The m6A RNA demethylase FTO is a HIF-independent synthetic lethal partner with the VHL tumor suppressor.

Loss of the von Hippel-Lindau (VHL) tumor suppressor is a hallmark feature of renal clear cell carcinoma. VHL inactivation results in the constitutive activation of the hypoxia-inducible factors (HIFs) HIF-1 and HIF-2 and their downstream targets, including the proangiogenic factors VEGF and PDGF. However, antiangiogenic agents and HIF-2 inhibitors have limited efficacy in cancer therapy due to the development of resistance. Here we employed an innovative computational platform, Mining of Synthetic Lethals (MiSL), to identify synthetic lethal interactions with the loss of VHL through analysis of primary tumor genomic and transcriptomic data. Using this approach, we identified a synthetic lethal interaction between VHL and the m6A RNA demethylase FTO in renal cell carcinoma. MiSL identified FTO as a synthetic lethal partner of VHL because deletions of FTO are mutually exclusive with VHL loss in pan cancer datasets. Moreover, FTO expression is increased in VHL-deficient ccRCC tumors compared to normal adjacent tissue. Genetic inactivation of FTO using multiple orthogonal approaches revealed that FTO inhibition selectively reduces the growth and survival of VHL-deficient cells in vitro and in vivo. Notably, FTO inhibition reduced the survival of both HIF wild type and HIF-deficient tumors, identifying FTO as an HIF-independent vulnerability of VHL-deficient cancers. Integrated analysis of transcriptome-wide m6A-seq and mRNA-seq analysis identified the glutamine transporter SLC1A5 as an FTO target that promotes metabolic reprogramming and survival of VHL-deficient ccRCC cells. These findings identify FTO as a potential HIF-independent therapeutic target for the treatment of VHL-deficient renal cell carcinoma.

Mebendazole for Differentiation Therapy of Acute Myeloid Leukemia Identified by a Lineage Maturation Index.

Accurate assessment of changes in cellular differentiation status in response to drug treatments or genetic perturbations is crucial for understanding tumorigenesis and developing novel therapeutics for human cancer. We have developed a novel computational approach, the Lineage Maturation Index (LMI), to define the changes in differentiation state of hematopoietic malignancies based on their gene expression profiles. We have confirmed that the LMI approach can detect known changes of differentiation state in both normal and malignant hematopoietic cells. To discover novel differentiation therapies, we applied this approach to analyze the gene expression profiles of HL-60 leukemia cells treated with a small molecule drug library. Among multiple drugs that significantly increased the LMIs, we identified mebendazole, an anti-helminthic clinically used for decades with no known significant toxicity. We tested the differentiation activity of mebendazole using primary leukemia blast cells isolated from human acute myeloid leukemia (AML) patients. We determined that treatment with mebendazole induces dramatic differentiation of leukemia blast cells as shown by cellular morphology and cell surface markers. Furthermore, mebendazole treatment significantly extended the survival of leukemia-bearing mice in a xenograft model. These findings suggest that mebendazole may be utilized as a low toxicity therapeutic for human acute myeloid leukemia and confirm the LMI approach as a robust tool for the discovery of novel differentiation therapies for cancer.

Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data.

Two genes are synthetically lethal (SL) when defects in both are lethal to a cell but a single defect is non-lethal. SL partners of cancer mutations are of great interest as pharmacological targets; however, identifying them by cell line-based methods is challenging. Here we develop MiSL (Mining Synthetic Lethals), an algorithm that mines pan-cancer human primary tumour data to identify mutation-specific SL partners for specific cancers. We apply MiSL to 12 different cancers and predict 145,891 SL partners for 3,120 mutations, including known mutation-specific SL partners. Comparisons with functional screens show that MiSL predictions are enriched for SLs in multiple cancers. We extensively validate a SL interaction identified by MiSL between the IDH1 mutation and ACACA in leukaemia using gene targeting and patient-derived xenografts. Furthermore, we apply MiSL to pinpoint genetic biomarkers for drug sensitivity. These results demonstrate that MiSL can accelerate precision oncology by identifying mutation-specific targets and biomarkers.

A geographically-diverse collection of 418 human gut microbiome pathway genome databases.

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn's disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.

A Pharmacogenetic Discovery: Cystamine Protects Against Haloperidol-Induced Toxicity and Ischemic Brain Injury.

Haloperidol is an effective antipsychotic agent, but it causes Parkinsonian-like extrapyramidal symptoms in the majority of treated subjects. To address this treatment-limiting toxicity, we analyzed a murine genetic model of haloperidol-induced toxicity (HIT). Analysis of a panel of consomic strains indicated that a genetic factor on chromosome 10 had a significant effect on susceptibility to HIT. We analyzed a whole-genome SNP database to identify allelic variants that were uniquely present on chromosome 10 in the strain that was previously shown to exhibit the highest level of susceptibility to HIT. This analysis implicated allelic variation within pantetheinase genes (Vnn1 and Vnn3), which we propose impaired the biosynthesis of cysteamine, could affect susceptibility to HIT. We demonstrate that administration of cystamine, which is rapidly metabolized to cysteamine, could completely prevent HIT in the murine model. Many of the haloperidol-induced gene expression changes in the striatum of the susceptible strain were reversed by cystamine coadministration. Since cystamine administration has previously been shown to have other neuroprotective actions, we investigated whether cystamine administration could have a broader neuroprotective effect. Cystamine administration caused a 23% reduction in infarct volume after experimentally induced cerebral ischemia. Characterization of this novel pharmacogenetic factor for HIT has identified a new approach for preventing the treatment-limiting toxicity of an antipsychotic agent, which could also be used to reduce the extent of brain damage after stroke.

Mutant WT1 is associated with DNA hypermethylation of PRC2 targets in AML and responds to EZH2 inhibition.

Acute myeloid leukemia (AML) is associated with deregulation of DNA methylation; however, many cases do not bear mutations in known regulators of cytosine guanine dinucleotide (CpG) methylation. We found that mutations in WT1, IDH2, and CEBPA were strongly linked to DNA hypermethylation in AML using a novel integrative analysis of The Cancer Genome Atlas data based on Boolean implications, if-then rules that identify all individual CpG sites that are hypermethylated in the presence of a mutation. Introduction of mutant WT1 (WT1mut) into wild-type AML cells induced DNA hypermethylation, confirming mutant WT1 to be causally associated with DNA hypermethylation. Methylated genes in WT1mut primary patient samples were highly enriched for polycomb repressor complex 2 (PRC2) targets, implicating PRC2 dysregulation in WT1mut leukemogenesis. We found that PRC2 target genes were aberrantly repressed in WT1mut AML, and that expression of mutant WT1 in CD34(+) cord blood cells induced myeloid differentiation block. Treatment of WT1mut AML cells with short hairpin RNA or pharmacologic PRC2/enhancer of zeste homolog 2 (EZH2) inhibitors promoted myeloid differentiation, suggesting EZH2 inhibitors may be active in this AML subtype. Our results highlight a strong association between mutant WT1 and DNA hypermethylation in AML and demonstrate that Boolean implications can be used to decipher mutation-specific methylation patterns that may lead to therapeutic insights.

MYC through miR-17-92 suppresses specific target genes to maintain survival, autonomous proliferation, and a neoplastic state.

The MYC oncogene regulates gene expression through multiple mechanisms, and its overexpression culminates in tumorigenesis. MYC inactivation reverses turmorigenesis through the loss of distinguishing features of cancer, including autonomous proliferation and survival. Here we report that MYC via miR-17-92 maintains a neoplastic state through the suppression of chromatin regulatory genes Sin3b, Hbp1, Suv420h1, and Btg1, as well as the apoptosis regulator Bim. The enforced expression of miR-17-92 prevents MYC suppression from inducing proliferative arrest, senescence, and apoptosis and abrogates sustained tumor regression. Knockdown of the five miR-17-92 target genes blocks senescence and apoptosis while it modestly delays proliferative arrest, thus partially recapitulating miR-17-92 function. We conclude that MYC, via miR-17-92, maintains a neoplastic state by suppressing specific target genes.

Mining TCGA data using Boolean implications.

Boolean implications (if-then rules) provide a conceptually simple, uniform and highly scalable way to find associations between pairs of random variables. In this paper, we propose to use Boolean implications to find relationships between variables of different data types (mutation, copy number alteration, DNA methylation and gene expression) from the glioblastoma (GBM) and ovarian serous cystadenoma (OV) data sets from The Cancer Genome Atlas (TCGA). We find hundreds of thousands of Boolean implications from these data sets. A direct comparison of the relationships found by Boolean implications and those found by commonly used methods for mining associations show that existing methods would miss relationships found by Boolean implications. Furthermore, many relationships exposed by Boolean implications reflect important aspects of cancer biology. Examples of our findings include cis relationships between copy number alteration, DNA methylation and expression of genes, a new hierarchy of mutations and recurrent copy number alterations, loss-of-heterozygosity of well-known tumor suppressors, and the hypermethylation phenotype associated with IDH1 mutations in GBM. The Boolean implication results used in the paper can be accessed at http://crookneck.stanford.edu/microarray/TCGANetworks/.

Liquid chromatography/mass spectrometry methods for measuring dipeptide abundance in non-small-cell lung cancer.

RATIONALE: Metabolomic profiling is a promising methodology of identifying candidate biomarkers for disease detection and monitoring. Although lung cancer is among the leading causes of cancer-related mortality worldwide, the lung tumor metabolome has not been fully characterized. METHODS: We utilized a targeted metabolomic approach to analyze discrete groups of related metabolites. We adopted a dansyl [5-(dimethylamino)-1-naphthalene sulfonamide] derivatization with liquid chromatography/mass spectrometry (LC/MS) to analyze changes of metabolites from paired tumor and normal lung tissues. Identification of dansylated dipeptides was confirmed with synthetic standards. A systematic analysis of retention times was required to reliably identify isobaric dipeptides. We validated our findings in a separate sample cohort. RESULTS: We produced a database of the LC retention times and MS/MS spectra of 361 dansyl dipeptides. Interpretation of the spectra is presented. Using this standard data, we identified a total of 279 dipeptides in lung tumor tissue. The abundance of 90 dipeptides was selectively increased in lung tumor tissue compared to normal tissue. In a second set of validation tissues, 12 dipeptides were selectively increased. CONCLUSIONS: A systematic evaluation of certain metabolite classes in lung tumors may identify promising disease-specific metabolites. Our database of all possible dipeptides will facilitate ongoing translational applications of metabolomic profiling as it relates to lung cancer.

Gene Expression Commons: an open platform for absolute gene expression profiling.

Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

Temporal changes in gene expression induced by sulforaphane in human prostate cancer cells.

BACKGROUND: Prostate cancer is thought to arise as a result of oxidative stresses and induction of antioxidant electrophile defense (phase 2) enzymes has been proposed as a prostate cancer prevention strategy. The isothiocyanate sulforaphane, derived from cruciferous vegetables like broccoli, potently induces surrogate markers of phase 2 enzyme activity in prostate cells in vitro and in vivo. To better understand the temporal effects of sulforaphane and broccoli sprouts on gene expression in prostate cells, we carried out comprehensive transcriptome analysis using cDNA microarrays. METHODS: Transcripts significantly modulated by sulforaphane over time were identified using StepMiner analysis. Ingenuity Pathway Analysis (IPA) was used to identify biological pathways, networks, and functions significantly altered by sulforaphane treatment. RESULTS: StepMiner and IPA revealed significant changes in many transcripts associated with cell growth and cell cycle, as well as a significant number associated with cellular response to oxidative damage and stress. Comparison to an existing dataset suggested that sulforaphane blocked cell growth by inducing G2/M arrest. Cell growth assays and flow cytometry analysis confirmed that sulforaphane inhibited cell growth and induced cell cycle arrest. CONCLUSIONS: Our data suggest that in prostate cells sulforaphane primarily induces cellular defenses and inhibits cell growth by causing G2/M phase arrest. Furthermore, based on the striking similarities in the gene expression patterns induced across experiments in these cells, sulforaphane appears to be the primary bioactive compound present in broccoli sprouts, suggesting that broccoli sprouts can serve as a suitable source for sulforaphane in intervention trials.

Combined analysis of murine and human microarrays and ChIP analysis reveals genes associated with the ability of MYC to maintain tumorigenesis.

The MYC oncogene has been implicated in the regulation of up to thousands of genes involved in many cellular programs including proliferation, growth, differentiation, self-renewal, and apoptosis. MYC is thought to induce cancer through an exaggerated effect on these physiologic programs. Which of these genes are responsible for the ability of MYC to initiate and/or maintain tumorigenesis is not clear. Previously, we have shown that upon brief MYC inactivation, some tumors undergo sustained regression. Here we demonstrate that upon MYC inactivation there are global permanent changes in gene expression detected by microarray analysis. By applying StepMiner analysis, we identified genes whose expression most strongly correlated with the ability of MYC to induce a neoplastic state. Notably, genes were identified that exhibited permanent changes in mRNA expression upon MYC inactivation. Importantly, permanent changes in gene expression could be shown by chromatin immunoprecipitation (ChIP) to be associated with permanent changes in the ability of MYC to bind to the promoter regions. Our list of candidate genes associated with tumor maintenance was further refined by comparing our analysis with other published results to generate a gene signature associated with MYC-induced tumorigenesis in mice. To validate the role of gene signatures associated with MYC in human tumorigenesis, we examined the expression of human homologs in 273 published human lymphoma microarray datasets in Affymetrix U133A format. One large functional group of these genes included the ribosomal structural proteins. In addition, we identified a group of genes involved in a diverse array of cellular functions including: BZW2, H2AFY, SFRS3, NAP1L1, NOLA2, UBE2D2, CCNG1, LIFR, FABP3, and EDG1. Hence, through our analysis of gene expression in murine tumor models and human lymphomas, we have identified a novel gene signature correlated with the ability of MYC to maintain tumorigenesis.