Search

The emergence of drug resistance is the most substantial challenge to the effectiveness of anticancer therapies. Orthogonal approaches have revealed that a subset of cells, known as drug-tolerant 'persister' (DTP) cells, have a prominent role in drug resistance. Although long recognized in bacterial populations which have acquired resistance to antibiotics, the presence of DTPs in various cancer types has come to light only in the past two decades, yet several aspects of their biology remain enigmatic. Here, we delve into the biological characteristics of DTPs and explore potential strategies for tracking and targeting them. Recent findings suggest that DTPs exhibit remarkable plasticity, being capable of transitioning between different cellular states, resulting in distinct DTP phenotypes within a single tumour. However, defining the biological features of DTPs has been challenging, partly due to the complex interplay between clonal dynamics and tissue-specific factors influencing their phenotype. Moreover, the interactions between DTPs and the tumour microenvironment, including their potential to evade immune surveillance, remain to be discovered. Finally, the mechanisms underlying DTP-derived drug resistance and their correlation with clinical outcomes remain poorly understood. This Roadmap aims to provide a comprehensive overview of the field of DTPs, encompassing past achievements and current endeavours in elucidating their biology. We also discuss the prospect of future advancements in technologies in helping to unveil the features of DTPs and propose novel therapeutic strategies that could lead to their eradication., (© 2024. Springer Nature Limited.)

Combining drugs can enhance their clinical efficacy, but the number of possible combinations and inter-tumor heterogeneity make identifying effective combinations challenging, while existing approaches often overlook clinically relevant activity. We screen one of the largest cell line panels (N = 757) with 51 clinically relevant combinations and identify responses at the level of individual cell lines and tissue populations. We establish three response classes to model cellular effects beyond monotherapy: synergy, Bliss additivity, and independent drug action (IDA). Synergy is rare (11% of responses) and frequently efficacious (>50% viability reduction), whereas Bliss and IDA are more frequent but less frequently efficacious. We introduce "efficacious combination benefit" (ECB) to describe high-efficacy responses classified as either synergy, Bliss, or IDA. We identify ECB biomarkers in vitro and show that ECB predicts response in patient-derived xenografts better than synergy alone. Our work here provides a valuable resource and framework for preclinical evaluation and the development of combination treatments., Competing Interests: Declaration of interests L.F.A.W. has received funding from Genmab BV and Bristol Myers Squibb. M.J.G. has received research grants from AstraZeneca, GlaxoSmithKline, Astex Pharmaceuticals, and Mosaic Therapeutics and is the Director and consultant for Mosaic Therapeutics., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Microsatellite-unstable (MSI) cancers require WRN helicase to resolve replication stress due to expanded DNA (TA)n dinucleotide repeats. WRN is a promising synthetic lethal target for MSI tumors, and WRN inhibitors are in development. In this study, we used CRISPR-Cas9 base editing to map WRN residues critical for MSI cells, validating the helicase domain as the primary drug target. Fragment-based screening led to the development of potent and highly selective WRN helicase covalent inhibitors. These compounds selectively suppressed MSI model growth in vitro and in vivo by mimicking WRN loss, inducing DNA double-strand breaks at expanded TA repeats and DNA damage. Assessment of biomarkers in preclinical models linked TA-repeat expansions and mismatch repair alterations to compound activity. Efficacy was confirmed in immunotherapy-resistant organoids and patient-derived xenograft models. The discovery of potent, selective covalent WRN inhibitors provides proof of concept for synthetic lethal targeting of WRN in MSI cancer and tools to dissect WRN biology. Significance: We report the discovery and characterization of potent, selective WRN helicase inhibitors for MSI cancer treatment, with biomarker analysis and evaluation of efficacy in vivo and in immunotherapy-refractory preclinical models. These findings pave the way to translate WRN inhibition into MSI cancer therapies and provide tools to investigate WRN biology. See related commentary by Wainberg, p. 1369., (©2024 American Association for Cancer Research.)

Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific "emergent" biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets., Significance: We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of "emergent" combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses. This article is featured in Selected Articles from This Issue, p. 695., (©2024 The Authors; Published by the American Association for Cancer Research.)

Nasopharyngeal carcinoma (NPC), a cancer that is etiologically associated with the Epstein-Barr virus (EBV), is endemic in Southern China and Southeast Asia. The scarcity of representative NPC cell lines owing to the frequent loss of EBV episomes following prolonged propagation and compromised authenticity of previous models underscores the critical need for new EBV-positive NPC models. Herein, we describe the establishment of a new EBV-positive NPC cell line, designated NPC268 from a primary non-keratinizing, differentiated NPC tissue. NPC268 can undergo productive lytic reactivation of EBV and is highly tumorigenic in immunodeficient mice. Whole-genome sequencing revealed close similarities with the tissue of origin, including large chromosomal rearrangements, while whole-genome bisulfite sequencing and RNA sequencing demonstrated a hypomethylated genome and enrichment in immune-related pathways, respectively. Drug screening of NPC268 together with six other NPC cell lines using 339 compounds, representing the largest high-throughput drug testing in NPC, revealed biomarkers associated with specific drug classes. NPC268 represents the first and only available EBV-positive non-keratinizing differentiated NPC model, and extensive genomic, methylomic, transcriptomic, and drug response data should facilitate research in EBV and NPC, where current models are limited., Significance: NPC268 is the first and only EBV-positive cell line derived from a primary non-keratinizing, differentiated nasopharyngeal carcinoma, an understudied but important subtype in Southeast Asian countries. This model adds to the limited number of authentic EBV-positive lines globally that will facilitate mechanistic studies and drug development for NPC., (© 2024 The Authors; Published by the American Association for Cancer Research.)

Human tissue three-dimensional (3D) organoid cultures have the potential to reproduce in vitro the physiological properties and cellular architecture of the organs from which they are derived. The ability of organoid cultures derived from human stomach, liver, kidney, and colon to metabolically activate three dietary carcinogens, aflatoxin B 1 (AFB 1 ), aristolochic acid I (AAI), and 2-amino-1-methyl-6-phenylimidazo[4,5- b ]pyridine (PhIP), was investigated. In each case, the response of a target tissue (liver for AFB 1 ; kidney for AAI; colon for PhIP) was compared with that of a nontarget tissue (gastric). After treatment cell viabilities were measured, DNA damage response (DDR) was determined by Western blotting for p-p53, p21, p-CHK2, and γ-H2AX, and DNA adduct formation was quantified by mass spectrometry. Induction of the key xenobiotic-metabolizing enzymes (XMEs) CYP1A1, CYP1A2, CYP3A4, and NQO1 was assessed by qRT-PCR. We found that organoids from different tissues can activate AAI, AFB 1 , and PhIP. In some cases, this metabolic potential varied between tissues and between different cultures of the same tissue. Similarly, variations in the levels of expression of XMEs were observed. At comparable levels of cytotoxicity, organoids derived from tissues that are considered targets for these carcinogens had higher levels of adduct formation than a nontarget tissue.

The epigenetic landscape of cancer is regulated by many factors, but primarily it derives from the underlying genome sequence. Chromothripsis is a catastrophic localized genome shattering event that drives, and often initiates, cancer evolution. We characterized five esophageal adenocarcinoma organoids with chromothripsis using long-read sequencing and transcriptome and epigenome profiling. Complex structural variation and subclonal variants meant that haplotype-aware de novo methods were required to generate contiguous cancer genome assemblies. Chromosomes were assembled separately and scaffolded using haplotype-resolved Hi-C reads, producing accurate assemblies even with up to 900 structural rearrangements. There were widespread differences between the chromothriptic and wild-type copies of chromosomes in topologically associated domains, chromatin accessibility, histone modifications, and gene expression. Differential epigenome peaks were most enriched within 10 kb of chromothriptic structural variants. Alterations in transcriptome and higher-order chromosome organization frequently occurred near differential epigenetic marks. Overall, chromothripsis reshapes gene regulation, causing coordinated changes in epigenetic landscape, transcription, and chromosome conformation., Competing Interests: Declaration of interests P.J.C. is an academic co-founder, stockholder, and consultant for Quotient Therapeutics., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development., Competing Interests: Declaration of interests This study was funded by Open Targets, a public-private initiative involving academia and industry. M.J.G. receives funding from AstraZeneca, GlaxoSmithKline, and Astex Pharmaceuticals. F.I. receives funding from Nerviano Medical Sciences S.r.l and performs consultancy for the Cancer Research Horizons-AstraZeneca Functional Genomics Center and for Mosaic Therapeutics. M.J.G. is a founder, has equity in and is a consultant for Mosaic Therapeutics., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

The pleural lining of the thorax regulates local immunity, inflammation and repair. A variety of conditions, both benign and malignant, including pleural mesothelioma, can affect this tissue. A lack of knowledge concerning the mesothelial and stromal cells comprising the pleura has hampered the development of targeted therapies. Here, we present the first comprehensive single-cell transcriptomic atlas of the human parietal pleura and demonstrate its utility in elucidating pleural biology. We confirm the presence of known universal fibroblasts and describe novel, potentially pleural-specific, fibroblast subtypes. We also present transcriptomic characterisation of multiple in vitro models of benign and malignant mesothelial cells, and characterise these through comparison with in vivo transcriptomic data. While bulk pleural transcriptomes have been reported previously, this is the first study to provide resolution at the single-cell level. We expect our pleural cell atlas will prove invaluable to those studying pleural biology and disease. It has already enabled us to shed light on the transdifferentiation of mesothelial cells, allowing us to develop a simple method for prolonging mesothelial cell differentiation in vitro ., Competing Interests: Conflicts of interest: In addition to the funding acknowledged in the support statement, the following conflicts are declared by the authors. J. Obacz reports grants from Victor Dahdaleh Charitable Foundation. A.S. Coonar reports grants from Innovate UK, consultancy for Viderigen, honoraria for lectures from AstraZeneca, book royalties from Springer Nature, payment for expert testimony from Medicolegal reports, leadership or fiduciary roles for Society for Cardiothoracic Surgery of GB and Ireland, and is Chair of the Thoracic Surgery Committee, NHS, National Clinical Lead for NHS England and a Governor of Royal Papworth Hospital. A. Peryt reports lecture honoraria from AstraZeneca, and travel support from Albyn Medical. N. Kaminski is a scientific founder at Thyron, served as a consultant to Biogen Idec, Boehringer Ingelheim, Third Rock, Pliant, Samumed, NuMedii, Theravance, LifeMax, Three Lake Partners, Optikira, AstraZeneca, RohBar, Veracyte, Augmanity, CSL Behring, Galapagos, Gilead, Chiesi, Arrowhead, Sofinnova and Thyron over the last 3 years, reports Equity in Pliant and Thyron, and grants from Veracyte, Boehringer Ingelheim, BMS and Three Lakes Foundation, and non-financial support from MiRagen and Astra Zeneca; N. Kaminski also has the following patents licensed to biotech: New therapies for IPF, New Therapies for ARDS and New Biomarkers in IPF. M.J. Garnett reports consultancy fees from and equity in Mosaic Therapeutics, and has a patent pending for describing suspension organoid cultures. R.C. Rintoul is chief investigator of Mesobank UK and is part funded by Asthma+Lung UK. The remaining authors have no potential conflicts of interest to disclose., (Copyright ©The authors 2024.)

CRISPR screens with single-cell transcriptomic readouts are a valuable tool to understand the effect of genetic perturbations including single nucleotide variants (SNVs) associated with diseases. Interpretation of these data is currently limited as genotypes cannot be accurately inferred from guide RNA identity alone. scSNV-seq overcomes this limitation by coupling single-cell genotyping and transcriptomics of the same cells enabling accurate and high-throughput screening of SNVs. Analysis of variants across the JAK1 gene with scSNV-seq demonstrates the importance of determining the precise genetic perturbation and accurately classifies clinically observed missense variants into three functional categories: benign, loss of function, and separation of function., (© 2024. The Author(s).)

Genome-wide genetic screens using CRISPR-guide RNA libraries are widely performed in mammalian cells to functionally characterize individual genes and for the discovery of new anticancer therapeutic targets. As the effectiveness of such powerful and precise tools for cancer pharmacogenomics is emerging, tools and methods for their quality assessment are becoming increasingly necessary. Here, we provide an R package and a high-quality reference data set for the assessment of novel experimental pipelines through which a single calibration experiment has been executed: a screen of the HT-29 human colorectal cancer cell line with a commercially available genome-wide library of single-guide RNAs. This package and data allow experimental researchers to benchmark their screens and produce a quality-control report, encompassing several quality and validation metrics. The R code used for processing the reference data set, for its quality assessment, as well as to evaluate the quality of a user-provided screen, and to reproduce the figures presented in this article is available at https://github.com/DepMap-Analytics/HT29benchmark. The reference data is publicly available on FigShare.

The systematic identification of tumour vulnerabilities through perturbational experiments on cancer models, including genome editing and drug screens, is playing a crucial role in combating cancer. This collective effort is known as the Cancer Dependency Map (DepMap). The 1st European Cancer Dependency Map Symposium (EuroDepMap), held in Milan last May, featured talks, a roundtable discussion, and a poster session, showcasing the latest discoveries and future challenges related to the DepMap. The symposium aimed to facilitate interactions among participants across Europe, encourage idea exchange with leading experts, and present their work and future projects. Importantly, it sparked discussions on future endeavours, such as screening more complex cancer models and accounting for tumour evolution., (© 2023 Federation of European Biochemical Societies.)

Combination of anti-cancer drugs is broadly seen as way to overcome the often-limited efficacy of single agents. The design and testing of combinations are however very challenging. Here we present a uniquely large dataset screening over 5000 targeted agent combinations across 81 non-small cell lung cancer cell lines. Our analysis reveals a profound heterogeneity of response across the tumor models. Notably, combinations very rarely result in a strong gain in efficacy over the range of response observable with single agents. Importantly, gain of activity over single agents is more often seen when co-targeting functionally proximal genes, offering a strategy for designing more efficient combinations. Because combinatorial effect is strongly context specific, tumor specificity should be achievable. The resource provided, together with an additional validation screen sheds light on major challenges and opportunities in building efficacious combinations against cancer and provides an opportunity for training computational models for synergy prediction., (© 2023. The Author(s).)

More than 30% of all human cancers are driven by RAS mutations and activating KRAS mutations are present in 40% of colorectal cancer (CRC) in the two main CRC subgroups, MSS (Microsatellite Stable) and MSI (Microsatellite Instable). Studies in RAS-driven tumors have shown essential roles of the RAS effectors RAF and specifically of RAF1, which can be dependent or independent of RAF's ability to activate the MEK/ERK module. In this study, we demonstrate that RAF1, but not its kinase activity, plays a crucial role in the proliferation of both MSI and MSS CRC cell line-derived spheroids and patient-derived organoids, and independently of KRAS mutation status. Moreover, we could define a RAF1 transcriptomic signature which includes genes that contribute to STAT3 activation, and could demonstrate that RAF1 ablation decreases STAT3 phosphorylation in all CRC spheroids tested. The genes involved in STAT3 activation as well as STAT3 targets promoting angiogenesis were also downregulated in human primary tumors expressing low levels of RAF1. These results indicate that RAF1 could be an attractive therapeutic target in both MSI and MSS CRC regardless of their KRAS status and support the development of selective RAF1 degraders rather than RAF1 inhibitors for clinical use in combination therapies., (© 2023. The Author(s).)

Interferon-γ (IFN-γ) signaling mediates host responses to infection, inflammation and anti-tumor immunity. Mutations in the IFN-γ signaling pathway cause immunological disorders, hematological malignancies, and resistance to immune checkpoint blockade (ICB) in cancer; however, the function of most clinically observed variants remains unknown. Here, we systematically investigate the genetic determinants of IFN-γ response in colorectal cancer cells using CRISPR-Cas9 screens and base editing mutagenesis. Deep mutagenesis of JAK1 with cytidine and adenine base editors, combined with pathway-wide screens, reveal loss-of-function and gain-of-function mutations, including causal variants in hematological malignancies and mutations detected in patients refractory to ICB. We functionally validate variants of uncertain significance in primary tumor organoids, where engineering missense mutations in JAK1 enhanced or reduced sensitivity to autologous tumor-reactive T cells. We identify more than 300 predicted missense mutations altering IFN-γ pathway activity, generating a valuable resource for interpreting gene variant function., Competing Interests: Declaration of interests M.J.G. has received research grants from AstraZeneca, GlaxoSmithKline, and Astex Pharmaceuticals, and is a founder and advisor for Mosaic Therapeutics., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The PI3K pathway is commonly activated in breast cancer, with PI3K-AKT pathway inhibitors used clinically. However, mechanisms that limit or enhance the therapeutic effects of PI3K-AKT inhibitors are poorly understood at a genome-wide level. Parallel CRISPR screens in 3 PTEN-null breast cancer cell lines identified genes mediating resistance to capivasertib (AKT inhibitor) and AZD8186 (PI3Kβ inhibitor). The dominant mechanism causing resistance is reactivated PI3K-AKT-mTOR signalling, but not other canonical signalling pathways. Deletion of TSC1/2 conferred resistance to PI3Kβi and AKTi through mTORC1. However, deletion of PIK3R2 and INPPL1 drove specific PI3Kβi resistance through AKT. Conversely deletion of PIK3CA, ERBB2, ERBB3 increased PI3Kβi sensitivity while modulation of RRAGC, LAMTOR1, LAMTOR4 increased AKTi sensitivity. Significantly, we found that Mcl-1 loss enhanced response through rapid apoptosis induction with AKTi and PI3Kβi in both sensitive and drug resistant TSC1/2 null cells. The combination effect was BAK but not BAX dependent. The Mcl-1i + PI3Kβ/AKTi combination was effective across a panel of breast cancer cell lines with PIK3CA and PTEN mutations, and delivered increased anti-tumor benefit in vivo. This study demonstrates that different resistance drivers to PI3Kβi and AKTi converge to reactivate PI3K-AKT or mTOR signalling and combined inhibition of Mcl-1 and PI3K-AKT has potential as a treatment strategy for PI3Kβi/AKTi sensitive and resistant breast tumours., (© 2022. The Author(s).)

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk., Competing Interests: Declaration of interests M.J.G. has received research funding from AstraZeneca, GSK, Astex Therapeutics, and Open Targets, a public-private initiative involving academia and industry, and is a co-founder of Mosaic Therapeutics. All other authors declare no competing interests., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Ongoing new insights in the field of cancer diagnostics, genomic profiling, and cancer behavior have raised the demand for novel, personalized cancer treatments. As the development of new cancer drugs is a challenging, costly, and time-consuming endeavor, drug repurposing is regarded as an attractive alternative to potentially accelerate this. In this review, we describe strategies for drug repurposing of anticancer agents, translation of preclinical findings in novel trial designs, and associated challenges. Furthermore, we provide suggestions to further utilize the potential of drug repurposing within precision oncology, with a focus on combinatorial approaches., Significance: Oncologic drug development is a timely and costly endeavor, with only few compounds progressing to meaningful therapy options. Although repurposing of existing agents for novel, oncologic indications provides an opportunity to accelerate this process, it is not without challenges., (©2022 American Association for Cancer Research.)

Organoid cell culture methodologies are enabling the generation of cell models from healthy and diseased tissue. Patient-derived cancer organoids that recapitulate the genetic and histopathological diversity of patient tumours are being systematically generated, providing an opportunity to investigate new cancer biology and therapeutic approaches. The use of organoid cultures for many applications, including genetic and chemical perturbation screens, is limited due to the technical demands and cost associated with their handling and propagation. Here we report and benchmark a suspension culture technique for cancer organoids which allows for the expansion of models to tens of millions of cells with increased efficiency in comparison to standard organoid culturing protocols. Using whole-genome DNA and RNA sequencing analyses, as well as medium-throughput drug sensitivity testing and genome-wide CRISPR-Cas9 screening, we demonstrate that cancer organoids grown as a suspension culture are genetically and phenotypically similar to their counterparts grown in standard conditions. This culture technique simplifies organoid cell culture and extends the range of organoid applications, including for routine use in large-scale perturbation screens., (© 2022. The Author(s).)

Combinations of anti-cancer drugs can overcome resistance and provide new treatments 1,2 . The number of possible drug combinations vastly exceeds what could be tested clinically. Efforts to systematically identify active combinations and the tissues and molecular contexts in which they are most effective could accelerate the development of combination treatments. Here we evaluate the potency and efficacy of 2,025 clinically relevant two-drug combinations, generating a dataset encompassing 125 molecularly characterized breast, colorectal and pancreatic cancer cell lines. We show that synergy between drugs is rare and highly context-dependent, and that combinations of targeted agents are most likely to be synergistic. We incorporate multi-omic molecular features to identify combination biomarkers and specify synergistic drug combinations and their active contexts, including in basal-like breast cancer, and microsatellite-stable or KRAS-mutant colon cancer. Our results show that irinotecan and CHEK1 inhibition have synergistic effects in microsatellite-stable or KRAS-TP53 double-mutant colon cancer cells, leading to apoptosis and suppression of tumour xenograft growth. This study identifies clinically relevant effective drug combinations in distinct molecular subpopulations and is a resource to guide rational efforts to develop combinatorial drug treatments., (© 2022. The Author(s).)

Background: CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), and to distinguish them from context-specific essential genes. This is of paramount importance to assess the safety profile of candidate therapeutic targets and for elucidating mechanisms involved in tissue-specific genetic diseases., Results: We have developed CoRe: an R package implementing existing and novel methods for the identification of core-fitness genes (at two different level of stringency) from joint analyses of multiple CRISPR-Cas9 screens. We demonstrate, through a fully reproducible benchmarking pipeline, that CoRe outperforms state-of-the-art tools, yielding more reliable and biologically relevant sets of core-fitness genes., Conclusions: CoRe offers a flexible pipeline, compatible with many pre-processing methods for the analysis of CRISPR data, which can be tailored onto different use-cases. The CoRe package can be used for the identification of high-confidence novel core-fitness genes, as well as a means to filter out potentially cytotoxic hits while analysing cancer dependency datasets for identifying and prioritising novel selective therapeutic targets., (© 2021. The Author(s).)

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy, exhibiting high levels of reactive oxygen species (ROS). ROS levels have been suggested to drive leukemogenesis and is thus a potential novel target for treating AML. MTH1 prevents incorporation of oxidized nucleotides into the DNA to maintain genome integrity and is upregulated in many cancers. Here we demonstrate that hematologic cancers are highly sensitive to MTH1 inhibitor TH1579 (karonudib). A functional precision medicine ex vivo screen in primary AML bone marrow samples demonstrated a broad response profile of TH1579, independent of the genomic alteration of AML, resembling the response profile of the standard-of-care treatments cytarabine and doxorubicin. Furthermore, TH1579 killed primary human AML blast cells (CD45 + ) as well as chemotherapy resistance leukemic stem cells (CD45 + Lin - CD34 + CD38 - ), which are often responsible for AML progression. TH1579 killed AML cells by causing mitotic arrest, elevating intracellular ROS levels, and enhancing oxidative DNA damage. TH1579 showed a significant therapeutic window, was well tolerated in animals, and could be combined with standard-of-care treatments to further improve efficacy. TH1579 significantly improved survival in two different AML disease models in vivo . In conclusion, the preclinical data presented here support that TH1579 is a promising novel anticancer agent for AML, providing a rationale to investigate the clinical usefulness of TH1579 in AML in an ongoing clinical phase I trial. SIGNIFICANCE: The MTH1 inhibitor TH1579 is a potential novel AML treatment, targeting both blasts and the pivotal leukemic stem cells while sparing normal bone marrow cells., (©2021 The Authors; Published by the American Association for Cancer Research.)

Malignant pleural mesothelioma (MPM) is an aggressive cancer most commonly caused by prior exposure to asbestos. Median survival is 12-18 months, since surgery is ineffective and chemotherapy offers minimal benefit. Preclinical models that faithfully recapitulate the genomic and histopathological features of cancer are critical for the development of new treatments. The most commonly used models of MPM are two-dimensional cell lines established from primary tumours or pleural fluid. While these have provided some important insights into MPM biology, these cell models have significant limitations. In order to address some of these limitations, spheroids and microfluidic chips have more recently been used to investigate the role of the three-dimensional environment in MPM. Efforts have also been made to develop animal models of MPM, including asbestos-induced murine tumour models, MPM-prone genetically modified mice and patient-derived xenografts. Here, we discuss the available in vitro and in vivo models of MPM and highlight their strengths and limitations. We discuss how newer technologies, such as the tumour-derived organoids, might allow us to address the limitations of existing models and aid in the identification of effective treatments for this challenging-to-treat disease., Competing Interests: Competing interests: MS and JO report grants from The British Lung Foundation, grants from The Victor Dahdaleh Foundation, during the conduct of the study; MG reports grants from Wellcome Trust grant 206194, outside the submitted work; RCR reports grants from British Lung Foundation, during the conduct of the study; other from Cambridge Biomedical Research Centre, other from Cancer Research UK Cambridge Centre, other from Royal Papworth Hospital, personal fees from AstraZeneca, personal fees from Roche, outside the submitted work; SJM reports grants from The British Lung Foundation, grants from The Victor Dahdaleh Foundation, during the conduct of the study., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Disparities between risk, treatment outcomes and survival rates in cancer patients across the world may be attributed to socioeconomic factors. In addition, the role of ancestry is frequently discussed. In preclinical studies, high-throughput drug screens in cancer cell lines have empowered the identification of clinically relevant molecular biomarkers of drug sensitivity; however, the genetic ancestry from tissue donors has been largely neglected in this setting. In order to address this, here, we show that the inferred ancestry of cancer cell lines is conserved and may impact drug response in patients as a predictive covariate in high-throughput drug screens. We found that there are differential drug responses between European and East Asian ancestries, especially when treated with PI3K/mTOR inhibitors. Our finding emphasizes a new angle in precision medicine, as cancer intervention strategies should consider the germline landscape, thereby reducing the failure rate of clinical trials.

Targeted therapies, chemotherapy, and immunotherapy are used to treat patients with mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) colorectal cancer. The clinical effectiveness of targeted therapy and chemotherapy is limited by resistance and drug toxicities, and about half of patients receiving immunotherapy have disease that is refractory to immune checkpoint inhibitors. Loss of Werner syndrome ATP-dependent helicase (WRN) is a synthetic lethality in dMMR/MSI-H cells. To inform the development of WRN as a therapeutic target, we performed WRN knockout or knockdown in 60 heterogeneous dMMR colorectal cancer preclinical models, demonstrating that WRN dependency is an almost universal feature and a robust marker for patient selection. Furthermore, models of resistance to clinically relevant targeted therapy, chemotherapy, and immunotherapy retain WRN dependency. These data show the potential of therapeutically targeting WRN in patients with dMMR/MSI-H colorectal cancer and support WRN as a therapeutic option for patients with dMMR/MSI-H cancers refractory to current treatment strategies. SIGNIFICANCE: We found that a large, diverse set of dMMR/MSI-H colorectal cancer preclinical models, including models of treatment-refractory disease, are WRN-dependent. Our results support WRN as a promising synthetic-lethal target in dMMR/MSI-H colorectal cancer tumors as a monotherapy or in combination with targeted agents, chemotherapy, or immunotherapy. This article is highlighted in the In This Issue feature, p. 1861 ., (©2021 American Association for Cancer Research.)

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.

Background: Schlafen 11 (SLFN11) has been linked with response to DNA-damaging agents (DDA) and PARP inhibitors. An in-depth understanding of several aspects of its role as a biomarker in cancer is missing, as is a comprehensive analysis of the clinical significance of SLFN11 as a predictive biomarker to DDA and/or DNA damage-response inhibitor (DDRi) therapies., Methods: We used a multidisciplinary effort combining specific immunohistochemistry, pharmacology tests, anticancer combination therapies and mechanistic studies to assess SLFN11 as a potential biomarker for stratification of patients treated with several DDA and/or DDRi in the preclinical and clinical setting., Results: SLFN11 protein associated with both preclinical and patient treatment response to DDA, but not to non-DDA or DDRi therapies, such as WEE1 inhibitor or olaparib in breast cancer. SLFN11-low/absent cancers were identified across different tumour types tested. Combinations of DDA with DDRi targeting the replication-stress response (ATR, CHK1 and WEE1) could re-sensitise SLFN11-absent/low cancer models to the DDA treatment and were effective in upper gastrointestinal and genitourinary malignancies., Conclusion: SLFN11 informs on the standard of care chemotherapy based on DDA and the effect of selected combinations with ATR, WEE1 or CHK1 inhibitor in a wide range of cancer types and models.

Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. Our studies reveal the fitness effects of FAM50A/FAM50B in cancer cells.

The RAS-regulated RAF-MEK1/2-ERK1/2 (RAS/MAPK) signaling pathway is a major driver in oncogenesis and is frequently dysregulated in human cancers, primarily by mutations in BRAF or RAS genes. The clinical benefit of inhibitors of this pathway as single agents has only been realized in BRAF -mutant melanoma, with limited effect of single-agent pathway inhibitors in KRAS -mutant tumors. Combined inhibition of multiple nodes within this pathway, such as MEK1/2 and ERK1/2, may be necessary to effectively suppress pathway signaling in KRAS -mutant tumors and achieve meaningful clinical benefit. Here, we report the discovery and characterization of AZD0364, a novel, reversible, ATP-competitive ERK1/2 inhibitor with high potency and kinase selectivity. In vitro , AZD0364 treatment resulted in inhibition of proximal and distal biomarkers and reduced proliferation in sensitive BRAF -mutant and KRAS -mutant cell lines. In multiple in vivo xenograft models, AZD0364 showed dose- and time-dependent modulation of ERK1/2-dependent signaling biomarkers resulting in tumor regression in sensitive BRAF - and KRAS -mutant xenografts. We demonstrate that AZD0364 in combination with the MEK1/2 inhibitor, selumetinib (AZD6244 and ARRY142886), enhances efficacy in KRAS -mutant preclinical models that are moderately sensitive or resistant to MEK1/2 inhibition. This combination results in deeper and more durable suppression of the RAS/MAPK signaling pathway that is not achievable with single-agent treatment. The AZD0364 and selumetinib combination also results in significant tumor regressions in multiple KRAS -mutant xenograft models. The combination of ERK1/2 and MEK1/2 inhibition thereby represents a viable clinical approach to target KRAS -mutant tumors., (©2020 American Association for Cancer Research.)

CRISPR guide RNA libraries have been iteratively improved to provide increasingly efficient reagents, although their large size is a barrier for many applications. We design an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9) by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other CRISPR-Cas9 libraries while preserving assay sensitivity and specificity. MinLibCas9 provides backward compatibility with existing datasets, increases the dynamic range of CRISPR-Cas9 screens and extends their application to complex models and assays.

CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR-Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Purpose: Targeting Bcl-2 family members upregulated in multiple cancers has emerged as an important area of cancer therapeutics. While venetoclax, a Bcl-2-selective inhibitor, has had success in the clinic, another family member, Bcl-x L , has also emerged as an important target and as a mechanism of resistance. Therefore, we developed a dual Bcl-2/Bcl-x L inhibitor that broadens the therapeutic activity while minimizing Bcl-x L -mediated thrombocytopenia., Experimental Design: We used structure-based chemistry to design a small-molecule inhibitor of Bcl-2 and Bcl-x L and assessed the activity against in vitro cell lines, patient samples, and in vivo models. We applied pharmacokinetic/pharmacodynamic (PK/PD) modeling to integrate our understanding of on-target activity of the dual inhibitor in tumors and platelets across dose levels and over time., Results: We discovered AZD4320, which has nanomolar affinity for Bcl-2 and Bcl-x L , and mechanistically drives cell death through the mitochondrial apoptotic pathway. AZD4320 demonstrates activity in both Bcl-2- and Bcl-x L -dependent hematologic cancer cell lines and enhanced activity in acute myeloid leukemia (AML) patient samples compared with the Bcl-2-selective agent venetoclax. A single intravenous bolus dose of AZD4320 induces tumor regression with transient thrombocytopenia, which recovers in less than a week, suggesting a clinical weekly schedule would enable targeting of Bcl-2/Bcl-x L -dependent tumors without incurring dose-limiting thrombocytopenia. AZD4320 demonstrates monotherapy activity in patient-derived AML and venetoclax-resistant xenograft models., Conclusions: AZD4320 is a potent molecule with manageable thrombocytopenia risk to explore the utility of a dual Bcl-2/Bcl-x L inhibitor across a broad range of tumor types with dysregulation of Bcl-2 prosurvival proteins., (©2020 American Association for Cancer Research.)

High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells' response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the curve fit and the potential variability in the raw readouts. Here, we model the experimental variance using Gaussian Processes, and subsequently, leverage uncertainty estimates to identify associated biomarkers with a new Bayesian framework. Applied to in vitro screening data on 265 compounds across 1074 cancer cell lines, our models identified 24 clinically established drug-response biomarkers, and provided evidence for six novel biomarkers by accounting for association with low uncertainty. We validated our uncertainty estimates with an additional drug screen of 26 drugs, 10 cell lines with 8 to 9 replicates. Our method is applicable to any dose-response data without replicates, and improves biomarker discovery for precision medicine., Competing Interests: DW, GK, TT, AG, JS, MG, MM No competing interests declared, JH James Hensman is an employee of Amazon.com. The author has no competing financial interests to declare. JD Jonathan Dry is affiliated with AstraZeneca and Tempus. The author has no competing financial interests to declare. FD Frank Dondelinger is an employee of Roche. The author has no competing financial interests to declare., (© 2020, Wang et al.)

New therapeutic targets for oral squamous cell carcinoma (OSCC) are urgently needed. We conducted genome-wide CRISPR-Cas9 screens in 21 OSCC cell lines, primarily derived from Asians, to identify genetic vulnerabilities that can be explored as therapeutic targets. We identify known and novel fitness genes and demonstrate that many previously identified OSCC-related cancer genes are non-essential and could have limited therapeutic value, while other fitness genes warrant further investigation for their potential as therapeutic targets. We validate a distinctive dependency on YAP1 and WWTR1 of the Hippo pathway, where the lost-of-fitness effect of one paralog can be compensated only in a subset of lines. We also discover that OSCCs with WWTR1 dependency signature are significantly associated with biomarkers of favorable response toward immunotherapy. In summary, we have delineated the genetic vulnerabilities of OSCC, enabling the prioritization of therapeutic targets for further exploration, including the targeting of YAP1 and WWTR1., Competing Interests: AC, PY, SP, SY, HL, VT, EG, FB, JB, JG, AT, MG, SC No competing interests declared, UM is affiliated with AstraZeneca, (© 2020, Chai et al.)

Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism-of-action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti-cancer drugs with genome-wide CRISPR loss-of-function screens in 484 cell lines to systematically investigate cellular drug mechanism-of-action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein-protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin-protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on-target and off-target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss-of-fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss-of-function screens can elucidate mechanism-of-action to advance drug development., (© 2020 The Authors. Published under the terms of the CC BY 4.0 license.)

Selecting appropriate cancer models is a key prerequisite for maximizing translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: an R package and R Shiny application allowing researchers to select the most relevant cancer cell lines in a patient-genomic-guided fashion. CELLector leverages tumor genomics to identify recurrent subtypes with associated genomic signatures. It then evaluates these signatures in cancer cell lines to prioritize their selection. This enables users to choose appropriate in vitro models for inclusion or exclusion in retrospective analyses and future studies. Moreover, this allows bridging outcomes from cancer cell line screens to precisely defined sub-cohorts of primary tumors. Here, we demonstrate the usefulness and applicability of CELLector, showing how it can aid prioritization of in vitro models for future development and unveil patient-derived multivariate prognostic and therapeutic markers. CELLector is freely available at https://ot-cellector.shinyapps.io/CELLector_App/ (code at https://github.com/francescojm/CELLector and https://github.com/francescojm/CELLector_App)., Competing Interests: Declaration of Interests M.J.G. and F.I. receive funding from Open Targets, a public-private initiative involving academia and industry. M.J.G. receives funding from AstraZeneca (United Kingdom) and performed consultancy for Sanofi (United Kingdom). F.I. performs consultancy for the CRUK - Astra Zeneca FGC. E.A.S. is an employee of GlaxoSmithKline. All the other authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Since the approval of trastuzumab for the treatment of breast cancers more than two decades ago, many clinically effective targeted anti-cancer therapies have been developed. Here we consider the evidence that supports genomics-guided drug development and review the concept of oncogene addiction, including recent findings that inform this therapeutic approach. We consider non-oncogene addiction and how this synthetic-lethal paradigm could expand the range of new therapies, particularly for currently undruggable cancers. We discuss how CRISPR-based genetic screening is enhancing the ability to identify new targets. We conclude by considering opportunities for expanding the scope and refining the use of precision cancer medicines., (© 2020. Springer Nature America, Inc.)

We report the derivation of 30 patient-derived organoid lines (PDOs) from tumors arising in the pancreas and distal bile duct. PDOs recapitulate tumor histology and contain genetic alterations typical of pancreatic cancer. In vitro testing of a panel of 76 therapeutic agents revealed sensitivities currently not exploited in the clinic, and underscores the importance of personalized approaches for effective cancer treatment. The PRMT5 inhibitor EZP015556, shown to target MTAP (a gene commonly lost in pancreatic cancer)-negative tumors, was validated as such, but also appeared to constitute an effective therapy for a subset of MTAP-positive tumors. Taken together, the work presented here provides a platform to identify novel therapeutics to target pancreatic tumor cells using PDOs.

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.

Imipridones constitute a novel class of antitumor agents. Here, we report that a second-generation imipridone, ONC212, possesses highly increased antitumor activity compared to the first-generation compound ONC201. In vitro studies using human acute myeloid leukemia (AML) cell lines, primary AML, and normal bone marrow (BM) samples demonstrate that ONC212 exerts prominent apoptogenic effects in AML, but not in normal BM cells, suggesting potential clinical utility. Imipridones putatively engage G protein-coupled receptors (GPCRs) and/or trigger an integrated stress response in hematopoietic tumor cells. Comprehensive GPCR screening identified ONC212 as activator of an orphan GPCR GPR132 and Gαq signaling, which functions as a tumor suppressor. Heterozygous knock-out of GPR132 decreased the antileukemic effects of ONC212. ONC212 induced apoptogenic effects through the induction of an integrated stress response, and reduced MCL-1 expression, a known resistance factor for BCL-2 inhibition by ABT-199. Oral administration of ONC212 inhibited AML growth in vivo and improved overall survival in xenografted mice. Moreover, ONC212 abrogated the engraftment capacity of patient-derived AML cells in an NSG PDX model, suggesting potential eradication of AML initiating cells, and was highly synergistic in combination with ABT-199. Collectively, our results suggest ONC212 as a novel therapeutic agent for AML.

Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: Patient-derived xenograft (PDX) models accurately recapitulate the tumor of origin in terms of histopathology, genomic landscape, and therapeutic response, but some limitations due to costs associated with their maintenance and restricted amenability for large-scale screenings still exist. To overcome these issues, we established a platform of 2D cell lines (xeno-cell lines, XL), derived from PDXs of colorectal cancer with matched patient germline gDNA available., Experimental Design: Whole-exome and transcriptome sequencing analyses were performed. Biomarkers of response and resistance to anti-HER therapy were annotated. Dependency on the WRN helicase gene was assessed in MSS, MSI-H, and MSI-like XLs using a reverse genetics functional approach., Results: XLs recapitulated the entire spectrum of colorectal cancer transcriptional subtypes. Exome and RNA-seq analyses delineated several molecular biomarkers of response and resistance to EGFR and HER2 blockade. Genotype-driven responses observed in vitro in XLs were confirmed in vivo in the matched PDXs. MSI-H models were dependent upon WRN gene expression, while loss of WRN did not affect MSS XLs growth. Interestingly, one MSS XL with transcriptional MSI-like traits was sensitive to WRN depletion., Conclusions: The XL platform represents a preclinical tool for functional gene validation and proof-of-concept studies to identify novel druggable vulnerabilities in colorectal cancer., (©2019 American Association for Cancer Research.)

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.

Many gene fusions are reported in tumours and for most their role remains unknown. As fusions are used for diagnostic and prognostic purposes, and are targets for treatment, it is crucial to assess their function in cancer. To systematically investigate the role of fusions in tumour cell fitness, we utilized RNA-sequencing data from 1011 human cancer cell lines to functionally link 8354 fusion events with genomic data, sensitivity to >350 anti-cancer drugs and CRISPR-Cas9 loss-of-fitness effects. Established clinically-relevant fusions were identified. Overall, detection of functional fusions was rare, including those involving cancer driver genes, suggesting that many fusions are dispensable for tumour fitness. Therapeutically actionable fusions involving RAF1, BRD4 and ROS1 were verified in new histologies. In addition, recurrent YAP1-MAML2 fusions were identified as activators of Hippo-pathway signaling in multiple cancer types. Our approach discriminates functional fusions, identifying new drivers of carcinogenesis and fusions that could have clinical implications.

Functional genomics approaches can overcome limitations-such as the lack of identification of robust targets and poor clinical efficacy-that hamper cancer drug development. Here we performed genome-scale CRISPR-Cas9 screens in 324 human cancer cell lines from 30 cancer types and developed a data-driven framework to prioritize candidates for cancer therapeutics. We integrated cell fitness effects with genomic biomarkers and target tractability for drug development to systematically prioritize new targets in defined tissues and genotypes. We verified one of our most promising dependencies, the Werner syndrome ATP-dependent helicase, as a synthetic lethal target in tumours from multiple cancer types with microsatellite instability. Our analysis provides a resource of cancer dependencies, generates a framework to prioritize cancer drug targets and suggests specific new targets. The principles described in this study can inform the initial stages of drug development by contributing to a new, diverse and more effective portfolio of cancer drug targets.

Multiple signatures of somatic mutations have been identified in cancer genomes. Exome sequences of 1,001 human cancer cell lines and 577 xenografts revealed most common mutational signatures, indicating past activity of the underlying processes, usually in appropriate cancer types. To investigate ongoing patterns of mutational-signature generation, cell lines were cultured for extended periods and subsequently DNA sequenced. Signatures of discontinued exposures, including tobacco smoke and ultraviolet light, were not generated in vitro. Signatures of normal and defective DNA repair and replication continued to be generated at roughly stable mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing exhibited substantial fluctuations in mutation rate over time with episodic bursts of mutations. The initiating factors for the bursts are unclear, although retrotransposon mobilization may contribute. The examined cell lines constitute a resource of live experimental models of mutational processes, which potentially retain patterns of activity and regulation operative in primary human cancers., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

Background: CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed., Results: Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene-independent manner. In contrast, amplifications caused by whole chromosomal duplication have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects., Conclusion: Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.