Single nucleotide variants in nuclear pore complex disassembly pathway associated with poor survival in osteosarcoma.

Introduction: The bone tumor, osteosarcoma, remains challenging to treat in children and young adults, especially when patients present with metastatic disease. Developing new therapies based on genomic data from sequencing projects has proven difficult given the lack of recurrent genetic lesions across tumors. MYC overexpression has been associated with poor outcomes in osteosarcoma. However, other genomic markers of disease severity are lacking. Materials and Methods: We utilized whole genome sequencing of 106 tumors and matched normal controls in order to define genomic characteristics that correlate with overall survival. Single nucleotide variants were overlaid onto annotated molecular pathways in order to define aberrant pathway signatures specific to aggressive osteosarcoma. Additionally, we calculated differential gene expression in a subsample of 71 tumors. Differentially expressed genes were then queried for known MYC-responsive genes. Results: Molecular pathways specific to nuclear pore complex disassembly (NPCD) show significant correlation with poor overall survival in osteosarcoma when mutations were present. Genes involved in immune response and immune regulation are enriched in the differential expression analysis of samples with and without NPCD pathway aberrations. Furthermore, neither MYC nor MYC-responsive genes show differential expression between NPCD-aberrant and non-aberrant groups. The NPCD pathway mutations are dominated by regulatory region variants rather than protein-altering mutations, suggesting that dysregulation of genetic regulatory networks may be the underlying mechanism for their relation to osteosarcoma phenotype. Discussion: Overall survival is significantly worse in patients whose tumors show aberrations in the NPCD pathway. Moreover, this difference in survival is not driven by MYC-overexpression, suggesting a novel mechanism for some aggressive osteosarcomas. These findings add light to the evolving understanding of the drivers of osteosarcoma and may aid in the search for new treatments based on patient-specific genetic data.

Graph Structured Neural Networks for Perturbation Biology.

Computational modeling of perturbation biology identifies relationships between molecular elements and cellular response, and an accurate understanding of these systems will support the full realization of precision medicine. Traditional deep learning, while often accurate in predicting response, is unlikely to capture the true sequence of involved molecular interactions. Our work is motivated by two assumptions: 1) Methods that encourage mechanistic prediction logic are likely to be more trustworthy, and 2) problem-specific algorithms are likely to outperform generic algorithms. We present an alternative to Graph Neural Networks (GNNs) termed Graph Structured Neural Networks (GSNN), which uses cell signaling knowledge, encoded as a graph data structure, to add inductive biases to deep learning. We apply our method to perturbation biology using the LINCS L1000 dataset and literature-curated molecular interactions. We demonstrate that GSNNs outperform baseline algorithms in several prediction tasks, including 1) perturbed expression, 2) cell viability of drug combinations, and 3) disease-specific drug prioritization. We also present a method called GSNNExplainer to explain GSNN predictions in a biologically interpretable form. This work has broad application in basic biological research and pre-clincal drug repurposing. Further refinement of these methods may produce trustworthy models of drug response suitable for use as clinical decision aids. Availability and implementation: Our implementation of the GSNN method is available at https://github.com/nathanieljevans/GSNN. All data used in this work is publicly available.

Genetic loci regulate Sarbecovirus pathogenesis: A comparison across mice and humans.

Coronavirus (CoV) cause considerable morbidity and mortality in humans and other mammals, as evidenced by the emergence of Severe Acute Respiratory CoV (SARS-CoV) in 2003, Middle East Respiratory CoV (MERS-CoV) in 2012, and SARS-CoV-2 in 2019. Although poorly characterized, natural genetic variation in human and other mammals modulate virus pathogenesis, as reflected by the spectrum of clinical outcomes ranging from asymptomatic infections to lethal disease. Using multiple human epidemic and zoonotic Sarbecoviruses, coupled with murine Collaborative Cross genetic reference populations, we identify several dozen quantitative trait loci that regulate SARS-like group-2B CoV pathogenesis and replication. Under a Chr4 QTL, we deleted a candidate interferon stimulated gene, Trim14 which resulted in enhanced SARS-CoV titers and clinical disease, suggesting an antiviral role during infection. Importantly, about 60 % of the murine QTL encode susceptibility genes identified as priority candidates from human genome-wide association studies (GWAS) studies after SARS-CoV-2 infection, suggesting that similar selective forces have targeted analogous genes and pathways to regulate Sarbecovirus disease across diverse mammalian hosts. These studies provide an experimental platform in rodents to investigate the molecular-genetic mechanisms by which potential cross mammalian susceptibility loci and genes regulate type-specific and cross-SARS-like group 2B CoV replication, immunity, and pathogenesis in rodent models. Our study also provides a paradigm for identifying susceptibility loci for other highly heterogeneous and virulent viruses that sporadically emerge from zoonotic reservoirs to plague human and animal populations.

Just how transformative will AI/ML be for immuno-oncology?

Immuno-oncology involves the study of approaches which harness the patient's immune system to fight malignancies. Immuno-oncology, as with every other biomedical and clinical research field as well as clinical operations, is in the midst of technological revolutions, which vastly increase the amount of available data. Recent advances in artificial intelligence and machine learning (AI/ML) have received much attention in terms of their potential to harness available data to improve insights and outcomes in many areas including immuno-oncology. In this review, we discuss important aspects to consider when evaluating the potential impact of AI/ML applications in the clinic. We highlight four clinical/biomedical challenges relevant to immuno-oncology and how they may be able to be addressed by the latest advancements in AI/ML. These challenges include (1) efficiency in clinical workflows, (2) curation of high-quality image data, (3) finding, extracting and synthesizing text knowledge as well as addressing, and (4) small cohort size in immunotherapeutic evaluation cohorts. Finally, we outline how advancements in reinforcement and federated learning, as well as the development of best practices for ethical and unbiased data generation, are likely to drive future innovations.

The TLK-ASF1 histone chaperone pathway plays a critical role in IL-1b-mediated AML progression.

Identifying and targeting microenvironment-driven pathways that are active across acute myeloid leukemia (AML) genetic subtypes should allow the development of more broadly effective therapies. The pro-inflammatory cytokine IL-1 is abundant in the AML microenvironment and promotes leukemic growth. Through RNA-sequencing analysis, we identify that IL-1 upregulated ASF1B (anti-silencing function-1B), a histone chaperone, in AML progenitors compared to healthy progenitors. ASF1B, along with its paralogous protein ASF1A recruits H3-H4 histones onto the replication fork during S-phase, a process regulated by tousled-like kinase 1 and 2 (TLKs). While ASF1s and TLKs are known to be overexpressed in multiple solid tumors and associated with poor prognosis, their functional roles in hematopoiesis and inflammation-driven leukemia remain unexplored. In this study, we identify that ASF1s and TLKs are over-expressed in multiple genetic subtypes of AML. We demonstrate that depletion of ASF1s significantly reduces leukemic cell growth in both in vitro and in vivo models using human cells. Using a murine model we show that overexpression of ASF1B accelerates leukemia progression. Moreover, Asf1b or Tlk2 deletion delayed leukemia progression while these proteins are dispensable for normal hematopoiesis. Through proteomics and phosphoproteomics analyses, we uncover that the TLK-ASF1 pathway promotes leukemogenesis by impacting the cell cycle and DNA damage pathways. Collectively, our findings identify the TLK1-ASF1 pathway as a novel mediator of inflammatory signaling and a promising therapeutic target for AML treatment across diverse genetic subtypes. Selective inhibition of this pathway offers potential opportunities to intervene effectively, address intratumoral heterogeneity, and ultimately improve clinical outcomes in AML.

Targeting CCL2/CCR2 signaling overcomes MEK inhibitor resistance in Acute Myeloid Leukemia.

PURPOSE: Emerging evidence underscores the critical role of extrinsic factors within the microenvironment in protecting leukemia cells from therapeutic interventions, driving disease progression, and promoting drug resistance in acute myeloid leukemia (AML). This emphasizes the need for the identification of targeted therapies that inhibit intrinsic and extrinsic signaling to overcome drug resistance in AML. EXPERIMENTAL DESIGN: We performed a comprehensive analysis utilizing a cohort of ~300 AML patient samples. This analysis encompassed the evaluation of secreted cytokines/growth factors, gene expression, and ex vivo drug sensitivity to small molecules. Our investigation pinpointed a notable association between elevated levels of CCL2 and diminished sensitivity to the MEK inhibitors. We validated this association through loss-of-function and pharmacological inhibition studies. Further, we deployed global phosphoproteomics and CRISPR/Cas9 screening to identify the mechanism of CCR2-mediated MEKi resistance in AML. RESULTS: Our multifaceted analysis unveiled that CCL2 activates multiple pro-survival pathways, including MAPK and cell cycle regulation in MEKi-resistant cells. Employing combination strategies to simultaneously target these pathways heightened growth inhibition in AML cells. Both genetic and pharmacological inhibition of CCR2 sensitized AML cells to trametinib, suppressing proliferation while enhancing apoptosis. These findings underscore a new role for CCL2 in MEKi resistance, offering combination therapies as an avenue to circumvent this resistance. CONCLUSIONS: Our study demonstrates a compelling rationale for translating CCL2/CCR2 axis inhibitors in combination with MEK pathway-targeting therapies, as a potent strategy for combating drug resistance in AML. This approach has the potential to enhance the efficacy of treatments to improve AML patient outcomes.

Identification of Cellular Interactions in the Tumor Immune Microenvironment Underlying CD8 T Cell Exhaustion.

While immune checkpoint inhibitors show success in treating a subset of patients with certain late-stage cancers, these treatments fail in many other patients as a result of mechanisms that have yet to be fully characterized. The process of CD8 T cell exhaustion, by which T cells become dysfunctional in response to prolonged antigen exposure, has been implicated in immunotherapy resistance. Single-cell RNA sequencing (scRNA-seq) produces an abundance of data to analyze this process; however, due to the complexity of the process, contributions of other cell types to a process within a single cell type cannot be simply inferred. We constructed an analysis framework to first rank human skin tumor samples by degree of exhaustion in tumor-infiltrating CD8 T cells and then identify immune cell type-specific gene-regulatory network patterns significantly associated with T cell exhaustion. Using this framework, we further analyzed scRNA-seq data from human tumor and chronic viral infection samples to compare the T cell exhaustion process between these two contexts. In doing so, we identified transcription factor activity in the macrophages of both tissue types associated with this process. Our framework can be applied beyond the tumor immune microenvironment to any system involving cell-cell communication, facilitating insights into key biological processes that underpin the effective treatment of cancer and other complicated diseases.

Proximity-dependent mapping of the HCMV US28 interactome identifies RhoGEF signaling as a requirement for efficient viral reactivation.

Human cytomegalovirus (HCMV) encodes multiple putative G protein-coupled receptors (GPCRs). US28 functions as a viral chemokine receptor and is expressed during both latent and lytic phases of virus infection. US28 actively promotes cellular migration, transformation, and plays a major role in mediating viral latency and reactivation; however, knowledge about the interaction partners involved in these processes is still incomplete. Herein, we utilized a proximity-dependent biotinylating enzyme (TurboID) to characterize the US28 interactome when expressed in isolation, and during both latent (CD34+ hematopoietic progenitor cells) and lytic (fibroblasts) HCMV infection. Our analyses indicate that the US28 signalosome converges with RhoA and EGFR signal transduction pathways, sharing multiple mediators that are major actors in processes such as cellular proliferation and differentiation. Integral members of the US28 signaling complex were validated in functional assays by immunoblot and small-molecule inhibitors. Importantly, we identified RhoGEFs as key US28 signaling intermediaries. In vitro latency and reactivation assays utilizing primary CD34+ hematopoietic progenitor cells (HPCs) treated with the small-molecule inhibitors Rhosin or Y16 indicated that US28 -RhoGEF interactions are required for efficient viral reactivation. These findings were recapitulated in vivo using a humanized mouse model where inhibition of RhoGEFs resulted in a failure of the virus to reactivate. Together, our data identifies multiple new proteins in the US28 interactome that play major roles in viral latency and reactivation, highlights the utility of proximity-sensor labeling to characterize protein interactomes, and provides insight into targets for the development of novel anti-HCMV therapeutics.

Clinical Correlates of Venetoclax-Based Combination Sensitivities to Augment Acute Myeloid Leukemia Therapy.

The BCL2 inhibitor venetoclax combined with the hypomethylating agent azacytidine shows significant clinical benefit in a subset of patients with acute myeloid leukemia (AML); however, resistance limits response and durability. We prospectively profiled the ex vivo activity of 25 venetoclax-inclusive combinations on primary AML patient samples to identify those with improved potency and synergy compared with venetoclax + azacytidine (Ven + azacytidine). Combination sensitivities correlated with tumor cell state to discern three patterns: primitive selectivity resembling Ven + azacytidine, monocytic selectivity, and broad efficacy independent of cell state. Incorporation of immunophenotype, mutation, and cytogenetic features further stratified combination sensitivity for distinct patient subtypes. We dissect the biology underlying the broad, cell state-independent efficacy for the combination of venetoclax plus the JAK1/2 inhibitor ruxolitinib. Together, these findings support opportunities for expanding the impact of venetoclax-based drug combinations in AML by leveraging clinical and molecular biomarkers associated with ex vivo responses. SIGNIFICANCE: By mapping drug sensitivity data to clinical features and tumor cell state, we identify novel venetoclax combinations targeting patient subtypes who lack sensitivity to Ven + azacytidine. This provides a framework for a taxonomy of AML informed by readily available sets of clinical and genetic features obtained as part of standard care. See related commentary by Becker, p. 437 . This article is featured in Selected Articles from This Issue, p. 419.

Biology-inspired graph neural network encodes reactome and reveals biochemical reactions of disease.

Functional heterogeneity of healthy human tissues complicates interpretation of molecular studies, impeding precision therapeutic target identification and treatment. Considering this, we generated a graph neural network with Reactome-based architecture and trained it using 9,115 samples from Genotype-Tissue Expression (GTEx). Our graph neural network (GNN) achieves adjusted Rand index (ARI) = 0.7909, while a Resnet18 control model achieves ARI = 0.7781, on 370 held-out healthy human tissue samples from The Cancer Genome Atlas (TCGA), despite the Resnet18 using over 600 times the parameters. Our GNN also succeeds in separating 83 healthy skin samples from 95 lesional psoriasis samples, revealing that upregulation of 26S- and NUB1-mediated degradation of NEDD8, UBD, and their conjugates is central to the largest perturbed reaction network component in psoriasis. We show that our results are not discoverable using traditional differential expression and hypergeometric pathway enrichment analyses yet are supported by separate human multi-omics and small-molecule mouse studies, suggesting future molecular disease studies may benefit from similar GNN analytical approaches.

Immune cell proportions correlate with clinicogenomic features and ex vivo drug responses in acute myeloid leukemia.

Introduction: The implementation of small-molecule and immunotherapies in acute myeloid leukemia (AML) has been challenging due to genetic and epigenetic variability amongst patients. There are many potential mechanisms by which immune cells could influence small-molecule or immunotherapy responses, yet, this area remains understudied. Methods: Here we performed cell type enrichment analysis from over 560 AML patient bone marrow and peripheral blood samples from the Beat AML dataset to describe the functional immune landscape of AML. Results: We identify multiple cell types that significantly correlate with AML clinical and genetic features, and we also observe significant correlations of immune cell proportions with ex vivo small-molecule and immunotherapy responses. Additionally, we generated a signature of terminally exhausted T cells (Tex) and identified AML with high monocytic proportions as strongly correlating with increased proportions of these immunosuppressive T cells. Discussion: Our work, which is accessible through a new "Cell Type" module in our visualization platform (Vizome; http://vizome.org/), can be leveraged to investigate potential contributions of different immune cells on many facets of the biology of AML.

Disruption of the MYC Superenhancer Complex by Dual Targeting of FLT3 and LSD1 in Acute Myeloid Leukemia.

Mutations in Fms-like tyrosine kinase 3 (FLT3) are common drivers in acute myeloid leukemia (AML) yet FLT3 inhibitors only provide modest clinical benefit. Prior work has shown that inhibitors of lysine-specific demethylase 1 (LSD1) enhance kinase inhibitor activity in AML. Here we show that combined LSD1 and FLT3 inhibition induces synergistic cell death in FLT3-mutant AML. Multi-omic profiling revealed that the drug combination disrupts STAT5, LSD1, and GFI1 binding at the MYC blood superenhancer, suppressing superenhancer accessibility as well as MYC expression and activity. The drug combination simultaneously results in the accumulation of repressive H3K9me1 methylation, an LSD1 substrate, at MYC target genes. We validated these findings in 72 primary AML samples with the nearly every sample demonstrating synergistic responses to the drug combination. Collectively, these studies reveal how epigenetic therapies augment the activity of kinase inhibitors in FLT3-ITD (internal tandem duplication) AML. IMPLICATIONS: This work establishes the synergistic efficacy of combined FLT3 and LSD1 inhibition in FLT3-ITD AML by disrupting STAT5 and GFI1 binding at the MYC blood-specific superenhancer complex.

Secondary fusion proteins as a mechanism of BCR::ABL1 kinase-independent resistance in chronic myeloid leukaemia.

Drug resistance in chronic myeloid leukaemia (CML) may occur via mutations in the causative BCR::ABL1 fusion or BCR::ABL1-independent mechanisms. We analysed 48 patients with BCR::ABL1-independent resistance for the presence of secondary fusion genes by RNA sequencing. We identified 10 of the most frequently detected secondary fusions in 21 patients. Validation studies, cell line models, gene expression analysis and drug screening revealed differences with respect to proliferation rate, differentiation and drug sensitivity. Notably, expression of RUNX1::MECOM led to resistance to ABL1 tyrosine kinase inhibitors in vitro. These results suggest secondary fusions contribute to BCR::ABL1-independent resistance and may be amenable to combined therapies.

Comparison and validation of the 2022 European LeukemiaNet guidelines in acute myeloid leukemia.

Risk stratification in acute myeloid leukemia (AML) remains principle in survival prognostication and treatment selection. The 2022 European LeukemiaNet (ELN) recommendations were recently published, with notable updates to risk group assignment. The complexity of risk stratification and comparative outcomes between the 2022 and 2017 ELN guidelines remains unknown. This comparative analysis evaluated outcomes between the 2017 and 2022 ELN criteria in patients enrolled within the multicenter Beat AML cohort. Five hundred thirteen patients were included. Most patients had 1 or 2 ELN risk-defining abnormalities. In patients with ≥2 ELN risk-defining mutations, 44% (n = 132) had mutations spanning multiple ELN risk categories. Compared with ELN 2017 criteria, the updated ELN 2022 guidelines changed the assigned risk group in 15% of patients, including 10%, 26%, and 6% of patients categorized as being at ELN 2017 favorable-, intermediate-, and adverse-risk, respectively. The median overall survival across ELN 2022 favorable-, intermediate-, and adverse-risk groups was not reached, 16.8, and 9.7 months, respectively. The ELN 2022 guidelines more accurately stratified survival between patients with intermediate- or adverse-risk AML treated with induction chemotherapy compared with ELN 2017 guidelines. The updated ELN 2022 guidelines better stratify survival between patients with intermediate- or adverse-risk AML treated with induction chemotherapy. The increased complexity of risk stratification with inclusion of additional cytogenetic and molecular aberrations necessitates clinical workflows simplifying risk stratification.

Biology and medicine in the landscape of quantum advantages.

Quantum computing holds substantial potential for applications in biology and medicine, spanning from the simulation of biomolecules to machine learning methods for subtyping cancers on the basis of clinical features. This potential is encapsulated by the concept of a quantum advantage, which is contingent on a reduction in the consumption of a computational resource, such as time, space or data. Here, we distill the concept of a quantum advantage into a simple framework to aid researchers in biology and medicine pursuing the development of quantum applications. We then apply this framework to a wide variety of computational problems relevant to these domains in an effort to (i) assess the potential of practical advantages in specific application areas and (ii) identify gaps that may be addressed with novel quantum approaches. In doing so, we provide an extensive survey of the intersection of biology and medicine with the current landscape of quantum algorithms and their potential advantages. While we endeavour to identify specific computational problems that may admit practical advantages throughout this work, the rapid pace of change in the fields of quantum computing, classical algorithms and biological research implies that this intersection will remain highly dynamic for the foreseeable future.

Comprehensive molecular characterization of a rare case of Philadelphia chromosome-positive acute myeloid leukemia.

The Philadelphia chromosome (Ph) resulting from the t(9;22) translocation generates the oncogenic BCR::ABL1 fusion protein that is most commonly associated with chronic myeloid leukemia (CML) and Ph-positive (Ph+) acute lymphoblastic leukemia (ALL). There are also rare instances of patients (≤1%) with newly diagnosed acute myeloid leukemia (AML) that harbor this translocation (Paietta et al., Leukemia 12: 1881 [1998]; Keung et al., Leuk Res 28: 579 [2004]; Soupir et al., Am J Clin Pathol 127: 642 [2007]). AML with BCR::ABL has only recently been provisionally classified by the World Health Organization as a diagnostically distinct subtype of AML. Discernment from the extremely close differential diagnosis of myeloid blast crisis CML is challenging, largely relying on medical history rather than clinical characteristics (Arber et al., Blood 127: 2391 [2016]). To gain insight into the genomic features underlying the evolution of AML with BCR::ABL, we identified a patient presenting with a high-risk myelodysplastic syndrome that acquired a BCR::ABL alteration after a peripheral blood stem cell transplant. Serial samples were collected and analyzed using whole-exome sequencing, RNA-seq, and ex vivo functional drug screens. Persistent subclones were identified, both at diagnosis and at relapse, including an SF3B1p.Lys700Glu mutation that later cooccurred with an NRASp.Gly12Cys mutation. Functional ex vivo drug screening performed on primary patient cells suggested that combination therapies of ABL1 with RAS or PI3K pathway inhibitors could have augmented the patient's response throughout the course of disease. Together, our findings argue for the importance of genomic profiling and the potential value of ABL1 inhibitor-inclusive combination treatment strategies in patients with this rare disease.

Targeted RNA editing in brainstem alleviates respiratory dysfunction in a mouse model of Rett syndrome.

Rett syndrome is a neurological disease due to loss-of-function mutations in the transcription factor, Methyl CpG binding protein 2 (MECP2). Because overexpression of endogenous MECP2 also causes disease, we have exploited a targeted RNA-editing approach to repair patient mutations where levels of MECP2 protein will never exceed endogenous levels. Here, we have constructed adeno-associated viruses coexpressing a bioengineered wild-type ADAR2 catalytic domain (Editasewt) and either Mecp2-targeting or nontargeting gfp RNA guides. The viruses are introduced systemically into male mice containing a guanosine to adenosine mutation that eliminates MeCP2 protein and causes classic Rett syndrome in humans. We find that in the mutant mice injected with the Mecp2-targeting virus, the brainstem exhibits the highest RNA-editing frequency compared to other brain regions. The efficiency is sufficient to rescue MeCP2 expression and function in the brainstem of mice expressing the Mecp2-targeting virus. Correspondingly, we find that abnormal Rett-like respiratory patterns are alleviated, and survival is prolonged, compared to mice injected with the control gfp guide virus. The levels of RNA editing among most brain regions corresponds to the distribution of guide RNA rather than Editasewt. Our results provide evidence that a targeted RNA-editing approach can alleviate a hallmark symptom in a mouse model of human disease.

Luxeptinib (CG-806) Targets FLT3 and Clusters of Kinases Operative in Acute Myeloid Leukemia.

Luxeptinib (CG-806) simultaneously targets FLT3 and select other kinase pathways operative in myeloid malignancies. We investigated the range of kinases it inhibits, its cytotoxicity landscape ex vivo with acute myeloid leukemia (AML) patient samples, and its efficacy in xenograft models. Luxeptinib inhibits wild-type (WT) and many of the clinically relevant mutant forms of FLT3 at low nanomolar concentrations. It is a more potent inhibitor of the activity of FLT3-internal tandem duplication, FLT3 kinase domain and gatekeeper mutants than against WT FLT3. Broad kinase screens disclosed that it also inhibits other kinases that can drive oncogenic signaling and rescue pathways, but spares kinases known to be associated with clinical toxicity. In vitro profiling of luxeptinib against 186 AML fresh patient samples demonstrated greater potency relative to other FLT3 inhibitors, including cases with mutations in FLT3, isocitrate dehydrogenase-1/2, ASXL1, NPM1, SRSF2, TP53, or RAS, and activity was documented in a xenograft AML model. Luxeptinib administered continuously orally every 12 hours at a dose that yielded a mean Cmin plasma concentration of 1.0 ± 0.3 µmol/L (SEM) demonstrated strong antitumor activity but no myelosuppression or evidence of tissue damage in mice or dogs in acute toxicology studies. On the basis of these studies, luxeptinib was advanced into a phase I trial for patients with AML and myelodysplastic/myeloproliferative neoplasms.