Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.

BACKGROUND: High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors. METHODS: We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA). RESULTS: High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup. CONCLUSIONS: We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

Subtype and pathway specific responses to anticancer compounds in breast cancer.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.

Genomic and transcriptional aberrations linked to breast cancer pathophysiologies.

This study explores the roles of genome copy number abnormalities (CNAs) in breast cancer pathophysiology by identifying associations between recurrent CNAs, gene expression, and clinical outcome in a set of aggressively treated early-stage breast tumors. It shows that the recurrent CNAs differ between tumor subtypes defined by expression pattern and that stratification of patients according to outcome can be improved by measuring both expression and copy number, especially high-level amplification. Sixty-six genes deregulated by the high-level amplifications are potential therapeutic targets. Nine of these (FGFR1, IKBKB, ERBB2, PROCC, ADAM9, FNTA, ACACA, PNMT, and NR1D1) are considered druggable. Low-level CNAs appear to contribute to cancer progression by altering RNA and cellular metabolism.

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer.

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

The investigation into CYP2E1 in relation to the level of response to alcohol through a combination of linkage and association analysis.

BACKGROUND: A low level of response to alcohol during an individual's early experience with alcohol is associated with an increase risk of alcoholism. A family-based genome-wide linkage analysis using sibling pairs that underwent an alcohol challenge where the level of response to alcohol was measured with the Subjective High Assessment Scale (SHAS) implicated the 10q terminal (10qter) region. CYP2E1, a gene known for its involvement with ethanol metabolism, maps to this region. METHODS: Variance component multipoint linkage analysis was performed on a combined map of single-nucleotide polymorphism (SNP) and microsatellite data. To account for the heterogeneity evident in the dataset, a calculation assuming locus heterogeneity was made using the Heterogeneity Log of Odds (HLOD) score. Association between SNP marker allele counts and copy number and SHAS scores were evaluated using a logistic regression model. RESULTS: Linkage analysis detected significant linkage to CYP2E1, which was diminished because of apparent locus heterogeneity traced to a single family with extreme phenotypes. In retrospect, circumstances recorded during testing for this family suggest that their phenotype data are likely to be unreliable. Significant allelic associations were detected for several CYP2E1 polymorphisms and the SHAS score. DNA sequencing from families that contributed the greatest evidence for linkage did not detect any changes directly affecting the primary amino acid sequence. With the removal of a single family, combined evidence from microsatellites and SNPs offers significant linkage between the level of response to alcohol and the region on the end of chromosome 10. CONCLUSION: Combined linkage and association indicate that sequence changes in or near CYP2E1 affect the level of response to alcohol providing a predictor of risk of alcoholism. The absence of coding sequence changes indicates that regulatory sequences are responsible. Implicating CYP2E1 in the level of response to alcohol allows inferences to be made about how the brain perceives alcohol.

The helix-loop-helix Id-1 inhibits PSA expression in prostate cancer cells.

The inhibitor of basic helix-loop-helix transcription factors, Id-1, is an important gene whose expression increases during prostate cancer progression and that upregulates proliferation, migration and invasion. We used microarray analysis to identify the downstream genes whose transcriptional expression is modulated by Id-1 protein. We compared gene expression in control LNCaP cells and Id-1-transduced LNCaP cells, which become significantly more aggressive after Id-1 overexpression, thus mimicking the high levels of Id-1 detected in metastatic cell lines. We used the Affy HTA U133A Expression Arrays with 45,000 probe sets representing more than 39,000 transcripts. We found that one of the most significantly downregulated genes on Id-1 expression was kallikrein 3 [also called prostate specific antigen (PSA)], the most commonly used biomarker of prostate cancer. Here, we show that the reduction in PSA mRNA and protein expression associated with high-grade prostate cancers, which generally express high levels of Id-1, could be the consequence of Id-1 overexpression.

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease.

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3, the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1. Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

Comparative analyses of gene copy number and mRNA expression in glioblastoma multiforme tumors and xenografts.

Development of model systems that recapitulate the molecular heterogeneity observed among glioblastoma multiforme (GBM) tumors will expedite the testing of targeted molecular therapeutic strategies for GBM treatment. In this study, we profiled DNA copy number and mRNA expression in 21 independent GBM tumor lines maintained as subcutaneous xenografts (GBMX), and compared GBMX molecular signatures to those observed in GBM clinical specimens derived from the Cancer Genome Atlas (TCGA). The predominant copy number signature in both tumor groups was defined by chromosome-7 gain/chromosome-10 loss, a poor-prognosis genetic signature. We also observed, at frequencies similar to that detected in TCGA GBM tumors, genomic amplification and overexpression of known GBM oncogenes, such as EGFR, MDM2, CDK6, and MYCN, and novel genes, including NUP107, SLC35E3, MMP1, MMP13, and DDX1. The transcriptional signature of GBMX tumors, which was stable over multiple subcutaneous passages, was defined by overexpression of genes involved in M phase, DNA replication, and chromosome organization (MRC) and was highly similar to the poor-prognosis mitosis and cell-cycle module (MCM) in GBM. Assessment of gene expression in TCGA-derived GBMs revealed overexpression of MRC cancer genes AURKB, BIRC5, CCNB1, CCNB2, CDC2, CDK2, and FOXM1, which form a transcriptional network important for G2/M progression and/or checkpoint activation. Our study supports propagation of GBM tumors as subcutaneous xenografts as a useful approach for sustaining key molecular characteristics of patient tumors, and highlights therapeutic opportunities conferred by this GBMX tumor panel for testing targeted therapeutic strategies for GBM treatment.

A systems analysis of the chemosensitivity of breast cancer cells to the polyamine analogue PG-11047.

BACKGROUND: Polyamines regulate important cellular functions and polyamine dysregulation frequently occurs in cancer. The objective of this study was to use a systems approach to study the relative effects of PG-11047, a polyamine analogue, across breast cancer cells derived from different patients and to identify genetic markers associated with differential cytotoxicity. METHODS: A panel of 48 breast cell lines that mirror many transcriptional and genomic features present in primary human breast tumours were used to study the antiproliferative activity of PG-11047. Sensitive cell lines were further examined for cell cycle distribution and apoptotic response. Cell line responses, quantified by the GI50 (dose required for 50% relative growth inhibition) were correlated with the omic profiles of the cell lines to identify markers that predict response and cellular functions associated with drug sensitivity. RESULTS: The concentrations of PG-11047 needed to inhibit growth of members of the panel of breast cell lines varied over a wide range, with basal-like cell lines being inhibited at lower concentrations than the luminal cell lines. Sensitive cell lines showed a significant decrease in S phase fraction at doses that produced little apoptosis. Correlation of the GI50 values with the omic profiles of the cell lines identified genomic, transcriptional and proteomic variables associated with response. CONCLUSIONS: A 13-gene transcriptional marker set was developed as a predictor of response to PG-11047 that warrants clinical evaluation. Analyses of the pathways, networks and genes associated with response to PG-11047 suggest that response may be influenced by interferon signalling and differential inhibition of aspects of motility and epithelial to mesenchymal transition.

Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells.

Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575-85. ©2017 AACR.

Correction: Decoupling of the PI3K Pathway via Mutation Necessitates Combinatorial Treatment in HER2+ Breast Cancer.

[This corrects the article DOI: 10.1371/journal.pone.0133219.].

Breast tumor copy number aberration phenotypes and genomic instability.

BACKGROUND: Genomic DNA copy number aberrations are frequent in solid tumors, although the underlying causes of chromosomal instability in tumors remain obscure. Genes likely to have genomic instability phenotypes when mutated (e.g. those involved in mitosis, replication, repair, and telomeres) are rarely mutated in chromosomally unstable sporadic tumors, even though such mutations are associated with some heritable cancer prone syndromes. METHODS: We applied array comparative genomic hybridization (CGH) to the analysis of breast tumors. The variation in the levels of genomic instability amongst tumors prompted us to investigate whether alterations in processes/genes involved in maintenance and/or manipulation of the genome were associated with particular types of genomic instability. RESULTS: We discriminated three breast tumor subtypes based on genomic DNA copy number alterations. The subtypes varied with respect to level of genomic instability. We find that shorter telomeres and altered telomere related gene expression are associated with amplification, implicating telomere attrition as a promoter of this type of aberration in breast cancer. On the other hand, the numbers of chromosomal alterations, particularly low level changes, are associated with altered expression of genes in other functional classes (mitosis, cell cycle, DNA replication and repair). Further, although loss of function instability phenotypes have been demonstrated for many of the genes in model systems, we observed enhanced expression of most genes in tumors, indicating that over expression, rather than deficiency underlies instability. CONCLUSION: Many of the genes associated with higher frequency of copy number aberrations are direct targets of E2F, supporting the hypothesis that deregulation of the Rb pathway is a major contributor to chromosomal instability in breast tumors. These observations are consistent with failure to find mutations in sporadic tumors in genes that have roles in maintenance or manipulation of the genome.

Decoupling of the PI3K Pathway via Mutation Necessitates Combinatorial Treatment in HER2+ Breast Cancer.

We report here on experimental and theoretical efforts to determine how best to combine drugs that inhibit HER2 and AKT in HER2(+) breast cancers. We accomplished this by measuring cellular and molecular responses to lapatinib and the AKT inhibitors (AKTi) GSK690693 and GSK2141795 in a panel of 22 HER2(+) breast cancer cell lines carrying wild type or mutant PIK3CA. We observed that combinations of lapatinib plus AKTi were synergistic in HER2(+)/PIK3CA(mut) cell lines but not in HER2(+)/PIK3CA(wt) cell lines. We measured changes in phospho-protein levels in 15 cell lines after treatment with lapatinib, AKTi or lapatinib + AKTi to shed light on the underlying signaling dynamics. This revealed that p-S6RP levels were less well attenuated by lapatinib in HER2(+)/PIK3CA(mut) cells compared to HER2(+)/PIK3CAwt cells and that lapatinib + AKTi reduced p-S6RP levels to those achieved in HER2(+)/PIK3CA(wt) cells with lapatinib alone. We also found that that compensatory up-regulation of p-HER3 and p-HER2 is blunted in PIK3CA(mut) cells following lapatinib + AKTi treatment. Responses of HER2(+) SKBR3 cells transfected with lentiviruses carrying control or PIK3CA(mut )sequences were similar to those observed in HER2(+)/PIK3CA(mut) cell lines but not in HER2(+)/PIK3CA(wt) cell lines. We used a nonlinear ordinary differential equation model to support the idea that PIK3CA mutations act as downstream activators of AKT that blunt lapatinib inhibition of downstream AKT signaling and that the effects of PIK3CA mutations can be countered by combining lapatinib with an AKTi. This combination does not confer substantial benefit beyond lapatinib in HER2+/PIK3CA(wt) cells.

17q-linked frontotemporal dementia-amyotrophic lateral sclerosis without tau mutations with tau and alpha-synuclein inclusions.

BACKGROUND: Frontotemporal dementia (FTD) is a clinically heterogeneous condition that can be associated with clinical manifestations of an extrapyramidal disorder or motor neuron disease. A range of histologic patterns has been described in patients with FTD. The most common familial form of this condition is caused by mutations in the microtubule-associated protein tau gene (MAP tau) and is associated with neuronal or glial tau inclusions. OBJECTIVES: To determine the clinical, anatomic, and pathological features of San Francisco family A and to map the mutation responsible for disease in this family. DESIGN: A systematic clinical, neuropsychologic, neuroimaging, and chromosome segregation analysis of San Francisco family A was performed. A pathological and biochemical assessment of a family member was made. SETTING: Family study. PATIENTS: San Francisco family A, with FTD, variable extrapyramidal symptoms, and prominent motor neuron disease. Afflicted family members do not have a MAP tau coding or splice regulatory sequence mutation, and the MAP tau is genetically excluded. MAIN OUTCOME MEASURES: Comparison of clinical, neuropsychologic, neuroimaging, and linkage findings of San Francisco family A with other familial forms of FTD and amyotrophic lateral sclerosis (ALS). RESULTS: The most probable location for the mutation responsible for this condition is on chromosome arm 17q, distal to the MAP tau. All previously identified susceptibility loci for FTD and ALS are excluded. Autopsy findings from an afflicted family member show distinctive tau and alpha-synuclein inclusions. Another unique feature is that the insoluble tau protein consists predominantly of the 4R/0N isoform. CONCLUSION: The condition affecting members of San Francisco family A is clinically, pathologically, and genetically distinct from previous familial forms of FTD and ALS.

Environmental and genetic determinants of tobacco use: methodology for a multidisciplinary, longitudinal family-based investigation.

This article describes the ongoing collaborative effort of six research teams to operationalize and execute an integrative approach to the study of gene x environment interactions in the development of tobacco dependence. At the core of the project is a longitudinal investigation of social and behavioral risk factors for tobacco use in individuals who were, on average, 13 years of age at intake and for whom smoking outcomes extending from early adolescence to young adulthood have been characterized previously (current average age of the cohort is 29 years). The conceptual framework for the integrative approach and the longitudinal investigation on which the study is based is presented. A description is also provided of the methods used to: (a) recruit participants and families to provide DNA samples and information on tobacco use; (b) assess participants for relevant tobacco-related phenotypes including smoking history, current use of tobacco, and nicotine metabolism; (c) assess the quality of the DNA samples collected from participants for genome-wide scanning and candidate gene analysis; (d) examine several research questions concerning the role of genetic and environmental factors in the onset and maintenance of tobacco use; and (e) ensure adherence to local and federal guidelines for ethical and legal investigations of genotypic associations with tobacco-related phenotypes in families. This investigation is unique among ongoing studies of the genetics of tobacco dependence in the extent to which equal importance has been assigned to both phenotypic and genotypic measurements.

Genome-wide linkage scan of antisocial behavior, depression, and impulsive substance use in the UCSF family alcoholism study.

OBJECTIVE: Epidemiological and clinical studies suggest that the rates of antisocial behavior, depression, and impulsive substance use are increased among individuals diagnosed with alcohol dependence relative to those who are not. Thus, the present study conducted genome-wide linkage scans of antisocial behavior, depression, and impulsive substance use in the University of California at San Francisco Family Alcoholism Study. METHODS: Antisocial behavior, depressive symptoms, and impulsive substance use were assessed using three scales from the Minnesota Multiphasic Personality Inventory - 2nd ed.: the Antisocial Practices content scale, the Depression content scale, and the revised MacAndrew Alcoholism scale. Linkage analyses were carried out using a variance components approach. RESULTS: Suggestive evidence of linkage to three genomic regions independent of alcohol and cannabis dependence diagnostic status was observed: the Antisocial Practices content scale showed evidence of linkage to chromosome 13 at 11 cM, the MacAndrew Alcoholism scale showed evidence of linkage to chromosome 15 at 47 cM, and all three scales showed evidence of linkage to chromosome 17 at 57-58 cM. CONCLUSION: Each of these regions has shown previous evidence of linkage and association to substance dependence as well as other psychiatric disorders such as mood and anxiety disorders, attention-deficit hyperactivity disorder, and schizophrenia, thus suggesting potentially broad relations between these regions and psychopathology.

Linkage scan of alcohol dependence in the UCSF Family Alcoholism Study.

Ample data suggest that alcohol dependence represents a heritable condition, and several research groups have performed linkage analysis to identify genomic regions influencing this disorder. In the present study, a genome-wide linkage scan for alcohol dependence was conducted in a community sample of 565 probands and 1080 first-degree relatives recruited through the UCSF Family Alcoholism Study. The Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) was used to derive DSM-IV alcohol dependence diagnoses. Although no loci achieved genome-wide significance (i.e., LOD score > 3.0), several linkage peaks of interest (i.e., LOD score > 1.0) were identified. When the strict DSM-IV alcohol dependence diagnosis requiring the temporal clustering of symptoms served as the phenotype, linkage peaks were identified on chromosomes 1p36.31-p36.22, 2q37.3, 8q24.3, and 18p11.21-p11.2. When the temporal clustering of symptoms was not required, linkage peaks were again identified on chromosomes 1p36.31-p36.22 and 8q24.3 as well as novel loci on chromosomes 1p22.3, 2p24.3-p24.1, 9p24.1-p23, and 22q12.3-q13.1. Follow-up analyses were conducted by performing linkage analysis for the 12 alcohol dependence symptoms assessed by the SSAGA across the support intervals for the observed linkage peaks. These analyses demonstrated that different collections of symptoms often assessing distinct aspects of alcohol dependence (e.g., uncontrollable drinking and withdrawal vs. tolerance and drinking despite health problems) contributed to each linkage peak and often yielded LOD scores exceeding that reported for the alcohol dependence diagnosis. Such findings provide insight into how specific genomic regions may influence distinct aspects of alcohol dependence.

Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy.

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease. Overall survival is typically 6 months from diagnosis. Numerous phase 3 trials of agents effective in other malignancies have failed to benefit unselected PDA populations, although patients do occasionally respond. Studies in other solid tumors have shown that heterogeneity in response is determined, in part, by molecular differences between tumors. Furthermore, treatment outcomes are improved by targeting drugs to tumor subtypes in which they are selectively effective, with breast and lung cancers providing recent examples. Identification of PDA molecular subtypes has been frustrated by a paucity of tumor specimens available for study. We have overcome this problem by combined analysis of transcriptional profiles of primary PDA samples from several studies, along with human and mouse PDA cell lines. We define three PDA subtypes: classical, quasimesenchymal and exocrine-like, and we present evidence for clinical outcome and therapeutic response differences between them. We further define gene signatures for these subtypes that may have utility in stratifying patients for treatment and present preclinical model systems that may be used to identify new subtype specific therapies.