The Wnt-dependent master regulator NKX1-2 controls mouse pre-implantation development.

Embryo size, specification, and homeostasis are regulated by a complex gene regulatory and signaling network. Here we used gene expression signatures of Wnt-activated mouse embryonic stem cell (mESC) clones to reverse engineer an mESC regulatory network. We identify NKX1-2 as a novel master regulator of preimplantation embryo development. We find that Nkx1-2 inhibition reduces nascent RNA synthesis, downregulates genes controlling ribosome biogenesis, RNA translation, and transport, and induces severe alteration of nucleolus structure, resulting in the exclusion of RNA polymerase I from nucleoli. In turn, NKX1-2 loss of function leads to chromosome missegregation in the 2- to 4-cell embryo stages, severe decrease in blastomere numbers, alterations of tight junctions (TJs), and impairment of microlumen coarsening. Overall, these changes impair the blastocoel expansion-collapse cycle and embryo cavitation, leading to altered lineage specification and developmental arrest.

Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium.

The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have implemented an efficient integrative experimental and computational framework leveraging the systematic generation and analysis of drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Protein activity-based analyses revealed highly reproducible, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide polypharmacology map, characterization of MoA-related drug clusters and off-target effects, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins. The proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, could help support more systematic and quantitative approaches to precision oncology.

The relative impact of parental and current environment on plant transcriptomes depends on type of stress and genotype.

Through developmental plasticity, an individual organism integrates influences from its immediate environment with those due to the environment of its parents. While both effects on phenotypes are well documented, their relative impact has been little studied in natural systems, especially at the level of gene expression. We examined this issue in four genotypes of the annual plant Persicaria maculosa by varying two key resources-light and soil moisture-in both generations. Transcriptomic analyses showed that the relative effects of parent and offspring environment on gene expression (i.e. the number of differentially expressed transcripts, DETs) varied both for the two types of resource stress and among genotypes. For light, immediate environment induced more DETs than parental environment for all genotypes, although the precise proportion of parental versus immediate DETs varied among genotypes. By contrast, the relative effect of soil moisture varied dramatically among genotypes, from 8-fold more DETs due to parental than immediate conditions to 10-fold fewer. These findings provide evidence at the transcriptomic level that the relative impacts of parental and immediate environment on the developing organism may depend on the environmental factor and vary strongly among genotypes, providing potential for the interplay of these developmental influences to evolve.

OncoLoop: A Network-Based Precision Cancer Medicine Framework.

Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide. SIGNIFICANCE: OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.

Network-based assessment of HDAC6 activity predicts preclinical and clinical responses to the HDAC6 inhibitor ricolinostat in breast cancer.

Inhibiting individual histone deacetylase (HDAC) is emerging as well-tolerated anticancer strategy compared with pan-HDAC inhibitors. Through preclinical studies, we demonstrated that the sensitivity to the leading HDAC6 inhibitor (HDAC6i) ricolinstat can be predicted by a computational network-based algorithm (HDAC6 score). Analysis of ~3,000 human breast cancers (BCs) showed that ~30% of them could benefice from HDAC6i therapy. Thus, we designed a phase 1b dose-escalation clinical trial to evaluate the activity of ricolinostat plus nab-paclitaxel in patients with metastatic BC (MBC) (NCT02632071). Study results showed that the two agents can be safely combined, that clinical activity is identified in patients with HR+/HER2- disease and that the HDAC6 score has potential as predictive biomarker. Analysis of other tumor types also identified multiple cohorts with predicted sensitivity to HDAC6i's. Mechanistically, we have linked the anticancer activity of HDAC6i's to their ability to induce c-Myc hyperacetylation (ac-K148) promoting its proteasome-mediated degradation in sensitive cancer cells.

A Patient-to-Model-to-Patient (PMP) Cancer Drug Discovery Protocol for Identifying and Validating Therapeutic Agents Targeting Tumor Regulatory Architecture.

The current Achilles heel of cancer drug discovery is the inability to forge precise and predictive connections among mechanistic drivers of the cancer cell state, therapeutically significant molecular targets, effective drugs, and responsive patient subgroups. Although advances in molecular biology have helped identify molecular markers and stratify patients into molecular subtypes, these associational strategies typically fail to provide a mechanistic rationale to identify cancer vulnerabilities. Recently, integrative systems biology methodologies have been used to reverse engineer cellular networks and identify master regulators (MRs), proteins whose activity is both necessary and sufficient to implement phenotypic states under physiological and pathological conditions, which are organized into highly interconnected regulatory modules called tumor checkpoints. Because of their functional relevance, MRs represent ideal pharmacological targets and biomarkers. Here, we present a six-step patient-to-model-to-patient protocol that employs computational and experimental methodologies to reconstruct and interrogate the regulatory logic of human cancer cells for identifying and therapeutically targeting the tumor checkpoint with novel as well as existing pharmacological agents. This protocol systematically identifies, from specific patient tumor samples, the MRs that comprise the tumor checkpoint. Then, it identifies in vitro and in vivo models that, by recapitulating the patient's tumor checkpoint, constitute the appropriate cell lines and xenografts to further elucidate the tissue context-specific drug mechanism of action (MOA) and permit precise, biomarker-based preclinical validations of drug efficacy. The combination of determination of a drug's context-specific MOA and precise identification of patients' tumor checkpoints provides a personalized, mechanism-based biomarker to enrich prospective clinical trials with patients likely to respond. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

A model for network-based identification and pharmacological targeting of aberrant, replication-permissive transcriptional programs induced by viral infection.

SARS-CoV-2 hijacks the host cell transcriptional machinery to induce a phenotypic state amenable to its replication. Here we show that analysis of Master Regulator proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2 in infected cells revealed coordinated inactivation of Master Regulators enriched in physical interactions with SARS-CoV-2 proteins, suggesting their mechanistic role in maintaining a host cell state refractory to virus replication. To test their functional relevance, we measured SARS-CoV-2 replication in epithelial cells treated with drugs predicted to activate the entire repertoire of repressed Master Regulators, based on their experimentally elucidated, context-specific mechanism of action. Overall, 15 of the 18 drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 replication, without affecting cell viability. This model for host-directed pharmacological therapy is fully generalizable and can be deployed to identify drugs targeting host cell-based Master Regulator signatures induced by virtually any pathogen.

A Model for Network-Based Identification and Pharmacological Targeting of Aberrant, Replication-Permissive Transcriptional Programs Induced by Viral Infection.

Precise characterization and targeting of host cell transcriptional machinery hijacked by viral infection remains challenging. Here, we show that SARS-CoV-2 hijacks the host cell transcriptional machinery to induce a phenotypic state amenable to its replication. Specifically, analysis of Master Regulator (MR) proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2 in infected cells revealed coordinated inactivation of MRs enriched in physical interactions with SARS-CoV-2 proteins, suggesting their mechanistic role in maintaining a host cell state refractory to virus replication. To test their functional relevance, we measured SARS-CoV-2 replication in epithelial cells treated with drugs predicted to activate the entire repertoire of repressed MRs, based on their experimentally elucidated, context-specific mechanism of action. Overall, >80% of drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 replication, without affecting cell viability. This model for host-directed pharmacological therapy is fully generalizable and can be deployed to identify drugs targeting host cell-based MR signatures induced by virtually any pathogen.

A Phase II Study of the Efficacy and Safety of Oral Selinexor in Recurrent Glioblastoma.

PURPOSE: Selinexor is an oral selective inhibitor of exportin-1 (XPO1) with efficacy in various solid and hematologic tumors. We assessed intratumoral penetration, safety, and efficacy of selinexor monotherapy for recurrent glioblastoma. PATIENTS AND METHODS: Seventy-six adults with Karnofsky Performance Status ≥ 60 were enrolled. Patients undergoing cytoreductive surgery received up to three selinexor doses (twice weekly) preoperatively (Arm A; n = 8 patients). Patients not undergoing surgery received 50 mg/m2 (Arm B, n = 24), or 60 mg (Arm C, n = 14) twice weekly, or 80 mg once weekly (Arm D; n = 30). Primary endpoint was 6-month progression-free survival rate (PFS6). RESULTS: Median selinexor concentrations in resected tumors from patients receiving presurgical selinexor was 105.4 nmol/L (range 39.7-291 nmol/L). In Arms B, C, and D, respectively, the PFS6 was 10% [95% confidence interval (CI), 2.79-35.9], 7.7% (95% CI, 1.17-50.6), and 17% (95% CI, 7.78-38.3). Measurable reduction in tumor size was observed in 19 (28%) and RANO-response rate overall was 8.8% [Arm B, 8.3% (95% CI, 1.0-27.0); C: 7.7% (95% CI, 0.2-36.0); D: 10% (95% CI, 2.1-26.5)], with one complete and two durable partial responses in Arm D. Serious adverse events (AEs) occurred in 26 (34%) patients; 1 (1.3%) was fatal. The most common treatment-related AEs were fatigue (61%), nausea (59%), decreased appetite (43%), and thrombocytopenia (43%), and were manageable by supportive care and dose modification. Molecular studies identified a signature predictive of response (AUC = 0.88). CONCLUSIONS: At 80 mg weekly, single-agent selinexor induced responses and clinically relevant PFS6 with manageable side effects requiring dose reductions. Ongoing trials are evaluating safety and efficacy of selinexor in combination with other therapies for newly diagnosed or recurrent glioblastoma.

Alignment-free methods for polyploid genomes: Quick and reliable genetic distance estimation.

Polyploid genomes pose several inherent challenges to population genetic analyses. While alignment-based methods are fundamentally limited in their applicability to polyploids, alignment-free methods bypass most of these limits. We investigated the use of Mash, a k-mer analysis tool that uses the MinHash method to reduce complexity in large genomic data sets, for basic population genetic analyses of polyploid sequences. We measured the degree to which Mash correctly estimated pairwise genetic distance in simulated haploid and polyploid short-read sequences with various levels of missing data. Mash-based estimates of genetic distance were comparable to alignment-based estimates, and were less impacted by missing data. We also used Mash to analyse publicly available short-read data for three polyploid and one diploid species, then compared Mash results to published results. For both simulated and real data, Mash accurately estimated pairwise genetic differences for polyploids as well as diploids as much as 476 times faster than alignment-based methods, though we found that Mash genetic distance estimates could be biased by per-sample read depth. Mash may be a particularly useful addition to the toolkit of polyploid geneticists for rapid confirmation of alignment-based results and for basic population genetics in reference-free systems or those with only poor-quality sequence data available.

Genetic differences in the temporal and environmental stability of transgenerational environmental effects.

Environments influence the expression of phenotypes of individuals, their progeny, and even their grandprogeny. The duration of environmental effects and how they are modified by subsequent environments are predicted to be targets of natural selection in variable environments. However, little is known about the genetic basis of the temporal persistence of environmental effects and their stability of expression across subsequent environments, or even the extent to which natural genotypes differ in these attributes of environmental effects. We factorially manipulated the thermal environment experienced in three successive generations, to quantify the temporal persistence and environmental stability of temperature effects in contrasting genotypes of Arabidopsis thaliana. We found that genotypes differed in the manner in which environmental effects dissipated across successive generations, the manner in which responses to ancestral environments were stably expressed in present environments, the manner in which ancestral environments altered responses to present environments, and in the manner in which ancestral environments altered fitness in present conditions. Genetic variation exists in nature for these trait-specific environmental responses, suggesting that the temporal persistence and stability of environmental effects in variable environments have the potential to evolve in response to natural selection imposed by different environments and sequences of environments.

Inheritance of DNA methylation differences in the mangrove Rhizophora mangle.

The capacity to respond to environmental challenges ultimately relies on phenotypic variation which manifests from complex interactions of genetic and nongenetic mechanisms through development. While we know something about genetic variation and structure of many species of conservation importance, we know very little about the nongenetic contributions to variation. Rhizophora mangle is a foundation species that occurs in coastal estuarine habitats throughout the neotropics where it provides critical ecosystem functions and is potentially threatened by anthropogenic environmental changes. Several studies have documented landscape-level patterns of genetic variation in this species, but we know virtually nothing about the inheritance of nongenetic variation. To assess one type of nongenetic variation, we examined the patterns of DNA sequence and DNA methylation in maternal plants and offspring from natural populations of R. mangle from the Gulf Coast of Florida. We used a reduced representation bisulfite sequencing approach (epi-genotyping by sequencing; epiGBS) to address the following questions: (a) What are the levels of genetic and epigenetic diversity in natural populations of R. mangle? (b) How are genetic and epigenetic variation structured within and among populations? (c) How faithfully is epigenetic variation inherited? We found low genetic diversity but high epigenetic diversity from natural populations of maternal plants in the field. In addition, a large portion (up to ~25%) of epigenetic differences among offspring grown in common garden was explained by maternal family. Therefore, epigenetic variation could be an important source of response to challenging environments in the genetically depauperate populations of this foundation species.

Fimepinostat (CUDC-907) in patients with relapsed/refractory diffuse large B cell and high-grade B-cell lymphoma: report of a phase 2 trial and exploratory biomarker analyses.

Fimepinostat (CUDC-907), a first-in-class oral small-molecule inhibitor of histone deacetylase and phosphatidylinositol 3-kinase, demonstrated efficacy in a phase 1 study of patients with relapsed/refractory (R/R) diffuse large and high-grade B-cell lymphomas (DLBCL/HGBL), particularly those with increased MYC protein expression and/or MYC gene rearrangement/copy number gain (MYC-altered disease). Therefore, a phase 2 study of fimepinostat was conducted in this patient population with 66 eligible patients treated. The primary end-point of overall response (OR) rate for patients with MYC-IHC ≥40% (n = 46) was 15%. Subsequently, exploratory pooled analyses were performed including patients treated on both the phase 1 and 2 studies based upon the presence of MYC-altered disease as well as a biomarker identified by Virtual Inference of Protein activity by Enriched Regulon analysis (VIPER). For these patients with MYC-altered disease (n = 63), the overall response (OR) rate was 22% with seven responding patients remaining on treatment for approximately two years or longer, and VIPER yielded a three-protein biomarker classification with positive and negative predictive values of ≥85%. Prolonged durations of response were achieved by patients with MYC-altered R/R DLBCL/HGBL treated with single-agent fimepinostat. Combination therapies and/or biomarker-based patient selection strategies may lead to higher response rates in future clinical trials.

A 2:1 randomized, open-label, phase II study of selinexor vs. physician's choice in older patients with relapsed or refractory acute myeloid leukemia.

Selinexor, a selective inhibitor of nuclear export, has demonstrated promising activity in patients with acute myeloid leukemia (AML). This randomized, phase II study evaluated selinexor 60 mg twice weekly (n = 118) vs. physician's choice (PC) treatment (n = 57) in patients aged ≥60 years with relapsed/refractory (R/R) AML. The primary outcome was overall survival (OS). Median OS did not differ significantly for selinexor vs. PC (3.2 vs. 5.6 months; HR = 1.18 [95% CI: 0.79-1.75]; p = 0.422). Complete remission (CR) plus CR with incomplete hematologic recovery trending in favor of selinexor occurred in a minority of patients. Selinexor treated patients had an increased incidence of adverse events. The most common grade ≥3 adverse events were thrombocytopenia, febrile neutropenia, anemia, hyponatremia. Despite well-balanced baseline characteristics, there were numerically higher rates of TP53 mutations, prior myelodysplastic syndrome, and lower absolute neutrophil counts in the selinexor group; warranting further investigation of selinexor in more carefully stratified R/R AML patients.Registered trial: NCT02088541.

Patterns of population genomic diversity in the invasive Japanese knotweed species complex.

PREMISE: Invasive species are expected to undergo a reduction in genetic diversity due to founder effects, which should limit their ability to adapt to new habitats. Still, many invasive species achieve widespread distributions and dense populations. This paradox of invasions could potentially be overcome through multiple introductions or hybridization, both of which increase genetic diversity. We conducted a population genomics study of Japanese knotweed (Reynoutria japonica), which is a polyploid, clonally reproducing invasive species that has been notoriously successful worldwide despite supposedly low genetic diversity. METHODS: We used genotyping by sequencing to collect 12,912 SNP markers from 88 samples collected at 38 locations across North America for the species complex. We used alignment-free k-mer hashing analysis in addition to traditional population genetic analyses to account for the challenges of genotyping polyploids. RESULTS: Genotypes conformed to three genetic clusters, likely representing Japanese knotweed, giant knotweed, and hybrid bohemian knotweed. We found that, contrary to previous findings, the Japanese knotweed cluster had substantial genetic diversity, though it had no apparent genetic structure across the landscape. In contrast, giant knotweed and hybrids showed distinct population groups. We did not find evidence of isolation by distance in the species complex, likely reflecting the stochastic introduction history of this species complex. CONCLUSIONS: The results indicate that clonal invasive species can show substantial genetic diversity and can be successful at colonizing a variety of habitats without showing evidence of local adaptation or genetic structure.

A modular master regulator landscape controls cancer transcriptional identity.

Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.

Systematic elucidation of neuron-astrocyte interaction in models of amyotrophic lateral sclerosis using multi-modal integrated bioinformatics workflow.

Cell-to-cell communications are critical determinants of pathophysiological phenotypes, but methodologies for their systematic elucidation are lacking. Herein, we propose an approach for the Systematic Elucidation and Assessment of Regulatory Cell-to-cell Interaction Networks (SEARCHIN) to identify ligand-mediated interactions between distinct cellular compartments. To test this approach, we selected a model of amyotrophic lateral sclerosis (ALS), in which astrocytes expressing mutant superoxide dismutase-1 (mutSOD1) kill wild-type motor neurons (MNs) by an unknown mechanism. Our integrative analysis that combines proteomics and regulatory network analysis infers the interaction between astrocyte-released amyloid precursor protein (APP) and death receptor-6 (DR6) on MNs as the top predicted ligand-receptor pair. The inferred deleterious role of APP and DR6 is confirmed in vitro in models of ALS. Moreover, the DR6 knockdown in MNs of transgenic mutSOD1 mice attenuates the ALS-like phenotype. Our results support the usefulness of integrative, systems biology approach to gain insights into complex neurobiological disease processes as in ALS and posit that the proposed methodology is not restricted to this biological context and could be used in a variety of other non-cell-autonomous communication mechanisms.

The Host Cell ViroCheckpoint: Identification and Pharmacologic Targeting of Novel Mechanistic Determinants of Coronavirus-Mediated Hijacked Cell States.

Most antiviral agents are designed to target virus-specific proteins and mechanisms rather than the host cell proteins that are critically dysregulated following virus-mediated reprogramming of the host cell transcriptional state. To overcome these limitations, we propose that elucidation and pharmacologic targeting of host cell Master Regulator proteins-whose aberrant activities govern the reprogramed state of coronavirus-infected cells-presents unique opportunities to develop novel mechanism-based therapeutic approaches to antiviral therapy, either as monotherapy or as a complement to established treatments. Specifically, we propose that a small module of host cell Master Regulator proteins (ViroCheckpoint) is hijacked by the virus to support its efficient replication and release. Conventional methodologies are not well suited to elucidate these potentially targetable proteins. By using the VIPER network-based algorithm, we successfully interrogated 12h, 24h, and 48h signatures from Calu-3 lung adenocarcinoma cells infected with SARS-CoV, to elucidate the time-dependent reprogramming of host cells and associated Master Regulator proteins. We used the NYS CLIA-certified Darwin OncoTreat algorithm, with an existing database of RNASeq profiles following cell perturbation with 133 FDA-approved and 195 late-stage experimental compounds, to identify drugs capable of virtually abrogating the virus-induced Master Regulator signature. This approach to drug prioritization and repurposing can be trivially extended to other viral pathogens, including SARS-CoV-2, as soon as the relevant infection signature becomes available.

Genotypic variation in the persistence of transgenerational responses to seasonal cues.

Phenotypes respond to environments experienced directly by an individual, via phenotypic plasticity, or to the environment experienced by ancestors, via transgenerational environmental effects. The adaptive value of environmental effects depends not only on the strength and direction of the induced response but also on how long the response persists within and across generations, and how stably it is expressed across environments that are encountered subsequently. Little is known about the genetic basis of those distinct components, or even whether they exhibit genetic variation. We tested for genetic differences in the inducibility, temporal persistence, and environmental stability of transgenerational environmental effects in Arabidopsis thaliana. Genetic variation existed in the inducibility of transgenerational effects on traits expressed across the life cycle. Surprisingly, the persistence of transgenerational effects into the third generation was uncorrelated with their induction in the second generation. Although environmental effects for some traits in some genotypes weakened over successive generations, others were stronger or even in the opposite direction in more distant generations. Therefore, transgenerational effects in more distant generations are not merely caused by the retention or dissipation of those expressed in prior generations, but they may be genetically independent traits with the potential to evolve independently.