Todd R. Golub

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case. A class discovery procedure automatically discovered the distinction between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) without previous knowledge of these classes. An automatically derived class predictor was able to determine the class of new leukemia cases. The results demonstrate the feasibility of cancer classification based solely on gene expression monitoring and suggest a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.

The Cancer Cell Line Encyclopedia presents the first results from a large-scale screen of some 947 cancer cell lines with 24 anticancer drugs, with the aim of identifying specific genomic alterations and gene expression profiles associated with selective sensitivity or resistance to potential therapeutic agents. Cancer cell lines are widely used as preclinical models to gain mechanistic and therapeutic insight. Two manuscripts in this issue describe the large-scale genetic and pharmacological characterization of human cancer cell lines. Each group characterized collections of several-hundred cell lines using different platforms and analytical methods. Their results are complementary, and confirm that many human cell lines capture the genomic diversity of their respective cancers. Initial findings include the identification of a number of potential markers of drug sensitivity and resistance. For example, Garnett et al. report an association between EWS-FLI1 gene translocations, frequently found in Ewing's sarcoma, and sensitivity to PARP inhibitors, a class of drug currently in clinical trials for other cancer types. Barretina et al. report a possible association between SLFN11 expression and sensitivity to topoisomerase inhibitors. The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available1. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens2.

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this “Connectivity Map” resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project.

A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-κΒ pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types. Two Articles in this issue add major data sets to the growing picture of the cancer genome. Bignell et al. analysed a large number of homozygous gene deletions in a collection of 746 publicly available cancer cell lines. Combined with information about hemizygous deletions of the same genes, the data suggest that many deletions found in cancer reflect the position of a gene at a fragile site in the genome, rather than as a recessive cancer gene whose loss confers a selective growth advantage. Beroukhim et al. present the largest data set to date on somatic copy-number variations across more than 3,000 specimens of human primary cancers. Many alterations are shared between multiple tumour types. Functional experiments demonstrate an oncogenic role for the apoptosis genes MCL1 and BCL2L1 that are associated with amplifications found in many cancers. One way of discovering genes with key roles in cancer development is to identify genomic regions that are frequently altered in human cancers. Here, high-resolution analyses of somatic copy-number alterations (SCNAs) in numerous cancer specimens provide an overview of regions of focal SCNA that are altered at significant frequency across several cancer types. An oncogenic function is also found for the anti-apoptosis genes MCL1 and BCL2L1, which reside in amplified genome regions in many cancers.

Array technologies have made it straightforward to monitor simultaneously the expression pattern of thousands of genes. The challenge now is to interpret such massive data sets. The first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidimensional data. The method has been implemented in a publicly available computer package, GENECLUSTER, that performs the analytical calculations and provides easy data visualization. To illustrate the value of such analysis, the approach is applied to hematopoietic differentiation in four well studied models (HL-60, U937, Jurkat, and NB4 cells). Expression patterns of some 6,000 human genes were assayed, and an online database was created. GENECLUSTER was used to organize the genes into biologically relevant clusters that suggest novel hypotheses about hematopoietic differentiation-for example, highlighting certain genes and pathways involved in "differentiation therapy" used in the treatment of acute promyelocytic leukemia.

Polycythemia vera (PV), essential thrombocythemia (ET), and myeloid metaplasia with myelofibrosis (MMM) are clonal disorders arising from hematopoietic progenitors. An internet-based protocol was used to collect clinical information and biological specimens from patients with these diseases. High-throughput DNA resequencing identified a recurrent somatic missense mutation JAK2V617F in granulocyte DNA samples of 121 of 164 PV patients, of which 41 had homozygous and 80 had heterozygous mutations. Molecular and cytogenetic analyses demonstrated that homozygous mutations were due to duplication of the mutant allele. JAK2V617F was also identified in granulocyte DNA samples from 37 of 115 ET and 16 of 46 MMM patients, but was not observed in 269 normal individuals. In vitro analysis demonstrated that JAK2V617F is a constitutively active tyrosine kinase.

Although a few cancer genes are mutated in a high proportion of tumours of a given type (>20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600–5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics. Large-scale genomic analysis of somatic point mutations in exomes from tumour–normal pairs across 21 cancer types identifies most known cancer genes in these tumour types as well as 33 genes not known to be significantly mutated, and down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. Most cancer genes are mutated at intermediate frequencies, appearing in less than one in five samples of a particular tumour type, so the accurate identification of cancer genes needs to be based on large-scale sampling in order to take account of this mutation-rate heterogeneity. This study presents a statistical analysis of 21 tumour types from more than 4,700 tumour–normal pairs. The authors identify 33 previously unknown genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Further analyses suggest that near-saturation may be achieved with between 600 and 5,000 samples for a given tumour type, depending on background mutation rate.

We have generated a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, we analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct subclasses of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.

<h2>Summary</h2> We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

The mutational profile of head and neck cancer is complex and may pose challenges to the development of targeted therapies.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR–Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines. The original Cancer Cell Line Encyclopedia (CCLE) is expanded with deeper characterization of over 1,000 cell lines, including genomic, transcriptomic, and proteomic data, and integration with drug-sensitivity and gene-dependency data.

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a support vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.

Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean. We found predictive models for 426 dependencies (55%) by nonlinear regression modeling considering 66,646 molecular features. Many dependencies fall into a limited number of classes, and unexpectedly, in 82% of models, the top biomarkers were expression based. We demonstrated the basis behind one such predictive model linking hypermethylation of the UBB ubiquitin gene to a dependency on UBC. Together, these observations provide a foundation for a cancer dependency map that facilitates the prioritization of therapeutic targets.

Comprehensive identification of all functional elements encoded in the human genome is a fundamental need in biomedical research. Here, we present a comparative analysis of the human, mouse, rat and dog genomes to create a systematic catalogue of common regulatory motifs in promoters and 3' untranslated regions (3' UTRs). The promoter analysis yields 174 candidate motifs, including most previously known transcription-factor binding sites and 105 new motifs. The 3'-UTR analysis yields 106 motifs likely to be involved in post-transcriptional regulation. Nearly one-half are associated with microRNAs (miRNAs), leading to the discovery of many new miRNA genes and their likely target genes. Our results suggest that previous estimates of the number of human miRNA genes were low, and that miRNAs regulate at least 20% of human genes. The overall results provide a systematic view of gene regulation in the human, which will be refined as additional mammalian genomes become available.

We describe here the use of nonnegative matrix factorization (NMF), an algorithm based on decomposition by parts that can reduce the dimension of expression data from thousands of genes to a handful of metagenes. Coupled with a model selection mechanism, adapted to work for any stochastic clustering algorithm, NMF is an efficient method for identification of distinct molecular patterns and provides a powerful method for class discovery. We demonstrate the ability of NMF to recover meaningful biological information from cancer-related microarray data. NMF appears to have advantages over other methods such as hierarchical clustering or self-organizing maps. We found it less sensitive to a priori selection of genes or initial conditions and able to detect alternative or context-dependent patterns of gene expression in complex biological systems. This ability, similar to semantic polysemy in text, provides a general method for robust molecular pattern discovery.

Drug resistance presents a challenge to the treatment of cancer patients. Many studies have focused on cell-autonomous mechanisms of drug resistance. By contrast, we proposed that the tumour micro-environment confers innate resistance to therapy. Here we developed a co-culture system to systematically assay the ability of 23 stromal cell types to influence the innate resistance of 45 cancer cell lines to 35 anticancer drugs. We found that stroma-mediated resistance is common, particularly to targeted agents. We characterized further the stroma-mediated resistance of BRAF-mutant melanoma to RAF inhibitors because most patients with this type of cancer show some degree of innate resistance. Proteomic analysis showed that stromal cell secretion of hepatocyte growth factor (HGF) resulted in activation of the HGF receptor MET, reactivation of the mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI(3)K)-AKT signalling pathways, and immediate resistance to RAF inhibition. Immunohistochemistry experiments confirmed stromal cell expression of HGF in patients with BRAF-mutant melanoma and showed a significant correlation between HGF expression by stromal cells and innate resistance to RAF inhibitor treatment. Dual inhibition of RAF and either HGF or MET resulted in reversal of drug resistance, suggesting RAF plus HGF or MET inhibitory combination therapy as a potential therapeutic strategy for BRAF-mutant melanoma. A similar resistance mechanism was uncovered in a subset of BRAF-mutant colorectal and glioblastoma cell lines. More generally, this study indicates that the systematic dissection of interactions between tumours and their micro-environment can uncover important mechanisms underlying drug resistance.

Genome-wide expression analysis was used to identify genes whose expression depends on the functions of key components of the transcription initiation machinery in yeast. Components of the RNA polymerase II holoenzyme, the general transcription factor TFIID, and the SAGA chromatin modification complex were found to have roles in expression of distinct sets of genes. The results reveal an unanticipated level of regulation which is superimposed on that due to gene-specific transcription factors, a novel mechanism for coordinate regulation of specific sets of genes when cells encounter limiting nutrients, and evidence that the ultimate targets of signal transduction pathways can be identified within the initiation apparatus.

Clinical trials in melanoma patients carrying B-RAF gene mutations have shown promising results with the B-RAF kinase inhibitor PLX4032, but many patients go on to become resistant. Two papers now uncover possible mechanisms for this resistance. Nazarian et al. report that melanomas can acquire resistance due to mutations of N-RAS or increased expression of PDGFRβ, and Johannessen et al. report resistance due to upregulation of MAP3K8/COT. Each of these mechanisms seems to apply to some patients in the recent PLX4032 trial, yet surprisingly, no secondary B-RAF mutations were observed. Recent data from early clinical trials in melanoma patients carrying mutations in the B-RAF gene have shown promising results with the B-RAF kinase inhibitor PLX4032; however, many patients eventually develop resistance to this treatment. Two papers now uncover possible mechanisms of resistance to PLX4032. One paper shows that upregulation of MAP3K8 (which encodes COT) can confer resistance of melanoma cells to B-RAF inhibitors, whereas another paper found that melanomas can acquire resistance due to mutations of N-RAS or increased expression of PDGFRβ. Each of these resistance mechanisms seems to apply to at least some patients on recent PLX4032 trial, whereas, surprisingly, so far no secondary B-RAF mutations have been observed. Oncogenic mutations in the serine/threonine kinase B-RAF (also known as BRAF) are found in 50–70% of malignant melanomas1. Pre-clinical studies have demonstrated that the B-RAF(V600E) mutation predicts a dependency on the mitogen-activated protein kinase (MAPK) signalling cascade in melanoma2,3,4,5,6—an observation that has been validated by the success of RAF and MEK inhibitors in clinical trials7,8,9. However, clinical responses to targeted anticancer therapeutics are frequently confounded by de novo or acquired resistance10,11,12. Identification of resistance mechanisms in a manner that elucidates alternative ‘druggable’ targets may inform effective long-term treatment strategies13. Here we expressed ∼600 kinase and kinase-related open reading frames (ORFs) in parallel to interrogate resistance to a selective RAF kinase inhibitor. We identified MAP3K8 (the gene encoding COT/Tpl2) as a MAPK pathway agonist that drives resistance to RAF inhibition in B-RAF(V600E) cell lines. COT activates ERK primarily through MEK-dependent mechanisms that do not require RAF signalling. Moreover, COT expression is associated with de novo resistance in B-RAF(V600E) cultured cell lines and acquired resistance in melanoma cells and tissue obtained from relapsing patients following treatment with MEK or RAF inhibitors. We further identify combinatorial MAPK pathway inhibition or targeting of COT kinase activity as possible therapeutic strategies for reducing MAPK pathway activation in this setting. Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.

Prostate cancer is the second most common cancer in men worldwide and causes over 250,000 deaths each year. Overtreatment of indolent disease also results in significant morbidity. Common genetic alterations in prostate cancer include losses of NKX3.1 (8p21) and PTEN (10q23), gains of AR (the androgen receptor gene) and fusion of ETS family transcription factor genes with androgen-responsive promoters. Recurrent somatic base-pair substitutions are believed to be less contributory in prostate tumorigenesis but have not been systematically analyzed in large cohorts. Here, we sequenced the exomes of 112 prostate tumor and normal tissue pairs. New recurrent mutations were identified in multiple genes, including MED12 and FOXA1. SPOP was the most frequently mutated gene, with mutations involving the SPOP substrate-binding cleft in 6-15% of tumors across multiple independent cohorts. Prostate cancers with mutant SPOP lacked ETS family gene rearrangements and showed a distinct pattern of genomic alterations. Thus, SPOP mutations may define a new molecular subtype of prostate cancer.

Multiple myeloma is an incurable malignancy of plasma cells, and its pathogenesis is poorly understood. Here we report the massively parallel sequencing of 38 tumour genomes and their comparison to matched normal DNAs. Several new and unexpected oncogenic mechanisms were suggested by the pattern of somatic mutation across the data set. These include the mutation of genes involved in protein translation (seen in nearly half of the patients), genes involved in histone methylation, and genes involved in blood coagulation. In addition, a broader than anticipated role of NF-κB signalling was indicated by mutations in 11 members of the NF-κB pathway. Of potential immediate clinical relevance, activating mutations of the kinase BRAF were observed in 4% of patients, suggesting the evaluation of BRAF inhibitors in multiple myeloma clinical trials. These results indicate that cancer genome sequencing of large collections of samples will yield new insights into cancer not anticipated by existing knowledge.

The JAK2V617F allele has recently been identified in patients with polycythemia vera (PV), essential thrombocytosis (ET), and myelofibrosis with myeloid metaplasia (MF). Subsequent analysis has shown that constitutive activation of the JAK-STAT signal transduction pathway is an important pathogenetic event in these patients, and that enzymatic inhibition of JAK2V617F may be of therapeutic benefit in this context. However, a significant proportion of patients with ET or MF are JAK2V617F-negative. We hypothesized that activation of the JAK-STAT pathway might also occur as a consequence of activating mutations in certain hematopoietic-specific cytokine receptors, including the erythropoietin receptor (EPOR), the thrombopoietin receptor (MPL), or the granulocyte-colony stimulating factor receptor (GCSFR).DNA sequence analysis of the exons encoding the transmembrane and juxtamembrane domains of EPOR, MPL, and GCSFR, and comparison with germline DNA derived from buccal swabs, identified a somatic activating mutation in the transmembrane domain of MPL (W515L) in 9% (4/45) of JAKV617F-negative MF. Expression of MPLW515L in 32D, UT7, or Ba/F3 cells conferred cytokine-independent growth and thrombopoietin hypersensitivity, and resulted in constitutive phosphorylation of JAK2, STAT3, STAT5, AKT, and ERK. Furthermore, a small molecule JAK kinase inhibitor inhibited MPLW515L-mediated proliferation and JAK-STAT signaling in vitro. In a murine bone marrow transplant assay, expression of MPLW515L, but not wild-type MPL, resulted in a fully penetrant myeloproliferative disorder characterized by marked thrombocytosis (Plt count 1.9-4.0 x 10(12)/L), marked splenomegaly due to extramedullary hematopoiesis, and increased reticulin fibrosis.Activation of JAK-STAT signaling via MPLW515L is an important pathogenetic event in patients with JAK2V617F-negative MF. The bone marrow transplant model of MPLW515L-mediated myeloproliferative disorders (MPD) exhibits certain features of human MF, including extramedullary hematopoiesis, splenomegaly, and megakaryocytic proliferation. Further analysis of positive and negative regulators of the JAK-STAT pathway is warranted in JAK2V617F-negative MPD.

Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification. Comprehensive integration of mutational and structural alterations in clinically-annotated DLBCL patient samples provides a novel molecular classification of the disease.

Molecular tumour profiling is one way in which effective targeted cancer treatment regimes might be developed. Two groups report significant developments in this direction. Bild et al. studied gene expression patterns that reflect the activation of various oncogenic (cancer-causing) signal transduction pathways. Using combinations of these pathway signatures, they predict which patients with breast, lung or ovarian cancer have a particularly poor prognosis. The ability to identify molecular pathways that are deregulated in a particular cancer in this way might be used to predict its sensitivity to specific therapeutic drugs. Solit et al. studied tumour cells with mutations in the RAS and BRAF genes, thought to cause cancer at least in part by activating the MEK/ERK signalling pathway. They show that tumours with the BRAF mutation, but not RAS, are highly sensitive to PD0325901, an MEK inhibitor that is in early-stage clinical trials in patients with melanoma, colon, breast and lung cancers. So by testing for the presence of BRAF mutations it may be possible to identify those patients most likely to benefit from this type of drug. The kinase pathway comprising RAS, RAF, mitogen-activated protein kinase kinase (MEK) and extracellular signal regulated kinase (ERK) is activated in most human tumours, often through gain-of-function mutations of RAS and RAF family members1. Using small-molecule inhibitors of MEK and an integrated genetic and pharmacologic analysis, we find that mutation of BRAF is associated with enhanced and selective sensitivity to MEK inhibition when compared to either ‘wild-type’ cells or cells harbouring a RAS mutation. This MEK dependency was observed in BRAF mutant cells regardless of tissue lineage, and correlated with both downregulation of cyclin D1 protein expression and the induction of G1 arrest. Pharmacological MEK inhibition completely abrogated tumour growth in BRAF mutant xenografts, whereas RAS mutant tumours were only partially inhibited. These data suggest an exquisite dependency on MEK activity in BRAF mutant tumours, and offer a rational therapeutic strategy for this genetically defined tumour subtype.

Chronic myelomonocytic leukemia (CMML) is a myelodysplastic syndrome characterized by abnormal clonal myeloid proliferation and by progression to acute myelogenous leukemia (AML). CMML thus offers an opportunity to study early genetic events in the transition to AML. A recently recognized sub group of CMML has a t(5;12)(q33;p13) balanced translocation. We report that the consequence of the t(5;12) translocation is expression of a fusion transcript in which the tyrosine kinase domain of the platelet-derived growth factor receptor β (PDGFRβ) on chromosome 5 is coupled to a novel ets-like gene, tel, on chromosome 12. The tel-PDGFRβ fusion demonstrates the oncogenic potential of PDGFRβ and may provide a paradigm for early events in the pathogenesis of AML.

It is a challenge to identify patients who, after undergoing potentially curative treatment for hepatocellular carcinoma, are at greatest risk for recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissue.We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed, paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival.The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of tissue samples from 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (P=0.04).We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlated with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma.

Prostate cancer is the second most common cause of male cancer deaths in the United States. However, the full range of prostate cancer genomic alterations is incompletely characterized. Here we present the complete sequence of seven primary human prostate cancers and their paired normal counterparts. Several tumours contained complex chains of balanced (that is, 'copy-neutral') rearrangements that occurred within or adjacent to known cancer genes. Rearrangement breakpoints were enriched near open chromatin, androgen receptor and ERG DNA binding sites in the setting of the ETS gene fusion TMPRSS2-ERG, but inversely correlated with these regions in tumours lacking ETS fusions. This observation suggests a link between chromatin or transcriptional regulation and the genesis of genomic aberrations. Three tumours contained rearrangements that disrupted CADM2, and four harboured events disrupting either PTEN (unbalanced events), a prostate tumour suppressor, or MAGI2 (balanced events), a PTEN interacting protein not previously implicated in prostate tumorigenesis. Thus, genomic rearrangements may arise from transcriptional or chromatin aberrancies and engage prostate tumorigenic mechanisms.

Classical Hodgkin lymphoma (cHL) and mediastinal large B-cell lymphoma (MLBCL) are lymphoid malignancies with certain shared clinical, histologic, and molecular features. Primary cHLs and MLBCLs include variable numbers of malignant cells within an inflammatory infiltrate, suggesting that these tumors escape immune surveillance. Herein, we integrate high-resolution copy number data with transcriptional profiles and identify the immunoregulatory genes, PD-L1 and PD-L2, as key targets at the 9p24.1 amplification peak in HL and MLBCL cell lines. We extend these findings to laser-capture microdissected primary Hodgkin Reed-Sternberg cells and primary MLBCLs and find that programmed cell death-1 (PD-1) ligand/9p24.1 amplification is restricted to nodular sclerosing HL, the cHL subtype most closely related to MLBCL. Using quantitative immunohistochemical methods, we document the association between 9p24.1 copy number and PD-1 ligand expression in primary tumors. In cHL and MLBCL, the extended 9p24.1 amplification region also included the Janus kinase 2 (JAK2) locus. Of note, JAK2 amplification increased protein expression and activity, specifically induced PD-1 ligand transcription and enhanced sensitivity to JAK2 inhibition. Therefore, 9p24.1 amplification is a disease-specific structural alteration that increases both the gene dosage of PD-1 ligands and their induction by JAK2, defining the PD-1 pathway and JAK2 as complementary rational therapeutic targets.

Growing evidence suggests that microbes can influence the efficacy of cancer therapies. By studying colon cancer models, we found that bacteria can metabolize the chemotherapeutic drug gemcitabine (2',2'-difluorodeoxycytidine) into its inactive form, 2',2'-difluorodeoxyuridine. Metabolism was dependent on the expression of a long isoform of the bacterial enzyme cytidine deaminase (CDDL), seen primarily in Gammaproteobacteria. In a colon cancer mouse model, gemcitabine resistance was induced by intratumor Gammaproteobacteria, dependent on bacterial CDDL expression, and abrogated by cotreatment with the antibiotic ciprofloxacin. Gemcitabine is commonly used to treat pancreatic ductal adenocarcinoma (PDAC), and we hypothesized that intratumor bacteria might contribute to drug resistance of these tumors. Consistent with this possibility, we found that of the 113 human PDACs that were tested, 86 (76%) were positive for bacteria, mainly Gammaproteobacteria.

Breast carcinoma is the leading cause of cancer-related mortality in women worldwide, with an estimated 1.38 million new cases and 458,000 deaths in 2008 alone. This malignancy represents a heterogeneous group of tumours with characteristic molecular features, prognosis and responses to available therapy. Recurrent somatic alterations in breast cancer have been described, including mutations and copy number alterations, notably ERBB2 amplifications, the first successful therapy target defined by a genomic aberration. Previous DNA sequencing studies of breast cancer genomes have revealed additional candidate mutations and gene rearrangements. Here we report the whole-exome sequences of DNA from 103 human breast cancers of diverse subtypes from patients in Mexico and Vietnam compared to matched-normal DNA, together with whole-genome sequences of 22 breast cancer/normal pairs. Beyond confirming recurrent somatic mutations in PIK3CA, TP53, AKT1, GATA3 and MAP3K1, we discovered recurrent mutations in the CBFB transcription factor gene and deletions of its partner RUNX1. Furthermore, we have identified a recurrent MAGI3-AKT3 fusion enriched in triple-negative breast cancer lacking oestrogen and progesterone receptors and ERBB2 expression. The MAGI3-AKT3 fusion leads to constitutive activation of AKT kinase, which is abolished by treatment with an ATP-competitive AKT small-molecule inhibitor.

Human T cell leukemias can arise from oncogenes activated by specific chromosomal translocations involving the T cell receptor genes. Here we show that five different T cell oncogenes (HOX11, TAL1, LYL1, LMO1, and LMO2) are often aberrantly expressed in the absence of chromosomal abnormalities. Using oligonucleotide microarrays, we identified several gene expression signatures that were indicative of leukemic arrest at specific stages of normal thymocyte development: LYL1+ signature (pro-T), HOX11+ (early cortical thymocyte), and TAL1+ (late cortical thymocyte). Hierarchical clustering analysis of gene expression signatures grouped samples according to their shared oncogenic pathways and identified HOX11L2 activation as a novel event in T cell leukemogenesis. These findings have clinical importance, since HOX11 activation is significantly associated with a favorable prognosis, while expression of TAL1, LYL1, or, surprisingly, HOX11L2 confers a much worse response to treatment. Our results illustrate the power of gene expression profiles to elucidate transformation pathways relevant to human leukemia.

Androgen receptor (AR) plays a central role in prostate cancer, and most patients respond to androgen deprivation therapies, but they invariably relapse with a more aggressive prostate cancer that has been termed hormone refractory or androgen independent. To identify proteins that mediate this tumor progression, gene expression in 33 androgen-independent prostate cancer bone marrow metastases versus 22 laser capture-microdissected primary prostate cancers was compared using Affymetrix oligonucleotide microarrays. Multiple genes associated with aggressive behavior were increased in the androgen-independent metastatic tumors (MMP9, CKS2, LRRC15, WNT5A, EZH2, E2F3, SDC1, SKP2, and BIRC5), whereas a candidate tumor suppressor gene (KLF6) was decreased. Consistent with castrate androgen levels, androgen-regulated genes were reduced 2- to 3-fold in the androgen-independent tumors. Nonetheless, they were still major transcripts in these tumors, indicating that there was partial reactivation of AR transcriptional activity. This was associated with increased expression of AR (5.8-fold) and multiple genes mediating androgen metabolism (HSD3B2, AKR1C3, SRD5A1, AKR1C2, AKR1C1, and UGT2B15). The increase in aldo-keto reductase family 1, member C3 (AKR1C3), the prostatic enzyme that reduces adrenal androstenedione to testosterone, was confirmed by real-time reverse transcription-PCR and immunohistochemistry. These results indicate that enhanced intracellular conversion of adrenal androgens to testosterone and dihydrotestosterone is a mechanism by which prostate cancer cells adapt to androgen deprivation and suggest new therapeutic targets.

The somatic genetic basis of chronic lymphocytic leukemia, a common and clinically heterogeneous leukemia occurring in adults, remains poorly understood.We obtained DNA samples from leukemia cells in 91 patients with chronic lymphocytic leukemia and performed massively parallel sequencing of 88 whole exomes and whole genomes, together with sequencing of matched germline DNA, to characterize the spectrum of somatic mutations in this disease.Nine genes that are mutated at significant frequencies were identified, including four with established roles in chronic lymphocytic leukemia (TP53 in 15% of patients, ATM in 9%, MYD88 in 10%, and NOTCH1 in 4%) and five with unestablished roles (SF3B1, ZMYM3, MAPK1, FBXW7, and DDX3X). SF3B1, which functions at the catalytic core of the spliceosome, was the second most frequently mutated gene (with mutations occurring in 15% of patients). SF3B1 mutations occurred primarily in tumors with deletions in chromosome 11q, which are associated with a poor prognosis in patients with chronic lymphocytic leukemia. We further discovered that tumor samples with mutations in SF3B1 had alterations in pre-messenger RNA (mRNA) splicing.Our study defines the landscape of somatic mutations in chronic lymphocytic leukemia and highlights pre-mRNA splicing as a critical cellular process contributing to chronic lymphocytic leukemia.

Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.

Abstract Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight independent patient cohorts across the world. In addition, aiming to establish the real world applicability of a classification system, we profiled 118 formalin-fixed, paraffin-embedded tissues from an additional patient cohort. A total of 603 patients were analyzed, representing the major etiologies of HCC (hepatitis B and C) collected from Western and Eastern countries. We observed three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum α-fetoprotein levels. An analysis of the components of the signatures indicated that S1 reflected aberrant activation of the WNT signaling pathway, S2 was characterized by proliferation as well as MYC and AKT activation, and S3 was associated with hepatocyte differentiation. Functional studies indicated that the WNT pathway activation signature characteristic of S1 tumors was not simply the result of β-catenin mutation but rather was the result of transforming growth factor-β activation, thus representing a new mechanism of WNT pathway activation in HCC. These experiments establish the first consensus classification framework for HCC based on gene expression profiles and highlight the power of integrating multiple data sets to define a robust molecular taxonomy of the disease. [Cancer Res 2009;69(18):7385–92]

A chemical screen has identified a small molecule, piperlongumine (PL), as a compound that induces selective killing of cancer cells. Piperlongumine acts by increasing reactive oxygen species (ROS) levels in cancer cells. Although it is active against a number of tumour models in vivo irrespective of p53 status, it does not affect normal tissues, including rapidly proliferating non-tumour cells. This work suggests a novel strategy for eradicating cancer cells by targeting the ROS stress-response pathway, but further work will be needed to identify determinants of piperlongumine sensitivity in a wider range of cancers. Malignant transformation, driven by gain-of-function mutations in oncogenes and loss-of-function mutations in tumour suppressor genes, results in cell deregulation that is frequently associated with enhanced cellular stress (for example, oxidative, replicative, metabolic and proteotoxic stress, and DNA damage)1. Adaptation to this stress phenotype is required for cancer cells to survive, and consequently cancer cells may become dependent upon non-oncogenes that do not ordinarily perform such a vital function in normal cells. Thus, targeting these non-oncogene dependencies in the context of a transformed genotype may result in a synthetic lethal interaction and the selective death of cancer cells2. Here we used a cell-based small-molecule screening and quantitative proteomics approach that resulted in the unbiased identification of a small molecule that selectively kills cancer cells but not normal cells. Piperlongumine increases the level of reactive oxygen species (ROS) and apoptotic cell death in both cancer cells and normal cells engineered to have a cancer genotype, irrespective of p53 status, but it has little effect on either rapidly or slowly dividing primary normal cells. Significant antitumour effects are observed in piperlongumine-treated mouse xenograft tumour models, with no apparent toxicity in normal mice. Moreover, piperlongumine potently inhibits the growth of spontaneously formed malignant breast tumours and their associated metastases in mice. Our results demonstrate the ability of a small molecule to induce apoptosis selectively in cells that have a cancer genotype, by targeting a non-oncogene co-dependency acquired through the expression of the cancer genotype in response to transformation-induced oxidative stress3,4,5.

Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures. We infer that most cancer cells are differentiated along two specialized glial programs, whereas a rare subpopulation of cells is undifferentiated and associated with a neural stem cell expression program. Cells with expression signatures for proliferation are highly enriched in this rare subpopulation, consistent with a model in which CSCs are primarily responsible for fuelling the growth of oligodendroglioma in humans. Analysis of copy number variation (CNV) shows that distinct CNV sub-clones within tumours display similar cellular hierarchies, suggesting that the architecture of oligodendroglioma is primarily dictated by developmental programs. Subclonal point mutation analysis supports a similar model, although a full phylogenetic tree would be required to definitively determine the effect of genetic evolution on the inferred hierarchies. Our single-cell analyses provide insight into the cellular architecture of oligodendrogliomas at single-cell resolution and support the cancer stem cell model, with substantial implications for disease management.

To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88, CARD11, EZH2, and CREBBP. We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO, and TNFRSF14. Further, we show that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase-mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.

We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations and discovered putative tumor suppressor genes by determining homozygous deletions and loss of heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53, and DIS3 (particularly in nonhyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of nonmutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions.

Somatic chromosomal deletions in cancer are thought to indicate the location of tumour suppressor genes, by which a complete loss of gene function occurs through biallelic deletion, point mutation or epigenetic silencing, thus fulfilling Knudson's two-hit hypothesis. In many recurrent deletions, however, such biallelic inactivation has not been found. One prominent example is the 5q- syndrome, a subtype of myelodysplastic syndrome characterized by a defect in erythroid differentiation. Here we describe an RNA-mediated interference (RNAi)-based approach to discovery of the 5q- disease gene. We found that partial loss of function of the ribosomal subunit protein RPS14 phenocopies the disease in normal haematopoietic progenitor cells, and also that forced expression of RPS14 rescues the disease phenotype in patient-derived bone marrow cells. In addition, we identified a block in the processing of pre-ribosomal RNA in RPS14-deficient cells that is functionally equivalent to the defect in Diamond-Blackfan anaemia, linking the molecular pathophysiology of the 5q- syndrome to a congenital syndrome causing bone marrow failure. These results indicate that the 5q- syndrome is caused by a defect in ribosomal protein function and suggest that RNAi screening is an effective strategy for identifying causal haploinsufficiency disease genes.

Though many individual transcription factors are known to regulate hematopoietic differentiation, major aspects of the global architecture of hematopoiesis remain unknown. Here, we profiled gene expression in 38 distinct purified populations of human hematopoietic cells and used probabilistic models of gene expression and analysis of cis-elements in gene promoters to decipher the general organization of their regulatory circuitry. We identified modules of highly coexpressed genes, some of which are restricted to a single lineage but most of which are expressed at variable levels across multiple lineages. We found densely interconnected cis-regulatory circuits and a large number of transcription factors that are differentially expressed across hematopoietic states. These findings suggest a more complex regulatory system for hematopoiesis than previously assumed.

MYC affects normal and neoplastic cell proliferation by altering gene expression, but the precise pathways remain unclear. We used oligonucleotide microarray analysis of 6,416 genes and expressed sequence tags to determine changes in gene expression caused by activation of c-MYC in primary human fibroblasts. In these experiments, 27 genes were consistently induced, and 9 genes were repressed. The identity of the genes revealed that MYC may affect many aspects of cell physiology altered in transformed cells: cell growth, cell cycle, adhesion, and cytoskeletal organization. Identified targets possibly linked to MYC's effects on cell growth include the nucleolar proteins nucleolin and fibrillarin, as well as the eukaryotic initiation factor 5A. Among the cell cycle genes identified as targets, the G1 cyclin D2 and the cyclin-dependent kinase binding protein CksHs2 were induced whereas the cyclin-dependent kinase inhibitor p21(Cip1) was repressed. A role for MYC in regulating cell adhesion and structure is suggested by repression of genes encoding the extracellular matrix proteins fibronectin and collagen, and the cytoskeletal protein tropomyosin. A possible mechanism for MYC-mediated apoptosis was revealed by identification of the tumor necrosis factor receptor associated protein TRAP1 as a MYC target. Finally, two immunophilins, peptidyl-prolyl cis-trans isomerase F and FKBP52, the latter of which plays a role in cell division in Arabidopsis, were up-regulated by MYC. We also explored pattern-matching methods as an alternative approach for identifying MYC target genes. The genes that displayed an expression profile most similar to endogenous Myc in microarray-based expression profiling of myeloid differentiation models were highly enriched for MYC target genes.

George Daley and colleagues show that Lin28 and Lin28B promote cellular transformation by repressing let-7 family members, leading to derepression of let-7 targets. They also find that LIN28 and LIN28B are overexpressed in ∼15% of primary human tumors and cancer cell lines and that their expression is associated with aggressive disease and poor prognosis across multiple tumor types. Multiple members of the let-7 family of miRNAs are often repressed in human cancers1,2, thereby promoting oncogenesis by derepressing targets such as HMGA2, K-Ras and c-Myc3,4. However, the mechanism by which let-7 miRNAs are coordinately repressed is unclear. The RNA-binding proteins LIN28 and LIN28B block let-7 precursors from being processed to mature miRNAs5,6,7,8, suggesting that their overexpression might promote malignancy through repression of let-7. Here we show that LIN28 and LIN28B are overexpressed in primary human tumors and human cancer cell lines (overall frequency ∼15%), and that overexpression is linked to repression of let-7 family miRNAs and derepression of let-7 targets. LIN28 and LIN28b facilitate cellular transformation in vitro, and overexpression is associated with advanced disease across multiple tumor types. Our work provides a mechanism for the coordinate repression of let-7 miRNAs observed in a subset of human cancers, and associates activation of LIN28 and LIN28B with poor clinical prognosis.

Tumor subclasses differ according to the genotypes and phenotypes of malignant cells as well as the composition of the tumor microenvironment (TME). We dissected these influences in isocitrate dehydrogenase (IDH)–mutant gliomas by combining 14,226 single-cell RNA sequencing (RNA-seq) profiles from 16 patient samples with bulk RNA-seq profiles from 165 patient samples. Differences in bulk profiles between IDH-mutant astrocytoma and oligodendroglioma can be primarily explained by distinct TME and signature genetic events, whereas both tumor types share similar developmental hierarchies and lineages of glial differentiation. As tumor grade increases, we find enhanced proliferation of malignant cells, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia expression programs in TME. Our work provides a unifying model for IDH-mutant gliomas and a general framework for dissecting the differences among human tumor subclasses.

Chromosomal rearrangements involving band 12p13 are found in a wide variety of human leukemias but are particularly common in childhood acute lymphoblastic leukemia. The genes involved in these rearrangements, however, have not been identified. We now report the cloning of a t(12;21) translocation breakpoint involving 12p13 and 21q22 in two cases of childhood pre-B acute lymphoblastic leukemia, in which t(12;21) rearrangements were not initially apparent. The consequence of the translocation is fusion of the helix-loop-helix domain of TEL, an ETS-like putative transcription factor, to the DNA-binding and transactivation domains of the transcription factor AML1. These data show that TEL, previously shown to be fused to the platelet-derived growth factor receptor beta in chronic myelomonocytic leukemia, can be implicated in the pathogenesis of leukemia through its fusion to either a receptor tyrosine kinase or a transcription factor. The TEL-AML1 fusion also indicates that translocations affecting the AML1 gene can be associated with lymphoid, as well as myeloid, malignancy.

Kit/SCF signaling and Mitf-dependent transcription are both essential for melanocyte development and pigmentation. To identify Mitf-dependent Kit transcriptional targets in primary melanocytes, microarray studies were undertaken. Among identified targets was BCL2, whose germline deletion produces melanocyte loss and which exhibited phenotypic synergy with Mitf in mice. BCL2's regulation by Mitf was verified in melanocytes and melanoma cells and by chromatin immunoprecipitation of the BCL2 promoter. Mitf also regulates BCL2 in osteoclasts, and both Mitf(mi/mi) and Bcl2(-/-) mice exhibit severe osteopetrosis. Disruption of Mitf in melanocytes or melanoma triggered profound apoptosis susceptible to rescue by BCL2 overexpression. Clinically, primary human melanoma expression microarrays revealed tight nearest neighbor linkage for MITF and BCL2. This linkage helps explain the vital roles of both Mitf and Bcl2 in the melanocyte lineage and the well-known treatment resistance of melanoma.

Melanoma is notable for its metastatic propensity, lethality in the advanced setting and association with ultraviolet exposure early in life. To obtain a comprehensive genomic view of melanoma in humans, we sequenced the genomes of 25 metastatic melanomas and matched germline DNA. A wide range of point mutation rates was observed: lowest in melanomas whose primaries arose on non-ultraviolet-exposed hairless skin of the extremities (3 and 14 per megabase (Mb) of genome), intermediate in those originating from hair-bearing skin of the trunk (5-55 per Mb), and highest in a patient with a documented history of chronic sun exposure (111 per Mb). Analysis of whole-genome sequence data identified PREX2 (phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 2)--a PTEN-interacting protein and negative regulator of PTEN in breast cancer--as a significantly mutated gene with a mutation frequency of approximately 14% in an independent extension cohort of 107 human melanomas. PREX2 mutations are biologically relevant, as ectopic expression of mutant PREX2 accelerated tumour formation of immortalized human melanocytes in vivo. Thus, whole-genome sequencing of human melanoma tumours revealed genomic evidence of ultraviolet pathogenesis and discovered a new recurrently mutated gene in melanoma.

Adam Bass, Gad Getz and colleagues report whole-exome sequencing of 149 esophageal adenocarcinomas (EACs) and whole-genome sequencing of 15 EACs. They identify a mutational signature defined by a high prevalence of A>C transversions, as well as 26 genes mutated at high frequency in EACs. The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With a 5-year survival rate of ∼15%, the identification of new therapeutic targets for EAC is greatly important. We analyze the mutation spectra from whole-exome sequencing of 149 EAC tumor-normal pairs, 15 of which have also been subjected to whole-genome sequencing. We identify a mutational signature defined by a high prevalence of A>C transversions at AA dinucleotides. Statistical analysis of exome data identified 26 significantly mutated genes. Of these genes, five (TP53, CDKN2A, SMAD4, ARID1A and PIK3CA) have previously been implicated in EAC. The new significantly mutated genes include chromatin-modifying factors and candidate contributors SPG20, TLR4, ELMO1 and DOCK2. Functional analyses of EAC-derived mutations in ELMO1 identifies increased cellular invasion. Therefore, we suggest the potential activation of the RAC1 pathway as a contributor to EAC tumorigenesis.

Human cancer cell lines are the workhorse of cancer research. Although cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origins and consequences of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research. The extent, origins and consequences of genetic variation within human cell lines are studied, providing a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.

In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible.

In an effort to find gene regulatory networks and clusters of genes that affect cancer susceptibility to anticancer agents, we joined a database with baseline expression levels of 7,245 genes measured by using microarrays in 60 cancer cell lines, to a database with the amounts of 5,084 anticancer agents needed to inhibit growth of those same cell lines. Comprehensive pair-wise correlations were calculated between gene expression and measures of agent susceptibility. Associations weaker than a threshold strength were removed, leaving networks of highly correlated genes and agents called relevance networks. Hypotheses for potential single-gene determinants of anticancer agent susceptibility were constructed. The effect of random chance in the large number of calculations performed was empirically determined by repeated random permutation testing; only associations stronger than those seen in multiply permuted data were used in clustering. We discuss the advantages of this methodology over alternative approaches, such as phylogenetic-type tree clustering and self-organizing maps.

MicroRNAs are recently discovered regulators of gene expression and are becoming increasingly recognized as important regulators of heart function. Genome-wide profiling of microRNAs in human heart failure has not been reported previously. We measured expression of 428 microRNAs in 67 human left ventricular samples belonging to control (n = 10), ischemic cardiomyopathy (ICM, n = 19), dilated cardiomyopathy (DCM, n = 25), or aortic stenosis (AS, n = 13) diagnostic groups. miRNA expression between disease and control groups was compared by ANOVA with Dunnett's post hoc test. We controlled for multiple testing by estimating the false discovery rate. Out of 428 microRNAs measured, 87 were confidently detected; 43 were differentially expressed in at least one disease group. In supervised clustering, microRNA expression profiles correctly grouped samples by their clinical diagnosis, indicating that microRNA expression profiles are distinct between diagnostic groups. This was further supported by class prediction approaches, in which the class (control, ICM, DCM, AS) predicted by a microRNA-based classifier matched the clinical diagnosis 69% of the time (P < 0.001). These data show that expression of many microRNAs is altered in heart disease and that different types of heart disease are associated with distinct changes in microRNA expression. These data will guide further studies of the contribution of microRNAs to heart disease pathogenesis.

<h2>Summary</h2> Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy.

In modern clinical neuro-oncology, histopathological diagnosis affects therapeutic decisions and prognostic estimation more than any other variable. Among high-grade gliomas, histologically classic glioblastomas and anaplastic oligodendrogliomas follow markedly different clinical courses. Unfortunately, many malignant gliomas are diagnostically challenging; these nonclassic lesions are difficult to classify by histological features, generating considerable interobserver variability and limited diagnostic reproducibility. The resulting tentative pathological diagnoses create significant clinical confusion. We investigated whether gene expression profiling, coupled with class prediction methodology, could be used to classify high-grade gliomas in a manner more objective, explicit, and consistent than standard pathology. Microarray analysis was used to determine the expression of approximately 12000 genes in a set of 50 gliomas, 28 glioblastomas and 22 anaplastic oligodendrogliomas. Supervised learning approaches were used to build a two-class prediction model based on a subset of 14 glioblastomas and 7 anaplastic oligodendrogliomas with classic histology. A 20-feature k-nearest neighbor model correctly classified 18 of the 21 classic cases in leave-one-out cross-validation when compared with pathological diagnoses. This model was then used to predict the classification of clinically common, histologically nonclassic samples. When tumors were classified according to pathology, the survival of patients with nonclassic glioblastoma and nonclassic anaplastic oligodendroglioma was not significantly different (P = 0.19). However, class distinctions according to the model were significantly associated with survival outcome (P = 0.05). This class prediction model was capable of classifying high-grade, nonclassic glial tumors objectively and reproducibly. Moreover, the model provided a more accurate predictor of prognosis in these nonclassic lesions than did pathological classification. These data suggest that class prediction models, based on defined molecular profiles, classify diagnostically challenging malignant gliomas in a manner that better correlates with clinical outcome than does standard pathology.

More complete knowledge of the molecular mechanisms underlying cancer will improve prevention, diagnosis and treatment. Efforts such as The Cancer Genome Atlas are systematically characterizing the structural basis of cancer, by identifying the genomic mutations associated with each cancer type. A powerful complementary approach is to systematically characterize the functional basis of cancer, by identifying the genes essential for growth and related phenotypes in different cancer cells. Such information would be particularly valuable for identifying potential drug targets. Here, we report the development of an efficient, robust approach to perform genome-scale pooled shRNA screens for both positive and negative selection and its application to systematically identify cell essential genes in 12 cancer cell lines. By integrating these functional data with comprehensive genetic analyses of primary human tumors, we identified known and putative oncogenes such as EGFR, KRAS, MYC, BCR-ABL, MYB, CRKL, and CDK4 that are essential for cancer cell proliferation and also altered in human cancers. We further used this approach to identify genes involved in the response of cancer cells to tumoricidal agents and found 4 genes required for the response of CML cells to imatinib treatment: PTPN1, NF1, SMARCB1, and SMARCE1, and 5 regulators of the response to FAS activation, FAS, FADD, CASP8, ARID1A and CBX1. Broad application of this highly parallel genetic screening strategy will not only facilitate the rapid identification of genes that drive the malignant state and its response to therapeutics but will also enable the discovery of genes that participate in any biological process.

Tumor necrosis factor-alpha (TNF-alpha) is a contributing cause of the insulin resistance seen in obesity and obesity-linked type 2 diabetes, but the mechanism(s) by which TNF-alpha induces insulin resistance is not understood. By using 3T3-L1 adipocytes and oligonucleotide microarrays, we identified 142 known genes reproducibly upregulated by at least threefold after 4 h and/or 24 h of TNF-alpha treatment, and 78 known genes downregulated by at least twofold after 24 h of TNF-alpha incubation. TNF-alpha-induced genes include transcription factors implicated in preadipocyte gene expression or NF-kappaB activation, cytokines and cytokine-induced proteins, growth factors, enzymes, and signaling molecules. Importantly, a number of adipocyte-abundant genes, including GLUT4, hormone sensitive lipase, long-chain fatty acyl-CoA synthase, adipocyte complement-related protein of 30 kDa, and transcription factors CCAAT/enhancer binding protein-alpha, receptor retinoid X receptor-alpha, and peroxisome profilerator-activated receptor gamma were significantly downregulated by TNF-alpha treatment. Correspondingly, 24-h exposure of 3T3-L1 adipocytes to TNF-alpha resulted in reduced protein levels of GLUT4 and several insulin signaling proteins, including the insulin receptor, insulin receptor substrate 1 (IRS-1), and protein kinase B (AKT). Nuclear factor-kappaB (NF-kappaB) was activated within 15 min of TNF-alpha addition. 3T3-L1 adipocytes expressing IkappaBalpha-DN, a nondegradable NF-kappaB inhibitor, exhibited normal morphology, global gene expression, and insulin responses. However, absence of NF-kappaB activation abolished suppression of >98% of the genes normally suppressed by TNF-alpha and induction of 60-70% of the genes normally induced by TNF-alpha. Moreover, extensive cell death occurred in IkappaBalpha-DN-expressing adipocytes after 2 h of TNF-alpha treatment. Thus the changes in adipocyte gene expression induced by TNF-alpha could lead to insulin resistance. Further, NF-kappaB is an obligatory mediator of most of these TNF-alpha responses.

Abstract The CRISPR/Cas9 system enables genome editing and somatic cell genetic screens in mammalian cells. We performed genome-scale loss-of-function screens in 33 cancer cell lines to identify genes essential for proliferation/survival and found a strong correlation between increased gene copy number and decreased cell viability after genome editing. Within regions of copy-number gain, CRISPR/Cas9 targeting of both expressed and unexpressed genes, as well as intergenic loci, led to significantly decreased cell proliferation through induction of a G2 cell-cycle arrest. By examining single-guide RNAs that map to multiple genomic sites, we found that this cell response to CRISPR/Cas9 editing correlated strongly with the number of target loci. These observations indicate that genome targeting by CRISPR/Cas9 elicits a gene-independent antiproliferative cell response. This effect has important practical implications for the interpretation of CRISPR/Cas9 screening data and confounds the use of this technology for the identification of essential genes in amplified regions. Significance: We found that the number of CRISPR/Cas9-induced DNA breaks dictates a gene-independent antiproliferative response in cells. These observations have practical implications for using CRISPR/Cas9 to interrogate cancer gene function and illustrate that cancer cells are highly sensitive to site-specific DNA damage, which may provide a path to novel therapeutic strategies. Cancer Discov; 6(8); 914–29. ©2016 AACR. See related commentary by Sheel and Xue, p. 824. See related article by Munoz et al., p. 900. This article is highlighted in the In This Issue feature, p. 803

Whole-exome sequencing of circulating tumor cells enables accurate and powered calling of somatic point mutations. Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two patients with prostate cancer, including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were present in matched tissue. Moreover, we identified 10 early trunk and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these mutations, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

Drug resistance remains a major obstacle to successful cancer treatment. A database of drug-associated gene expression profiles was screened for molecules whose profile overlapped with a gene expression signature of glucocorticoid (GC) sensitivity/resistance in acute lymphoblastic leukemia (ALL) cells. The screen indicated that the mTOR inhibitor rapamycin profile matched the signature of GC sensitivity. We tested the hypothesis that rapamycin would induce GC sensitivity in lymphoid malignancy cells and found that it sensitized to GC-induced apoptosis via modulation of antiapoptotic MCL1. These data indicate that MCL1 is an important regulator of GC-induced apoptosis and that the combination of rapamycin and glucocorticoids has potential utility in lymphoid malignancies. Furthermore, this approach represents a strategy for identification of promising combination therapies for cancer.

The cellular composition of H3K27M gliomas Diffuse midline gliomas with histone H3 lysine27-to-methionine mutations (H3K27M-glioma) are an aggressive type of childhood cancer with few options for treatment. Filbin et al. used a single-cell sequencing approach to study the oncogenic programs, genetics, and cellular hierarchies of H3K27M-glioma. Tumors were mainly composed of cells resembling oligodendrocyte precursor cells, whereas differentiated malignant cells were a smaller fraction. In comparison with other gliomas, these cancers had distinct oncogenic programs and stem cell–like profiles that contributed to their stable tumor-propagating potential. The analysis also identified a lineage-specific marker that may be useful in developing therapies. Science , this issue p. 331

Effective clinical management of prostate cancer (PCA) has been challenged by significant intratumoural heterogeneity on the genomic and pathological levels and limited understanding of the genetic elements governing disease progression. Here, we exploited the experimental merits of the mouse to test the hypothesis that pathways constraining progression might be activated in indolent Pten-null mouse prostate tumours and that inactivation of such progression barriers in mice would engender a metastasis-prone condition. Comparative transcriptomic and canonical pathway analyses, followed by biochemical confirmation, of normal prostate epithelium versus poorly progressive Pten-null prostate cancers revealed robust activation of the TGFβ/BMP-SMAD4 signalling axis. The functional relevance of SMAD4 was further supported by emergence of invasive, metastatic and lethal prostate cancers with 100% penetrance upon genetic deletion of Smad4 in the Pten-null mouse prostate. Pathological and molecular analysis as well as transcriptomic knowledge-based pathway profiling of emerging tumours identified cell proliferation and invasion as two cardinal tumour biological features in the metastatic Smad4/Pten-null PCA model. Follow-on pathological and functional assessment confirmed cyclin D1 and SPP1 as key mediators of these biological processes, which together with PTEN and SMAD4, form a four-gene signature that is prognostic of prostate-specific antigen (PSA) biochemical recurrence and lethal metastasis in human PCA. This model-informed progression analysis, together with genetic, functional and translational studies, establishes SMAD4 as a key regulator of PCA progression in mice and humans.

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.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, whereas acute myeloid leukemia (AML) is the most common acute leukemia in adults. In general, ALL has a better prognosis than AML. To understand the distinct mechanisms in leukemogenesis between ALL and AML and to identify markers for diagnosis and treatment, we performed a large-scale genome-wide microRNA (miRNA, miR) expression profiling assay and identified 27 miRNAs that are differentially expressed between ALL and AML. Among them, miR-128a and -128b are significantly overexpressed, whereas let-7b and miR-223 are significantly down-regulated in ALL compared with AML. They are the most discriminatory miRNAs between ALL and AML. Using the expression signatures of a minimum of two of these miRNAs resulted in an accuracy rate of >95% in the diagnosis of ALL and AML. The differential expression patterns of these four miRNAs were validated further through large-scale real-time PCR on 98 acute leukemia samples covering most of the common cytogenetic subtypes, along with 10 normal control samples. Furthermore, we found that overexpression of miR-128 in ALL was at least partly associated with promoter hypomethylation and not with an amplification of its genomic locus. Taken together, we showed that expression signatures of as few as two miRNAs could accurately discriminate ALL from AML, and that epigenetic regulation might play an important role in the regulation of expression of miRNAs in acute leukemias.

Whole genome expression profiles are widely used to discover molecular subtypes of diseases. A remaining challenge is to identify the correspondence or commonality of subtypes found in multiple, independent data sets generated on various platforms. While model-based supervised learning is often used to make these connections, the models can be biased to the training data set and thus miss inherent, relevant substructure in the test data. Here we describe an unsupervised subclass mapping method (SubMap), which reveals common subtypes between independent data sets. The subtypes within a data set can be determined by unsupervised clustering or given by predetermined phenotypes before applying SubMap. We define a measure of correspondence for subtypes and evaluate its significance building on our previous work on gene set enrichment analysis. The strength of the SubMap method is that it does not impose the structure of one data set upon another, but rather uses a bi-directional approach to highlight the common substructures in both. We show how this method can reveal the correspondence between several cancer-related data sets. Notably, it identifies common subtypes of breast cancer associated with estrogen receptor status, and a subgroup of lymphoma patients who share similar survival patterns, thus improving the accuracy of a clinical outcome predictor.

Key Points PCNSLs and PTLs have a defining genetic signature that differs from other LBCLs and suggests rational targeted therapies. PCNSLs and PTLs frequently exhibit 9p24.1/PD-L1/PD-L2 copy number alterations and translocations, likely genetic bases of immune evasion.

MicroRNAs (miRNAs) are postulated to be important regulators in cancers. Here, we report a genome-wide miRNA expression analysis in 52 acute myeloid leukemia (AML) samples with common translocations, including t(8;21)/AML1(RUNX1)-ETO(RUNX1T1), inv(16)/CBFB-MYH11, t(15;17)/PML-RARA, and MLL rearrangements. Distinct miRNA expression patterns were observed for t(15;17), MLL rearrangements, and core-binding factor (CBF) AMLs including both t(8;21) and inv(16) samples. Expression signatures of a minimum of two (i.e., miR-126/126*), three (i.e., miR-224, miR-368, and miR-382), and seven (miR-17-5p and miR-20a, plus the aforementioned five) miRNAs could accurately discriminate CBF, t(15;17), and MLL-rearrangement AMLs, respectively, from each other. We further showed that the elevated expression of miR-126/126* in CBF AMLs was associated with promoter demethylation but not with amplification or mutation of the genomic locus. Our gain- and loss-of-function experiments showed that miR-126/126* inhibited apoptosis and increased the viability of AML cells and enhanced the colony-forming ability of mouse normal bone marrow progenitor cells alone and particularly, in cooperation with AML1-ETO, likely through targeting Polo-like kinase 2 (PLK2), a tumor suppressor. Our results demonstrate that specific alterations in miRNA expression distinguish AMLs with common translocations and imply that the deregulation of specific miRNAs may play a role in the development of leukemia with these associated genetic rearrangements.

Pediatric Ewing sarcoma is characterized by the expression of chimeric fusions of EWS and ETS family transcription factors, representing a paradigm for studying cancers driven by transcription factor rearrangements. In this study, we describe the somatic landscape of pediatric Ewing sarcoma. These tumors are among the most genetically normal cancers characterized to date, with only EWS-ETS rearrangements identified in the majority of tumors. STAG2 loss, however, is present in more than 15% of Ewing sarcoma tumors; occurs by point mutation, rearrangement, and likely nongenetic mechanisms; and is associated with disease dissemination. Perhaps the most striking finding is the paucity of mutations in immediately targetable signal transduction pathways, highlighting the need for new therapeutic approaches to target EWS-ETS fusions in this disease.We performed next-generation sequencing of Ewing sarcoma, a pediatric cancer involving bone, characterized by expression of EWS-ETS fusions. We found remarkably few mutations. However, we discovered that loss of STAG2 expression occurs in 15% of tumors and is associated with metastatic disease, suggesting a potential genetic vulnerability in Ewing sarcoma.

Biallelic inactivation of BRCA1 or BRCA2 is associated with a pattern of genome-wide mutations known as signature 3. By analyzing ∼1,000 breast cancer samples, we confirmed this association and established that germline nonsense and frameshift variants in PALB2, but not in ATM or CHEK2, can also give rise to the same signature. We were able to accurately classify missense BRCA1 or BRCA2 variants known to impair homologous recombination (HR) on the basis of this signature. Finally, we show that epigenetic silencing of RAD51C and BRCA1 by promoter methylation is strongly associated with signature 3 and, in our data set, was highly enriched in basal-like breast cancers in young individuals of African descent.

Here we describe how patterns of gene expression in human tumors have been deconvoluted to reveal a mechanism of action for the cyclin D1 oncogene. Computational analysis of the expression patterns of thousands of genes across hundreds of tumor specimens suggested that a transcription factor, C/EBPbeta/Nf-Il6, participates in the consequences of cyclin D1 overexpression. Functional analyses confirmed the involvement of C/EBPbeta in the regulation of genes affected by cyclin D1 and established this protein as an indispensable effector of a potentially important facet of cyclin D1 biology. This work demonstrates that tumor gene expression databases can be used to study the function of a human oncogene in situ.

While the global down-regulation of microRNAs (miRNAs) is a common feature of human tumors, its genetic basis is largely undefined. To explore this question, we analyzed the consequences of conditional Dicer1 mutation (Dicer1 "floxed" or Dicer1(fl)) on several mouse models of cancer. Here we show Dicer1 functions as a haploinsufficient tumor suppressor gene. Deletion of a single copy of Dicer1 in tumors from Dicer1(fl/+) animals led to reduced survival compared with controls. These tumors exhibited impaired miRNA processing but failed to lose the wild-type Dicer1 allele. Moreover, tumors from Dicer1(fl/fl) animals always maintained one functional Dicer1 allele. Consistent with selection against full loss of Dicer1 expression, enforced Dicer1 deletion caused inhibition of tumorigenesis. Analysis of human cancer genome copy number data reveals frequent deletion of DICER1. Importantly, however, the gene has not been reported to undergo homozygous deletion, suggesting that DICER1 is haploinsufficient in human cancer. These findings suggest Dicer1 may be an important haploinsufficient tumor suppressor gene and, furthermore, that other factors controlling miRNA biogenesis may also function in this manner.

To assess the extent of abnormal gene expression in clones, we assessed global gene expression by microarray analysis on RNA from the placentas and livers of neonatal cloned mice derived by nuclear transfer (NT) from both cultured embryonic stem cells and freshly isolated cumulus cells. Direct comparison of gene expression profiles of more than 10,000 genes showed that for both donor cell types approximately 4% of the expressed genes in the NT placentas differed dramatically in expression levels from those in controls and that the majority of abnormally expressed genes were common to both types of clones. Importantly, however, the expression of a smaller set of genes differed between the embryonic stem cell- and cumulus cell-derived clones. The livers of the cloned mice also showed abnormal gene expression, although to a lesser extent, and with a different set of affected genes, than seen in the placentas. Our results demonstrate frequent abnormal gene expression in clones, in which most expression abnormalities appear common to the NT procedure whereas others appear to reflect the particular donor nucleus.

Tumors put in a vulnerable position Cancer cells often display alterations in metabolism that help fuel their growth. Such metabolic “rewiring” may also work against the cancer cells, however, by creating new vulnerabilities that can be exploited therapeutically. A variety of human tumors show changes in methionine metabolism caused by loss of the gene coding for 5-methylthioadenosine phosphorylase (MTAP). Mavrakis et al. and Kryukov et al. found that the loss of MTAP renders cancer cell lines sensitive to growth inhibition by compounds that suppress the activity of a specific arginine methyltransferase called PRMT5. Conceivably, drugs that inhibit PRMT5 activity could be developed into a tailored therapy for MTAP-deficient tumors. Science , this issue pp. 1208 and 1214

We recently found that MLL-rearranged acute lymphoblastic leukemias (MLL) have a unique gene expression profile including high level expression of the receptor tyrosine kinase FLT3. We hypothesized that FLT3 might be a therapeutic target in MLL and found that 5 of 30 MLLs contain mutations in the activation loop of FLT3 that result in constitutive activation. Three are a newly described deletion of I836 and the others are D835 mutations. The recently described FLT3 inhibitor PKC412 proved cytotoxic to Ba/F3 cells dependent upon activated FLT3 containing either mutation. PKC412 is also differentially cytotoxic to leukemia cells with MLL translocations and FLT3 that is activated by either overexpression of the wild-type receptor or mutation. Finally, we developed a mouse model of MLL and used bioluminescent imaging to determine that PKC412 is active against MLL in vivo.

The genomic organization of the CDK2 gene, which overlaps the melanocyte-specific gene SILV/PMEL17, poses an interesting regulatory challenge. We show that, despite its ubiquitous expression, CDK2 exhibits tissue-specific regulation by the essential melanocyte lineage transcription factor MITF. In addition, functional studies revealed this regulation to be critical for maintaining CDK2 kinase activity and growth of melanoma cells. Expression levels of MITF and CDK2 are tightly correlated in primary melanoma specimens and predict susceptibility to the CDK2 inhibitor roscovitine. CDK2 depletion suppressed growth and cell cycle progression in melanoma, but not other cancers, corroborating previous results. Collectively, these data indicate that CDK2 activity in melanoma is largely maintained at the transcriptional level by MITF, and unlike other malignancies, it may be a suitable drug target in melanoma.

RAFT1/FRAP/mTOR is a key regulator of cell growth and division and the mammalian target of rapamycin, an immunosuppressive and anticancer drug.Rapamycin deprivation and nutrient deprivation have similar effects on the activity of S6 kinase 1 (S6K1) and 4E-BP1, two downstream effectors of RAFT1, but the relationship between nutrient-and rapamycin-sensitive pathways is unknown.Using transcriptional profiling, we show that, in human BJAB B-lymphoma cells and murine CTLL-2 T lymphocytes, rapamycin treatment affects the expression of many genes involved in nutrient and protein metabolism.The rapamycin-induced transcriptional profile is distinct from those induced by glucose, glutamine, or leucine deprivation but is most similar to that induced by amino acid deprivation.In particular, rapamycin treatment and amino acid deprivation up-regulate genes involved in nutrient catabolism and energy production and down-regulate genes participating in lipid and nucleotide synthesis and in protein synthesis, turnover, and folding.Surprisingly, however, rapamycin had effects opposite from those of amino acid starvation on the expression of a large group of genes involved in the synthesis, transport, and use of amino acids.Supported by measurements of nutrient use, the data suggest that RAFT1 is an energy and nutrient sensor and that rapamycin mimics a signal generated by the starvation of amino acids but that the signal is unlikely to be the absence of amino acids themselves.These observations underscore the importance of metabolism in controlling lymphocyte proliferation and offer a novel explanation for immunosuppression by rapamycin.

Osteosarcoma is the most common primary bone tumor, yet there have been no substantial advances in treatment or survival in three decades. We examined 59 tumor/normal pairs by whole-exome, whole-genome, and RNA-sequencing. Only the TP53 gene was mutated at significant frequency across all samples. The mean nonsilent somatic mutation rate was 1.2 mutations per megabase, and there was a median of 230 somatic rearrangements per tumor. Complex chains of rearrangements and localized hypermutation were detected in almost all cases. Given the intertumor heterogeneity, the extent of genomic instability, and the difficulty in acquiring a large sample size in a rare tumor, we used several methods to identify genomic events contributing to osteosarcoma survival. Pathway analysis, a heuristic analytic algorithm, a comparative oncology approach, and an shRNA screen converged on the phosphatidylinositol 3-kinase/mammalian target of rapamycin (PI3K/mTOR) pathway as a central vulnerability for therapeutic exploitation in osteosarcoma. Osteosarcoma cell lines are responsive to pharmacologic and genetic inhibition of the PI3K/mTOR pathway both in vitro and in vivo.

Cancer is principally considered a genetic disease, and numerous mutations are thought essential to drive its growth. However, the existence of genomically stable cancers and the emergence of mutations in genes that encode chromatin remodelers raise the possibility that perturbation of chromatin structure and epigenetic regulation are capable of driving cancer formation. Here we sequenced the exomes of 35 rhabdoid tumors, highly aggressive cancers of early childhood characterized by biallelic loss of SMARCB1, a subunit of the SWI/SNF chromatin remodeling complex. We identified an extremely low rate of mutation, with loss of SMARCB1 being essentially the sole recurrent event. Indeed, in 2 of the cancers there were no other identified mutations. Our results demonstrate that high mutation rates are dispensable for the genesis of cancers driven by mutation of a chromatin remodeling complex. Consequently, cancer can be a remarkably genetically simple disease.

During cancer therapy, tumor heterogeneity can drive the evolution of multiple tumor subclones harboring unique resistance mechanisms in an individual patient1-3. Previous case reports and small case series have suggested that liquid biopsy (specifically, cell-free DNA (cfDNA)) may better capture the heterogeneity of acquired resistance4-8. However, the effectiveness of cfDNA versus standard single-lesion tumor biopsies has not been directly compared in larger-scale prospective cohorts of patients following progression on targeted therapy. Here, in a prospective cohort of 42 patients with molecularly defined gastrointestinal cancers and acquired resistance to targeted therapy, direct comparison of postprogression cfDNA versus tumor biopsy revealed that cfDNA more frequently identified clinically relevant resistance alterations and multiple resistance mechanisms, detecting resistance alterations not found in the matched tumor biopsy in 78% of cases. Whole-exome sequencing of serial cfDNA, tumor biopsies and rapid autopsy specimens elucidated substantial geographic and evolutionary differences across lesions. Our data suggest that acquired resistance is frequently characterized by profound tumor heterogeneity, and that the emergence of multiple resistance alterations in an individual patient may represent the 'rule' rather than the 'exception'. These findings have profound therapeutic implications and highlight the potential advantages of cfDNA over tissue biopsy in the setting of acquired resistance.

Calcium signaling is a central regulator of cardiomyocyte growth and function. Calmodulin is a critical mediator of calcium signals. Because the amount of calmodulin within cardiomyocytes is limiting, the precise control of calmodulin expression is important for the regulation of calcium signaling. In this study, we show for the first time that calmodulin levels are regulated posttranscriptionally in heart failure. The cardiomyocyte-restricted microRNA miR-1 inhibited the translation of calmodulin-encoding mRNAs via highly conserved target sites within their 3' untranslated regions. In keeping with its effect on calmodulin expression, miR-1 downregulated calcium-calmodulin signaling through calcineurin to NFAT. miR-1 also negatively regulated the expression of Mef2a and Gata4, key transcription factors that mediate calcium-dependent changes in gene expression. Consistent with the downregulation of these hypertrophy-associated genes, miR-1 attenuated cardiomyocyte hypertrophy in cultured neonatal rat cardiomyocytes and in the intact adult heart. Our data indicate that miR-1 regulates cardiomyocyte growth responses by negatively regulating the calcium signaling components calmodulin, Mef2a, and Gata4.

Abstract Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features.

ABSTRACT: Aberrant gene expression is critical for tumor initiation and progression. However, we lack a comprehensive understanding of all genes that are aberrantly expressed in human cancer. Recently, DNA microarrays have been used to obtain global views of human cancer gene expression and to identify genetic markers that might be important for diagnosis and therapy. We review clinical applications of these novel tools, discuss some important recent studies, identify promising avenues of research in this emerging field of study, and discuss the likely impact that expression profiling will have on clinical oncology.

Key Points A gene expression profile consistent with activated JAK2 signaling is seen in all MPN patients, including in patients with CALR mutations. Transcriptional profiling discriminates subsets of MPNs based on JAK2V617F allele burden and on the presence of CALR and TET2 mutations.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.