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Biology subjects

Root, D. E.

Publications and source records attributed to Root, D. E..

At least 19 recordsLinked to original sources

Dynamic inositol pyrophosphate synthesis is a targetable therapeutic opportunity in ovarian cancer.

We previously reported that the phosphate exporter XPR1 is required to prevent toxic phosphate accumulation in ovarian cancer cells. To guide therapeutic development, we sought to systematically compare potential strategies to inhibit XPR1: directly targeting the phosphate efflux channel, targeting its partner protein KIDINS220, or inhibiting the synthesis of inositol pyrophosphates (PP-InsPs), metabolites which activate XPR1. We evaluated functional domains in XPR1 and KIDINS220 using mutational scanning and found that loss of function mutations in XPR1 clustered in distinct regions throughout the protein, with the most deleterious mutations in the PP-InsP-binding domain. In contrast, loss of function mutations in KIDINS220 were infrequent and altered the localization of XPR1, consistent with a scaffolding role for KIDINS220. These data highlight the functional relevance of PP-InsPs, which we confirmed by inhibiting their synthesis using IP6K inhibitors. We demonstrate that IP6K inhibition phenocopies XPR1 inhibition across hundreds of cancer cell lines, with the mechanism of sensitivity solely due to inhibition of cellular phosphate efflux. Finally, we show that IP6K inhibitors decrease tumor burden in xenograft models of ovarian cancer, but that the rapid resynthesis of PP-InsPs requires high exposures to achieve efficacy. This study comprehensively evaluates the XPR1-dependent phosphate efflux network and reinforces the concept of directly targeting XPR1 as a precision medicine strategy to benefit patients with ovarian cancer.

cancer biology↗

Aurora kinase A is a synthetic lethal target in FANCA-deficient cancers

Loss-of-function genomic alterations in FANCA occur across multiple cancer types, yet no molecularly tailored therapies have successfully exploited this potential vulnerability. Using complementary unbiased approaches, including a genome-wide CRISPR/Cas9 loss-of-function screen and a high-throughput drug screen in isogenic cancer cell-based models, we identified Aurora kinase A (AURKA) as a reproducible synthetic lethal target of FANCA-deficient cancers. Inhibition of AURKA induced chromosomal instability, micronucleation, and early G2/M arrest selectively in FANCA-deficient cells, consistent with an increased reliance on mitotic checkpoint control. Mechanistically, FANCA deficiency is associated with an elevated AURKA expression at both the transcriptomic and protein levels, and with an upregulation of mitotic spindle and G2/M checkpoint gene signatures. Analysis of large-scale cancer genomics datasets, including over 650,000 clinically sequenced tumors, confirms that FANCA is the most frequently altered Fanconi anemia pathway gene across cancers, and that Fanconi anemia-defective tumors exhibit an increased tumor mutational burden and genomic instability. Collectively, our findings point to AURKA inhibition as a promising precision treatment strategy in FANCA-deficient cancers and provide a rationale to further explore this strategy in the clinic.

cancer biology↗

Deep Mutational Scanning of FDX1 Identifies Key Structural Determinants of Lipoylation and Cuproptosis

Cuproptosis is a recently described form of regulated cell death triggered by ionophore-induced copper (Cu) overload in mitochondria. It is critically dependent on ferredoxin 1 (FDX1), a mitochondrial reductase that facilitates cuproptosis by reducing ionophore-bound Cu(II) to Cu(I) thereby triggering its release, and by promoting mitochondrial protein lipoylation, which is directly targeted by the released Cu to drive cell death. Despite the pivotal role of FDX1 in cuproptosis, the structural determinants underlying its distinct functions remain unclear. To address this, we performed deep mutational scanning (DMS) of FDX1 and identified two conserved, solvent-exposed residues--D136 and D139--on its third alpha helix (-helix 3) that are critical for both FDX1-mediated cuproptosis and lipoylation. Charge-reversal mutations at these positions abolished FDX1s ability to induce cuproptosis and support lipoylation in cells, despite retaining full enzymatic activity in vitro. Guided by structural and genomic analyses, we further identified dihydrolipoamide dehydrogenase (DLD), the E3 subunit of lipoylated complexes as an alternative FDX1 reductase both in cells and in vitro. Together, these findings establish the acidic -helix 3 of FDX1 as a critical interface for its upstream regulation and suggest that FDX1s roles in cuproptosis and in lipoylation are both structurally and functionally linked.

cell biology↗

Chromatin Perturbation Promotes Susceptibility to Hypomethylating Agents

Cancer-directed drugs are often clinically deployed without definitive understanding of their molecular mechanisms of action (MOA). Hypomethylating agents (HMAs), which result in the degradation of the DNA methyltransferase 1 (DNMT1), have been deployed for decades in the treatment of haematological malignancies1,2. The precise mechanism of action of these drugs, however, has been debated, rendering the design of rational combination therapies challenging. Here, we identified the deubiquitinating enzyme USP48 as a crucial regulator of posttranslational histone modification in the context of DNA demethylation. USP48 loss selectively enhances response to DNMT1 inhibition, leading to a rapid induction of cell death. We demonstrate that USP48 is localized at sites of DNA damage and deubiquitinates H2A variants and proteins important for DNA damage repair. Functionally, loss of USP48 triggers an increase in chromatin accessibility upon HMA treatment, rendering AML cells more susceptible to DNA damage. Our results support USP48 as a posttranslational histone modifier for chromatin stability and DNA damage in response to HMA-related DNA demethylation. These findings propose USP48 as a new target for combination therapy with HMAs for acute myeloid leukaemia (AML).

cancer biology↗

Riboflavin drives nucleotide biosynthesis and iron-sulfur metabolism to promote acute myeloid leukemia

Riboflavin is a diet-derived vitamin in higher organisms that serves as a precursor for flavin mononucleotide and flavin adenine dinucleotide, key cofactors that participate in oxidoreductase reactions. Here, using proteomic, metabolomic and functional genomics approaches, we describe a specific riboflavin dependency in acute myeloid leukemia and demonstrate that, in addition to energy production via oxidative phosphorylation, a key biological role of riboflavin is to enable nucleotide biosynthesis and iron-sulfur cluster metabolism. Genetic perturbation of riboflavin metabolism pathways or exogenous depletion in physiological culture medium induce nucleotide imbalance and DNA damage responses, as well as impair the stability and activity of proteins which utilize [4Fe-4S] iron-sulfur clusters as cofactors. We identify a window of therapeutic opportunity upon riboflavin starvation or chemical riboflavin metabolism perturbation and demonstrate that this strongly synergizes with BCL-2 inhibition. Our work identifies riboflavin as a critical metabolic dependency in leukemia, with functions beyond energy production.

cancer biology↗

A comprehensive map of missense trafficking variants in rhodopsin and their response to pharmacologic correction

Rhodopsin (RHO) missense variants are a leading cause of autosomal dominant retinitis pigmentosa (adRP), a progressive retinal degeneration with no currently approved therapies. Interpreting the pathogenicity of the growing number of identified RHO variants is a major clinical challenge, and understanding their disease mechanisms is essential for developing effective therapies. Here, we present a high-resolution map of RHO missense variant trafficking using two complementary deep mutational scanning (DMS) approaches based on a surface abundance immunoassay and a membrane proximity assay. We generated a comprehensive dataset encompassing all 6,612 possible single-residue missense variants, revealing a strong correlation between the two methods. Over 700 variants were identified with pathogenic trafficking scores, significantly expanding the number of RHO variants with functional evidence supporting pathogenicity. We demonstrate a high concordance between the trafficking scores and ClinVar pathogenicity classifications, highlighting this approachs utility in resolving variants of uncertain significance (VUS). The data also identified structurally clustered trafficking-deficient variants, predominantly within the N-terminal region and second extracellular loop, in and above the extracellular/intradiscal beta-plug region. Furthermore, we evaluated the efficacy of the non-retinoid pharmacological chaperone YC-001, observing significant rescue of trafficking defects in a majority of mistrafficking variants. This comprehensive functional map of RHO missense variants provides a valuable resource for pathogenicity assessment, genotype-phenotype correlations, and the development of targeted therapeutic strategies for RHO-adRP, paving the way for improved diagnosis and treatment for patients.

genomics↗

Morphological map of under- and over-expression of genes in human cells

Cell Painting images offer valuable insights into a cells state and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP (Joint Undertaking in Morphological Profiling) Cell Painting Consortium perturbed roughly 75% of the protein-coding genome in human U-2 OS cells, generating a rich resource of single-cell images and extracted features. These profiles capture the phenotypic impacts of perturbing 15,243 human genes, including overexpressing 12,609 genes (using open reading frames, ORFs) and knocking out 7,975 genes (using CRISPR-Cas9). We mitigated technical artifacts by rigorously evaluating data processing options and validated the datasets robustness and biological relevance. Analysis of phenotypic profiles revealed novel gene clusters and functional relationships, including those associated with mitochondrial function, cancer, and neural processes. The JUMP Cell Painting genetic dataset is a valuable resource for exploring gene relationships and uncovering novel functions.

bioinformatics↗

Comprehensive structure-function analysis reveals gain- and loss-of-function mechanisms impacting oncogenic KRAS activity

To dissect variant-function relationships in the KRAS oncoprotein, we performed deep mutational scanning (DMS) screens for both wild-type and KRASG12D mutant alleles. We defined the spectrum of oncogenic potential for nearly all possible KRAS variants, identifying several novel transforming alleles and elucidating a model to describe the frequency of KRAS mutations in human cancer as a function of transforming potential, mutational probability, and tissue-specific mutational signatures. Biochemical and structural analyses of variants identified in a KRASG12D second-site suppressor DMS screen revealed that attenuation of oncogenic KRAS can be mediated by protein instability and conformational rigidity, resulting in reduced binding affinity to effector proteins, such as RAF and PI3-kinases, or reduced SOS-mediated nucleotide exchange activity. These studies define the landscape of single amino acid alterations that modulate the function of KRAS, providing a resource for the clinical interpretation of KRAS variants and elucidating mechanisms of oncogenic KRAS inactivation for therapeutic exploitation.

cancer biology↗

Generation of a biliary tract cancer cell line atlas reveals molecular subtypes and therapeutic targets

Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.

cancer biology↗

Cholesterol biosynthesis inhibition synergizes with AKT inhibitors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is responsible for a disproportionate number of breast cancer deaths due to its molecular heterogeneity, high recurrence rate and lack of targeted therapies. Dysregulation of the phosphoinositide 3-kinase (PI3K)/AKT pathway occurs in approximately 50% of TNBC patients. We performed a genome-wide CRISPR/Cas9 screen with PI3K and AKT inhibitors to find targetable synthetic lethalities in TNBC. We identified cholesterol homeostasis as a collateral vulnerability with AKT inhibition. Disruption of cholesterol homeostasis with pitavastatin synergized with AKT inhibition to induce TNBC cytotoxicity in vitro, in mouse TNBC xenografts and in patient-derived, estrogen receptor (ER)-negative breast cancer organoids. Neither ER-positive breast cancer cell lines nor ER-positive organoids were sensitive to combined AKT inhibitor and pitavastatin. Mechanistically, TNBC cells showed impaired sterol regulatory element-binding protein 2 (SREBP-2) activation in response to single agent or combination treatment with AKT inhibitor and pitavastatin. This was rescued by inhibition of the cholesterol trafficking protein Niemann-Pick C1 (NPC1). NPC1 loss caused lysosomal cholesterol accumulation, decreased endoplasmic reticulum cholesterol levels and promoted SREBP-2 activation. Taken together, these data identify a TNBC-specific vulnerability to the combination of AKT inhibitors and pitavastatin mediated by dysregulated cholesterol trafficking. Our work motivates combining AKT inhibitors with pitavastatin as a therapeutic modality in TNBC.

cancer biology↗

Vps18 contributes to phagosome membrane integrity in Mycobacterium tuberculosis-infected macrophages.

Mycobacterium tuberculosis (Mtb) has evolved to be exquisitely adapted to survive within host macrophages. The capacity to damage the phagosomal membrane has emerged as central to Mtb virulence. While Mtb factors driving membrane damage have been described, host factors that repair that damage to contain the pathogen remain largely unknown. We used a genome-wide CRISPR screen to identify novel host factors required to repair Mtb-damaged phagosomal membranes. Vacuolar protein sorting-associated protein 18 (Vps18), a member of the HOPS and CORVET trafficking complexes, was among the top hits. Vps18 colocalized with Mtb in macrophages beginning shortly after infection, and Vps18-knockout macrophages demonstrated increased damage of Mtb-containing phagosomes without impaired autophagy. Mtb grew more robustly in Vps18-knockout cells, and the first-line anti-tuberculosis antibiotic pyrazinamide was less effective. Our results identify Vps18 as required for phagosomal membrane integrity in Mtb-infected cells and suggest that modulating phagosome integrity may hold promise for improving the efficacy of antibiotic treatment for TB.

microbiology↗

EZH2 synergizes with BRD4-NUT to drive NUT carcinoma growth through silencing of key tumor suppressor genes

NUT carcinoma (NC) is an aggressive carcinoma driven by the BRD4-NUT fusion oncoprotein, which activates chromatin to promote expression of pro-growth genes. BET bromodomain inhibitors (BETi) impede BRD4-NUTs ability to activate genes and are thus a promising treatment but limited as monotherapy. The role of gene repression in NC is unknown. Here, we demonstrate that EZH2, which silences genes through establishment of repressive chromatin, is a dependency in NC. Inhibition of EZH2 with the clinical compound tazemetostat (taz) potently blocked growth of NC cells. Epigenetic and transcriptomic analysis revealed that taz reversed the EZH2-specific H3K27me3 silencing mark, and restored expression of multiple tumor suppressor genes while having no effect on key oncogenic BRD4- NUT-regulated genes. CDKN2A was identified as the only gene amongst all taz-derepressed genes to confer resistance to taz in a CRISPR-Cas9 screen. Combined EZH2 inhibition and BET inhibition synergized to downregulate cell proliferation genes resulting in more pronounced growth arrest and differentiation than either inhibitor alone. In pre-clinical models, combined taz and BETi synergistically blocked growth and prolonged survival of NC-xenografted mice, with all mice cured in one cohort. STATEMENT OF SIGNIFICANCEIdentification of EZH2 as a dependency in NC substantiates the reliance of NC tumor cells on epigenetic dysregulation of functionally opposite, yet highly complementary chromatin regulatory pathways to maintain NC growth. In particular, repression of CDKN2A expression by EZH2 provides a mechanistic rationale for combining EZH2i with BETi for the clinical treatment of NC.

cancer biology↗

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames. To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a step-wise approach to employ multiple CRISPR-Cas9 screens to elucidate functional non-canonical ORFs implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream open reading frames (uORFs) exhibited selective functionality independent of the main coding sequence. One of these, ASNSD1-uORF or ASDURF, was upregulated, associated with the MYC family oncogenes, and was required for medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future cancer genomics studies seeking to define new cancer targets. HighlightsO_LIRibo-seq reveals widespread translation of non-canonical ORFs in medulloblastoma C_LIO_LIHigh-resolution CRISPR tiling reveals uORF functions in medulloblastoma C_LIO_LIASNSD1-uORF controls downstream pathways with the prefoldin-like complex C_LIO_LIASNSD1-uORF is necessary for medulloblastoma cell survival C_LI

cancer biology↗

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Reducing disparities is critical to promote equity of access to precision treatments for all patients with cancer. While socioenvironmental factors are a major driver behind such disparities, biological differences also are likely to contribute. The prioritization of cancer drug targets is foundational for drug discovery, yet whether ancestry-related signals in target discovery pipelines exist has not been systematically explored due to the absence of data at the appropriate scale. Here, we analyzed data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models as part of the Cancer Dependency Map to identify ancestry-associated genetic dependencies. Surprisingly, we found that most putative associations between ancestry and dependency arose from artifacts related to germline variants that are present at different frequencies across ancestry groups. In 2-5% of genes profiled in each cellular model, germline variants in sgRNA targeting sequences likely reduced cutting by the CRISPR/Cas9 nuclease. Unfortunately, this bias disproportionately affected cell models derived from individuals of recent African descent because their genomes tended to diverge more from the consensus genome typically used for CRISPR/Cas9 guide design. To help the scientific community begin to resolve this source of bias, we report three complementary methods for ancestry-agnostic CRISPR experiments. This report adds to a growing body of literature describing ways in which ancestry bias impacts cancer research in underappreciated ways.

cancer biology↗

Mapping the landscape of genetic dependencies in chordoma

Identifying the spectrum of genes required for cancer cell survival can reveal essential cancer circuitry and therapeutic targets, but such a map remains incomplete for many cancer types. We applied genome-scale CRISPR-Cas9 loss-of-function screens to map the landscape of selectively essential genes in chordoma, a bone cancer with few validated targets. This approach confirmed a known chordoma dependency, TBXT (T; brachyury), and identified a range of additional dependencies, including PTPN11, ADAR, PRKRA, LUC7L2, SRRM2, SLC2A1, SLC7A5, FANCM, and THAP1. CDK6, SOX9, and EGFR, genes previously implicated in chordoma biology, were also recovered. We found genomic and transcriptomic features that predict specific dependencies, including interferon-stimulated gene expression, which correlates with ADAR dependence and is elevated in chordoma. Validating the therapeutic relevance of dependencies, small-molecule inhibitors of SHP2, encoded by PTPN11, had potent preclinical efficacy against chordoma. Our results generate an emerging map of chordoma dependencies to enable biological and therapeutic hypotheses.

cancer biology↗

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

Hundreds of genome-wide loss-of-function screens have been performed, as part of efforts such as The Cancer Dependency Map, to create a catalog of genetic dependencies in a diverse set of cancer contexts. In recent years, large-scale screening efforts have shifted perturbation technology from RNAi to CRISPR-Cas9, due to the superior efficacy and specificity of CRISPR-Cas9-mediated approaches. However, questions remain about the extent to which partial suppression of gene targets could result in selective dependency across cell lines, potentially revealing a larger set of targetable cancer vulnerabilities than can be identified using CRISPR knockout alone. Here, we use CRISPR-Cas9 and RNAi screening data for more than 400 shared cell lines to represent knockout and partial suppression genetic perturbation modalities and evaluate the utility of each for therapeutic target discovery and the inference of gene function. We find that CRISPR screens identify more dependencies, and yield more accurate predictive models and co-dependency relationships overall. However, RNAi outperforms CRISPR in identifying associations (omics, drug, co-dependencies) with genes that are common dependencies for most cell lines (pan-dependencies). As pan-dependencies occur frequently in the CRISPR dataset (~2,000 genes), using results from both RNAi and CRISPR analyses facilitates the discovery of predictive models and associated co-dependencies for a wider range of gene targets than could be detected using either dataset alone. These findings can aid in the interpretation of contrasting results obtained from CRISPR and RNAi screens and reinforce the importance of partial gene suppression methods in building a cancer dependency map.

cancer biology↗

Targeting TRIP13 in Wilms Tumor with Nuclear Export Inhibitors

Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies in a systematic manner remains challenging in part due to the lack of faithful preclinical in vitro models. We established ten short-term patient-derived WT cell lines and characterized these models using low-coverage whole genome sequencing, whole exome sequencing and RNA-sequencing, which demonstrated that these ex-vivo models faithfully recapitulate WT biology. We then performed targeted RNAi and CRISPR-Cas9 loss-of-function screens and identified the nuclear export genes (XPO1 and KPNB1) as strong vulnerabilities. We observed that these models are sensitive to nuclear export inhibition using the FDA approved therapeutic agent, selinexor (KPT-330). Selinexor treatment of FHWT suppressed TRIP13 expression, which was required for survival. We further identified in vitro and in vivo synergy between selinexor and doxorubicin, a chemotherapy used in high risk FHWT. Taken together, we identified XPO1 inhibition with selinexor as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

cancer biology↗

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

Identifying genetic and chemical perturbations with similar impacts on cell morphology can reveal compounds mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here, we create such a Resource dataset, CPJUMP1, where each perturbed gene is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same gene, and we find that identifying matches between chemical perturbations and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling, such as functional genomics and drug discovery.

bioinformatics↗