Single-cell Multiomics Analysis of Myelodysplastic Syndromes and Clinical Response to Hypomethylating Therapy.

Alterations in epigenetic marks, such as DNA methylation, represent a hallmark of cancer that has been successfully exploited for therapy in myeloid malignancies. Hypomethylating agents (HMA), such as azacitidine, have become standard-of-care therapy to treat myelodysplastic syndromes (MDS), myeloid neoplasms that can evolve into acute myeloid leukemia. However, our capacity to identify who will respond to HMAs, and the duration of response, remains limited. To shed light on this question, we have leveraged the unprecedented analytic power of single-cell technologies to simultaneously map the genome and immunoproteome of MDS samples throughout clinical evolution. We were able to chart the architecture and evolution of molecular clones in precious paired bone marrow MDS samples at diagnosis and posttreatment to show that a combined imbalance of specific cell lineages with diverse mutational profiles is associated with the clinical response of patients with MDS to hypomethylating therapy. SIGNIFICANCE: MDS are myeloid clonal hemopathies with a low 5-year survival rate, and approximately half of the cases do not respond to standard HMA therapy. Our innovative single-cell multiomics approach offers valuable biological insights and potential biomarkers associated with the demethylating agent efficacy. It also identifies vulnerabilities that can be targeted using personalized combinations of small drugs and antibodies.

Lysin (K)-specific demethylase 1 inhibition enhances proteasome inhibitor response and overcomes drug resistance in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is an incurable plasma cell malignancy, accounting for approximately 1% of all cancers. Despite recent advances in the treatment of MM, due to the introduction of proteasome inhibitors (PIs) such as bortezomib (BTZ) and carfilzomib (CFZ), relapses and disease progression remain common. Therefore, a major challenge is the development of novel therapeutic approaches to overcome drug resistance, improve patient outcomes, and broaden PIs applicability to other pathologies. METHODS: We performed genetic and drug screens to identify new synthetic lethal partners to PIs, and validated candidates in PI-sensitive and -resistant MM cells. We also tested best synthetic lethal interactions in other B-cell malignancies, such as mantle cell, Burkitt's and diffuse large B-cell lymphomas. We evaluated the toxicity of combination treatments in normal peripheral blood mononuclear cells (PBMCs) and bone marrow stromal cells (BMSCs). We confirmed the combo treatment' synergistic effects ex vivo in primary CD138+ cells from MM patients, and in different MM xenograft models. We exploited RNA-sequencing and Reverse-Phase Protein Arrays (RPPA) to investigate the molecular mechanisms of the synergy. RESULTS: We identified lysine (K)-specific demethylase 1 (LSD1) as a top candidate whose inhibition can synergize with CFZ treatment. LSD1 silencing enhanced CFZ sensitivity in both PI-resistant and -sensitive MM cells, resulting in increased tumor cell death. Several LSD1 inhibitors (SP2509, SP2577, and CC-90011) triggered synergistic cytotoxicity in combination with different PIs in MM and other B-cell neoplasms. CFZ/SP2509 treatment exhibited a favorable cytotoxicity profile toward PBMCs and BMSCs. We confirmed the clinical potential of LSD1-proteasome inhibition in primary CD138+ cells of MM patients, and in MM xenograft models, leading to the inhibition of tumor progression. DNA damage response (DDR) and proliferation machinery were the most affected pathways by CFZ/SP2509 combo treatment, responsible for the anti-tumoral effects. CONCLUSIONS: The present study preclinically demonstrated that LSD1 inhibition could provide a valuable strategy to enhance PI sensitivity and overcome drug resistance in MM patients and that this combination might be exploited for the treatment of other B-cell malignancies, thus extending the therapeutic impact of the project.

Macrophage and neutrophil heterogeneity at single-cell spatial resolution in human inflammatory bowel disease.

Ulcerative colitis and Crohn's disease are chronic inflammatory intestinal diseases with perplexing heterogeneity in disease manifestation and response to treatment. While the molecular basis for this heterogeneity remains uncharacterized, single-cell technologies allow us to explore the transcriptional states within tissues at an unprecedented resolution which could further understanding of these complex diseases. Here, we apply single-cell RNA-sequencing to human inflamed intestine and show that the largest differences among patients are present within the myeloid compartment including macrophages and neutrophils. Using spatial transcriptomics in human tissue at single-cell resolution (CosMx Spatial Molecular Imaging) we spatially localize each of the macrophage and neutrophil subsets identified by single-cell RNA-sequencing and unravel further macrophage diversity based on their tissue localization. Finally, single-cell RNA-sequencing combined with single-cell spatial analysis reveals a strong communication network involving macrophages and inflammatory fibroblasts. Our data sheds light on the cellular complexity of these diseases and points towards the myeloid and stromal compartments as important cellular subsets for understanding patient-to-patient heterogeneity.

Targeting lymphoid-derived IL-17 signaling to delay skin aging.

Skin aging is characterized by structural and functional changes that contribute to age-associated frailty. This probably depends on synergy between alterations in the local niche and stem cell-intrinsic changes, underscored by proinflammatory microenvironments that drive pleotropic changes. The nature of these age-associated inflammatory cues, or how they affect tissue aging, is unknown. Based on single-cell RNA sequencing of the dermal compartment of mouse skin, we show a skew towards an IL-17-expressing phenotype of T helper cells, γδ T cells and innate lymphoid cells in aged skin. Importantly, in vivo blockade of IL-17 signaling during aging reduces the proinflammatory state of the skin, delaying the appearance of age-related traits. Mechanistically, aberrant IL-17 signals through NF-κB in epidermal cells to impair homeostatic functions while promoting an inflammatory state. Our results indicate that aged skin shows signs of chronic inflammation and that increased IL-17 signaling could be targeted to prevent age-associated skin ailments.

Glioblastoma cell fate is differentially regulated by the microenvironments of the tumor bulk and infiltrative margin.

Glioblastoma (GBM) recurrence originates from invasive margin cells that escape surgical debulking, but to what extent these cells resemble their bulk counterparts remains unclear. Here, we generated three immunocompetent somatic GBM mouse models, driven by subtype-associated mutations, to compare matched bulk and margin cells. We find that, regardless of mutations, tumors converge on common sets of neural-like cellular states. However, bulk and margin have distinct biology. Injury-like programs associated with immune infiltration dominate in the bulk, leading to the generation of lowly proliferative injured neural progenitor-like cells (iNPCs). iNPCs account for a significant proportion of dormant GBM cells and are induced by interferon signaling within T cell niches. In contrast, developmental-like trajectories are favored within the immune-cold margin microenvironment resulting in differentiation toward invasive astrocyte-like cells. These findings suggest that the regional tumor microenvironment dominantly controls GBM cell fate and biological vulnerabilities identified in the bulk may not extend to the margin residuum.

Euchromatic Histone Lysine Methyltransferase 2 Inhibition Enhances Carfilzomib Sensitivity and Overcomes Drug Resistance in Multiple Myeloma Cell Lines.

Proteasome inhibitors (PIs) are extensively used for the therapy of multiple myeloma. However, patients continuously relapse or are intrinsically resistant to this class of drugs. In addition, adverse toxic effects such as peripheral neuropathy and cardiotoxicity could arise. Here, to identify compounds that can increase the efficacy of PIs, we performed a functional screening using a library of small-molecule inhibitors covering key signaling pathways. Among the best synthetic lethal interactions, the euchromatic histone-lysine N-methyltransferase 2 (EHMT2) inhibitor UNC0642 displayed a cooperative effect with carfilzomib (CFZ) in numerous multiple myeloma (MM) cell lines, including drug-resistant models. In MM patients, EHMT2 expression correlated to worse overall and progression-free survival. Moreover, EHMT2 levels were significantly increased in bortezomib-resistant patients. We demonstrated that CFZ/UNC0642 combination exhibited a favorable cytotoxicity profile toward peripheral blood mononuclear cells and bone-marrow-derived stromal cells. To exclude off-target effects, we proved that UNC0642 treatment reduces EHMT2-related molecular markers and that an alternative EHMT2 inhibitor recapitulated the synergistic activity with CFZ. Finally, we showed that the combinatorial treatment significantly perturbs autophagy and the DNA damage repair pathways, suggesting a multi-layered mechanism of action. Overall, the present study demonstrates that EHMT2 inhibition could provide a valuable strategy to enhance PI sensitivity and overcome drug resistance in MM patients.

Extraction Bottleneck in the Diagnosis of SARS-CoV-2: Evaluation of an Alternative Protocol Derived from Veterinary Use.

The COVID-19 pandemic represented a challenge for health-care systems, and a major bottleneck in SARS-CoV-2 diagnosis was the unavailability of extraction reagents. To overcome this limitation, we performed a comparative analysis to evaluate the performance of an alternative extraction protocol derived from veterinary use adapted to an open robotic platform (Testing method). A total of 73 nasopharyngeal swabs collected for diagnosis of SARS-CoV-2 infection were simultaneously extracted with the Testing protocol and the laboratory Standard of Care in order to assess the performance of the first one. The Cohen's coefficient between both procedures was excellent (K Value = 0.955). Analysis of cycle threshold and linear regression showed a significant correlation between the two methods for each tested genetic target. Although validated for veterinary applications, the Testing method showed excellent performances in RNA extraction, with several advantages: lower sample input volume, the possibility to overcome the lack of deep-well plates and adaptability to robotic liquid handlers.

Green Preparation of Antimicrobial 1D-Coordination Polymers: [Zn(4,4'-bipy)Cl2]∞ and [Zn(4,4'-bipy)2(OAc)2]∞ by Ultrasonication of Zn(II) Salts and 4,4'-Bipyridine.

We report on the green preparation of one-dimensional metal coordination polymers by sonochemical approach. The spacer ligand 4,4'-bipyridine was ultrasonicated with chloride or acetate zinc salts to obtain [Zn(4,4'-bipy)Cl2]∞ and [Zn(4,4'-bipy)2(OAc)2]∞, respectively. Benign solvents such as ethanol and water were selected as reaction media, and the synthesis took place in a few minutes-a very short time compared to conventional methods where some days' synthesis is required. X-ray powder diffraction, Fourier transform infrared spectroscopy, thermal analysis (thermogravimetric and differential scanning calorimetry), and CHN techniques investigated the influence of using different reaction solvents on the chemical, structural, and thermal properties of the final products. The 1D [Zn(4,4'-bipy)Cl2]∞ and [Zn(4,4'-bipy)2(OAc)2]∞ polymers, in agreement with the structures reported in the literature, were obtained in the form of nanocrystals with an average crystal size around 100 nm. As a proof of concept, a set of Gram-positive (Staphylococcus aureus) and Gram-negative bacteria (Klebsiella pneumoniae), and three yeast strains (Candida albicans, Candida krusei, Candida glabrata) were tested to evaluate the antimicrobial activity of the coordination polymers, following the Kirby-Bauer procedure and microplate dilution method. Thus, minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and minimal biofilm inhibitory concentration (MBIC) were evaluated. Except for Candida krusei, the compounds showed an appreciable antimicrobial and antibiofilm activity against these strains grown in the liquid medium.

Cohesin couples transcriptional bursting probabilities of inducible enhancers and promoters.

Innate immune responses rely on inducible gene expression programmes which, in contrast to steady-state transcription, are highly dependent on cohesin. Here we address transcriptional parameters underlying this cohesin-dependence by single-molecule RNA-FISH and single-cell RNA-sequencing. We show that inducible innate immune genes are regulated predominantly by an increase in the probability of active transcription, and that probabilities of enhancer and promoter transcription are coordinated. Cohesin has no major impact on the fraction of transcribed inducible enhancers, or the number of mature mRNAs produced per transcribing cell. Cohesin is, however, required for coupling the probabilities of enhancer and promoter transcription. Enhancer-promoter coupling may not be explained by spatial proximity alone, and at the model locus Il12b can be disrupted by selective inhibition of the cohesinopathy-associated BET bromodomain BD2. Our data identify discrete steps in enhancer-mediated inducible gene expression that differ in cohesin-dependence, and suggest that cohesin and BD2 may act on shared pathways.

A single-cell tumor immune atlas for precision oncology.

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy.

Single-cell technologies and analyses in hematopoiesis and hematological malignancies.

In recent years, single-cell technologies have emerged as breakthrough techniques that enable the characterization of hematopoietic cell populations of normal and malignant tissue samples and will be combined in the near future with bulk technologies, currently used in clinical practice, to improve diagnosis, prognosis, and the search for novel molecular targets. These single-cell methods have the advantage of not masking cell-to-cell variation features and involve the study of genetic, epigenetic, transcriptional, and proteomic landscapes from a single-cell perspective. Latest advances in this field have enabled the development of novel strategies that significantly increase both sensitivity and high throughput. In this review, we emphasize emerging techniques aimed at assessing individual or multiomic parameters at single-cell resolution and analyze how these technologies have helped us understand hematopoietic variability and identify unknown and/or rare subpopulations. We also summarize the impact of these single-cell profiling strategies on the characterization of cell diversity within the tumor and the clonal evolution of multiple hematological malignancies in samples from untreated and treated patients, which provide valuable information for diagnosis, prognosis, and future treatments and explain why current therapies may fail. However, despite these improvements, new challenges lie ahead.

The Landscape of Signaling Pathways and Proteasome Inhibitors Combinations in Multiple Myeloma.

Multiple myeloma is a malignancy of terminally differentiated plasma cells, characterized by an extreme genetic heterogeneity that poses great challenges for its successful treatment. Due to antibody overproduction, MM cells depend on the precise regulation of the protein degradation systems. Despite the success of PIs in MM treatment, resistance and adverse toxic effects such as peripheral neuropathy and cardiotoxicity could arise. To this end, the use of rational combinatorial treatments might allow lowering the dose of inhibitors and therefore, minimize their side-effects. Even though the suppression of different cellular pathways in combination with proteasome inhibitors have shown remarkable anti-myeloma activities in preclinical models, many of these promising combinations often failed in clinical trials. Substantial progress has been made by the simultaneous targeting of proteasome and different aspects of MM-associated immune dysfunctions. Moreover, targeting deranged metabolic hubs could represent a new avenue to identify effective therapeutic combinations with PIs. Finally, epigenetic drugs targeting either DNA methylation, histone modifiers/readers, or chromatin remodelers are showing pleiotropic anti-myeloma effects alone and in combination with PIs. We envisage that the positive outcome of patients will probably depend on the availability of more effective drug combinations and treatment of early MM stages. Therefore, the identification of sensitive targets and aberrant signaling pathways is instrumental for the development of new personalized therapies for MM patients.

SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes.

Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections and further fine-mapped normal and neoplastic cell states. Trained on an external single-cell pancreatic tumor references, we further charted the localization of clinical-relevant and tumor-specific immune cell states, an illustrative example of its flexible application spectrum and future potential in digital pathology.

Improved Diagnosis of Rare Disease Patients through Systematic Detection of Runs of Homozygosity.

Autozygosity is associated with an increased risk of genetic rare disease, thus being a relevant factor for clinical genetic studies. More than 2400 exome sequencing data sets were analyzed and screened for autozygosity on the basis of detection of >1 Mbp runs of homozygosity (ROHs). A model was built to predict if an individual is likely to be a consanguineous offspring (accuracy, 98%), and probability of consanguinity ranges were established according to the total ROH size. Application of the model resulted in the reclassification of the consanguinity status of 12% of the patients. The analysis of a subset of 79 consanguineous cases with the Rare Disease (RD)-Connect Genome-Phenome Analysis Platform, combining variant filtering and homozygosity mapping, enabled a 50% reduction in the number of candidate variants and the identification of homozygous pathogenic variants in 41 patients, with an overall diagnostic yield of 52%. The newly defined consanguinity ranges provide, for the first time, specific ROH thresholds to estimate inbreeding within a pedigree on disparate exome sequencing data, enabling confirmation or (re)classification of consanguineous status, hence increasing the efficiency of molecular diagnosis and reporting on secondary consanguinity findings, as recommended by American College of Medical Genetics and Genomics guidelines.

Immune Cell Associations with Cancer Risk.

Proper immune system function hinders cancer development, but little is known about whether genetic variants linked to cancer risk alter immune cells. Here, we report 57 cancer risk loci associated with differences in immune and/or stromal cell contents in the corresponding tissue. Predicted target genes show expression and regulatory associations with immune features. Polygenic risk scores also reveal associations with immune and/or stromal cell contents, and breast cancer scores show consistent results in normal and tumor tissue. SH2B3 links peripheral alterations of several immune cell types to the risk of this malignancy. Pleiotropic SH2B3 variants are associated with breast cancer risk in BRCA1/2 mutation carriers. A retrospective case-cohort study indicates a positive association between blood counts of basophils, leukocytes, and monocytes and age at breast cancer diagnosis. These findings broaden our knowledge of the role of the immune system in cancer and highlight promising prevention strategies for individuals at high risk.

Benchmarking single-cell RNA-sequencing protocols for cell atlas projects.

Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas.

Zonation of Ribosomal DNA Transcription Defines a Stem Cell Hierarchy in Colorectal Cancer.

Colorectal cancers (CRCs) are composed of an amalgam of cells with distinct genotypes and phenotypes. Here, we reveal a previously unappreciated heterogeneity in the biosynthetic capacities of CRC cells. We discover that the majority of ribosomal DNA transcription and protein synthesis in CRCs occurs in a limited subset of tumor cells that localize in defined niches. The rest of the tumor cells undergo an irreversible loss of their biosynthetic capacities as a consequence of differentiation. Cancer cells within the biosynthetic domains are characterized by elevated levels of the RNA polymerase I subunit A (POLR1A). Genetic ablation of POLR1A-high cell population imposes an irreversible growth arrest on CRCs. We show that elevated biosynthesis defines stemness in both LGR5+ and LGR5- tumor cells. Therefore, a common architecture in CRCs is a simple cell hierarchy based on the differential capacity to transcribe ribosomal DNA and synthesize proteins.

Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data.

BACKGROUND: Many functional analysis tools have been developed to extract functional and mechanistic insight from bulk transcriptome data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events and low library sizes. It is thus not clear if functional TF and pathway analysis tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way. RESULTS: To address this question, we perform benchmark studies on simulated and real scRNA-seq data. We include the bulk-RNA tools PROGENy, GO enrichment, and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compare them against the tools SCENIC/AUCell and metaVIPER, designed for scRNA-seq. For the in silico study, we simulate single cells from TF/pathway perturbation bulk RNA-seq experiments. We complement the simulated data with real scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on simulated and real data reveal comparable performance to the original bulk data. Additionally, we show that the TF and pathway activities preserve cell type-specific variability by analyzing a mixture sample sequenced with 13 scRNA-seq protocols. We also provide the benchmark data for further use by the community. CONCLUSIONS: Our analyses suggest that bulk-based functional analysis tools that use manually curated footprint gene sets can be applied to scRNA-seq data, partially outperforming dedicated single-cell tools. Furthermore, we find that the performance of functional analysis tools is more sensitive to the gene sets than to the statistic used.

GATA2 Promotes Hematopoietic Development and Represses Cardiac Differentiation of Human Mesoderm.

In vertebrates, GATA2 is a master regulator of hematopoiesis and is expressed throughout embryo development and in adult life. Although the essential role of GATA2 in mouse hematopoiesis is well established, its involvement during early human hematopoietic development is not clear. By combining time-controlled overexpression of GATA2 with genetic knockout experiments, we found that GATA2, at the mesoderm specification stage, promotes the generation of hemogenic endothelial progenitors and their further differentiation to hematopoietic progenitor cells, and negatively regulates cardiac differentiation. Surprisingly, genome-wide transcriptional and chromatin immunoprecipitation analysis showed that GATA2 bound to regulatory regions, and repressed the expression of cardiac development-related genes. Moreover, genes important for hematopoietic differentiation were upregulated by GATA2 in a mostly indirect manner. Collectively, our data reveal a hitherto unrecognized role of GATA2 as a repressor of cardiac fates, and highlight the importance of coordinating the specification and repression of alternative cell fates.