Rapid, economical diagnostic classification of ATRT molecular subgroup using NanoString nCounter platform.

Background: Despite genomic simplicity, recent studies have reported at least 3 major atypical teratoid rhabdoid tumor (ATRT) subgroups with distinct molecular and clinical features. Reliable ATRT subgrouping in clinical settings remains challenging due to a lack of suitable biological markers, sample rarity, and the relatively high cost of conventional subgrouping methods. This study aimed to develop a reliable ATRT molecular stratification method to implement in clinical settings. Methods: We have developed an ATRT subgroup predictor assay using a custom genes panel for the NanoString nCounter System and a flexible machine learning classifier package. Seventy-one ATRT primary tumors with matching gene expression array and NanoString data were used to construct a multi-algorithms ensemble classifier. Additional validation was performed using an independent gene expression array against the independently generated dataset. We also analyzed 11 extra-cranial rhabdoid tumors with our classifier and compared our approach against DNA methylation classification to evaluate the result consistency with existing methods. Results: We have demonstrated that our novel ensemble classifier has an overall average of 93.6% accuracy in the validation dataset, and a striking 98.9% accuracy was achieved with the high-prediction score samples. Using our classifier, all analyzed extra-cranial rhabdoid tumors are classified as MYC subgroups. Compared with the DNA methylation classification, the results show high agreement, with 84.5% concordance and up to 95.8% concordance for high-confidence predictions. Conclusions: Here we present a rapid, cost-effective, and accurate ATRT subgrouping assay applicable for clinical use.

The Incidence of Multiple Fusions in a Series of Pediatric Soft Tissue and Bone Tumors.

BACKGROUND: Next generation sequencing (NGS) has increased the detection of fusion genes in cancer. NGS has found multiple fusions in single tumor samples; however, the incidence of this in pediatric soft tissue and bone tumors (PSTBTs) is not well documented. The aim of this study is to catalogue the incidence of multiple fusions in a series of PSTBTs, and apply a modified gene fusion classification system to determine clinical relevance. METHODOLOGY: RNA from 78 bone and soft tissue tumors and 7 external quality assessment samples were sequenced and analyzed using recently-described Metafusion (MF) software and classified using a modification of previously-published schema for fusion classification into 3 tiers: 1, strong clinical significance; 2, potential clinical significance; and 3, unknown clinical significance. RESULTS: One-hundred forty-five fusions were detected in 85 samples. Fifty-five samples (65%) had a single fusion and 30 (35%) had more than 1 fusion. No samples contained more than 1 tier 1 fusion. There were 40 tier 1 (28%), 36 tier 2 (24%), and 69 (48%) tier 3 fusions. CONCLUSIONS: A significant percentage of PSTBTs harbor more than 1 fusion, and by applying a modified fusion classification scheme, the potential clinical relevance of such fusions can be determined.

Clinical Implementation of MetaFusion for Accurate Cancer-Driving Fusion Detection from RNA Sequencing.

Oncogenic fusion genes may be identified from next-generation sequencing data, typically RNA-sequencing. However, in a clinical setting, identifying these alterations is challenging against a background of nonrelevant fusion calls that reduce workflow precision and specificity. Furthermore, although numerous algorithms have been developed to detect fusions in RNA-sequencing, there are variations in their individual sensitivities. Here this problem was addressed by introducing MetaFusion into clinical use. Its utility was illustrated when applied to both whole-transcriptome and targeted sequencing data sets. MetaFusion combines ensemble fusion calls from eight individual fusion-calling algorithms with practice-informed identification of gene fusions that are known to be clinically relevant. In doing so, it allows oncogenic fusions to be identified with near-perfect sensitivity and high precision and specificity, significantly outperforming the individual fusion callers it uses as well as existing clinical-grade software. MetaFusion enhances clinical yield over existing methods and is able to identify fusions that have patient relevance for the purposes of diagnosis, prognosis, and treatment.

Clinical impact of combined epigenetic and molecular analysis of pediatric low-grade gliomas.

BACKGROUND: Both genetic and methylation analysis have been shown to provide insight into the diagnosis and prognosis of many brain tumors. However, the implication of methylation profiling and its interaction with genetic alterations in pediatric low-grade gliomas (PLGGs) are unclear. METHODS: We performed a comprehensive analysis of PLGG with long-term clinical follow-up. In total 152 PLGGs were analyzed from a range of pathological subtypes, including 40 gangliogliomas. Complete molecular analysis was compared with genome-wide methylation data and outcome in all patients. For further analysis of specific PLGG groups, including BRAF p.V600E mutant gliomas, we compiled an additional cohort of clinically and genetically defined tumors from 3 large centers. RESULTS: Unsupervised hierarchical clustering revealed 5 novel subgroups of PLGG. These were dominated by nonneoplastic factors such as tumor location and lymphocytic infiltration. Midline PLGG clustered together while deep hemispheric lesions differed from lesions in the periphery. Mutations were distributed throughout these location-driven clusters of PLGG. A novel methylation cluster suggesting high lymphocyte infiltration was confirmed pathologically and exhibited worse progression-free survival compared with PLGG harboring similar molecular alterations (P = 0.008; multivariate analysis: P = 0.035). Although the current methylation classifier revealed low confidence in 44% of cases and failed to add information in most PLGG, it was helpful in reclassifying rare cases. The addition of histopathological and molecular information to specific methylation subgroups such as pleomorphic xanthoastrocytoma-like tumors could stratify these tumors into low and high risk (P = 0.0014). CONCLUSION: The PLGG methylome is affected by multiple nonneoplastic factors. Combined molecular and pathological analysis is key to provide additional information when methylation classification is used for PLGG in the clinical setting.

Integrated Molecular and Clinical Analysis of 1,000 Pediatric Low-Grade Gliomas.

Pediatric low-grade gliomas (pLGG) are frequently driven by genetic alterations in the RAS-mitogen-activated protein kinase (RAS/MAPK) pathway yet show unexplained variability in their clinical outcome. To address this, we characterized a cohort of >1,000 clinically annotated pLGG. Eighty-four percent of cases harbored a driver alteration, while those without an identified alteration also often exhibited upregulation of the RAS/MAPK pathway. pLGG could be broadly classified based on their alteration type. Rearrangement-driven tumors were diagnosed at a younger age, enriched for WHO grade I histology, infrequently progressed, and rarely resulted in death as compared with SNV-driven tumors. Further sub-classification of clinical-molecular correlates stratified pLGG into risk categories. These data highlight the biological and clinical differences between pLGG subtypes and opens avenues for future treatment refinement.

Multiplexed Digital Detection of B-Cell Acute Lymphoblastic Leukemia Fusion Transcripts Using the NanoString nCounter System.

Chromosomal rearrangements resulting in fusion transcripts have been reported in precursor B-cell acute lymphoblastic leukemia (B-ALL). The identification of fusion events is crucial in the diagnosis of B-ALL. In this study, we used NanoString nCounter technology to design, validate, and evaluate a multiplex panel for the detection of B-ALL fusion transcripts. Fifty-one B-ALL fusion transcripts reported in children in the literature were included in the design of the NanoString panel. Twenty-six fusion transcripts were validated using 64 positive-control samples and 74 negative-control samples with 100% sensitivity and 99% specificity in comparison to RT-PCR. Our results support a potential role of NanoString's technology as a robust and cost-effective technique that could be used in the detection of fusion transcripts and implemented into the diagnostic algorithm of B-ALL.

Alterations in ALK/ROS1/NTRK/MET drive a group of infantile hemispheric gliomas.

Infant gliomas have paradoxical clinical behavior compared to those in children and adults: low-grade tumors have a higher mortality rate, while high-grade tumors have a better outcome. However, we have little understanding of their biology and therefore cannot explain this behavior nor what constitutes optimal clinical management. Here we report a comprehensive genetic analysis of an international cohort of clinically annotated infant gliomas, revealing 3 clinical subgroups. Group 1 tumors arise in the cerebral hemispheres and harbor alterations in the receptor tyrosine kinases ALK, ROS1, NTRK and MET. These are typically single-events and confer an intermediate outcome. Groups 2 and 3 gliomas harbor RAS/MAPK pathway mutations and arise in the hemispheres and midline, respectively. Group 2 tumors have excellent long-term survival, while group 3 tumors progress rapidly and do not respond well to chemoradiation. We conclude that infant gliomas comprise 3 subgroups, justifying the need for specialized therapeutic strategies.

Immunohistochemistry for ATRX Can Miss ATRX Mutations: Lessons From Neuroblastoma.

Neuroblastoma is the most common extracranial solid tumor of childhood with a median age of presentation of 17 months. A common theme in high-risk neuroblastoma is maintenance of telomeres, one mechanism for which involves alternate lengthening of telomeres (ALT) associated with ATRX gene mutations. Mutations are believed to result in loss of ATRX protein, and therefore immunohistochemistry is used to detect mutations. We screened 133 cases of neuroblastoma by ATRX immunohistochemistry, and found 9 cases with partial to total absence of ATRX. Sequencing for ATRX mutations detected a mutation in 1 of 9 cases, suggesting immunostaining was not reliable for detecting mutations. To correlate immunostaining with ALT, fluorescence in situ hybridization (FISH) for ALT was performed in 6 of these cases and 5 (from 4 patients) showed ALT, implying impaired ATRX protein function, despite the failure to identify a mutation. Two other cases with large deletions in the ATRX gene showed diffusely positive staining for ATRX protein but showed ALT by FISH. Four of the 6 patients with ALT-positive tumors were over 5 years old. Therefore, 29 additional patients 5 years old and above with ATRX-positive tumors were screened for ALT by FISH and 6 additional cases with ALT were detected, bringing the total to 29% (10/34) of children 5 years old and above, 70% of which showed positive ATRX immunohistochemistry. Patients with ATRX mutations in neuroblastoma tend to have a more chronic and progressive course of disease. Screening neuroblastoma tumors at diagnosis for ATRX mutations may help identify patients who might benefit from personalized therapy directed against ALT. However, relaying on negative immunohistochemistry for ATRX protein to identify ALT in neuroblastoma may miss a significant proportion of patients. The addition of FISH for ALT as part of the diagnostic workup, especially for older children (5 y old and above), would help ensure that patients are correctly identified for anti-ALT therapy.

Sarcoma Subgrouping by Detection of Fusion Transcripts Using NanoString nCounter Technology.

BACKGROUND: NanoString technology is an innovative barcode-based system that requires less tissue than traditional techniques and can test for multiple fusion transcripts in a single reaction. The objective of this study was to determine the utility of NanoString technology in the detection of sarcoma-specific fusion transcripts in pediatric sarcomas. DESIGN: Probe pairs for the most common pediatric sarcoma fusion transcripts were designed for the assay. The NanoString assay was used to test 22 specific fusion transcripts in 45 sarcoma samples that had exhibited one of these fusion genes previously by reverse transcription polymerase chain reaction (RT-PCR). A mixture of frozen (n = 18), formalin-fixed, paraffin-embedded (FFPE) tissue (n = 23), and rapid extract template (n = 4) were used for testing. RESULTS: Each of the 22 transcripts tested was detected in at least one of the 45 tumor samples. The results of the NanoString assay were 100% concordant with the previous RT-PCR results for the tumor samples, and the technique was successful using both FFPE and rapid extract method. CONCLUSION: Multiplexed interrogation for sarcoma-specific fusion transcripts using NanoString technology is a reliable approach for molecular diagnosis of pediatric sarcomas and works well with FFPE tissues. Future work will involve validating additional sarcoma fusion transcripts as well as determining the optimal workflow for diagnostic purposes.

Detecting Stem Cell Marker Expression Using the NanoString nCounter System.

The use of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) has become commonplace in the study of neuronal development, physiology, disease modelling, and therapy development. Due to the transient nature of working with these cells, it is important to regularly confirm the cell status as a naive stem cell versus a more defined neural progenitor cell (NPC). Classically, this has been done using a panel of specific antibodies to test for the expression of transcription factors known to be observed in ESCs, but not NPCs. However, this method is both time consuming and expensive. Here, we describe the use of the NanoString nCounter system for determining the levels of expression of key transcription factors that will effectively aid in determining the state of your stem cell cultures.

Differential patterns of metastatic dissemination across medulloblastoma subgroups.

OBJECTIVE Metastatic dissemination is a major treatment challenge and cause of death in patients with medulloblastoma. However, the influence of molecular biology on the pattern of metastatic dissemination at diagnosis is not known. In this study, the authors sought to define the location, pattern, and imaging characteristics of medulloblastoma metastases across subgroups at diagnosis. METHODS A consecutive cohort of patients with metastatic medulloblastoma at The Hospital for Sick Children and the University Hospital Motol, who underwent up-front MRI of the craniospinal axis, was assembled and allocated to subgroups using NanoString limited gene-expression profiling. Radiological characteristics (including location, morphology, size, diffusion restriction, and contrast enhancement) were discerned through a retrospective review. RESULTS Forty metastatic medulloblastomas were identified with up-front neuroimaging of the craniospinal axis: 5 sonic hedgehog (SHH), 16 Group 3, and 19 Group 4 metastases. Significant subgroup-specific differences were observed, particularly with respect to tumor location, size, and morphology. Group 3 metastases were most frequently laminar compared with a more nodular pattern in Group 4 (14 of 16 in Group 3 vs 8 of 19 in Group 4; p = 0.0004). Laminar metastases were not observed in patients with SHH medulloblastoma. Suprasellar metastases are highly specific to Group 4 (p = 0.016). Two of the 5 SHH cases had multifocal lesions in the cerebellum, raising the possibility that these were in fact synchronous primary tumors and not true metastases. A minority of patients with Group 4 metastases harbored metastatic deposits that did not enhance on MRI after contrast administration, often in patients whose primary tumor did not enhance. CONCLUSIONS The location, morphology, and imaging characteristics of metastatic medulloblastoma differ across molecular subgroups, with implications for diagnosis and management. This suggests that the biology of leptomeningeal dissemination differs among medulloblastoma subgroups.

Multiplex Detection of Pediatric Low-Grade Glioma Signature Fusion Transcripts and Duplications Using the NanoString nCounter System.

Previous studies identified recurrent fusion and duplication events in pediatric low-grade glioma (pLGG). In addition to their role in diagnosis, the presence of these events aid in dictating therapy and predicting patient survival. Clinically, BRAF alterations are most commonly identified using fluorescent in situ hybridization (FISH). However, this method is costly, labor-intensive and does not identify nonBRAF events. Here, we evaluated the NanoString nCounter gene expression system for detecting 32 of the most commonly reported fusion/duplication events in pLGG. The assay was validated on 90 pLGG samples using FISH as the gold standard and showed sensitivity and specificity of 97% and 98%, respectively. We next profiled formalin-fixed paraffin-embedded preserved biopsy specimens from 429 pLGG cases. 171 (40%) of the cases within our cohort tested positive for a fusion or duplication event contained within our panel. These events, in order of prevalence, were KIAA1549-BRAF 16;9 (89/171, 52.0%), KIAA1549-BRAF 15;9 (42/171, 24.6%), KIAA1549-BRAF 16;11 (14/171, 8.2%), FGFR1-TACC1 17;7 (13/171, 7.6%), MYBL1 duplication (5/171, 2.9%), KIAA1549-BRAF 18;10 (4/171, 2.3%), KIAA1549-BRAF 15;11 (2/171, 1.2%), FAM131B-BRAF 2;9 (1/171, 0.6%), and RNF130-BRAF 3;9 (1/171, 0.6%). This work introduces NanoString as a viable clinical replacement for the detection of fusion and duplication events in pLGG.

Therapeutic and Prognostic Implications of BRAF V600E in Pediatric Low-Grade Gliomas.

Purpose BRAF V600E is a potentially highly targetable mutation detected in a subset of pediatric low-grade gliomas (PLGGs). Its biologic and clinical effect within this diverse group of tumors remains unknown. Patients and Methods A combined clinical and genetic institutional study of patients with PLGGs with long-term follow-up was performed (N = 510). Clinical and treatment data of patients with BRAF V600E mutated PLGG (n = 99) were compared with a large international independent cohort of patients with BRAF V600E mutated-PLGG (n = 180). Results BRAF V600E mutation was detected in 69 of 405 patients (17%) with PLGG across a broad spectrum of histologies and sites, including midline locations, which are not often routinely biopsied in clinical practice. Patients with BRAF V600E PLGG exhibited poor outcomes after chemotherapy and radiation therapies that resulted in a 10-year progression-free survival of 27% (95% CI, 12.1% to 41.9%) and 60.2% (95% CI, 53.3% to 67.1%) for BRAF V600E and wild-type PLGG, respectively ( P < .001). Additional multivariable clinical and molecular stratification revealed that the extent of resection and CDKN2A deletion contributed independently to poor outcome in BRAF V600E PLGG. A similar independent role for CDKN2A and resection on outcome were observed in the independent cohort. Quantitative imaging analysis revealed progressive disease and a lack of response to conventional chemotherapy in most patients with BRAF V600E PLGG. Conclusion BRAF V600E PLGG constitutes a distinct entity with poor prognosis when treated with current adjuvant therapy.

Targeted detection of genetic alterations reveal the prognostic impact of H3K27M and MAPK pathway aberrations in paediatric thalamic glioma.

Paediatric brain tumours arising in the thalamus present significant diagnostic and therapeutic challenges to physicians due to their sensitive midline location. As such, genetic analysis for biomarkers to aid in the diagnosis, prognosis and treatment of these tumours is needed. Here, we identified 64 thalamic gliomas with clinical follow-up and characterized targeted genomic alterations using newly optimized droplet digital and NanoString-based assays. The median age at diagnosis was 9.25 years (range, 0.63-17.55) and median survival was 6.43 (range, 0.01-27.63) years. Our cohort contained 42 and 22 tumours reviewed as low and high grade gliomas, respectively. Five (12 %) low grade and 11 (50 %) high grade gliomas were positive for the H3F3A/HIST1H3B K27M (H3K27M) mutation. Kaplan-Meier survival analysis revealed significantly worse overall survival for patients harbouring the H3K27M mutation versus H3F3A/HIST1H3B wild type (H3WT) samples (log-rank p < 0.0001) with a median survival of 1.02 vs. 9.12 years. Mitogen-activated protein kinase (MAPK) pathway activation via BRAF or FGFR1 hotspot mutations or fusion events were detected in 44 % of patients, and was associated with long-term survival in the absence of H3K27M (log-rank p < 0.0001). Multivariate analysis demonstrated H3K27M status and high grade histology to be the most significant independent predictors of poor overall survival with hazard ratios of 6.945 and 7.721 (p < 0.0001), respectively. In contrast, MAPK pathway activation is a predictor of favourable patient outcome, although not independent of other clinical factors. Importantly, we show that low grade malignancies may harbour H3K27M mutations and that these tumours show a dismal survival compared to low grade H3WT cases. Our data strongly supports the inclusion of targeted genetic testing in childhood thalamic tumours to most accurately stratify patients into appropriate risk groups.

Phase II Weekly Vinblastine for Chemotherapy-Naïve Children With Progressive Low-Grade Glioma: A Canadian Pediatric Brain Tumor Consortium Study.

Purpose Vinblastine monotherapy has shown promising activity and a low-toxicity profile in patients with pediatric low-grade glioma (PLGG) who experienced treatment failure after initial treatment with chemotherapy and/or radiation. The aim of this study was to assess the activity of vinblastine in therapy-naïve children. Patients and Methods Patients < 18 years old with unresectable and/or progressive therapy-naïve PLGG were eligible. Vinblastine was administered once per week at a dose of 6 mg/m2 intravenously over a period of 70 weeks. Vision, quality of life, neurofibromatosis type 1 (NF1) status, and BRAF mutation/fusion status were also determined and correlated with outcome. Results Fifty-four patients were enrolled onto the study, with a median age of 8 years (range, 0.7 to 17.2 years). Most patients had chiasmatic/hypothalamic tumors (55.5%), and 13 patients (24.1%) had NF1. The most common histology was pilocytic astrocytoma (46.3%). Seventeen patients were diagnosed using radiologic criteria alone. Best response to chemotherapy was centrally reviewed with a response rate (complete, partial, or minor response) of 25.9%. Disease stabilization (complete, partial, or minor response or stable disease) was achieved in 47 patients (87.0%). Visual improvement was observed in 20% of patients with optic pathway glioma. Five-year overall survival and progression-free survival (PFS) rates were 94.4% (95% CI, 88.5% to 100%) and 53.2% (95% CI, 41.3% to 68.5%), respectively, for the entire cohort. Patients with NF1 had a significantly better PFS (85.1%; 95% CI, 68.0% to 100%) when compared with patients without NF1 (42.0%; 95% CI, 29.1% to 60.7%; P = .012). Age< 3 years or > 10 years was not associated with poor outcome. Treatment was well tolerated, and quality of life was not affected during treatment. In this trial, there was no correlation between BRAF alterations and outcome. Conclusion Vinblastine administered once per week is well tolerated in children with treatment naïve PLGG. Overall survival and PFS are comparable to current therapies, with a favorable toxicity profile and a maintained quality of life.

A genome scale overexpression screen to reveal drug activity in human cells.

Target identification is a critical step in the lengthy and expensive process of drug development. Here, we describe a genome-wide screening platform that uses systematic overexpression of pooled human ORFs to understand drug mode-of-action and resistance mechanisms. We first calibrated our screen with the well-characterized drug methotrexate. We then identified new genes involved in the bioactivity of diverse drugs including antineoplastic agents and biologically active molecules. Finally, we focused on the transcription factor RHOXF2 whose overexpression conferred resistance to DNA damaging agents. This approach represents an orthogonal method for functional screening and, to our knowledge, has never been reported before.

CHIP-MYTH: a novel interactive proteomics method for the assessment of agonist-dependent interactions of the human ß2-adrenergic receptor.

G-protein coupled receptors (GPCRs) are involved in a variety of disease processes and comprise major drug targets. However, the complexity of integral membrane proteins such as GPCRs makes the identification of their interacting partners and subsequent drug development challenging. A comprehensive understanding of GPCR protein interaction networks is needed to design effective therapeutic strategies to inhibit these drug targets. Here, we developed a novel split-ubiquitin membrane yeast two-hybrid (MYTH) technology called CHIP-MYTH, which allows the unbiased characterization of interaction partners of full-length GPCRs in a drug-dependent manner. This was achieved by coupling DNA microarray technology to the MYTH approach, which allows a quantitative evaluation of interacting partners of a given integral membrane protein in the presence or absence of drug. As a proof of principle, we applied the CHIP-MYTH approach to the human ß2-adrenergic receptor (ß2AR), a target of interest in the treatment of asthma, chronic obstructive pulmonary disease (COPD), neurological disease, cardiovascular disease, and obesity. A CHIP-MYTH screen was performed in the presence or absence of salmeterol, a long-acting ß2AR-agonist. Our results suggest that ß2AR activation with salmeterol can induce the dissociation of heterotrimeric G-proteins, Gαßγ, into Gα and Gßγ subunits, which in turn activates downstream signaling cascades. Using CHIP-MYTH, we confirmed previously known and identified novel ß2AR interactors involved in GPCR-mediated signaling cascades. Several of these interactions were confirmed in mammalian cells using LUminescence-based Mammalian IntERactome (LUMIER) and co-immunoprecipitation assays. In summary, the CHIP-MYTH approach is ideal for conducting comprehensive protein-protein interactions (PPI) screenings of full-length GPCRs in the presence or absence of drugs, thus providing a valuable tool to further our understanding of GPCR-mediated signaling.

Miniature short hairpin RNA screens to characterize antiproliferative drugs.

The application of new proteomics and genomics technologies support a view in which few drugs act solely by inhibiting a single cellular target. Indeed, drug activity is modulated by complex, often incompletely understood cellular mechanisms. Therefore, efforts to decipher mode of action through genetic perturbation such as RNAi typically yields "hits" that fall into several categories. Of particular interest to the present study, we aimed to characterize secondary activities of drugs on cells. Inhibiting a known target can result in clinically relevant synthetic phenotypes. In one scenario, drug perturbation could, for example, improperly activate a protein that normally inhibits a particular kinase. In other cases, additional, lower affinity targets can be inhibited as in the example of inhibition of c-Kit observed in Bcr-Abl-positive cells treated with Gleevec. Drug transport and metabolism also play an important role in the way any chemicals act within the cells. Finally, RNAi per se can also affect cell fitness by more general off-target effects, e.g., via the modulation of apoptosis or DNA damage repair. Regardless of the root cause of these unwanted effects, understanding the scope of a drug's activity and polypharmacology is essential for better understanding its mechanism(s) of action, and such information can guide development of improved therapies. We describe a rapid, cost-effective approach to characterize primary and secondary effects of small-molecules by using small-scale libraries of virally integrated short hairpin RNAs. We demonstrate this principle using a "minipool" composed of shRNAs that target the genes encoding the reported protein targets of approved drugs. Among the 28 known reported drug-target pairs, we successfully identify 40% of the targets described in the literature and uncover several unanticipated drug-target interactions based on drug-induced synthetic lethality. We provide a detailed protocol for performing such screens and for analyzing the data. This cost-effective approach to mammalian knockdown screens, combined with the increasing maturation of RNAi technology will expand the accessibility of similar approaches in academic settings.

A comprehensive platform for highly multiplexed mammalian functional genetic screens.

BACKGROUND: Genome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens. RESULTS: Experiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens. CONCLUSION: Herein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.