, we show that OX40 is also upregulated on T cells infiltrating GVHD target organs in a rhesus macaque model, supporting the hypothesis that targeted ablation of OX40+ T cells will mitigate GVHD pathogenesis. We thus created an OX40-specific cytotoxic receptor that, when expressed on human T cells, enables selective elimination of OX40+ T cells. Because OX40 is primarily upregulated on CD4+ T cells upon activation, engineered OX40-specific T cells mediated potent cytotoxicity against activated CD4+ T cells and suppressed alloreactive T-cell expansion in a mixed lymphocyte reaction model. OX40 targeting did not inhibit antiviral activity of memory T cells specific to Epstein-Barr virus, cytomegalovirus, and adenoviral antigens. Systemic administration of OX40-targeting T cells fully protected mice from fatal xenogeneic GVHD mediated by human peripheral blood mononuclear cells. Furthermore, combining OX40 targeting with a leukemia-specific chimeric antigen receptor in a single T cell product provides simultaneous protection against leukemia and aGVHD in a mouse xenograft model of residual disease posttransplant. These results underscore the central role of OX40+ T cells in mediating aGVHD pathogenesis and support the feasibility of a bifunctional engineered T-cell product derived from the stem cell donor to suppress both disease relapse and aGVHD following allo-HSCT.

Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways.

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.

OncoboxPD: human 51 672 molecular pathways database with tools for activity calculating and visualization.

OncoboxPD (Oncobox pathway databank) available at https://open.oncobox.com is the collection of 51 672 uniformly processed human molecular pathways. Superposition of all pathways formed interactome graph of protein-protein interactions and metabolic reactions containing 361 654 interactions and 64 095 molecular participants. Pathways are uniformly classified by biological processes, and each pathway node is algorithmically functionally annotated by specific activator/repressor role. This enables online calculation of statistically supported pathway activation levels (PALs) with the built-in bioinformatic tool using custom RNA/protein expression profiles. Each pathway can be visualized as static or dynamic graph, where vertices are molecules participating in a pathway and edges are interactions or reactions between them. Differentially expressed nodes in a pathway can be visualized in two-color mode with user-defined color scale. For every comparison, OncoboxPD also generates a graph summarizing top up- and downregulated pathways.

Better Agreement of Human Transcriptomic and Proteomic Cancer Expression Data at the Molecular Pathway Activation Level.

Previously, we have shown that the aggregation of RNA-level gene expression profiles into quantitative molecular pathway activation metrics results in lesser batch effects and better agreement between different experimental platforms. Here, we investigate whether pathway level of data analysis provides any advantage when comparing transcriptomic and proteomic data. We compare the paired proteomic and transcriptomic gene expression and pathway activation profiles obtained for the same human cancer biosamples in The Cancer Genome Atlas (TCGA) and the NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects, for a total of 755 samples of glioblastoma, breast, liver, lung, ovarian, pancreatic, and uterine cancers. In a CPTAC assay, expression levels of 15,112 protein-coding genes were profiled using the Thermo QE series of mass spectrometers. In TCGA, RNA expression levels of the same genes were obtained using the Illumina HiSeq 4000 engine for the same biosamples. At the gene level, absolute gene expression values are compared, whereas pathway-grade comparisons are made between the pathway activation levels (PALs) calculated using average sample-normalized transcriptomic and proteomic profiles. We observed remarkably different average correlations between the primary RNA- and protein expression data for different cancer types: Spearman Rho between 0.017 (p = 1.7 × 10−13) and 0.27 (p < 2.2 × 10−16). However, at the pathway level we detected overall statistically significantly higher correlations: averaged Rho between 0.022 (p < 2.2 × 10−16) and 0.56 (p < 2.2 × 10−16). Thus, we conclude that data analysis at the PAL-level yields results of a greater similarity when comparing high-throughput RNA and protein expression profiles.

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways.

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.

Algorithmically Deduced FREM2 Molecular Pathway Is a Potent Grade and Survival Biomarker of Human Gliomas.

Gliomas are the most common malignant brain tumors with high mortality rates. Recently we showed that the FREM2 gene has a role in glioblastoma progression. Here we reconstructed the FREM2 molecular pathway using the human interactome model. We assessed the biomarker capacity of FREM2 expression and its pathway as the overall survival (OS) and progression-free survival (PFS) biomarkers. To this end, we used three literature and one experimental RNA sequencing datasets collectively covering 566 glioblastomas (GBM) and 1097 low-grade gliomas (LGG). The activation level of deduced FREM2 pathway showed strong biomarker characteristics and significantly outperformed the FREM2 expression level itself. For all relevant datasets, it could robustly discriminate GBM and LGG (p < 1.63 × 10-13, AUC > 0.74). High FREM2 pathway activation level was associated with poor OS in LGG (p < 0.001), and low PFS in LGG (p < 0.001) and GBM (p < 0.05). FREM2 pathway activation level was poor prognosis biomarker for OS (p < 0.05) and PFS (p < 0.05) in LGG with IDH mutation, for PFS in LGG with wild type IDH (p < 0.001) and mutant IDH with 1p/19q codeletion(p < 0.05), in GBM with unmethylated MGMT (p < 0.05), and in GBM with wild type IDH (p < 0.05). Thus, we conclude that the activation level of the FREM2 pathway is a potent new-generation diagnostic and prognostic biomarker for multiple molecular subtypes of GBM and LGG.

Machine Learning Applicability for Classification of PAD/VCD Chemotherapy Response Using 53 Multiple Myeloma RNA Sequencing Profiles.

Multiple myeloma (MM) affects ~500,000 people and results in ~100,000 deaths annually, being currently considered treatable but incurable. There are several MM chemotherapy treatment regimens, among which eleven include bortezomib, a proteasome-targeted drug. MM patients respond differently to bortezomib, and new prognostic biomarkers are needed to personalize treatments. However, there is a shortage of clinically annotated MM molecular data that could be used to establish novel molecular diagnostics. We report new RNA sequencing profiles for 53 MM patients annotated with responses on two similar chemotherapy regimens: bortezomib, doxorubicin, dexamethasone (PAD), and bortezomib, cyclophosphamide, dexamethasone (VCD), or with responses to their combinations. Fourteen patients received both PAD and VCD; six received only PAD, and 33 received only VCD. We compared profiles for the good and poor responders and found five genes commonly regulated here and in the previous datasets for other bortezomib regimens (all upregulated in the good responders): FGFR3, MAF, IGHA2, IGHV1-69, and GRB14. Four of these genes are linked with known immunoglobulin locus rearrangements. We then used five machine learning (ML) methods to build a classifier distinguishing good and poor responders for two cohorts: PAD + VCD (53 patients), and separately VCD (47 patients). We showed that the application of FloWPS dynamic data trimming was beneficial for all ML methods tested in both cohorts, and also in the previous MM bortezomib datasets. However, the ML models build for the different datasets did not allow cross-transferring, which can be due to different treatment regimens, experimental profiling methods, and MM heterogeneity.

Phase II Trial of Costimulation Blockade With Abatacept for Prevention of Acute GVHD.

PURPOSE: Severe (grade 3-4) acute graft-versus-host disease (AGVHD) is a major cause of death after unrelated-donor (URD) hematopoietic cell transplant (HCT), resulting in particularly high mortality after HLA-mismatched transplantation. There are no approved agents for AGVHD prevention, underscoring the critical unmet need for novel therapeutics. ABA2 was a phase II trial to rigorously assess safety, efficacy, and immunologic effects of adding T-cell costimulation blockade with abatacept to calcineurin inhibitor (CNI)/methotrexate (MTX)-based GVHD prophylaxis, to test whether abatacept could decrease AGVHD. METHODS: ABA2 enrolled adults and children with hematologic malignancies under two strata: a randomized, double-blind, placebo-controlled stratum (8/8-HLA-matched URD), comparing CNI/MTX plus abatacept with CNI/MTX plus placebo, and a single-arm stratum (7/8-HLA-mismatched URD) comparing CNI/MTX plus abatacept versus CNI/MTX CIBMTR controls. The primary end point was day +100 grade 3-4 AGVHD, with day +180 severe-AGVHD-free-survival (SGFS) a key secondary end point. Sample sizes were calculated using a higher type-1 error (0.2) as recommended for phase II trials, and were based on predicting that abatacept would reduce grade 3-4 AGVHD from 20% to 10% (8/8s) and 30% to 10% (7/8s). ABA2 enrolled 142 recipients (8/8s, median follow-up = 716 days) and 43 recipients (7/8s, median follow-up = 708 days). RESULTS: In 8/8s, grade 3-4 AGVHD was 6.8% (abatacept) versus 14.8% (placebo) (P = .13, hazard ratio = 0.45). SGFS was 93.2% (CNI/MTX plus abatacept) versus 82% (CNI/MTX plus placebo, P = .05). In the smaller 7/8 cohort, grade 3-4 AGVHD was 2.3% (CNI/MTX plus abatacept, intention-to-treat population), which compared favorably with a nonrandomized matched cohort of CNI/MTX (30.2%, P < .001), and the SGFS was better (97.7% v 58.7%, P < .001). Immunologic analysis revealed control of T-cell activation in abatacept-treated patients. CONCLUSION: Adding abatacept to URD HCT was safe, reduced AGVHD, and improved SGFS. These results suggest that abatacept may substantially improve AGVHD-related transplant outcomes, with a particularly beneficial impact on HLA-mismatched HCT.

Spatiotemporal single-cell profiling reveals that invasive and tissue-resident memory donor CD8+ T cells drive gastrointestinal acute graft-versus-host disease.

Organ infiltration by donor T cells is critical to the development of acute graft-versus-host disease (aGVHD) in recipients after allogeneic hematopoietic stem cell transplant (allo-HCT). However, deconvoluting the transcriptional programs of newly recruited donor T cells from those of tissue-resident T cells in aGVHD target organs remains a challenge. Here, we combined the serial intravascular staining technique with single-cell RNA sequencing to dissect the tightly connected processes by which donor T cells initially infiltrate tissues and then establish a pathogenic tissue residency program in a rhesus macaque allo-HCT model that develops aGVHD. Our results enabled creation of a spatiotemporal map of the transcriptional programs controlling donor CD8+ T cell infiltration into the primary aGVHD target organ, the gastrointestinal (GI) tract. We identified the large and small intestines as the only two sites demonstrating allo-specific, rather than lymphodepletion-driven, T cell infiltration. GI-infiltrating donor CD8+ T cells demonstrated a highly activated, cytotoxic phenotype while simultaneously developing a canonical tissue-resident memory T cell (TRM) transcriptional signature driven by interleukin-15 (IL-15)/IL-21 signaling. We found expression of a cluster of genes directly associated with tissue invasiveness, including those encoding adhesion molecules (ITGB2), specific chemokines (CCL3 and CCL4L1) and chemokine receptors (CD74), as well as multiple cytoskeletal proteins. This tissue invasion transcriptional signature was validated by its ability to discriminate the CD8+ T cell transcriptome of patients with GI aGVHD from those of GVHD-free patients. These results provide insights into the mechanisms controlling tissue occupancy of target organs by pathogenic donor CD8+ TRM cells during aGVHD in primate transplant recipients.

Measurement of leukocyte trafficking kinetics in macaques by serial intravascular staining.

Leukocyte trafficking enables detection of pathogens, immune responses, and immune memory. Dysregulation of leukocyte trafficking is often found in disease, highlighting its important role in homeostasis and the immune response. Whereas some of the molecular mechanisms mediating leukocyte trafficking are understood, little is known about the regulation of trafficking, including trafficking kinetics and its impact on immune homeostasis. We developed a method of serial intravascular staining (SIVS) to measure trafficking kinetics in nonhuman primates using infusions of fluorescently labeled antibodies to label circulating leukocytes. Because antibody infusions labeled only leukocytes in the blood, cells were "barcoded" according to their location at the time of each infusion, providing positional histories that could be used to infer trafficking kinetics. We used SIVS and multiparameter flow cytometry to quantitate cellular trafficking into lymphoid tissues of healthy animals at homeostasis and to identify perivascular cells that could be unique to nonlymphoid organs. To investigate how these parameters could be influenced during disease, SIVS was used to quantify lymphocyte trafficking in macaques infected with the bacterial pathogen Mycobacterium tuberculosis and to enumerate intravascular leukocytes in lung granulomas. We showed that whereas most cells in lung granulomas were localized there for more than 24 hours, granulomas were dynamic with a slow continual cellular influx, the rate of which predicted clearance of M. tuberculosis from the granulomas. SIVS, in combination with intracellular staining and multiparametric flow cytometry, is a powerful method to quantify the kinetics of leukocyte trafficking in nonhuman primates in vivo.