Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens

The present and future of the Cancer Dependency Map

Despite tremendous progress in the past decade, the complex and heterogeneous nature of cancer complicates efforts to identify new therapies and therapeutic combinations that achieve durable responses in most patients. Further advances in cancer therapy will rely, in part, on the development of targeted therapeutics matched with the genetic and molecular characteristics of cancer. The Cancer Dependency Map (DepMap) is a large-scale data repository and research platform, aiming to systematically reveal the landscape of cancer vulnerabilities in thousands of genetically and molecularly annotated cancer models. DepMap is used routinely by cancer researchers and translational scientists and has facilitated the identification of several novel and selective therapeutic strategies for multiple cancer types that are being tested in the clinic. However, it is also clear that the current version of DepMap is not yet comprehensive. In this Perspective, we review (1) the impact and current uses of DepMap, (2) the opportunities to enhance DepMap to overcome its current limitations, and (3) the ongoing efforts to further improve and expand DepMap.

A disease-associated PPP2R3C-MAP3K1 phospho-regulatory module controls centrosome function

Centrosomes have critical roles in microtubule organization, ciliogenesis, and cell signaling.1,2,3,4,5,6,7,8 Centrosomal alterations also contribute to diseases, including microcephaly, cancer, and ciliopathies.9,10,11,12,13 To date, over 150 centrosomal proteins have been identified, including several kinases and phosphatases that control centrosome biogenesis, function, and maintenance.2,3,4,5,14,15,16,17,18,19,20,21 However, the regulatory mechanisms that govern centrosome function are not fully defined, and thus how defects in centrosomal regulation contribute to disease is incompletely understood. Using a systems genetics approach, we find here that PPP2R3C, a poorly characterized PP2A phosphatase subunit, is a distal centriole protein and functional partner of centriolar proteins CEP350 and FOP. We further show that a key function of PPP2R3C is to counteract the kinase activity of MAP3K1. In support of this model, MAP3K1 knockout suppresses growth defects caused by PPP2R3C inactivation, and MAP3K1 and PPP2R3C have opposing effects on basal and microtubule stress-induced JNK signaling. Illustrating the importance of balanced MAP3K1 and PPP2R3C activities, acute overexpression of MAP3K1 severely inhibits centrosome function and triggers rapid centriole disintegration. Additionally, inactivating PPP2R3C mutations and activating MAP3K1 mutations both cause congenital syndromes characterized by gonadal dysgenesis.22,23,24,25,26,27,28 As a syndromic PPP2R3C variant is defective in centriolar localization and binding to centriolar protein FOP, we propose that imbalanced activity of this centrosomal kinase-phosphatase pair is the shared cause of these disorders. Thus, our findings reveal a new centrosomal phospho-regulatory module, shed light on disorders of gonadal development, and illustrate the power of systems genetics to identify previously unrecognized gene functions.

The Mitochondrial Ubiquitin Ligase MARCHF5 Cooperates with MCL1 to Inhibit Apoptosis in KSHV-Transformed Primary Effusion Lymphoma Cell Lines

Kaposi's sarcoma-associated herpesvirus (KSHV) causes several malignancies in people with HIV including Kaposi's sarcoma and primary effusion lymphoma (PEL). We have previously shown that PEL cell lines require myeloid cell leukemia-1 (MCL1) to inhibit apoptosis. MCL1 is an oncogene that is amplified in cancers and causes resistance to chemotherapy regimens. MCL1 is thus an attractive target for drug development. The emerging clinical relevance and therapeutic potential of MCL1 motivated us to study the roles of this oncogene in PEL in depth. Using a systems biology approach, we uncovered an unexpected genetic interaction between MCL1 and MARCHF5 indicating that they function in the same pathway. MARCHF5 is an E3 ubiquitin ligase most known for regulating mitochondrial homeostasis and antiviral signaling, but not apoptosis. We thus investigated how MCL1 and MARCHF5 cooperate to promote PEL cell survival. CRISPR knockout (KO) of MARCHF5 in PEL cell lines resulted in a significant increase in apoptosis despite the presence of MCL1. The anti-apoptotic function of MARCHF5 was dependent on its E3 ligase and dimerization activities. Loss of MARCHF5 or inhibition of the 26S proteasome furthermore stabilized the MCL1 antagonist NOXA without affecting levels of MCL1. Interestingly, NOXA KO provides a fitness advantage to PEL cells suggesting that NOXA is the pro-apoptotic signal that necessitates the anti-apoptotic activities of MCL1 and MARCHF5. Finally, endogenous reciprocal co-immunoprecipitation experiments show that MARCHF5 and NOXA are found in the same protein complex. Our findings thus provide the mechanistic link that underlies the genetic interaction between MCL1 and MARCHF5. We propose that MARCHF5 induces the degradation of the MCL1 antagonist NOXA thus reinforcing the pro-survival role of MCL1 in these tumor cells. This newly appreciated interaction of the MCL1 and MARCHF5 oncogenes may be useful to improve the design of combination therapies for KSHV malignancies.

BMAL1-HIF2α heterodimers contribute to ccRCC

Circadian disruption enhances cancer risk, and many tumors exhibit disordered circadian gene expression. We show rhythmic gene expression is unexpectedly robust in clear cell renal cell carcinoma (ccRCC). Furthermore, the clock gene BMAL1 is higher in ccRCC than in healthy kidneys, unlike in other tumor types. BMAL1 is closely related to ARNT, and we show that BMAL1-HIF2α regulates a subset of HIF2α target genes in ccRCC cells. Depletion of BMAL1 reprograms HIF2α chromatin association and target gene expression and reduces ccRCC growth in culture and in xenografts. Analysis of pre-existing data reveals higher BMAL1 in patient-derived xenografts that are sensitive to growth suppression by a HIF2α antagonist (PT2399). We show that BMAL1-HIF2α is more sensitive than ARNT-HIF2α to suppression by PT2399, and increasing BMAL1 sensitizes 786O cells to growth inhibition by PT2399. Together, these findings indicate that an alternate HIF2α heterodimer containing the circadian partner BMAL1 contributes to HIF2α activity, growth, and sensitivity to HIF2α antagonist drugs in ccRCC cells.

On knowing a gene: A distributional hypothesis of gene function

As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions without considering biological contexts. We contend that the gene function problem in genetics may be informed by recent technological leaps in natural language processing, in which representations of word semantics can be automatically learned from diverse language contexts. In contrast to efforts to model semantics as "is-a" relationships in the 1990s, modern distributional semantics represents words as vectors in a learned semantic space and fuels current advances in transformer-based models such as large language models and generative pre-trained transformers. A similar shift in thinking of gene functions as distributions over cellular contexts may enable a similar breakthrough in data-driven learning from large biological datasets to inform gene function.

BMAL1-HIF2α heterodimers contribute to ccRCC

Circadian disruption enhances cancer risk, and many tumors exhibit disordered circadian gene expression. We show rhythmic gene expression is unexpectedly robust in clear cell renal cell carcinoma (ccRCC). Furthermore, the clock gene BMAL1 is higher in ccRCC than in healthy kidneys, unlike in other tumor types. BMAL1 is closely related to ARNT, and we show that BMAL1-HIF2α regulates a subset of HIF2α target genes in ccRCC cells. Depletion of BMAL1 reprograms HIF2α chromatin association and target gene expression and reduces ccRCC growth in culture and in xenografts. Analysis of pre-existing data reveals higher BMAL1 in patient-derived xenografts that are sensitive to growth suppression by a HIF2α antagonist (PT2399). We show that BMAL1-HIF2α is more sensitive than ARNT-HIF2α to suppression by PT2399, and increasing BMAL1 sensitizes 786O cells to growth inhibition by PT2399. Together, these findings indicate that an alternate HIF2α heterodimer containing the circadian partner BMAL1 contributes to HIF2α activity, growth, and sensitivity to HIF2α antagonist drugs in ccRCC cells.

The KAT module of the SAGA complex maintains the oncogenic gene expression program in MYCN-amplified neuroblastoma

Pediatric cancers are frequently driven by genomic alterations that result in aberrant transcription factor activity. Here, we used functional genomic screens to identify multiple genes within the transcriptional coactivator Spt-Ada-Gcn5-acetyltransferase (SAGA) complex as selective dependencies for MYCN-amplified neuroblastoma, a disease of dysregulated development driven by an aberrant oncogenic transcriptional program. We characterized the DNA recruitment sites of the SAGA complex in neuroblastoma and the consequences of loss of SAGA complex lysine acetyltransferase (KAT) activity on histone acetylation and gene expression. We demonstrate that loss of SAGA complex KAT activity is associated with reduced MYCN binding on chromatin, suppression of MYC/MYCN gene expression programs, and impaired cell cycle progression. Further, we showed that the SAGA complex is pharmacologically targetable in vitro and in vivo with a KAT2A/KAT2B proteolysis targeting chimeric. Our findings expand our understanding of the histone-modifying complexes that maintain the oncogenic transcriptional state in this disease and suggest therapeutic potential for inhibitors of SAGA KAT activity in MYCN-amplified neuroblastoma.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors for a wide range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed "DrugMap," an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF-κB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF-κB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription-factor activity.

Tight regulation of a nuclear HAPSTR1-HUWE1 pathway essential for mammalian life

The recently discovered HAPSTR1 protein broadly oversees cellular stress responses. This function requires HUWE1, a ubiquitin ligase that paradoxically marks HAPSTR1 for degradation, but much about this pathway remains unclear. Here, leveraging multiplexed proteomics, we find that HAPSTR1 enables nuclear localization of HUWE1 with implications for nuclear protein quality control. We show that HAPSTR1 is tightly regulated and identify ubiquitin ligase TRIP12 and deubiquitinase USP7 as upstream regulators titrating HAPSTR1 stability. Finally, we generate conditional Hapstr1 knockout mice, finding that Hapstr1-null mice are perinatal lethal, adult mice depleted of Hapstr1 have reduced fitness, and primary cells explanted from Hapstr1-null animals falter in culture coincident with HUWE1 mislocalization and broadly remodeled signaling. Notably, although HAPSTR1 potently suppresses p53, we find that Hapstr1 is essential for life even in mice lacking p53. Altogether, we identify novel components and functional insights into the conserved HAPSTR1-HUWE1 pathway and demonstrate its requirement for mammalian life.

A disease-associated PPP2R3C-MAP3K1 phospho-regulatory module controls centrosome function

Centrosomes have critical roles in microtubule organization and in cell signaling.1-8 However, the mechanisms that regulate centrosome function are not fully defined, and thus how defects in centrosomal regulation contribute to disease is incompletely understood. From functional genomic analyses, we find here that PPP2R3C, a PP2A phosphatase subunit, is a distal centriole protein and functional partner of centriolar proteins CEP350 and FOP. We further show that a key function of PPP2R3C is to counteract the kinase activity of MAP3K1. In support of this model, MAP3K1 knockout suppresses growth defects caused by PPP2R3C inactivation, and MAP3K1 and PPP2R3C have opposing effects on basal and microtubule stress-induced JNK signaling. Illustrating the importance of balanced MAP3K1 and PPP2R3C activities, acute overexpression of MAP3K1 severely inhibits centrosome function and triggers rapid centriole disintegration. Additionally, inactivating PPP2R3C mutations and activating MAP3K1 mutations both cause congenital syndromes characterized by gonadal dysgenesis.9-15 As a syndromic PPP2R3C variant is defective in centriolar localization and binding to centriolar protein FOP, we propose that imbalanced activity of this centrosomal kinase-phosphatase pair is the shared cause of these disorders. Thus, our findings reveal a new centrosomal phospho-regulatory module, shed light on disorders of gonadal development, and illustrate the power of systems genetics to identify previously unrecognized gene functions.

Histone lysine acetyltransferase inhibitors: an emerging class of drugs for cancer therapy

Lysine acetyltransferases (KATs) are a family of epigenetic enzymes involved in the regulation of gene expression; they represent a promising class of emerging drug targets. The frequent molecular dysregulation of these enzymes, as well as their mechanistic links to biological functions that are crucial to cancer, have led to exploration around the development of small-molecule inhibitors against KATs. Despite early challenges, recent advances have led to the development of potent and selective enzymatic and bromodomain (BRD) KAT inhibitors. In this review we discuss the discovery and development of new KAT inhibitors and their application as oncology therapeutics. Additionally, new chemically induced proximity approaches are presented, offering opportunities for unique target selectivity profiles and tissue-specific targeting of KATs. Emerging clinical data for CREB binding protein (CREBBP)/EP300 BRD inhibitors and KAT6 catalytic inhibitors indicate the promise of this target class in cancer therapeutics.

Research progress of SWI/SNF complex in breast cancer

In the past decade, numerous epigenetic mechanisms have been discovered to be associated with cancer. The mammalian SWI/SNF complex is an ATP-dependent chromatin remodeling complex whose mutations are associated with various malignancies including breast cancer. As the SWI/SNF complex has become one of the most commonly mutated complexes in cancer, targeting epigenetic mutations acquired during breast cancer progress is a potential means of improving clinical efficacy in treatment strategies. This article reviews the composition of the SWI/SNF complex, its main roles and research progress in breast cancer, and links these findings to the latest discoveries in cancer epigenomics to discuss the potential mechanisms and therapeutic potential of SWI/SNF in breast cancer.

ARID1A loss is associated with increased NRF2 signaling in human head and neck squamous cell carcinomas

Prior to the next generation sequencing and characterization of the tumor genome landscape, mutations in the SWI/SNF chromatin remodeling complex and the KEAP1-NRF2 signaling pathway were underappreciated. While these two classes of mutations appeared to independently contribute to tumor development, recent reports have demonstrated a mechanistic link between these two regulatory mechanisms in specific cancer types and cell models. In this work, we expand upon these data by exploring the relationship between mutations in BAF and PBAF subunits of the SWI/SNF complex and activation of NRF2 signal transduction across many cancer types. ARID1A/B mutations were strongly associated with NRF2 transcriptional activity in head and neck squamous carcinomas (HNSC). Many additional tumor types showed significant association between NRF2 signaling and mutation of specific components of the SWI/SNF complex. Different effects of BAF and PBAF mutations on the polarity of NRF2 signaling were observed. Overall, our results support a context-dependent functional link between SWI/SNF and NRF2 mutations across human cancers and implicate ARID1A inactivation in HPV-negative HNSC in promoting tumor progression and survival through activation of the KEAP1-NRF2 signaling pathway. The tumor-specific effects of these mutations open a new area of study for how mutations in the KEAP1-NRF2 pathway and the SWI/SNF complex contribute to cancer.

Co-fractionation-mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain

Human mitochondrial (mt) protein assemblies are vital for neuronal and brain function, and their alteration contributes to many human disorders, e.g., neurodegenerative diseases resulting from abnormal protein-protein interactions (PPIs). Knowledge of the composition of mt protein complexes is, however, still limited. Affinity purification mass spectrometry (MS) and proximity-dependent biotinylation MS have defined protein partners of some mt proteins, but are too technically challenging and laborious to be practical for analyzing large numbers of samples at the proteome level, e.g., for the study of neuronal or brain-specific mt assemblies, as well as altered mtPPIs on a proteome-wide scale for a disease of interest in brain regions, disease tissues or neurons derived from patients. To address this challenge, we adapted a co-fractionation-MS platform to survey native mt assemblies in adult mouse brain and in human NTERA-2 embryonal carcinoma stem cells or differentiated neuronal-like cells. The workflow consists of orthogonal separations of mt extracts isolated from chemically cross-linked samples to stabilize PPIs, data-dependent acquisition MS to identify co-eluted mt protein profiles from collected fractions and a computational scoring pipeline to predict mtPPIs, followed by network partitioning to define complexes linked to mt functions as well as those essential for neuronal and brain physiological homeostasis. We developed an R/CRAN software package, Macromolecular Assemblies from Co-elution Profiles for automated scoring of co-fractionation-MS data to define complexes from mtPPI networks. Presently, the co-fractionation-MS procedure takes 1.5-3.5 d of proteomic sample preparation, 31 d of MS data acquisition and 8.5 d of data analyses to produce meaningful biological insights.

Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens

CRISPR-Cas9 screens facilitate the discovery of gene functional relationships and phenotype-specific dependencies. The Cancer Dependency Map (DepMap) is the largest compendium of whole-genome CRISPR screens aimed at identifying cancer-specific genetic dependencies across human cell lines. A mitochondria-associated bias has been previously reported to mask signals for genes involved in other functions, and thus, methods for normalizing this dominant signal to improve co-essentiality networks are of interest. In this study, we explore three unsupervised dimensionality reduction methods-autoencoders, robust, and classical principal component analyses (PCA)-for normalizing the DepMap to improve functional networks extracted from these data. We propose a novel "onion" normalization technique to combine several normalized data layers into a single network. Benchmarking analyses reveal that robust PCA combined with onion normalization outperforms existing methods for normalizing the DepMap. Our work demonstrates the value of removing low-dimensional signals from the DepMap before constructing functional gene networks and provides generalizable dimensionality reduction-based normalization tools.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors of a wide-range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed DrugMap , an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NFκB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NFκB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription factor activity.

MMD collaborates with ACSL4 and MBOAT7 to promote polyunsaturated phosphatidylinositol remodeling and susceptibility to ferroptosis

Ferroptosis is a form of regulated cell death with roles in degenerative diseases and cancer. Excessive iron-catalyzed peroxidation of membrane phospholipids, especially those containing the polyunsaturated fatty acid arachidonic acid (AA), is central in driving ferroptosis. Here, we reveal that an understudied Golgi-resident scaffold protein, MMD, promotes susceptibility to ferroptosis in ovarian and renal carcinoma cells in an ACSL4- and MBOAT7-dependent manner. Mechanistically, MMD physically interacts with both ACSL4 and MBOAT7, two enzymes that catalyze sequential steps to incorporate AA in phosphatidylinositol (PI) lipids. Thus, MMD increases the flux of AA into PI, resulting in heightened cellular levels of AA-PI and other AA-containing phospholipid species. This molecular mechanism points to a pro-ferroptotic role for MBOAT7 and AA-PI, with potential therapeutic implications, and reveals that MMD is an important regulator of cellular lipid metabolism.

FDX1 regulates cellular protein lipoylation through direct binding to LIAS

Ferredoxins are a family of iron-sulfur (Fe-S) cluster proteins that serve as essential electron donors in numerous cellular processes that are conserved through evolution. The promiscuous nature of ferredoxins as electron donors enables them to participate in many metabolic processes including steroid, heme, vitamin D, and Fe-S cluster biosynthesis in different organisms. However, the unique natural function(s) of each of the two human ferredoxins (FDX1 and FDX2) are still poorly characterized. We recently reported that FDX1 is both a crucial regulator of copper ionophore-induced cell death and serves as an upstream regulator of cellular protein lipoylation, a mitochondrial lipid-based post-translational modification naturally occurring on four mitochondrial enzymes that are crucial for TCA cycle function. Here we show that FDX1 directly regulates protein lipoylation by binding the lipoyl synthase (LIAS) enzyme promoting its functional binding to the lipoyl carrier protein GCSH and not through indirect regulation of cellular Fe-S cluster biosynthesis. Metabolite profiling revealed that the predominant cellular metabolic outcome of FDX1 loss of function is manifested through the regulation of the four lipoylation-dependent enzymes ultimately resulting in loss of cellular respiration and sensitivity to mild glucose starvation. Transcriptional profiling established that FDX1 loss-of-function results in the induction of both compensatory metabolism-related genes and the integrated stress response, consistent with our findings that FDX1 loss-of-function is conditionally lethal. Together, our findings establish that FDX1 directly engages with LIAS, promoting its role in cellular protein lipoylation, a process essential in maintaining cell viability under low glucose conditions.

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

BACKGROUND

Hundreds of functional genomic screens have been performed across a diverse set of cancer contexts, as part of efforts such as the Cancer Dependency Map, to identify gene dependencies-genes whose loss of function reduces cell viability or fitness. Recently, large-scale screening efforts have shifted from RNAi to CRISPR-Cas9, due to superior efficacy and specificity. However, many effective oncology drugs only partially inhibit their protein targets, leading us to question whether partial suppression of genes using RNAi could reveal cancer vulnerabilities that are missed by complete knockout using CRISPR-Cas9. Here, we compare CRISPR-Cas9 and RNAi dependency profiles of genes across approximately 400 matched cancer cell lines.

RESULTS

We find that CRISPR screens accurately identify more gene dependencies per cell line, but the majority of each cell line's dependencies are part of a set of 1867 genes that are shared dependencies across the entire collection (pan-lethals). While RNAi knockdown of about 30% of these genes is also pan-lethal, approximately 50% have selective dependency patterns across cell lines, suggesting they could still be cancer vulnerabilities. The accuracy of the unique RNAi selectivity is supported by associations to multi-omics profiles, drug sensitivity, and other expected co-dependencies.

CONCLUSIONS

Incorporating RNAi data for genes that are pan-lethal knockouts facilitates the discovery of a wider range of gene targets than could be detected using the CRISPR dataset alone. This 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.

Collateral lethality between HDAC1 and HDAC2 exploits cancer-specific NuRD complex vulnerabilities

Transcriptional co-regulators have been widely pursued as targets for disrupting oncogenic gene regulatory programs. However, many proteins in this target class are universally essential for cell survival, which limits their therapeutic window. Here we unveil a genetic interaction between histone deacetylase 1 (HDAC1) and HDAC2, wherein each paralog is synthetically lethal with hemizygous deletion of the other. This collateral synthetic lethality is caused by recurrent chromosomal deletions that occur in diverse solid and hematological malignancies, including neuroblastoma and multiple myeloma. Using genetic disruption or dTAG-mediated degradation, we show that targeting HDAC2 suppresses the growth of HDAC1-deficient neuroblastoma in vitro and in vivo. Mechanistically, we find that targeted degradation of HDAC2 in these cells prompts the degradation of several members of the nucleosome remodeling and deacetylase (NuRD) complex, leading to diminished chromatin accessibility at HDAC2-NuRD-bound sites of the genome and impaired control of enhancer-associated transcription. Furthermore, we reveal that several of the degraded NuRD complex subunits are dependencies in neuroblastoma and multiple myeloma, providing motivation to develop paralog-selective HDAC1 or HDAC2 degraders that could leverage HDAC1/2 synthetic lethality to target NuRD vulnerabilities. Altogether, we identify HDAC1/2 collateral synthetic lethality as a potential therapeutic target and reveal an unexplored mechanism for targeting NuRD-associated cancer dependencies.

Context-defined cancer co-dependency mapping identifies a functional interplay between PRC2 and MLL-MEN1 complex in lymphoma

Interplay between chromatin-associated complexes and modifications critically contribute to the partitioning of epigenome into stable and functionally distinct domains. Yet there is a lack of systematic identification of chromatin crosstalk mechanisms, limiting our understanding of the dynamic transition between chromatin states during development and disease. Here we perform co-dependency mapping of genes using CRISPR-Cas9-mediated fitness screens in pan-cancer cell lines to quantify gene-gene functional relationships. We identify 145 co-dependency modules and further define the molecular context underlying the essentiality of these modules by incorporating mutational, epigenome, gene expression and drug sensitivity profiles of cell lines. These analyses assign new protein complex composition and function, and predict new functional interactions, including an unexpected co-dependency between two transcriptionally counteracting chromatin complexes - polycomb repressive complex 2 (PRC2) and MLL-MEN1 complex. We show that PRC2-mediated H3K27 tri-methylation regulates the genome-wide distribution of MLL1 and MEN1. In lymphoma cells with EZH2 gain-of-function mutations, the re-localization of MLL-MEN1 complex drives oncogenic gene expression and results in a hypersensitivity to pharmacologic inhibition of MEN1. Together, our findings provide a resource for discovery of trans-regulatory interactions as mechanisms of chromatin regulation and potential targets of synthetic lethality.

GRETTA: an R package for mapping in silico genetic interaction and essentiality networks

SUMMARY

Mapping genetic interactions and essentiality networks in human cell lines has been used to identify vulnerabilities of cells carrying specific genetic alterations and to associate novel functions to genes, respectively. In vitro and in vivo genetic screens to decipher these networks are resource-intensive, limiting the throughput of samples that can be analyzed. In this application note, we provide an R package we call Genetic inteRaction and EssenTiality neTwork mApper (GRETTA). GRETTA is an accessible tool for in silico genetic interaction screens and essentiality network analyses using publicly available data, requiring only basic R programming knowledge.

AVAILABILITY AND IMPLEMENTATION

The R package, GRETTA, is licensed under GNU General Public License v3.0 and freely available at https://github.com/ytakemon/GRETTA and https://doi.org/10.5281/zenodo.6940757, with documentation and tutorial. A Singularity container is also available at https://cloud.sylabs.io/library/ytakemon/gretta/gretta.

Global analysis of the yeast knockout phenome

Genome-wide phenotypic screens in the budding yeast Saccharomyces cerevisiae, enabled by its knockout collection, have produced the largest, richest, and most systematic phenotypic description of any organism. However, integrative analyses of this rich data source have been virtually impossible because of the lack of a central data repository and consistent metadata annotations. Here, we describe the aggregation, harmonization, and analysis of ~14,500 yeast knockout screens, which we call Yeast Phenome. Using this unique dataset, we characterized two unknown genes (YHR045W and YGL117W) and showed that tryptophan starvation is a by-product of many chemical treatments. Furthermore, we uncovered an exponential relationship between phenotypic similarity and intergenic distance, which suggests that gene positions in both yeast and human genomes are optimized for function.

Multi-Omic Analysis of CIC's Functional Networks Reveals Novel Interaction Partners and a Potential Role in Mitotic Fidelity

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CIC's interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, as well as novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines, predominantly at 3' and 5' untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CIC's functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CIC's potential roles in cancer. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts.

Automated assembly of molecular mechanisms at scale from text mining and curated databases

The analysis of omic data depends on machine-readable information about protein interactions, modifications, and activities as found in protein interaction networks, databases of post-translational modifications, and curated models of gene and protein function. These resources typically depend heavily on human curation. Natural language processing systems that read the primary literature have the potential to substantially extend knowledge resources while reducing the burden on human curators. However, machine-reading systems are limited by high error rates and commonly generate fragmentary and redundant information. Here, we describe an approach to precisely assemble molecular mechanisms at scale using multiple natural language processing systems and the Integrated Network and Dynamical Reasoning Assembler (INDRA). INDRA identifies full and partial overlaps in information extracted from published papers and pathway databases, uses predictive models to improve the reliability of machine reading, and thereby assembles individual pieces of information into non-redundant and broadly usable mechanistic knowledge. Using INDRA to create high-quality corpora of causal knowledge we show it is possible to extend protein-protein interaction databases and explain co-dependencies in the Cancer Dependency Map.

BRD9 Degradation Disrupts Ribosome Biogenesis in Multiple Myeloma

PURPOSE

BRD9 is a defining component of the noncanonical SWI/SNF complex, which regulates gene expression by controlling chromatin dynamics. Although recent studies have found an oncogenic role for BRD9 in multiple cancer types including multiple myeloma, its clinical significance and oncogenic mechanism have not yet been elucidated. Here, we sought to identify the clinical and biological impact of BRD9 in multiple myeloma, which may contribute to the development of novel therapeutic strategies.

EXPERIMENTAL DESIGN

We performed integrated analyses of BRD9 in vitro and in vivo using multiple myeloma cell lines and primary multiple myeloma cells in established preclinical models, which identified the molecular functions of BRD9 contributing to multiple myeloma cell survival.

RESULTS

We found that high BRD9 expression was a poor prognostic factor in multiple myeloma. Depleting BRD9 by genetic (shRNA) and pharmacologic (dBRD9-A; proteolysis-targeting chimera; BRD9 degrader) approaches downregulated ribosome biogenesis genes, decreased the expression of the master regulator MYC, and disrupted the protein-synthesis maintenance machinery, thereby inhibiting multiple myeloma cell growth in vitro and in vivo in preclinical models. Importantly, we identified that the expression of ribosome biogenesis genes was associated with the disease progression and prognosis of patients with multiple myeloma. Our results suggest that BRD9 promotes gene expression by predominantly occupying the promoter regions of ribosome biogenesis genes and cooperating with BRD4 to enhance the transcriptional function of MYC.

CONCLUSIONS

Our study identifies and validates BRD9 as a novel therapeutic target in preclinical models of multiple myeloma, which provides the framework for the clinical evaluation of BRD9 degraders to improve patient outcome.

A global genetic interaction network by single-cell imaging and machine learning

Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different organisms. Here, we generated synthetic genetic interaction and cell morphology profiles of more than 6,800 genes in cultured Drosophila cells. The resulting map of genetic interactions was used for machine learning-based gene function discovery, assigning functions to genes in 47 modules. Furthermore, we devised Cytoclass as a method to dissect genetic interactions for discrete cell states at the single-cell resolution. This approach identified an interaction of Cdk2 and the Cop9 signalosome complex, triggering senescence-associated secretory phenotypes and immunogenic conversion in hemocytic cells. Together, our data constitute a genome-scale resource of functional gene profiles to uncover the mechanisms underlying genetic interactions and their plasticity at the single-cell level.

Stepwise activities of mSWI/SNF family chromatin remodeling complexes direct T cell activation and exhaustion

Highly coordinated changes in gene expression underlie T cell activation and exhaustion. However, the mechanisms by which such programs are regulated and how these may be targeted for therapeutic benefit remain poorly understood. Here, we comprehensively profile the genomic occupancy of mSWI/SNF chromatin remodeling complexes throughout acute and chronic T cell stimulation, finding that stepwise changes in localization over transcription factor binding sites direct site-specific chromatin accessibility and gene activation leading to distinct phenotypes. Notably, perturbation of mSWI/SNF complexes using genetic and clinically relevant chemical strategies enhances the persistence of T cells with attenuated exhaustion hallmarks and increased memory features in vitro and in vivo. Finally, pharmacologic mSWI/SNF inhibition improves CAR-T expansion and results in improved anti-tumor control in vivo. These findings reveal the central role of mSWI/SNF complexes in the coordination of T cell activation and exhaustion and nominate small-molecule-based strategies for the improvement of current immunotherapy protocols.

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 apply 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 confirms a known chordoma dependency, TBXT (T; brachyury), and identifies 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, are also recovered. We find 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, have potent preclinical efficacy against chordoma. Our results generate an emerging map of chordoma dependencies to enable biological and therapeutic hypotheses.

Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens

CRISPR-Cas9 screens facilitate the discovery of gene functional relationships and phenotype-specific dependencies. The Cancer Dependency Map (DepMap) is the largest compendium of whole-genome CRISPR screens aimed at identifying cancer-specific genetic dependencies across human cell lines. A mitochondria-associated bias has been previously reported to mask signals for genes involved in other functions, and thus, methods for normalizing this dominant signal to improve co-essentiality networks are of interest. In this study, we explore three unsupervised dimensionality reduction methods - autoencoders, robust, and classical principal component analyses (PCA) - for normalizing the DepMap to improve functional networks extracted from these data. We propose a novel "onion" normalization technique to combine several normalized data layers into a single network. Benchmarking analyses reveal that robust PCA combined with onion normalization outperforms existing methods for normalizing the DepMap. Our work demonstrates the value of removing low-dimensional signals from the DepMap before constructing functional gene networks and provides generalizable dimensionality reduction-based normalization tools.

A Ubiquitination Cascade Regulating the Integrated Stress Response and Survival in Carcinomas

Systematic identification of signaling pathways required for the fitness of cancer cells will facilitate the development of new cancer therapies. We used gene essentiality measurements in 1,086 cancer cell lines to identify selective coessentiality modules and found that a ubiquitin ligase complex composed of UBA6, BIRC6, KCMF1, and UBR4 is required for the survival of a subset of epithelial tumors that exhibit a high degree of aneuploidy. Suppressing BIRC6 in cell lines that are dependent on this complex led to a substantial reduction in cell fitness in vitro and potent tumor regression in vivo. Mechanistically, BIRC6 suppression resulted in selective activation of the integrated stress response (ISR) by stabilization of the heme-regulated inhibitor, a direct ubiquitination target of the UBA6/BIRC6/KCMF1/UBR4 complex. These observations uncover a novel ubiquitination cascade that regulates ISR and highlight the potential of ISR activation as a new therapeutic strategy.

SIGNIFICANCE

We describe the identification of a heretofore unrecognized ubiquitin ligase complex that prevents the aberrant activation of the ISR in a subset of cancer cells. This provides a novel insight on the regulation of ISR and exposes a therapeutic opportunity to selectively eliminate these cancer cells. See related commentary Leli and Koumenis, p. 535. This article is highlighted in the In This Issue feature, p. 517.

Pharmacological disruption of mSWI/SNF complex activity restricts SARS-CoV-2 infection

Identification of host determinants of coronavirus infection informs mechanisms of viral pathogenesis and can provide new drug targets. Here we demonstrate that mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) chromatin remodeling complexes, specifically canonical BRG1/BRM-associated factor (cBAF) complexes, promote severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and represent host-directed therapeutic targets. The catalytic activity of SMARCA4 is required for mSWI/SNF-driven chromatin accessibility at the ACE2 locus, ACE2 expression and virus susceptibility. The transcription factors HNF1A/B interact with and recruit mSWI/SNF complexes to ACE2 enhancers, which contain high HNF1A motif density. Notably, small-molecule mSWI/SNF ATPase inhibitors or degraders abrogate angiotensin-converting enzyme 2 (ACE2) expression and confer resistance to SARS-CoV-2 variants and a remdesivir-resistant virus in three cell lines and three primary human cell types, including airway epithelial cells, by up to 5 logs. These data highlight the role of mSWI/SNF complex activities in conferring SARS-CoV-2 susceptibility and identify a potential class of broad-acting antivirals to combat emerging coronaviruses and drug-resistant variants.

FDX1 regulates cellular protein lipoylation through direct binding to LIAS

Ferredoxins are a family of iron-sulfur (Fe-S) cluster proteins that serve as essential electron donors in numerous cellular processes that are conserved through evolution. The promiscuous nature of ferredoxins as electron donors enables them to participate in many metabolic processes including steroid, heme, vitamin D and Fe-S cluster biosynthesis in different organisms. However, the unique natural function(s) of each of the two human ferredoxins (FDX1 and FDX2) are still poorly characterized. We recently reported that FDX1 is both a crucial regulator of copper ionophore induced cell death and serves as an upstream regulator of cellular protein lipoylation, a mitochondrial lipid-based post translational modification naturally occurring on four mitochondrial enzymes that are crucial for TCA cycle function. Here we show that FDX1 regulates protein lipoylation by directly binding to the lipoyl synthase (LIAS) enzyme and not through indirect regulation of cellular Fe-S cluster biosynthesis. Metabolite profiling revealed that the predominant cellular metabolic outcome of FDX1 loss-of-function is manifested through the regulation of the four lipoylation-dependent enzymes ultimately resulting in loss of cellular respiration and sensitivity to mild glucose starvation. Transcriptional profiling of cells growing in either normal or low glucose conditions established that FDX1 loss-of-function results in the induction of both compensatory metabolism related genes and the integrated stress response, consistent with our findings that FDX1 loss-of-functions is conditionally lethal. Together, our findings establish that FDX1 directly engages with LIAS, promoting cellular protein lipoylation, a process essential in maintaining cell viability under low glucose conditions.

Prioritization of New Candidate Genes for Rare Genetic Diseases by a Disease-Aware Evaluation of Heterogeneous Molecular Networks

Screening for pathogenic variants in the diagnosis of rare genetic diseases can now be performed on all genes thanks to the application of whole exome and genome sequencing (WES, WGS). Yet the repertoire of gene-disease associations is not complete. Several computer-based algorithms and databases integrate distinct gene-gene functional networks to accelerate the discovery of gene-disease associations. We hypothesize that the ability of every type of information to extract relevant insights is disease-dependent. We compiled 33 functional networks classified into 13 knowledge categories (KCs) and observed large variability in their ability to recover genes associated with 91 genetic diseases, as measured using efficiency and exclusivity. We developed GLOWgenes, a network-based algorithm that applies random walk with restart to evaluate KCs' ability to recover genes from a given list associated with a phenotype and modulates the prediction of new candidates accordingly. Comparison with other integration strategies and tools shows that our disease-aware approach can boost the discovery of new gene-disease associations, especially for the less obvious ones. KC contribution also varies if obtained using recently discovered genes. Applied to 15 unsolved WES, GLOWgenes proposed three new genes to be involved in the phenotypes of patients with syndromic inherited retinal dystrophies.

BRD9-containing non-canonical BAF complex maintains somatic cell transcriptome and acts as a barrier to human reprogramming

Epigenetic reprogramming to pluripotency requires extensive remodeling of chromatin landscapes to silence existing cell-type-specific genes and activate pluripotency genes. ATP-dependent chromatin remodeling complexes are important regulators of chromatin structure and gene expression; however, the role of recently identified Bromodomain-containing protein 9 (BRD9) and the associated non-canonical BRG1-associated factors (ncBAF) complex in reprogramming remains unknown. Here, we show that genetic or chemical inhibition of BRD9, as well as ncBAF complex subunit GLTSCR1, but not the closely related BRD7, increase human somatic cell reprogramming efficiency and can replace KLF4 and c-MYC. We find that BRD9 is dispensable for human induced pluripotent stem cells under primed but not under naive conditions. Mechanistically, BRD9 inhibition downregulates fibroblast-related genes and decreases chromatin accessibility at somatic enhancers. BRD9 maintains the expression of transcriptional regulators MN1 and ZBTB38, both of which impede reprogramming. Collectively, these results establish BRD9 as an important safeguarding factor for somatic cell identity whose inhibition lowers chromatin-based barriers to reprogramming.

The phenotypic landscape of essential human genes

Understanding the basis for cellular growth, proliferation, and function requires determining the roles of essential genes in diverse cellular processes, including visualizing their contributions to cellular organization and morphology. Here, we combined pooled CRISPR-Cas9-based functional screening of 5,072 fitness-conferring genes in human HeLa cells with microscopy-based imaging of DNA, the DNA damage response, actin, and microtubules. Analysis of >31 million individual cells identified measurable phenotypes for >90% of gene knockouts, implicating gene targets in specific cellular processes. Clustering of phenotypic similarities based on hundreds of quantitative parameters further revealed co-functional genes across diverse cellular activities, providing predictions for gene functions and associations. By conducting pooled live-cell screening of ∼450,000 cell division events for 239 genes, we additionally identified diverse genes with functional contributions to chromosome segregation. Our work establishes a resource detailing the consequences of disrupting core cellular processes that represents the functional landscape of essential human genes.

Molecular characterization of renal cell carcinoma tumors from a phase III anti-angiogenic adjuvant therapy trial

Multigene assays can provide insight into key biological processes and prognostic information to guide development and selection of adjuvant cancer therapy. We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and that other factors such as immune response and tumor environment may be of greater importance.

C16orf72/HAPSTR1 is a molecular rheostat in an integrated network of stress response pathways

All cells contain specialized signaling pathways that enable adaptation to specific molecular stressors. Yet, whether these pathways are centrally regulated in complex physiological stress states remains unclear. Using genome-scale fitness screening data, we quantified the stress phenotype of 739 cancer cell lines, each representing a unique combination of intrinsic tumor stresses. Integrating dependency and stress perturbation transcriptomic data, we illuminated a network of genes with vital functions spanning diverse stress contexts. Analyses for central regulators of this network nominated C16orf72/HAPSTR1, an evolutionarily ancient gene critical for the fitness of cells reliant on multiple stress response pathways. We found that HAPSTR1 plays a pleiotropic role in cellular stress signaling, functioning to titrate various specialized cell-autonomous and paracrine stress response programs. This function, while dispensable to unstressed cells and nematodes, is essential for resilience in the presence of stressors ranging from DNA damage to starvation and proteotoxicity. Mechanistically, diverse stresses induce HAPSTR1, which encodes a protein expressed as two equally abundant isoforms. Perfectly conserved residues in a domain shared between HAPSTR1 isoforms mediate oligomerization and binding to the ubiquitin ligase HUWE1. We show that HUWE1 is a required cofactor for HAPSTR1 to control stress signaling and that, in turn, HUWE1 feeds back to ubiquitinate and destabilize HAPSTR1. Altogether, we propose that HAPSTR1 is a central rheostat in a network of pathways responsible for cellular adaptability, the modulation of which may have broad utility in human disease.

Integrating multi-omics data reveals function and therapeutic potential of deubiquitinating enzymes

Deubiquitinating enzymes (DUBs), ~100 of which are found in human cells, are proteases that remove ubiquitin conjugates from proteins, thereby regulating protein turnover. They are involved in a wide range of cellular activities and are emerging therapeutic targets for cancer and other diseases. Drugs targeting USP1 and USP30 are in clinical development for cancer and kidney disease respectively. However, the majority of substrates and pathways regulated by DUBs remain unknown, impeding efforts to prioritize specific enzymes for research and drug development. To assemble a knowledgebase of DUB activities, co-dependent genes, and substrates, we combined targeted experiments using CRISPR libraries and inhibitors with systematic mining of functional genomic databases. Analysis of the Dependency Map, Connectivity Map, Cancer Cell Line Encyclopedia, and multiple protein-protein interaction databases yielded specific hypotheses about DUB function, a subset of which were confirmed in follow-on experiments. The data in this paper are browsable online in a newly developed DUB Portal and promise to improve understanding of DUBs as a family as well as the activities of incompletely characterized DUBs (e.g. USPL1 and USP32) and those already targeted with investigational cancer therapeutics (e.g. USP14, UCHL5, and USP7).

Comprehensive identification of SWI/SNF complex subunits underpins deep eukaryotic ancestry and reveals new plant components

Over millions of years, eukaryotes evolved from unicellular to multicellular organisms with increasingly complex genomes and sophisticated gene expression networks. Consequently, chromatin regulators evolved to support this increased complexity. The ATP-dependent chromatin remodelers of the SWI/SNF family are multiprotein complexes that modulate nucleosome positioning and appear under different configurations, which perform distinct functions. While the composition, architecture, and activity of these subclasses are well understood in a limited number of fungal and animal model organisms, the lack of comprehensive information in other eukaryotic organisms precludes the identification of a reliable evolutionary model of SWI/SNF complexes. Here, we performed a systematic analysis using 36 species from animal, fungal, and plant lineages to assess the conservation of known SWI/SNF subunits across eukaryotes. We identified evolutionary relationships that allowed us to propose the composition of a hypothetical ancestral SWI/SNF complex in the last eukaryotic common ancestor. This last common ancestor appears to have undergone several rounds of lineage-specific subunit gains and losses, shaping the current conformation of the known subclasses in animals and fungi. In addition, our results unravel a plant SWI/SNF complex, reminiscent of the animal BAF subclass, which incorporates a set of plant-specific subunits of still unknown function.

SMARCE1 deficiency generates a targetable mSWI/SNF dependency in clear cell meningioma

Mammalian SWI/SNF (mSWI/SNF) ATP-dependent chromatin remodeling complexes establish and maintain chromatin accessibility and gene expression, and are frequently perturbed in cancer. Clear cell meningioma (CCM), an aggressive tumor of the central nervous system, is uniformly driven by loss of SMARCE1, an integral subunit of the mSWI/SNF core. Here, we identify a structural role for SMARCE1 in selectively stabilizing the canonical BAF (cBAF) complex core-ATPase module interaction. In CCM, cBAF complexes fail to stabilize on chromatin, reducing enhancer accessibility, and residual core module components increase the formation of BRD9-containing non-canonical BAF (ncBAF) complexes. Combined attenuation of cBAF function and increased ncBAF complex activity generates the CCM-specific gene expression signature, which is distinct from that of NF2-mutated meningiomas. Importantly, SMARCE1-deficient cells exhibit heightened sensitivity to small-molecule inhibition of ncBAF complexes. These data inform the function of a previously elusive SWI/SNF subunit and suggest potential therapeutic approaches for intractable SMARCE1-deficient CCM tumors.

Sparse dictionary learning recovers pleiotropy from human cell fitness screens

In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach (Webster) recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and predicted the stoichiometry of an unknown protein complex subunit from fitness data alone. Modeling compound sensitivity profiles in terms of genetic functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts.

HSF2 cooperates with HSF1 to drive a transcriptional program critical for the malignant state

Heat shock factor 1 (HSF1) is well known for its role in the heat shock response (HSR), where it drives a transcriptional program comprising heat shock protein (HSP) genes, and in tumorigenesis, where it drives a program comprising HSPs and many noncanonical target genes that support malignancy. Here, we find that HSF2, an HSF1 paralog with no substantial role in the HSR, physically and functionally interacts with HSF1 across diverse types of cancer. HSF1 and HSF2 have notably similar chromatin occupancy and regulate a common set of genes that include both HSPs and noncanonical transcriptional targets with roles critical in supporting malignancy. Loss of either HSF1 or HSF2 results in a dysregulated response to nutrient stresses in vitro and reduced tumor progression in cancer cell line xenografts. Together, these findings establish HSF2 as a critical cofactor of HSF1 in driving a cancer cell transcriptional program to support the anabolic malignant state.

Identification of a glioma functional network from gene fitness data using machine learning

Glioblastoma multiforme (GBM) is an aggressive form of brain tumours that remains incurable despite recent advances in clinical treatments. Previous studies have focused on sub-categorizing patient samples based on clustering various transcriptomic data. While functional genomics data are rapidly accumulating, there exist opportunities to leverage these data to decipher glioma-associated biomarkers. We sought to implement a systematic approach to integrating data from high throughput CRISPR-Cas9 screening studies with machine learning algorithms to infer a glioma functional network. We demonstrated the network significantly enriched various biological pathways and may play roles in glioma tumorigenesis. From densely connected glioma functional modules, we further predicted 12 potential Wnt/β-catenin signalling pathway targeted genes, including AARSD1, HOXB5, ITGA6, LRRC71, MED19, MED24, METTL11B, SMARCB1, SMARCE1, TAF6L, TENT5A and ZNF281. Cox regression modelling with these targets was significantly associated with glioma overall survival prognosis. Additionally, TRIB2 was identified as a glioma neoplastic cell marker in single-cell RNA-seq of GBM samples. This work establishes novel strategies for constructing functional networks to identify glioma biomarkers for the development of diagnosis and treatment in clinical practice.

Cyclin F drives proliferation through SCF-dependent degradation of the retinoblastoma-like tumor suppressor p130/RBL2

Cell cycle gene expression programs fuel proliferation and are universally dysregulated in cancer. The retinoblastoma (RB)-family of proteins, RB1, RBL1/p107, and RBL2/p130, coordinately represses cell cycle gene expression, inhibiting proliferation, and suppressing tumorigenesis. Phosphorylation of RB-family proteins by cyclin-dependent kinases is firmly established. Like phosphorylation, ubiquitination is essential to cell cycle control, and numerous proliferative regulators, tumor suppressors, and oncoproteins are ubiquitinated. However, little is known about the role of ubiquitin signaling in controlling RB-family proteins. A systems genetics analysis of CRISPR/Cas9 screens suggested the potential regulation of the RB-network by cyclin F, a substrate recognition receptor for the SCF family of E3 ligases. We demonstrate that RBL2/p130 is a direct substrate of SCF^{cyclin F}. We map a cyclin F regulatory site to a flexible linker in the p130 pocket domain, and show that this site mediates binding, stability, and ubiquitination. Expression of a mutant version of p130, which cannot be ubiquitinated, severely impaired proliferative capacity and cell cycle progression. Consistently, we observed reduced expression of cell cycle gene transcripts, as well a reduced abundance of cell cycle proteins, analyzed by quantitative, iterative immunofluorescent imaging. These data suggest a key role for SCF^{cyclin F} in the CDK-RB network and raise the possibility that aberrant p130 degradation could dysregulate the cell cycle in human cancers.

Towards a CRISPeR understanding of homologous recombination with high-throughput functional genomics

CRISPR-dependent genome editing enables the study of genes and mutations on a large scale. Here we review CRISPR-based functional genomics technologies that generate gene knockouts and single nucleotide variants (SNVs) and discuss how their use has provided new important insights into the function of homologous recombination (HR) genes. In particular, we highlight discoveries from CRISPR screens that have contributed to define the response to PARP inhibition in cells deficient for the HR genes BRCA1 and BRCA2, uncover genes whose loss causes synthetic lethality in combination with BRCA1/2 deficiency, and characterize the function of BRCA1/2 SNVs of uncertain clinical significance. Further use of these approaches, combined with next-generation CRISPR-based technologies, will aid to dissect the genetic network of the HR pathway, define the impact of HR mutations on cancer etiology and treatment, and develop novel targeted therapies for HR-deficient tumors.

Discovery of putative tumor suppressors from CRISPR screens reveals rewired lipid metabolism in acute myeloid leukemia cells

CRISPR knockout fitness screens in cancer cell lines reveal many genes whose loss of function causes cell death or loss of fitness or, more rarely, the opposite phenotype of faster proliferation. Here we demonstrate a systematic approach to identify these proliferation suppressors, which are highly enriched for tumor suppressor genes, and define a network of 145 such genes in 22 modules. One module contains several elements of the glycerolipid biosynthesis pathway and operates exclusively in a subset of acute myeloid leukemia cell lines. The proliferation suppressor activity of genes involved in the synthesis of saturated fatty acids, coupled with a more severe loss of fitness phenotype for genes in the desaturation pathway, suggests that these cells operate at the limit of their carrying capacity for saturated fatty acids, which we confirm biochemically. Overexpression of this module is associated with a survival advantage in juvenile leukemias, suggesting a clinically relevant subtype.

CRISPR-based knockout screens in cancer cells have suggested the existence of proliferation suppressor genes (PSG). Here, the authors develop an approach to systematically identify them, and reveal a PSG module involved in fatty acid synthesis and tumour suppression in acute myeloid leukemia cell lines.

Systematic pan-cancer characterization of nuclear receptors identifies potential cancer biomarkers and therapeutic targets

The nuclear receptor (NR) superfamily is one of the major druggable gene families, representing targets of approximately 13.5% of approved drugs. Certain NRs, such as estrogen receptor and androgen receptor, have been well demonstrated to be functionally involved in cancer and serve as informative biomarkers and therapeutic targets in oncology. However, the spectrum of NR dysregulation across cancers remains to be comprehensively characterized. Through computational integration of genetic, genomic, and pharmacologic profiles, we characterized the expression, recurrent genomic alterations, and cancer dependency of NRs at a large scale across primary tumor specimens and cancer cell lines. Expression levels of NRs were highly cancer-type specific and globally downregulated in tumors compared to corresponding normal tissue. Although the majority of NRs showed copy number losses in cancer, both recurrent focal gains and losses were identified in select NRs. Recurrent mutations and transcript fusions of NRs were observed in a small portion of cancers, serving as actionable genomic alterations. Analysis of large-scale CRISPR and RNAi screening datasets identified 10 NRs as strongly selective essential genes for cancer cell growth. In a subpopulation of tumor cells, growth dependencies correlated significantly with expression or genomic alterations. Overall, our comprehensive characterization of NRs across cancers may facilitate the identification and prioritization of potential biomarkers and therapeutic targets, as well as the selection of patients for precision cancer treatment.

Paralogous synthetic lethality underlies genetic dependencies of the cancer-mutated gene STAG2

STAG2, a component of the mitotically essential cohesin complex, is highly mutated in several different tumour types, including glioblastoma and bladder cancer. Whereas cohesin has roles in many cancer-related pathways, such as chromosome instability, DNA repair and gene expression, the complex nature of cohesin function has made it difficult to determine how STAG2 loss might either promote tumorigenesis or be leveraged therapeutically across divergent cancer types. Here, we have performed whole-genome CRISPR-Cas9 screens for STAG2-dependent genetic interactions in three distinct cellular backgrounds. Surprisingly, STAG1, the paralog of STAG2, was the only negative genetic interaction that was shared across all three backgrounds. We also uncovered a paralogous synthetic lethal mechanism behind a genetic interaction between STAG2 and the iron regulatory gene IREB2 Finally, investigation of an unusually strong context-dependent genetic interaction in HAP1 cells revealed factors that could be important for alleviating cohesin loading stress. Together, our results reveal new facets of STAG2 and cohesin function across a variety of genetic contexts.

Integrated evaluation of telomerase activation and telomere maintenance across cancer cell lines

In cancer, telomere maintenance is critical for the development of replicative immortality. Using genome sequences from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer Project, we calculated telomere content across 1299 cancer cell lines. We find that telomerase reverse transcriptase (TERT) expression correlates with telomere content in lung, central nervous system, and leukemia cell lines. Using CRISPR/Cas9 screening data, we show that lower telomeric content is associated with dependency of CST telomere maintenance genes. Increased dependencies of shelterin members are associated with wild-type TP53 status. Investigating the epigenetic regulation of TERT, we find widespread allele-specific expression in promoter-wildtype contexts. TERT promoter-mutant cell lines exhibit hypomethylation at PRC2-repressed regions, suggesting a cooperative global epigenetic state in the reactivation of telomerase. By incorporating telomere content with genomic features across comprehensively characterized cell lines, we provide further insights into the role of telomere regulation in cancer immortality.