Glycolysis inhibition affects proliferation and cytotoxicity of Vγ9Vδ2 T cells expanded for adoptive cell therapy.

BACKGROUND AIMS: Vγ9Vδ2 T cells are under investigation as alternative effector cells for adoptive cell therapy (ACT) in cancer. Despite promising in vitro results, anti-tumor efficacies in early clinical studies have been lower than expected, which could be ascribed to the complex interplay of tumor and immune cell metabolism competing for the same nutrients in the tumor microenvironment. METHODS: To contribute to the scarce knowledge regarding gamma delta T-cell metabolism, we investigated the metabolic phenotype of 25-day-expanded Vγ9Vδ2 T cells and how it is intertwined with functionality. RESULTS: We found that Vγ9Vδ2 T cells displayed a quiescent metabolism, utilizing both glycolysis and oxidative phosphorylation (OXPHOS) for energy production, as measured in Seahorse assays. Upon T-cell receptor activation, both pathways were upregulated, and inhibition with metabolic inhibitors showed that Vγ9Vδ2 T cells were dependent on glycolysis and the pentose phosphate pathway for proliferation. The dependency on glucose for proliferation was confirmed in glucose-free conditions. Cytotoxicity against malignant melanoma was reduced by glycolysis inhibition but not OXPHOS inhibition. CONCLUSIONS: These findings lay the groundwork for further studies on manipulation of Vγ9Vδ2 T-cell metabolism for improved ACT outcome.

A multi-omics systems vaccinology resource to develop and test computational models of immunity.

Systems vaccinology studies have identified factors affecting individual vaccine responses, but comparing these findings is challenging due to varying study designs. To address this lack of reproducibility, we established a community resource for comparing Bordetella pertussis booster responses and to host annual contests for predicting patients' vaccination outcomes. We report here on our experiences with the "dry-run" prediction contest. We found that, among 20+ models adopted from the literature, the most successful model predicting vaccination outcome was based on age alone. This confirms our concerns about the reproducibility of conclusions between different vaccinology studies. Further, we found that, for newly trained models, handling of baseline information on the target variables was crucial. Overall, multiple co-inertia analysis gave the best results of the tested modeling approaches. Our goal is to engage community in these prediction challenges by making data and models available and opening a public contest in August 2024.

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy.

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

JAK2V617F drives gut microbiota differences in patients with myeloproliferative neoplasms.

BACKGROUND: Essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (MF) are myeloproliferative neoplasms (MPN). Inflammation is involved in the initiation, progression, and symptomology of the diseases. The gut microbiota impacts the immune system, infection control, and steady-state hematopoiesis. METHODS: We analyzed the gut microbiota of 227 MPN patients and healthy controls (HCs) using next-generation sequencing. We expanded our previous results in PV and ET patients with additional PV, pre-MF, and MF patients which allowed us to compare MPN patients collectively, MPN sub-diagnoses, and MPN mutations (separately and combined) vs. HCs (N = 42) and compare within MPN sub-diagnoses and MPN mutation. RESULTS: MPN patients had a higher observed richness (median, 245 [range, 49-659]) compared with HCs (191.5 [range, 111-300; p = .003]) and a lower relative abundance of taxa within the Firmicutes phylum; for example, Faecalibacterium (6% vs. 14%, p < .001). The microbiota of CALR-positive patients (N = 30) resembled that of HCs more than that of patients with JAK2V617F (N = 177). In JAK2V617F-positive patients, only minor differences in the gut microbiota were observed between MPN sub-diagnoses, illustrating the importance of this mutation. CONCLUSION: The gut microbiota in MPN patients differs from HCs and is driven by JAK2V617F, whereas the gut microbiota in CALR patients resembles HCs more.

Building flexible and robust analysis frameworks for molecular subtyping of cancers.

Molecular subtyping is essential to infer tumor aggressiveness and predict prognosis. In practice, tumor profiling requires in-depth knowledge of bioinformatics tools involved in the processing and analysis of the generated data. Additionally, data incompatibility (e.g., microarray versus RNA sequencing data) and technical and uncharacterized biological variance between training and test data can pose challenges in classifying individual samples. In this article, we provide a roadmap for implementing bioinformatics frameworks for molecular profiling of human cancers in a clinical diagnostic setting. We describe a framework for integrating several methods for quality control, normalization, batch correction, classification and reporting, and develop a use case of the framework in breast cancer.

Expression and splicing mediate distinct biological signals.

BACKGROUND: Through alternative splicing, most human genes produce multiple isoforms in a cell-, tissue-, and disease-specific manner. Numerous studies show that alternative splicing is essential for development, diseases, and their treatments. Despite these important examples, the extent and biological relevance of splicing are currently unknown. RESULTS: To solve this problem, we developed pairedGSEA and used it to profile transcriptional changes in 100 representative RNA-seq datasets. Our systematic analysis demonstrates that changes in splicing, on average, contribute to 48.1% of the biological signal in expression analyses. Gene-set enrichment analysis furthermore indicates that expression and splicing both convey shared and distinct biological signals. CONCLUSIONS: These findings establish alternative splicing as a major regulator of the human condition and suggest that most contemporary RNA-seq studies likely miss out on critical biological insights. We anticipate our results will contribute to the transition from a gene-centric to an isoform-centric research paradigm.

ZNF683 marks a CD8+ T cell population associated with anti-tumor immunity following anti-PD-1 therapy for Richter syndrome.

Unlike many other hematologic malignancies, Richter syndrome (RS), an aggressive B cell lymphoma originating from indolent chronic lymphocytic leukemia, is responsive to PD-1 blockade. To discover the determinants of response, we analyze single-cell transcriptome data generated from 17 bone marrow samples longitudinally collected from 6 patients with RS. Response is associated with intermediate exhausted CD8 effector/effector memory T cells marked by high expression of the transcription factor ZNF683, determined to be evolving from stem-like memory cells and divergent from terminally exhausted cells. This signature overlaps with that of tumor-infiltrating populations from anti-PD-1 responsive solid tumors. ZNF683 is found to directly target key T cell genes (TCF7, LMO2, CD69) and impact pathways of T cell cytotoxicity and activation. Analysis of pre-treatment peripheral blood from 10 independent patients with RS treated with anti-PD-1, as well as patients with solid tumors treated with anti-PD-1, supports an association of ZNF683high T cells with response.

Pronounced gut microbiota signatures in patients with JAK2V617F-positive essential thrombocythemia.

Essential thrombocythemia (ET) is part of the Philadelphia chromosome-negative myeloproliferative neoplasms. It is characterized by an increased risk of thromboembolic events and also to a certain degree hypermetabolic symptoms. The gut microbiota is an important initiator of hematopoiesis and regulation of the immune system, but in patients with ET, where inflammation is a hallmark of the disease, it is vastly unexplored. In this study, we compared the gut microbiota via amplicon-based 16S rRNA gene sequencing of the V3-V4 region in 54 patients with ET according to mutation status Janus-kinase 2 (JAK2V617F)-positive vs JAK2V617F-negative patients with ET, and in 42 healthy controls (HCs). Gut microbiota richness was higher in patients with ET (median-observed richness, 283.5; range, 75-535) compared with HCs (median-observed richness, 191.5; range, 111-300; P < 0.001). Patients with ET had a different overall bacterial composition (beta diversity) than HCs (analysis of similarities [ANOSIM]; R = 0.063, P = 0.004). Patients with ET had a significantly lower relative abundance of taxa within the Firmicutes phylum compared with HCs (51% vs 59%, P = 0.03), and within that phylum, patients with ET also had a lower relative abundance of the genus Faecalibacterium (8% vs 15%, P < 0.001), an important immunoregulative bacterium. The microbiota signatures were more pronounced in patients harboring the JAK2V617F mutation, and highly similar to patients with polycythemia vera as previously described. These findings suggest that patients with ET may have an altered immune regulation; however, whether this dysregulation is induced in part by, or is itself inducing, an altered gut microbiota remains to be investigated. IMPORTANCE Essential thrombocythemia (ET) is a cancer characterized by thrombocyte overproduction. Inflammation has been shown to be vital in both the initiation and progression of other myeloproliferative neoplasms, and it is well known that the gut microbiota is important in the regulation of our immune system. However, the gut microbiota of patients with ET remains uninvestigated. In this study, we characterized the gut microbiota of patients with ET compared with healthy controls and thereby provide new insights into the field. We show that the gut microbiota of patients with ET differs significantly from that of healthy controls and the patients with ET have a lower relative abundance of important immunoregulative bacteria. Furthermore, we demonstrate that patients with JAK2V617F-positive ET have pronounced gut microbiota signatures compared with JAK2V617F-negative patients. Thereby confirming the importance of the underlying mutation, the immune response as well as the composition of the microbiota.

A systems vaccinology resource to develop and test computational models of immunity.

Computational models that predict an individual's response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such 'dry run' for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.

An insulin hypersecretion phenotype precedes pancreatic ß cell failure in MODY3 patient-specific cells.

MODY3 is a monogenic hereditary form of diabetes caused by mutations in the transcription factor HNF1A. The patients progressively develop hyperglycemia due to perturbed insulin secretion, but the pathogenesis is unknown. Using patient-specific hiPSCs, we recapitulate the insulin secretion sensitivity to the membrane depolarizing agent sulfonylurea commonly observed in MODY3 patients. Unexpectedly, MODY3 patient-specific HNF1A+/R272C ß cells hypersecrete insulin both in vitro and in vivo after transplantation into mice. Consistently, we identified a trend of increased birth weight in human HNF1A mutation carriers compared with healthy siblings. Reduced expression of potassium channels, specifically the KATP channel, in MODY3 ß cells, increased calcium signaling, and rescue of the insulin hypersecretion phenotype by pharmacological targeting ATP-sensitive potassium channels or low-voltage-activated calcium channels suggest that more efficient membrane depolarization underlies the hypersecretion of insulin in MODY3 ß cells. Our findings identify a pathogenic mechanism leading to ß cell failure in MODY3.

The gut microbiota in patients with polycythemia vera is distinct from that of healthy controls and varies by treatment.

Chronic inflammation is believed to play an important role in the development and disease progression of polycythemia vera (PV). Because an association between gut microbiota, hematopoiesis, and inflammation is well established, we hypothesized that patients with PV have a gut microbiota distinct from healthy control participants (HCs). Recombinant interferon alfa 2 (IFN-α2)-treatment of patients with PV is reportedly disease modifying in terms of normalization of elevated blood cell counts in concert with a reduction in the JAK2V617F allelic burden. Therefore, we hypothesized that patients treated with IFN-α2 might have a composition of the gut microbiota toward normalization. Herein, via amplicon-based next-generation sequencing of the V3 to V4 regions of the 16S ribosomal RNA gene, we report on an abnormal gut microbiota in 102 patients with PV compared with 42 HCs. Patients with PV had a lower alpha diversity and a lower relative abundance of several taxa belonging to Firmicutes (45%) compared with HCs (59%, P <.001). Furthermore, we report the composition of the gut microbiota to differ between the treatment groups (IFN-α2, hydroxyurea, no treatment, and combination therapy with IFN-α2 and ruxolitinib) and the HCs. These observations are highly interesting considering the potential pathogenetic importance of an altered gut microbiota for development of other diseases, including chronic inflammatory diseases. Our observations call for further gut microbiota studies to decipher potential causal associations between treatment and the gut microbiota in PV and related neoplasms.

cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies.

Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. However, in many cases the full potential of co-analyses is not reached due to technical variance between data from different experimental batches. Here, we present cyCombine, a method to robustly integrate cytometry data from different batches, experiments, or even different experimental techniques, such as CITE-seq, flow cytometry, and mass cytometry. We demonstrate that cyCombine maintains the biological variance and the structure of the data, while minimizing the technical variance between datasets. cyCombine does not require technical replicates across datasets, and computation time scales linearly with the number of cells, allowing for integration of massive datasets. Robust, accurate, and scalable integration of cytometry data enables integration of multiple datasets for primary data analyses and the validation of results using public datasets.

High CD34 surface expression in BCP-ALL predicts poor induction therapy response and is associated with altered expression of genes related to cell migration and adhesion.

Minimal residual disease (MRD) constitutes the most important prognostic factor in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Flow cytometry is widely used in MRD assessment, yet little is known regarding the effect of different immunophenotypic subsets on outcome. In this study of 200 BCP-ALL patients, we found that a CD34-positive, CD38 dim-positive, nTdT dim-positive immunophenotype on the leukemic blasts was associated with poor induction therapy response and predicted an MRD level at the end of induction therapy (EOI) of ≥ 0.001. CD34 expression was strongly and positively associated with EOI MRD, whereas CD34-negative patients had a low relapse risk. Further, CD34 expression increased from diagnosis to relapse. CD34 is a stemness-associated cell-surface molecule, possibly involved in cell adhesion/migration or survival. Accordingly, genes associated with stemness were overrepresented among the most upregulated genes in CD34-positive leukemias, and protein-protein interaction networks showed an overrepresentation of genes associated with cell migration, cell adhesion, and negative regulation of apoptosis. The present work is the first to demonstrate a CD34-negative immunophenotype as a good prognostic factor in ALL, whereas high CD34 expression is associated with poor therapy response and an altered gene expression profile reminiscent of migrating cancer stem-like cells.

A Comparison of Tools for Copy-Number Variation Detection in Germline Whole Exome and Whole Genome Sequencing Data.

Copy-number variations (CNVs) have important clinical implications for several diseases and cancers. Relevant CNVs are hard to detect because common structural variations define large parts of the human genome. CNV calling from short-read sequencing would allow single protocol full genomic profiling. We reviewed 50 popular CNV calling tools and included 11 tools for benchmarking in a reference cohort encompassing 39 whole genome sequencing (WGS) samples paired current clinical standard-SNP-array based CNV calling. Additionally, for nine samples we also performed whole exome sequencing (WES), to address the effect of sequencing protocol on CNV calling. Furthermore, we included Gold Standard reference sample NA12878, and tested 12 samples with CNVs confirmed by multiplex ligation-dependent probe amplification (MLPA). Tool performance varied greatly in the number of called CNVs and bias for CNV lengths. Some tools had near-perfect recall of CNVs from arrays for some samples, but poor precision. Several tools had better performance for NA12878, which could be a result of overfitting. We suggest combining the best tools also based on different methodologies: GATK gCNV, Lumpy, DELLY, and cn.MOPS. Reducing the total number of called variants could potentially be assisted by the use of background panels for filtering of frequently called variants.

TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes.

We previously developed TANTIGEN, a comprehensive online database cataloging more than 1000 T cell epitopes and HLA ligands from 292 tumor antigens. In TANTIGEN 2.0, we significantly expanded coverage in both immune response targets (T cell epitopes and HLA ligands) and tumor antigens. It catalogs 4,296 antigen variants from 403 unique tumor antigens and more than 1500 T cell epitopes and HLA ligands. We also included neoantigens, a class of tumor antigens generated through mutations resulting in new amino acid sequences in tumor antigens. TANTIGEN 2.0 contains validated TCR sequences specific for cognate T cell epitopes and tumor antigen gene/mRNA/protein expression information in major human cancers extracted by Human Pathology Atlas. TANTIGEN 2.0 is a rich data resource for tumor antigens and their associated epitopes and neoepitopes. It hosts a set of tailored data analytics tools tightly integrated with the data to form meaningful analysis workflows. It is freely available at http://projects.met-hilab.org/tadb .

Clinical implications of intrinsic molecular subtypes of breast cancer for sentinel node status.

Axillary lymph node status is an important prognostic factor for breast cancer patients and sentinel lymph node biopsy (SLNB) is a less invasive surgical proxy. We examined if consecutively derived molecular subtypes from primary breast cancers provide additional predictive value for SLNB status. 1556 patients with a breast cancer > 10 mm underwent primary surgical procedure including SLNB and tumor specimens were assigned with a transcriptomics-based molecular subtype. 1020 patients had a negative sentinel node (SN) and 536 a positive. A significant association between tumor size and SN status (p < 0.0001) was found across all samples, but no association between size and SN status (p = 0.14) was found for BasL tumors. A BasL subtype was a predictor of an SN-negative status (p = 0.001, OR 0.58, 95% CI 0.38;0.90) and among the BasL, postmenopausal status was a predictor for SN-negative status (p = 0.01). Overall survival was significantly lower (p = 0.02) in patients with BasL tumors and a positive SN. Interestingly, we identified a significant correlation between hormone receptor activity and SN status within the BasL subtype. Taken together, molecular subtypes and hormone receptor activity of breast cancers add predictive value for SLNB status.

Personal neoantigen vaccines induce persistent memory T cell responses and epitope spreading in patients with melanoma.

Personal neoantigen vaccines have been envisioned as an effective approach to induce, amplify and diversify antitumor T cell responses. To define the long-term effects of such a vaccine, we evaluated the clinical outcome and circulating immune responses of eight patients with surgically resected stage IIIB/C or IVM1a/b melanoma, at a median of almost 4 years after treatment with NeoVax, a long-peptide vaccine targeting up to 20 personal neoantigens per patient ( NCT01970358 ). All patients were alive and six were without evidence of active disease. We observed long-term persistence of neoantigen-specific T cell responses following vaccination, with ex vivo detection of neoantigen-specific T cells exhibiting a memory phenotype. We also found diversification of neoantigen-specific T cell clones over time, with emergence of multiple T cell receptor clonotypes exhibiting distinct functional avidities. Furthermore, we detected evidence of tumor infiltration by neoantigen-specific T cell clones after vaccination and epitope spreading, suggesting on-target vaccine-induced tumor cell killing. Personal neoantigen peptide vaccines thus induce T cell responses that persist over years and broaden the spectrum of tumor-specific cytotoxicity in patients with melanoma.

Changes in the Tumor Immune Microenvironment during Disease Progression in Patients with Ovarian Cancer.

Anti-PD1/PDL1 therapy has proven efficacious against many cancers but only reached modest objective response rates against recurrent ovarian cancer. A deeper understanding of the tumor microenvironment (TME) may reveal other immunosuppressive mechanisms that warrant investigation as immunotherapeutic targets for this challenging disease. Matched primary and recurrent tumors from patients with high-grade serous ovarian carcinoma (HGSC) were analyzed by multicolor immunohistochemistry/immunofluorescence for the presence of T cells, B cells, macrophages, and for the expression of immunosuppressive and HLA molecules. Cancer- and immune-related gene expression was assessed by NanoString analysis. Recurrent tumors showed increased infiltration by immune cells, displayed higher expression of PDL1, IDO, and HLA molecules, and contained more stromal tissue. NanoString analysis demonstrated increased expression of gene signatures related to chemokines and T cell functions in recurrent tumors. The ovarian tumors showed high gene expression of LAG3 and HAVCR2 (TIM3) and enhanced levels of TIGIT and CTLA4 in recurrent tumors compared to primary tumors. The majority of HGSC developed into a more inflamed phenotype during progression from primary to recurrent disease, including indications of adaptive immune resistance. This suggests that recurrent tumors may be particularly sensitive to inhibition of adaptive immune resistance mechanisms.