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.

Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias

Clinical progress in multiple myeloma (MM), an incurable plasma cell (PC) neoplasia, has been driven by therapies that have limited applications beyond MM/PC neoplasias and do not target specific oncogenic mutations in MM. Instead, these agents target pathways critical for PC biology yet largely dispensable for malignant or normal cells of most other lineages. Here we systematically characterized the lineage-preferential molecular dependencies of MM through genome-scale clustered regularly interspaced short palindromic repeats (CRISPR) studies in 19 MM versus hundreds of non-MM lines and identified 116 genes whose disruption more significantly affects MM cell fitness compared with other malignancies. These genes, some known, others not previously linked to MM, encode transcription factors, chromatin modifiers, endoplasmic reticulum components, metabolic regulators or signaling molecules. Most of these genes are not among the top amplified, overexpressed or mutated in MM. Functional genomics approaches thus define new therapeutic targets in MM not readily identifiable by standard genomic, transcriptional or epigenetic profiling analyses.

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.

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.

BAF Complex Maintains Glioma Stem Cells in Pediatric H3K27M Glioma

Diffuse midline gliomas are uniformly fatal pediatric central nervous system cancers that are refractory to standard-of-care therapeutic modalities. The primary genetic drivers are a set of recurrent amino acid substitutions in genes encoding histone H3 (H3K27M), which are currently undruggable. These H3K27M oncohistones perturb normal chromatin architecture, resulting in an aberrant epigenetic landscape. To interrogate for epigenetic dependencies, we performed a CRISPR screen and show that patient-derived H3K27M-glioma neurospheres are dependent on core components of the mammalian BAF (SWI/SNF) chromatin remodeling complex. The BAF complex maintains glioma stem cells in a cycling, oligodendrocyte precursor cell-like state, in which genetic perturbation of the BAF catalytic subunit SMARCA4 (BRG1), as well as pharmacologic suppression, opposes proliferation, promotes progression of differentiation along the astrocytic lineage, and improves overall survival of patient-derived xenograft models. In summary, we demonstrate that therapeutic inhibition of the BAF complex has translational potential for children with H3K27M gliomas.

SIGNIFICANCE

Epigenetic dysregulation is at the core of H3K27M-glioma tumorigenesis. Here, we identify the BRG1-BAF complex as a critical regulator of enhancer and transcription factor landscapes, which maintain H3K27M glioma in their progenitor state, precluding glial differentiation, and establish pharmacologic targeting of the BAF complex as a novel treatment strategy for pediatric H3K27M glioma. See related commentary by Beytagh and Weiss, p. 2730. See related article by Mo et al., p. 2906.

Transcriptional Plasticity Drives Leukemia Immune Escape

Relapse of acute myeloid leukemia (AML) after allogeneic bone marrow transplantation has been linked to immune evasion due to reduced expression of major histocompatibility complex class II (MHCII) genes through unknown mechanisms. In this work, we developed CORENODE, a computational algorithm for genome-wide transcription network decomposition that identified a transcription factor (TF) tetrad consisting of IRF8, MYB, MEF2C, and MEIS1, regulating MHCII expression in AML cells. We show that reduced MHCII expression at relapse is transcriptionally driven by combinatorial changes in the expression of these TFs, where MYB and IRF8 play major opposing roles, acting independently of the IFNγ/CIITA pathway. Beyond the MHCII genes, MYB and IRF8 antagonistically regulate a broad genetic program responsible for cytokine signaling and T-cell stimulation that displays reduced expression at relapse. A small number of cells with altered TF abundance and silenced MHCII expression are present at the time of initial leukemia diagnosis, likely contributing to eventual relapse.

SIGNIFICANCE

Our findings point to an adaptive transcriptional mechanism of AML evolution after allogeneic transplantation whereby combinatorial fluctuations of TF expression under immune pressure result in the selection of cells with a silenced T-cell stimulation program. This article is highlighted in the In This Issue feature, p. 369.

Abstract 73: A ubiquitination cascade regulating the integrated stress response and survival in carcinomas

Targeting of mutated oncogenes has led to the identification of new targeted therapies. However, druggable oncogenes do not occur in most cancers. 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 793 cancer cell lines to identify selective co-essentiality modules and found that a ubiquitination ligase complex composed of UBA6, BIRC6, KCMF1 and UBR4, which encode an E1, E2 and two heterodimeric E3 subunits, respectively, is required for the survival of a subset of epithelial tumors. 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 and upregulation of the heme-regulated inhibitor (HRI), 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.

Citation Format: Lisa D. Cervia, Tsukasa Shibue, Benjamin Gaeta, Ashir A. Borah, Lisa Leung, Naomi Li, Nancy Dumont, Alfredo Gonzalez, Nolan Bick, Mariya Kazachkova, Joshua M. Dempster, John M. Krill-Burger, Federica Piccioni, Namrata D. Udeshi, Meagan E. Olive, Steven A. Carr, David E. Root, James M. McFarland, Francisca Vazquez, William C. Hahn. A ubiquitination cascade regulating the integrated stress response and survival in carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 73.

Phosphate dysregulation via the XPR1-KIDINS220 protein complex is a therapeutic vulnerability in ovarian cancer

Despite advances in precision medicine, the clinical prospects for patients with ovarian and uterine cancers have not substantially improved. Here, we analyzed genome-scale CRISPR/Cas9 loss-of-function screens across 851 human cancer cell lines and found that frequent overexpression of SLC34A2 – encoding a phosphate importer – is correlated to sensitivity to loss of the phosphate exporter XPR1 in vitro and in vivo. In patient-derived tumor samples, we observed frequent PAX8-dependent overexpression of SLC34A2, XPR1 copy number amplifications, and XPR1 mRNA overexpression. Mechanistically, in SLC34A2-high cancer cell lines, genetic or pharmacologic inhibition of XPR1-dependent phosphate efflux leads to the toxic accumulation of intracellular phosphate. Finally, we show that XPR1 requires the novel partner protein KIDINS220 for proper cellular localization and activity, and that disruption of this protein complex results in acidic vacuolar structures preceding cell death. These data point to the XPR1:KIDINS220 complex and phosphate dysregulation as a therapeutic vulnerability in ovarian cancer.

Golub and colleagues identify the phosphate exporter XPR1 as a therapeutic vulnerability in ovarian and uterine cancers, and show that phosphate efflux inhibition reduces tumor cell viability through accumulation of intracellular phosphate.

Comparative optimization of combinatorial CRISPR screens

Combinatorial CRISPR technologies have emerged as a transformative approach to systematically probe genetic interactions and dependencies of redundant gene pairs. However, the performance of different functional genomic tools for multiplexing sgRNAs vary widely. Here, we generate and benchmark ten distinct pooled combinatorial CRISPR libraries targeting paralog pairs to optimize digenic knockout screens. Libraries composed of dual Streptococcus pyogenes Cas9 (spCas9), orthogonal spCas9 and Staphylococcus aureus (saCas9), and enhanced Cas12a from Acidaminococcus were evaluated. We demonstrate a combination of alternative tracrRNA sequences from spCas9 consistently show superior effect size and positional balance between the sgRNAs as a robust combinatorial approach to profile genetic interactions of multiple genes.

A distinct core regulatory module enforces oncogene expression in KMT2A-rearranged leukemia

In this study, Harada et al. identified the transcription factors MEF2D and IRF8 as selective transcriptional dependencies of KMT2A-rearranged AML, where MEF2D displays partially redundant functions with its paralog, MEF2C. This study illustrates a mechanism of context-specific transcriptional addiction whereby a specific AML subclass depends on a highly specialized core regulatory module to directly enforce expression of common leukemia oncogenes.

Acute myeloid leukemia with KMT2A (MLL) rearrangements is characterized by specific patterns of gene expression and enhancer architecture, implying unique core transcriptional regulatory circuitry. Here, we identified the transcription factors MEF2D and IRF8 as selective transcriptional dependencies of KMT2A-rearranged AML, where MEF2D displays partially redundant functions with its paralog, MEF2C. Rapid transcription factor degradation followed by measurements of genome-wide transcription rates and superresolution microscopy revealed that MEF2D and IRF8 form a distinct core regulatory module with a narrow direct transcriptional program that includes activation of the key oncogenes MYC, HOXA9, and BCL2. Our study illustrates a mechanism of context-specific transcriptional addiction whereby a specific AML subclass depends on a highly specialized core regulatory module to directly enforce expression of common leukemia oncogenes.

Abstract P3-09-01: A ubiquitination cascade regulating the integrated stress response and survival in carcinomas

Targeting of mutated oncogenes has led to the identification of new targeted therapies. However, druggable oncogenes do not occur in most cancers. 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 793 cancer cell lines to identify selective co-essentiality modules and found that a ubiquitination ligase complex composed of UBA6, BIRC6, KCMF1 and UBR4, which encode an E1, E2 and two heterodimeric E3 subunits, respectively, is required for the survival of a subset of epithelial tumors, particularly subtypes of breast cancer. 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 and upregulation of the heme-regulated inhibitor (HRI), 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.

Citation Format: Lisa D Cervia, Tsukasa Shibue, Benjamin Gaeta, Ashir A Borah, Lisa Leung, Naomi Li, Nancy Dumont, Alfredo Gonzalez, Nolan Bick, Mariya Kazachkova, Joshua M Dempster, John M Krill-Burger, Federica Piccioni, Namrata D Udeshi, Meagan E Olive, Steven A Carr, David E Root, James M McFarland, Francisca Vazquez, William C Hahn. A ubiquitination cascade regulating the integrated stress response and survival in carcinomas [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-09-01.

Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects

CRISPR loss of function screens are powerful tools to interrogate biology but exhibit a number of biases and artifacts that can confound the results. Here, we introduce Chronos, an algorithm for inferring gene knockout fitness effects based on an explicit model of cell proliferation dynamics after CRISPR gene knockout. We test Chronos on two pan-cancer CRISPR datasets and one longitudinal CRISPR screen. Chronos generally outperforms competitors in separation of controls and strength of biomarker associations, particularly when longitudinal data is available. Additionally, Chronos exhibits the lowest copy number and screen quality bias of evaluated methods. Chronos is available at https://github.com/broadinstitute/chronos .

Noncanonical open reading frames encode functional proteins essential for cancer cell survival

Although genomic analyses predict many noncanonical open reading frames (ORFs) in the human genome, it is unclear whether they encode biologically active proteins. Here we experimentally interrogated 553 candidates selected from noncanonical ORF datasets. Of these, 57 induced viability defects when knocked out in human cancer cell lines. Following ectopic expression, 257 showed evidence of protein expression and 401 induced gene expression changes. Clustered regularly interspaced short palindromic repeat (CRISPR) tiling and start codon mutagenesis indicated that their biological effects required translation as opposed to RNA-mediated effects. We found that one of these ORFs, G029442-renamed glycine-rich extracellular protein-1 (GREP1)-encodes a secreted protein highly expressed in breast cancer, and its knockout in 263 cancer cell lines showed preferential essentiality in breast cancer-derived lines. The secretome of GREP1-expressing cells has an increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth-inhibitory effect of GREP1 knockout. Our experiments suggest that noncanonical ORFs can express biologically active proteins that are potential therapeutic targets.

Selective Modulation of a Pan-Essential Protein as a Therapeutic Strategy in Cancer

Cancer dependency maps, which use CRISPR/Cas9 depletion screens to profile the landscape of genetic dependencies in hundreds of cancer cell lines, have identified context-specific dependencies that could be therapeutically exploited. An ideal therapy is both lethal and precise, but these depletion screens cannot readily distinguish between gene effects that are cytostatic or cytotoxic. Here, we use a diverse panel of functional genomic screening assays to identify NXT1 as a selective and rapidly lethal in vivo relevant genetic dependency in MYCN-amplified neuroblastoma. NXT1 heterodimerizes with NXF1, and together they form the principal mRNA nuclear export machinery. We describe a previously unrecognized mechanism of synthetic lethality between NXT1 and its paralog NXT2: their common essential binding partner NXF1 is lost only in the absence of both. We propose a potential therapeutic strategy for tumor-selective elimination of a protein that, if targeted directly, is expected to cause widespread toxicity. SIGNIFICANCE: We provide a framework for identifying new therapeutic targets from functional genomic screens. We nominate NXT1 as a selective lethal target in neuroblastoma and propose a therapeutic approach where the essential protein NXF1 can be selectively eliminated in tumor cells by exploiting the NXT1-NXT2 paralog relationship.See related commentary by Wang and Abdel-Wahab, p. 2129.This article is highlighted in the In This Issue feature, p. 2113.

A first-generation pediatric cancer dependency map

Exciting therapeutic targets are emerging from CRISPR-based screens of high mutational-burden adult cancers. A key question, however, is whether functional genomic approaches will yield new targets in pediatric cancers, known for remarkably few mutations, which often encode proteins considered challenging drug targets. To address this, we created a first-generation pediatric cancer dependency map representing 13 pediatric solid and brain tumor types. Eighty-two pediatric cancer cell lines were subjected to genome-scale CRISPR-Cas9 loss-of-function screening to identify genes required for cell survival. In contrast to the finding that pediatric cancers harbor fewer somatic mutations, we found a similar complexity of genetic dependencies in pediatric cancer cell lines compared to that in adult models. Findings from the pediatric cancer dependency map provide preclinical support for ongoing precision medicine clinical trials. The vulnerabilities observed in pediatric cancers were often distinct from those in adult cancer, indicating that repurposing adult oncology drugs will be insufficient to address childhood cancers.

Integrated cross-study datasets of genetic dependencies in cancer

CRISPR-Cas9 viability screens are increasingly performed at a genome-wide scale across large panels of cell lines to identify new therapeutic targets for precision cancer therapy. Integrating the datasets resulting from these studies is necessary to adequately represent the heterogeneity of human cancers and to assemble a comprehensive map of cancer genetic vulnerabilities. Here, we integrated the two largest public independent CRISPR-Cas9 screens performed to date (at the Broad and Sanger institutes) by assessing, comparing, and selecting methods for correcting biases due to heterogeneous single-guide RNA efficiency, gene-independent responses to CRISPR-Cas9 targeting originated from copy number alterations, and experimental batch effects. Our integrated datasets recapitulate findings from the individual datasets, provide greater statistical power to cancer- and subtype-specific analyses, unveil additional biomarkers of gene dependency, and improve the detection of common essential genes. We provide the largest integrated resources of CRISPR-Cas9 screens to date and the basis for harmonizing existing and future functional genetics datasets.

Synthetic Lethal Interaction of SHOC2 Depletion with MEK Inhibition in RAS-Driven Cancers

The mitogen-activated protein kinase (MAPK) pathway is a critical effector of oncogenic RAS signaling, and MAPK pathway inhibition may be an effective combination treatment strategy. We performed genome-scale loss-of-function CRISPR-Cas9 screens in the presence of a MEK1/2 inhibitor (MEKi) in KRAS-mutant pancreatic and lung cancer cell lines and identified genes that cooperate with MEK inhibition. While we observed heterogeneity in genetic modifiers of MEKi sensitivity across cell lines, several recurrent classes of synthetic lethal vulnerabilities emerged at the pathway level. Multiple members of receptor tyrosine kinase (RTK)-RAS-MAPK pathways scored as sensitizers to MEKi. In particular, we demonstrate that knockout, suppression, or degradation of SHOC2, a positive regulator of MAPK signaling, specifically cooperated with MEK inhibition to impair proliferation in RAS-driven cancer cells. The depletion of SHOC2 disrupted survival pathways triggered by feedback RTK signaling in response to MEK inhibition. Thus, these findings nominate SHOC2 as a potential target for combination therapy.

Abstract LB-100: Systematic target prioritization and validation from genome-scale loss-of-function screens in large panels of human cancer cell lines

Despite its increasing success and revolutionary impact on clinical oncology, Precision Cancer Medicine still has major roadblocks before it becomes applicable to a large proportion of patients. One such roadblock is the limited number of therapeutic targets available. Indeed, for the vast majority of cancer patients, we either do not know what their specific vulnerabilities are or do not have strategies to precisely target their vulnerabilities. In the Cancer Dependency Map Project (DepMap) at the Broad Institute, we aim to overcome these limitations through the use of genome-scale loss-of-function screens in a large panel of cancer cell lines combined with systematic molecular characterization of these cell lines. To date, we have conducted viability screens with genome-wide RNAi and CRISPR/Cas9 libraries on > 800 cell lines, all of which have also been comprehensively profiled with various omics approaches. In order to systematically identify and prioritize potential therapeutic targets, we created an analytical framework that uses a multifaceted approach to score gene dependencies based on the information extracted from screening outcomes, predictive models of sensitivity from all the genetic and molecular information, and the use of priors. To reproducibly validate the nominated targets, we also developed a toolbox of standardized assays that include confirmation of cell viability effects with orthogonal reagents/read-outs and efficient testing for in vivo efficacy across multiple cancer models. Using this approach, we have identified and validated several promising targets, including the WRN DNA helicase that is selectively essential in cancers with microsatellite instability (MSI). The data, framework, and toolbox developed here can inform the nomination and advancement of promising targets for drug development for Precision Cancer Medicine.

Citation Format: Tsukasa Shibue, John M. Krill-Burger, Brenton R. Paolella, Benjamin Gaeta, Adhana Asfaw, Joshua M. Dempster, James M. McFarland, David E. Root, Jesse S. Boehm, Aviad Tsherniak, William C. Hahn, Francisca Vazquez. Systematic target prioritization and validation from genome-scale loss-of-function screens in large panels of human cancer cell lines [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-100.

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyze data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger Institutes. Despite significant differences in experimental protocols and reagents, we find that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one data set are recovered in the other. Through further analysis and replication experiments at each institute, we show that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.

Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

The availability of multiple datasets comprising genome-scale RNAi viability screens in hundreds of diverse cancer cell lines presents new opportunities for understanding cancer vulnerabilities. Integrated analyses of these data to assess differential dependency across genes and cell lines are challenging due to confounding factors such as batch effects and variable screen quality, as well as difficulty assessing gene dependency on an absolute scale. To address these issues, we incorporated cell line screen-quality parameters and hierarchical Bayesian inference into DEMETER2, an analytical framework for analyzing RNAi screens ( https://depmap.org/R2-D2 ). This model substantially improves estimates of gene dependency across a range of performance measures, including identification of gold-standard essential genes and agreement with CRISPR/Cas9-based viability screens. It also allows us to integrate information across three large RNAi screening datasets, providing a unified resource representing the most extensive compilation of cancer cell line genetic dependencies to date.

Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

The availability of multiple datasets comprising genome-scale RNAi viability screens in hundreds of diverse cancer cell lines presents new opportunities for understanding cancer vulnerabilities. Integrated analyses of these data to assess differential dependency across genes and cell lines are challenging due to confounding factors such as batch effects and variable screen quality, as well as difficulty assessing gene dependency on an absolute scale. To address these issues, we incorporated cell line screen-quality parameters and hierarchical Bayesian inference into DEMETER2, an analytical framework for analyzing RNAi screens (https://depmap.org/R2-D2). This model substantially improves estimates of gene dependency across a range of performance measures, including identification of gold-standard essential genes and agreement with CRISPR/Cas9-based viability screens. It also allows us to integrate information across three large RNAi screening datasets, providing a unified resource representing the most extensive compilation of cancer cell line genetic dependencies to date.

Integrated analyses of multiple large-scale screenings can be complicated by batch effects and technical artefacts. McFarland et al. introduce DEMETER2, a hierarchical model coupled with model-based normalization, which allows the assessment of differential dependencies across genes and cell lines.

Contractile actuation and dynamical gel assembly of paramagnetic filaments in fast precessing fields

Flexible superparamagnetic filaments are studied under the influence of fast precessing magnetic fields using simulations and a continuum approximation analysis. We find that individual filaments can be made to exert controllable tensile forces along the precession axis. These forces are exploited for microscopic actuation. In bulk, the filaments can be rapidly assembled into different configurations whose material properties depend on the field parameters. The precession frequency affects filament aggregation and conformation by changing the net torques on the filament ends. Using a time-dependent precession angle allows considerable freedom in choosing properties for filament aggregates. As an example, we design a field that twists chains together to dynamically assemble a self-healing gel.

Contractile actuation and dynamical gel assembly of paramagnetic filaments in fast precessing fields

Flexible superparamagnetic filaments are studied under the influence of fast precessing magnetic fields using simulations and a continuum approximation analysis. We find that individual filaments can be made to exert controllable tensile forces along the precession axis. These forces are exploited for microscopic actuation. In bulk, the filaments can be rapidly assembled into different configurations whose material properties depend on the field parameters. The precession frequency affects filament aggregation and conformation by changing the net torques on the filament ends. Using a time-dependent precession angle allows considerable freedom in choosing properties for filament aggregates. As an example, we design a field that twists chains together to dynamically assemble a self-healing gel.

Aggregation of Heterogeneously Charged Colloids

Patchy colloids are attractive as programmable building blocks for metamaterials. Inverse patchy colloids, in which a charged surface is decorated with patches of the opposite charge, are additionally noteworthy as models for heterogeneously charged biological materials such as proteins. We study the phases and aggregation behavior of a single charged patch in an oppositely charged colloid with a single-site model. This single-patch inverse patchy colloid model shows a large number of phases when varying patch size. For large patch sizes we find ferroelectric crystals, while small patch sizes produce cross-linked gels. Intermediate values produce monodisperse clusters and unusual worm structures that preserve finite ratios of area to volume. The polarization observed at large patch sizes is robust under extreme disorder in patch size and shape. We examine phase-temperature dependence and coexistence curves and find that large patch sizes produce polarized liquids, in contrast to mean-field predictions. Finally, we introduce small numbers of unpatched charged colloids. These can either suppress or encourage aggregation depending on their concentration and the size of the patches on the patched colloids. These effects can be exploited to control aggregation and to measure effective patch size.

Self-replication with magnetic dipolar colloids

Colloidal self-replication represents an exciting research frontier in soft matter physics. Currently, all reported self-replication schemes involve coating colloidal particles with stimuli-responsive molecules to allow switchable interactions. In this paper, we introduce a scheme using ferromagnetic dipolar colloids and preprogrammed external magnetic fields to create an autonomous self-replication system. Interparticle dipole-dipole forces and periodically varying weak-strong magnetic fields cooperate to drive colloid monomers from the solute onto templates, bind them into replicas, and dissolve template complexes. We present three general design principles for autonomous linear replicators, derived from a focused study of a minimalist sphere-dimer magnetic system in which single binding sites allow formation of dimeric templates. We show via statistical models and computer simulations that our system exhibits nonlinear growth of templates and produces nearly exponential growth (low error rate) upon adding an optimized competing electrostatic potential. We devise experimental strategies for constructing the required magnetic colloids based on documented laboratory techniques. We also present qualitative ideas about building more complex self-replicating structures utilizing magnetic colloids.

Self-replication in colloids with asymmetric interactions

Self-replication is a ubiquitous process in organisms. Understanding the key ingredients of self-replication is critical for developing self-sustaining systems in the laboratory. Moreover, finding the optimal conditions to generate accurate replicas and adequate output can accelerate industrial processes enormously. Here, we propose a scheme for self-replication where asymmetric interactions in colloids are used to find optimal self-replication conditions by controlling the input of energy. We generalize a recently developed kinetic Monte Carlo algorithm to treat both translational and rotational motions of Brownian anisotropic colloids. We report two main findings from our simulations: first, by fine tuning the particle interactions, highly accurate self-replication is achievable with a moderate sacrifice of reaction speed. Second, with the introduction of energy cycling to enable periodic assembly/disassembly of the system's components the replicator population grows exponentially. The exponential growth constant is a non-monotonic function of the period of the pulsed energy delivery.