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.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling.

Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.

PRMT1-Mediated Translation Regulation Is a Crucial Vulnerability of Cancer.

Through an shRNA screen, we identified the protein arginine methyltransferase Prmt1 as a vulnerable intervention point in murine p53/Rb-null osteosarcomas, the human counterpart of which lacks effective therapeutic options. Depletion of Prmt1 in p53-deficient cells impaired tumor initiation and maintenance in vitro and in vivo Mechanistic studies reveal that translation-associated pathways were enriched for Prmt1 downstream targets, implicating Prmt1 in translation control. In particular, loss of Prmt1 led to a decrease in arginine methylation of the translation initiation complex, thereby disrupting its assembly and inhibiting translation. p53/Rb-null cells were sensitive to p53-induced translation stress, and analysis of human cancer cell line data from Project Achilles further revealed that Prmt1 and translation-associated pathways converged on the same functional networks. We propose that targeted therapy against Prmt1 and its associated translation-related pathways offer a mechanistic rationale for treatment of osteosarcomas and other cancers that exhibit dependencies on translation stress response. Cancer Res; 77(17); 4613-25. ©2017 AACR.

Correlating chemical sensitivity and basal gene expression reveals mechanism of action.

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset.

UNLABELLED: Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). SIGNIFICANCE: We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses.

An informatic pipeline for managing high-throughput screening experiments and analyzing data from stereochemically diverse libraries.

Integration of flexible data-analysis tools with cheminformatics methods is a prerequisite for successful identification and validation of "hits" in high-throughput screening (HTS) campaigns. We have designed, developed, and implemented a suite of robust yet flexible cheminformatics tools to support HTS activities at the Broad Institute, three of which are described herein. The "hit-calling" tool allows a researcher to set a hit threshold that can be varied during downstream analysis. The results from the hit-calling exercise are reported to a database for record keeping and further data analysis. The "cherry-picking" tool enables creation of an optimized list of hits for confirmatory and follow-up assays from an HTS hit list. This tool allows filtering by computed chemical property and by substructure. In addition, similarity searches can be performed on hits of interest and sets of related compounds can be selected. The third tool, an "S/SAR viewer," has been designed specifically for the Broad Institute's diversity-oriented synthesis (DOS) collection. The compounds in this collection are rich in chiral centers and the full complement of all possible stereoisomers of a given compound are present in the collection. The S/SAR viewer allows rapid identification of both structure/activity relationships and stereo-structure/activity relationships present in HTS data from the DOS collection. Together, these tools enable the prioritization and analysis of hits from diverse compound collections, and enable informed decisions for follow-up biology and chemistry efforts.

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence.

BACKGROUND: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. RESULTS: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, inter-population differentiation, and the degree to which allele frequencies are correlated between populations. CONCLUSIONS: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Dynamics of Pseudomonas aeruginosa genome evolution.

One of the hallmarks of the Gram-negative bacterium Pseudomonas aeruginosa is its ability to thrive in diverse environments that includes humans with a variety of debilitating diseases or immune deficiencies. Here we report the complete sequence and comparative analysis of the genomes of two representative P. aeruginosa strains isolated from cystic fibrosis (CF) patients whose genetic disorder predisposes them to infections by this pathogen. The comparison of the genomes of the two CF strains with those of other P. aeruginosa presents a picture of a mosaic genome, consisting of a conserved core component, interrupted in each strain by combinations of specific blocks of genes. These strain-specific segments of the genome are found in limited chromosomal locations, referred to as regions of genomic plasticity. The ability of P. aeruginosa to shape its genomic composition to favor survival in the widest range of environmental reservoirs, with corresponding enhancement of its metabolic capacity is supported by the identification of a genomic island in one of the sequenced CF isolates, encoding enzymes capable of degrading terpenoids produced by trees. This work suggests that niche adaptation is a major evolutionary force influencing the composition of bacterial genomes. Unlike genome reduction seen in host-adapted bacterial pathogens, the genetic capacity of P. aeruginosa is determined by the ability of individual strains to acquire or discard genomic segments, giving rise to strains with customized genomic repertoires. Consequently, this organism can survive in a wide range of environmental reservoirs that can serve as sources of the infecting organisms.

Conrad: gene prediction using conditional random fields.

We present Conrad, the first comparative gene predictor based on semi-Markov conditional random fields (SMCRFs). Unlike the best standalone gene predictors, which are based on generalized hidden Markov models (GHMMs) and trained by maximum likelihood, Conrad is discriminatively trained to maximize annotation accuracy. In addition, unlike the best annotation pipelines, which rely on heuristic and ad hoc decision rules to combine standalone gene predictors with additional information such as ESTs and protein homology, Conrad encodes all sources of information as features and treats all features equally in the training and inference algorithms. Conrad outperforms the best standalone gene predictors in cross-validation and whole chromosome testing on two fungi with vastly different gene structures. The performance improvement arises from the SMCRF's discriminative training methods and their ability to easily incorporate diverse types of information by encoding them as feature functions. On Cryptococcus neoformans, configuring Conrad to reproduce the predictions of a two-species phylo-GHMM closely matches the performance of Twinscan. Enabling discriminative training increases performance, and adding new feature functions further increases performance, achieving a level of accuracy that is unprecedented for this organism. Similar results are obtained on Aspergillus nidulans comparing Conrad versus Fgenesh. SMCRFs are a promising framework for gene prediction because of their highly modular nature, simplifying the process of designing and testing potential indicators of gene structure. Conrad's implementation of SMCRFs advances the state of the art in gene prediction in fungi and provides a robust platform for both current application and future research.

Eradication of a large outbreak of a single strain of vanB vancomycin-resistant Enterococcus faecium at a major Australian teaching hospital.

OBJECTIVE: To demonstrate that nosocomial transmission of vancomycin-resistant enterococci (VRE) can be terminated and endemicity prevented despite widespread dissemination of an epidemic strain in a large tertiary-care referral hospital. INTERVENTIONS: Two months after the index case was detected in the intensive care unit, 68 patients became either infected or colonized with an epidemic strain of vanB vancomycin-resistant Enterococcus faecium despite standard infection control procedures. The following additional interventions were then introduced to control the outbreak: (1) formation of a VRE executive group; (2) rapid laboratory identification (30 to 48 hours) using culture and polymerase chain reaction detection of vanA and vanB resistance genes; (3) mass screening of all hospitalized patients with isolation of carriers and cohorting of contacts; (4) environmental screening and increased cleaning; (5) electronic flagging of medical records of contacts; and (6) antibiotic restrictions (third-generation cephalosporins and vancomycin). RESULTS: A total of 19,658 patient and 24,396 environmental swabs were processed between July and December 2001. One hundred sixty-nine patients in 23 wards were colonized with a single strain of vanB vancomycin-resistant E. faecium. Introducing additional control measures rapidly brought the outbreak under control. Hospital-wide screening found 39 previously unidentified colonized patients, with only 7 more nonsegregated patients being detected in the next 2 months. The outbreak was terminated within 3 months at a cost of dollar 2.7 million (Australian dollars). CONCLUSION: Despite widespread dissemination of VRE in a large acute care facility, eradication was achievable by a well-resourced, coordinated, multifaceted approach and was in accordance with good clinical governance.