Single-cell functional genomics reveals determinants of sensitivity and resistance to natural killer cells in blood cancers.

Cancer cells can evade natural killer (NK) cell activity, thereby limiting anti-tumor immunity. To reveal genetic determinants of susceptibility to NK cell activity, we examined interacting NK cells and blood cancer cells using single-cell and genome-scale functional genomics screens. Interaction of NK and cancer cells induced distinct activation and type I interferon (IFN) states in both cell types depending on the cancer cell lineage and molecular phenotype, ranging from more sensitive myeloid to less sensitive B-lymphoid cancers. CRISPR screens in cancer cells uncovered genes regulating sensitivity and resistance to NK cell-mediated killing, including adhesion-related glycoproteins, protein fucosylation genes, and transcriptional regulators, in addition to confirming the importance of antigen presentation and death receptor signaling pathways. CRISPR screens with a single-cell transcriptomic readout provided insight into underlying mechanisms, including regulation of IFN-γ signaling in cancer cells and NK cell activation states. Our findings highlight the diversity of mechanisms influencing NK cell susceptibility across different cancers and provide a resource for NK cell-based therapies.

The genomic basis of childhood T-lineage acute lymphoblastic leukaemia.

T-lineage acute lymphoblastic leukaemia (T-ALL) is a high-risk tumour1 that has eluded comprehensive genomic characterization, which is partly due to the high frequency of noncoding genomic alterations that result in oncogene deregulation2,3. Here we report an integrated analysis of genome and transcriptome sequencing of tumour and remission samples from more than 1,300 uniformly treated children with T-ALL, coupled with epigenomic and single-cell analyses of malignant and normal T cell precursors. This approach identified 15 subtypes with distinct genomic drivers, gene expression patterns, developmental states and outcomes. Analyses of chromatin topology revealed multiple mechanisms of enhancer deregulation that involve enhancers and genes in a subtype-specific manner, thereby demonstrating widespread involvement of the noncoding genome. We show that the immunophenotypically described, high-risk entity of early T cell precursor ALL is superseded by a broader category of 'early T cell precursor-like' leukaemia. This category has a variable immunophenotype and diverse genomic alterations of a core set of genes that encode regulators of hematopoietic stem cell development. Using multivariable outcome models, we show that genetic subtypes, driver and concomitant genetic alterations independently predict treatment failure and survival. These findings provide a roadmap for the classification, risk stratification and mechanistic understanding of this disease.

Classification and risk stratification in T-lineage acute lymphoblastic leukemia.

Cure rates for patients with acute lymphoblastic leukemia (ALL) have improved markedly in recent decades, in part due to risk stratification incorporating leukemia genomics, response to treatment, and clinical features to be able to determine at diagnosis which patients are more likely to relapse or have refractory disease. While risk stratification is well-developed for patients with B lineage ALL (B-ALL), it remains challenging for those with T lineage ALL (T-ALL). Prognostic factors validated across clinical trials and real-world data in T-ALL include age, central nervous system (CNS) involvement, and minimal residual disease (MRD) response. Immunophenotype, including early T-cell precursor (ETP) ALL is widely used to classify T-ALL, but is not consistently associated with outcome in multivariable risk models. Historically, few genetic alterations have been consistently associated with outcome, but recent comprehensive, large-scale genomic profiling has identified multiple genetic subtypes and alterations associated with outcome independent of MRD. This review highlights ongoing efforts to identify reliable prognostic biomarkers and underscores the potential of genomics-based classification to guide future T-ALL treatment strategies.

Signalling input from divergent pathways subverts B cell transformation.

Malignant transformation of cells typically involves several genetic lesions, whose combined activity gives rise to cancer1. Here we analyse 1,148 patient-derived B-cell leukaemia (B-ALL) samples, and find that individual mutations do not promote leukaemogenesis unless they converge on one single oncogenic pathway that is characteristic of the differentiation stage of transformed B cells. Mutations that are not aligned with this central oncogenic driver activate divergent pathways and subvert transformation. Oncogenic lesions in B-ALL frequently mimic signalling through cytokine receptors at the pro-B-cell stage (via activation of the signal-transduction protein STAT5)2-4 or pre-B-cell receptors in more mature cells (via activation of the protein kinase ERK)5-8. STAT5- and ERK-activating lesions are found frequently, but occur together in only around 3% of cases (P = 2.2 × 10-16). Single-cell mutation and phospho-protein analyses reveal the segregation of oncogenic STAT5 and ERK activation to competing clones. STAT5 and ERK engage opposing biochemical and transcriptional programs that are orchestrated by the transcription factors MYC and BCL6, respectively. Genetic reactivation of the divergent (suppressed) pathway comes at the expense of the principal oncogenic driver and reverses transformation. Conversely, deletion of divergent pathway components accelerates leukaemogenesis. Thus, persistence of divergent signalling pathways represents a powerful barrier to transformation, while convergence on one principal driver defines a central event in leukaemia initiation. Pharmacological reactivation of suppressed divergent circuits synergizes strongly with inhibition of the principal oncogenic driver. Hence, reactivation of divergent pathways can be leveraged as a previously unrecognized strategy to enhance treatment responses.

Erythroid/megakaryocytic differentiation confers BCL-XL dependency and venetoclax resistance in acute myeloid leukemia.

Myeloid neoplasms with erythroid or megakaryocytic differentiation include pure erythroid leukemia, myelodysplastic syndrome with erythroid features, and acute megakaryoblastic leukemia (FAB M7) and are characterized by poor prognosis and limited treatment options. Here, we investigate the drug sensitivity landscape of these rare malignancies. We show that acute myeloid leukemia (AML) cells with erythroid or megakaryocytic differentiation depend on the antiapoptotic protein B-cell lymphoma (BCL)-XL, rather than BCL-2, using combined ex vivo drug sensitivity testing, genetic perturbation, and transcriptomic profiling. High-throughput screening of >500 compounds identified the BCL-XL-selective inhibitor A-1331852 and navitoclax as highly effective against erythroid/megakaryoblastic leukemia cell lines. In contrast, these AML subtypes were resistant to the BCL-2 inhibitor venetoclax, which is used clinically in the treatment of AML. Consistently, genome-scale CRISPR-Cas9 and RNAi screening data demonstrated the striking essentiality of BCL-XL-encoding BCL2L1 but not BCL2 or MCL1, for the survival of erythroid/megakaryoblastic leukemia cell lines. Single-cell and bulk transcriptomics of patient samples with erythroid and megakaryoblastic leukemias identified high BCL2L1 expression compared with other subtypes of AML and other hematological malignancies, where BCL2 and MCL1 were more prominent. BCL-XL inhibition effectively killed blasts in samples from patients with AML with erythroid or megakaryocytic differentiation ex vivo and reduced tumor burden in a mouse erythroleukemia xenograft model. Combining the BCL-XL inhibitor with the JAK inhibitor ruxolitinib showed synergistic and durable responses in cell lines. Our results suggest targeting BCL-XL as a potential therapy option in erythroid/megakaryoblastic leukemias and highlight an AML subgroup with potentially reduced sensitivity to venetoclax-based treatments.

Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro.

BACKGROUND: CALCRL (calcitonin receptor-like) protein is an important mediator of the endothelial fluid shear stress response, which is associated with the genetic risk of coronary artery disease. In this study, we functionally characterized the noncoding regulatory elements carrying coronary artery disease that risks single-nucleotide polymorphisms and studied their role in the regulation of CALCRL expression in endothelial cells. METHODS: To functionally characterize the coronary artery disease single-nucleotide polymorphisms harbored around the gene CALCRL, we applied an integrative approach encompassing statistical, transcriptional (RNA-seq), and epigenetic (ATAC-seq [transposase-accessible chromatin with sequencing], chromatin immunoprecipitation assay-quantitative polymerase chain reaction, and electromobility shift assay) analyses, alongside luciferase reporter assays, and targeted gene and enhancer perturbations (siRNA and clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) in human aortic endothelial cells. RESULTS: We demonstrate that the regulatory element harboring rs880890 exhibits high enhancer activity and shows significant allelic bias. The A allele was favored over the G allele, particularly under shear stress conditions, mediated through alterations in the HSF1 (heat shock factor 1) motif and binding. CRISPR deletion of rs880890 enhancer resulted in downregulation of CALCRL expression, whereas HSF1 knockdown resulted in a significant decrease in rs880890-enhancer activity and CALCRL expression. A significant decrease in HSF1 binding to the enhancer region in endothelial cells was observed under disturbed flow compared with unidirectional flow. CALCRL knockdown and variant perturbation experiments indicated the role of CALCRL in mediating eNOS (endothelial nitric oxide synthase), APLN (apelin), angiopoietin, prostaglandins, and EDN1 (endothelin-1) signaling pathways leading to a decrease in cell proliferation, tube formation, and NO production. CONCLUSIONS: Overall, our results demonstrate the existence of an endothelial-specific HSF (heat shock factor)-regulated transcriptional enhancer that mediates CALCRL expression. A better understanding of CALCRL gene regulation and the role of single-nucleotide polymorphisms in the modulation of CALCRL expression could provide important steps toward understanding the genetic regulation of shear stress signaling responses.

Computational textural mapping harmonises sampling variation and reveals multidimensional histopathological fingerprints.

BACKGROUND: Technical factors can bias H&E digital slides potentially compromising computational histopathology studies. Here, we hypothesised that sample quality and sampling variation can introduce even greater and undocumented technical fallacy. METHODS: Using The Cancer Genome Atlas (TCGA) clear-cell renal cell carcinoma (ccRCC) as a model disease, we annotated ~78,000 image tiles and trained deep learning models to detect histological textures and lymphocyte infiltration at the tumour core and its surrounding margin and correlated these with clinical, immunological, genomic, and transcriptomic profiles. RESULTS: The models reached 95% validation accuracy for classifying textures and 95% for lymphocyte infiltration enabling reliable profiling of ccRCC samples. We validated the lymphocyte-per-texture distributions in the Helsinki dataset (n = 64). Texture analysis indicated constitutive sampling bias by TCGA clinical centres and technically suboptimal samples. We demonstrate how computational texture mapping (CTM) can abrogate these issues by normalising textural variance. CTM-harmonised histopathological architecture resonated with both expected associations and novel molecular fingerprints. For instance, tumour fibrosis associated with histological grade, epithelial-to-mesenchymal transition, low mutation burden and metastasis. CONCLUSIONS: This study highlights texture-based standardisation to resolve technical bias in computational histopathology and understand the molecular basis of tissue architecture. All code, data and models are released as a community resource.

Integrated drug profiling and CRISPR screening identify essential pathways for CAR T-cell cytotoxicity.

Chimeric antigen receptor (CAR) T-cell therapy has proven effective in relapsed and refractory B-cell malignancies, but resistance and relapses still occur. Better understanding of mechanisms influencing CAR T-cell cytotoxicity and the potential for modulation using small-molecule drugs could improve current immunotherapies. Here, we systematically investigated druggable mechanisms of CAR T-cell cytotoxicity using >500 small-molecule drugs and genome-scale CRISPR-Cas9 loss-of-function screens. We identified several tyrosine kinase inhibitors that inhibit CAR T-cell cytotoxicity by impairing T-cell signaling transcriptional activity. In contrast, the apoptotic modulator drugs SMAC mimetics sensitized B-cell acute lymphoblastic leukemia and diffuse large B-cell lymphoma cells to anti-CD19 CAR T cells. CRISPR screens identified death receptor signaling through FADD and TNFRSF10B (TRAIL-R2) as a key mediator of CAR T-cell cytotoxicity and elucidated the RIPK1-dependent mechanism of sensitization by SMAC mimetics. Death receptor expression varied across genetic subtypes of B-cell malignancies, suggesting a link between mechanisms of CAR T-cell cytotoxicity and cancer genetics. These results implicate death receptor signaling as an important mediator of cancer cell sensitivity to CAR T-cell cytotoxicity, with potential for pharmacological targeting to enhance cancer immunotherapy. The screening data provide a resource of immunomodulatory properties of cancer drugs and genetic mechanisms influencing CAR T-cell cytotoxicity.

Profiling of Primary and Mature miRNA Expression in Atherosclerosis-Associated Cell Types.

[Figure: see text].

Data-driven characterization of molecular phenotypes across heterogeneous sample collections.

Existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on molecular profiles. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensionality reduction algorithm t-distributed stochastic neighbor embedding (t-SNE) with multi-study and multi-platform data on hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation, comparison of molecular disease subtypes identified from separate t-SNE representations, and characterization of the obtained clusters based on pathway databases and additional data. In this manner, we performed an integrative analysis across multi-omics acute myeloid leukemia studies. Our approach indicated new molecular subtypes with differential survival and drug responsiveness among samples lacking fusion genes, including a novel myelodysplastic syndrome-like cluster and a cluster characterized with CEBPA mutations and differential activity of the S-adenosylmethionine-dependent DNA methylation pathway. In summary, integration across multiple studies can help to identify novel molecular disease subtypes and generate insight into disease biology.

Analysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture.

Changes in mature microRNA (miRNA) levels that occur downstream of signaling cascades play an important role during human development and disease. However, the regulation of primary microRNA (pri-miRNA) genes remains to be dissected in detail. To address this, we followed a data-driven approach and developed a transcript identification, validation and quantification pipeline for characterizing the regulatory domains of pri-miRNAs. Integration of 92 nascent transcriptomes and multilevel data from cells arising from ecto-, endo- and mesoderm lineages reveals cell type-specific expression patterns, allows fine-resolution mapping of transcription start sites (TSS) and identification of candidate regulatory regions. We show that inter- and intragenic pri-miRNA transcripts span vast genomic regions and active TSS locations differ across cell types, exemplified by the mir-29a∼29b-1, mir-100∼let-7a-2∼125b-1 and miR-221∼222 clusters. Considering the presence of multiple TSS as an important regulatory feature at miRNA loci, we developed a strategy to quantify differential TSS usage. We demonstrate that the TSS activities associate with cell type-specific super-enhancers, differential stimulus responsiveness and higher-order chromatin structure. These results pave the way for building detailed regulatory maps of miRNA loci.

The Effects of Sequence Variation on Genome-wide NRF2 Binding--New Target Genes and Regulatory SNPs.

Transcription factor binding specificity is crucial for proper target gene regulation. Motif discovery algorithms identify the main features of the binding patterns, but the accuracy on the lower affinity sites is often poor. Nuclear factor E2-related factor 2 (NRF2) is a ubiquitous redox-activated transcription factor having a key protective role against endogenous and exogenous oxidant and electrophile stress. Herein, we decipher the effects of sequence variation on the DNA binding sequence of NRF2, in order to identify both genome-wide binding sites for NRF2 and disease-associated regulatory SNPs (rSNPs) with drastic effects on NRF2 binding. Interactions between NRF2 and DNA were studied using molecular modelling, and NRF2 chromatin immunoprecipitation-sequence datasets together with protein binding microarray measurements were utilized to study binding sequence variation in detail. The binding model thus generated was used to identify genome-wide binding sites for NRF2, and genomic binding sites with rSNPs that have strong effects on NRF2 binding and reside on active regulatory elements in human cells. As a proof of concept, miR-126-3p and -5p were identified as NRF2 target microRNAs, and a rSNP (rs113067944) residing on NRF2 target gene (Ferritin, light polypeptide, FTL) promoter was experimentally verified to decrease NRF2 binding and result in decreased transcriptional activity.

Dysregulation of the Keap1-Nrf2 pathway in cancer.

Accumulating evidence suggests that dysregulation of the Kelch-like ECH-associated protein 1 (Keap1)-nuclear factor E2-related factor 2 (Nrf2) pathway resulting in constitutively active Nrf2 and increased expression of cytoprotective Nrf2 target genes, has a pivotal role in cancer. Cancer cells are able to hijack the Keap1-Nrf2 system via multiple mechanisms leading to enhanced chemo- and radio-resistance and proliferation via metabolic reprogramming as well as inhibition of apoptosis. In this mini-review, we will describe the mechanisms leading to increased Nrf2 activity in cancer with a focus on the information achieved from large-scale multi-omics projects across various cancer types.

Sequential drug treatment targeting cell cycle and cell fate regulatory programs blocks non-genetic cancer evolution in acute lymphoblastic leukemia.

BACKGROUND: Targeted therapies exploiting vulnerabilities of cancer cells hold promise for improving patient outcome and reducing side-effects of chemotherapy. However, efficacy of precision therapies is limited in part because of tumor cell heterogeneity. A better mechanistic understanding of how drug effect is linked to cancer cell state diversity is crucial for identifying effective combination therapies that can prevent disease recurrence. RESULTS: Here, we characterize the effect of G2/M checkpoint inhibition in acute lymphoblastic leukemia (ALL) and demonstrate that WEE1 targeted therapy impinges on cell fate decision regulatory circuits. We find the highest inhibition of recovery of proliferation in ALL cells with KMT2A-rearrangements. Single-cell RNA-seq and ATAC-seq of RS4;11 cells harboring KMT2A::AFF1, treated with the WEE1 inhibitor AZD1775, reveal diversification of cell states, with a fraction of cells exhibiting strong activation of p53-driven processes linked to apoptosis and senescence, and disruption of a core KMT2A-RUNX1-MYC regulatory network. In this cell state diversification induced by WEE1 inhibition, a subpopulation transitions to a drug tolerant cell state characterized by activation of transcription factors regulating pre-B cell fate, lipid metabolism, and pre-BCR signaling in a reversible manner. Sequential treatment with BCR-signaling inhibitors dasatinib, ibrutinib, or perturbing metabolism by fatostatin or AZD2014 effectively counteracts drug tolerance by inducing cell death and repressing stemness markers. CONCLUSIONS: Collectively, our findings provide new insights into the tight connectivity of gene regulatory programs associated with cell cycle and cell fate regulation, and a rationale for sequential administration of WEE1 inhibitors with low toxicity inhibitors of pre-BCR signaling or metabolism.

Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes.

The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including NOTCH1 , which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.

Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk.

Acute lymphoblastic leukemia expressing the gamma delta T-cell receptor (γδ T-ALL) is a poorly understood disease. We studied 200 children with γδ T-ALL from 13 clinical study groups to understand the clinical and genetic features of this disease. We found age and genetic drivers were significantly associated with outcome. γδ T-ALL diagnosed in children under 3 years of age was extremely high-risk and enriched for genetic alterations that result in both LMO2 activation and STAG2 inactivation. Mechanistically, using patient samples and isogenic cell lines, we show that inactivation of STAG2 profoundly perturbs chromatin organization by altering enhancer-promoter looping, resulting in deregulation of gene expression associated with T-cell differentiation. High-throughput drug screening identified a vulnerability in DNA repair pathways arising from STAG2 inactivation, which can be targeted by poly(ADP-ribose) polymerase inhibition. These data provide a diagnostic framework for classification and risk stratification of pediatric γδ T-ALL. Significance: Patients with acute lymphoblastic leukemia expressing the gamma delta T-cell receptor under 3 years old or measurable residual disease ≥1% at end of induction showed dismal outcomes and should be classified as having high-risk disease. The STAG2/LMO2 subtype was enriched in this very young age group. STAG2 inactivation may perturb chromatin conformation and cell differentiation and confer vulnerability to poly(ADP-ribose) polymerase inhibition.

A pan-cancer analysis shows immunoevasive characteristics in NRF2 hyperactive squamous malignancies.

The NRF2 pathway is frequently activated in various cancer types, yet a comprehensive analysis of its effects across different malignancies is currently lacking. We developed a NRF2 activity metric and utilized it to conduct a pan-cancer analysis of oncogenic NRF2 signaling. We identified an immunoevasive phenotype where high NRF2 activity is associated with low interferon-gamma (IFNγ), HLA-I expression and T cell and macrophage infiltration in squamous malignancies of the lung, head and neck area, cervix and esophagus. Squamous NRF2 overactive tumors comprise a molecular phenotype with SOX2/TP63 amplification, TP53 mutation and CDKN2A loss. These immune cold NRF2 hyperactive diseases are associated with upregulation of immunomodulatory NAMPT, WNT5A, SPP1, SLC7A11, SLC2A1 and PD-L1. Based on our functional genomics analyses, these genes represent candidate NRF2 targets, suggesting direct modulation of the tumor immune milieu. Single-cell mRNA data shows that cancer cells of this subtype exhibit decreased expression of IFNγ responsive ligands, and increased expression of immunosuppressive ligands NAMPT, SPP1 and WNT5A that mediate signaling in intercellular crosstalk. In addition, we discovered that the negative relationship of NRF2 and immune cells are explained by stromal populations of lung squamous cell carcinoma, and this effect spans multiple squamous malignancies based on our molecular subtyping and deconvolution data.

Whole genome sequencing provides comprehensive genetic testing in childhood B-cell acute lymphoblastic leukaemia.

Childhood B-cell acute lymphoblastic leukaemia (B-ALL) is characterised by recurrent genetic abnormalities that drive risk-directed treatment strategies. Using current techniques, accurate detection of such aberrations can be challenging, due to the rapidly expanding list of key genetic abnormalities. Whole genome sequencing (WGS) has the potential to improve genetic testing, but requires comprehensive validation. We performed WGS on 210 childhood B-ALL samples annotated with clinical and genetic data. We devised a molecular classification system to subtype these patients based on identification of key genetic changes in tumour-normal and tumour-only analyses. This approach detected 294 subtype-defining genetic abnormalities in 96% (202/210) patients. Novel genetic variants, including fusions involving genes in the MAP kinase pathway, were identified. WGS results were concordant with standard-of-care methods and whole transcriptome sequencing (WTS). We expanded the catalogue of genetic profiles that reliably classify PAX5alt and ETV6::RUNX1-like subtypes. Our novel bioinformatic pipeline improved detection of DUX4 rearrangements (DUX4-r): a good-risk B-ALL subtype with high survival rates. Overall, we have validated that WGS provides a standalone, reliable genetic test to detect all subtype-defining genetic abnormalities in B-ALL, accurately classifying patients for the risk-directed treatment stratification, while simultaneously performing as a research tool to identify novel disease biomarkers.