The genetic events responsible for tumor aggressiveness in endometrioid endometrial cancer (EEC) remain poorly understood. The chromosome 16q22 tumor suppressor genes CTCF and ZFHX3 are both frequently mutated in EEC, but their respective roles in outcome have not been determined.
Targeted deep sequencing of CTCF and ZFHX3 was performed for 542 EEC samples. Copy number loss (CNL) was determined using microsatellite typing of paired tumor and normal DNA and a novel Bayesian method based on variant allele frequencies of germline polymorphisms. All statistical tests were two-sided.
Mutation rates for CTCF and ZFHX3 were 25.3% and 20.4%, respectively, and there was a statistically significant excess of tumors with mutation in both genes (P = .003). CNL rates were 17.4% for CTCF and 17.2% for ZFHX3, and the majority of CNLs included both CTCF and ZFHX3. Mutations were more frequent in tumors with microsatellite instability, and CNLs were more common in microsatellite-stable tumors (P < .001). Patients with ZFHX3 mutation and/or CNL had higher-grade tumors (P = .001), were older (P < .001), and tended to have more frequent lymphovascular space invasion (P = .07). These patients had reduced recurrence-free and overall survival (RFS: hazard ratio [HR] = 2.35, 95% confidence interval [CI] = 1.38 to 3.99, P = .007; OS: HR = 1.51, 95% CI = 1.11 to 2.07, P = .04).
Our data demonstrate there is strong selection for inactivation of both CTCF and ZFHX3 in EEC. Mutation occurs at high frequency in microsatellite-unstable tumors, whereas CNLs are common in microsatellite-stable cancers. Loss of these two tumor suppressors is a frequent event in endometrial tumorigenesis, and ZFHX3 defects are associated with poor outcome.
The mutational profile of non-small cell lung cancer (NSCLC) has become an important tool in tailoring therapy to patients, with clear differences according to the population of origin. African Americans have higher lung cancer incidence and mortality than Caucasians, yet discrepant results have been reported regarding the frequency of somatic driver mutations. We hypothesized that NSCLC has a distinct mutational profile in this group.
We collected NSCLC samples resected from self-reported African Americans in five sites from Tennessee, Michigan, and Ohio. Gene mutations were assessed by either SNaPshot or next generation sequencing, and ALK translocations were evaluated by fluorescence in situ hybridization.
Two hundred sixty patients were included, mostly males (62.3%) and smokers (86.6%). Eighty-one samples (31.2%) were squamous cell carcinomas. The most frequently mutated genes were KRAS (15.4%), EGFR (5.0%), PIK3CA (0.8%), BRAF, NRAS, ERBB2, and AKT1 (0.4% each). ALK translocations were detected in 2 non-squamous tumors (1.7%), totaling 61 cases (23.5%) with driver oncogenic alterations. Among 179 non-squamous samples, 54 (30.2%) presented a driver alteration. The frequency of driver alterations altogether was lower than that reported in Caucasians, while no difference was detected in either EGFR or KRAS mutations. Overall survival was longer among patients with EGFR mutations.
We demonstrated that NSCLC from African Americans has a different pattern of somatic driver mutations than from Caucasians. The majority of driver alterations in this group are yet to be described, which will require more comprehensive panels and assessment of non-canonical alterations.
lung neoplasms; mutations; EGFR; African Americans; ethnic groups
The epidermal growth factor receptor (EGFR) inhibitor erlotinib has been shown to induce complete remission of acute myeloid leukemia (AML) in two patients with concurrent lung cancer and raised attention for a role of EGFR in AML whereas a recent phase II clinical study with gefitinib in AML demonstrated a negative result on the outcome. However, from several studies, EGFR expression in AML is poorly defined and the role of EGFR in AML remains unclear. Herein, we report the results of EGFR expression in AML of large cohorts of adult and pediatric AML patients with the data of total protein and phosphorylation levels of EGFR. Our data conclude that there is the expression of EGFR at the protein level in a subset of AML, which was identified to be functionally active in ~15 % of AML patients. This suggests that future studies need to be conducted with a subset of AML patients characterized by high EGFR expression.
Electronic supplementary material
The online version of this article (doi:10.1186/s13045-016-0294-x) contains supplementary material, which is available to authorized users.
EGFR; AML; RPPA; Kinome; Leukemia
Acute myeloid leukemia (AML) is a heterogenous disease with differential oncogene association, outcome and treatment regimens. Treatment strategies for AML have improved outcome but despite increased molecular biological information AML is still associated with poor prognosis. Proteomic analysis on the effects of a range of leukemogenic oncogenes showed that the protein transglutaminase 2 (TG2) is expressed at greater levels as a consequence of oncogenic transformation. Further analysis of this observation was performed with 511 AML samples using reverse phase proteomic arrays, demonstrating that TG2 expression was higher at relapse than diagnosis in many cases. In addition elevated TG2 expression correlated with increased expression of numerous adhesion proteins and many apoptosis regulating proteins, two processes related to leukemogenesis. TG2 has previously been linked to drug resistance in cancer and given the negative correlation between TG2 levels and peripheral blasts observed increased TG2 levels may lead to the protection of the leukemic stem cell due to increased adhesion/reduced motility. TG2 may therefore form part of a network of proteins that define poor outcome in AML patients and potentially offer a target to sensitize AML stem cells to drug treatment.
Acute myeloid leukemia; Biomedicine; Reverse phase protein array; Transglutaminase2
Acalabrutinib (ACP-196) is a second-generation inhibitor of Bruton agammaglobulinemia tyrosine kinase (BTK) with increased target selectivity and potency compared to ibrutinib. In this study, we evaluated acalabrutinib in spontaneously occurring canine lymphoma, a model of B-cell malignancy similar to human diffuse large B-cell lymphoma (DLBCL). First, we demonstrated that acalabrutinib potently inhibited BTK activity and downstream effectors in CLBL1, a canine B-cell lymphoma cell line, and primary canine lymphoma cells. Acalabrutinib also inhibited proliferation in CLBL1 cells. Twenty dogs were enrolled in the clinical trial and treated with acalabrutinib at dosages of 2.5 to 20mg/kg every 12 or 24 hours. Acalabrutinib was generally well tolerated, with adverse events consisting primarily of grade 1 or 2 anorexia, weight loss, vomiting, diarrhea and lethargy. Overall response rate (ORR) was 25% (5/20) with a median progression free survival (PFS) of 22.5 days. Clinical benefit was observed in 30% (6/20) of dogs. These findings suggest that acalabrutinib is safe and exhibits activity in canine B-cell lymphoma patients and support the use of canine lymphoma as a relevant model for human non-Hodgkin lymphoma (NHL).
Technologic advances have enabled the comprehensive analysis of genetic perturbations in non–small-cell lung cancer (NSCLC); however, African Americans have often been underrepresented in these studies. This ethnic group has higher lung cancer incidence and mortality rates, and some studies have suggested a lower incidence of epidermal growth factor receptor mutations. Herein, we report the most in-depth molecular profile of NSCLC in African Americans to date.
A custom panel was designed to cover the coding regions of 81 NSCLC-related genes and 40 ancestry-informative markers. Clinical samples were sequenced on a massively parallel sequencing instrument, and anaplastic lymphoma kinase translocation was evaluated by fluorescent in situ hybridization.
The study cohort included 99 patients (61% males, 94% smokers) comprising 31 squamous and 68 nonsquamous cell carcinomas. We detected 227 nonsilent variants in the coding sequence, including 24 samples with nonoverlapping, classic driver alterations. The frequency of driver mutations was not significantly different from that of whites, and no association was found between genetic ancestry and the presence of somatic mutations. Copy number alteration analysis disclosed distinguishable amplifications in the 3q chromosome arm in squamous cell carcinomas and pointed toward a handful of targetable alterations. We also found frequent SMARCA4 mutations and protein loss, mostly in driver-negative tumors.
Our data suggest that African American ancestry may not be significantly different from European/white background for the presence of somatic driver mutations in NSCLC. Furthermore, we demonstrated that using a comprehensive genotyping approach could identify numerous targetable alterations, with potential impact on therapeutic decisions.
Motivation: Nonlinear dose–response models are primary tools for estimating the potency [e.g. half-maximum inhibitory concentration (IC) known as IC50] of anti-cancer drugs. We present drexplorer software, which enables biologists to evaluate replicate reproducibility, detect outlier data points, fit different models, select the best model, estimate IC values at different percentiles and assess drug–drug interactions. drexplorer serves as a computation engine within the R environment and a graphical interface for users who do not have programming backgrounds.
Availability and implementation: The drexplorer R package is freely available from GitHub at https://github.com/nickytong/drexplorer. A graphical user interface is shipped with the package.
Supplementary data are available at Bioinformatics online.
With increasing use of publicly available gene expression data sets, the quality of the expression data is a critical issue for downstream analysis, gene signature development, and cross-validation of data sets. Thus, identifying reliable expression measurements by leveraging multiple mRNA expression platforms is an important analytical task. In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression levels using a beta-mixture model. The model-based selection provides an effective and objective way to separate good probes from probes with low quality, thereby improving the efficiency and accuracy of the analysis. The proposed method can be used to compare two microarray technologies or microarray and RNA sequencing measurements. We tested the approach in two matched profiling data sets, using microarray gene expression measurements from the same samples profiled on both Affymetrix and Illumina platforms. We also applied the algorithm to mRNA expression data to compare Affymetrix microarray data with RNA sequencing measurements. The algorithm successfully identified probes/genes with reliable measurements. Removing the unreliable measurements resulted in significant improvements for gene signature development and functional annotations.
beta-mixture model; correlation coefficients; cross-validation; gene expression; probe selection; RNA sequence
Motivation: High-throughput reverse-phase protein array (RPPA) technology allows for the parallel measurement of protein expression levels in approximately 1000 samples. However, the many steps required in the complex protocol (sample lysate preparation, slide printing, hybridization, washing and amplified detection) may create substantial variability in data quality. We are not aware of any other quality control algorithm that is tuned to the special characteristics of RPPAs.
Results: We have developed a novel classifier for quality control of RPPA experiments using a generalized linear model and logistic function. The outcome of the classifier, ranging from 0 to 1, is defined as the probability that a slide is of good quality. After training, we tested the classifier using two independent validation datasets. We conclude that the classifier can distinguish RPPA slides of good quality from those of poor quality sufficiently well such that normalization schemes, protein expression patterns and advanced biological analyses will not be drastically impacted by erroneous measurements or systematic variations.
Availability and implementation: The classifier, implemented in the “SuperCurve” R package, can be freely downloaded at http://bioinformatics.mdanderson.org/main/OOMPA:Overview or http://r-forge.r-project.org/projects/supercurve/. The data used to develop and validate the classifier are available at http://bioinformatics.mdanderson.org/MOAR.
Supplementary data are available at Bioinformatics online.
The molecular underpinnings that drive the heterogeneity of KRAS-mutant lung adenocarcinoma (LUAC) are poorly characterized. We performed an integrative analysis of genomic, transcriptomic and proteomic data from early-stage and chemo-refractory LUAC and identified three robust subsets of KRAS-mutant LUAC dominated, respectively, by co-occurring genetic events in STK11/LKB1 (the KL subgroup), TP53 (KP) and CDKN2A/B inactivation coupled with low expression of the NKX2-1 (TTF1) transcription factor (KC). We further reveal biologically and therapeutically relevant differences between the subgroups. KC tumors frequently exhibited mucinous histology and suppressed mTORC1 signaling. KL tumors had high rates of KEAP1 mutational inactivation and expressed lower levels of immune markers, including PD-L1. KP tumors demonstrated higher levels of somatic mutations, inflammatory markers, immune checkpoint effector molecules and improved relapse-free survival. Differences in drug sensitivity patterns were also observed; notably, KL cells showed increased vulnerability to HSP90-inhibitor therapy. This work provides evidence that co-occurring genomic alterations identify subgroups of KRAS-mutant LUAC with distinct biology and therapeutic vulnerabilities.
KRAS; co-mutations; lung adenocarcinoma; STK11; HSP90
Targeted therapies designed to exploit specific molecular pathways in aggressive cancers are an exciting area of current research. Mixed Lineage Leukemia (MLL) mutations such as the t(4;11) translocation cause aggressive leukemias that are refractory to conventional treatment. The t(4;11) translocation produces an MLL/AF4 fusion protein that activates key target genes through both epigenetic and transcriptional elongation mechanisms. In this study, we show that t(4;11) patient cells express high levels of BCL-2 and are highly sensitive to treatment with the BCL-2-specific BH3 mimetic ABT-199. We demonstrate that MLL/AF4 specifically upregulates the BCL-2 gene but not other BCL-2 family members via DOT1L-mediated H3K79me2/3. We use this information to show that a t(4;11) cell line is sensitive to a combination of ABT-199 and DOT1L inhibitors. In addition, ABT-199 synergizes with standard induction-type therapy in a xenotransplant model, advocating for the introduction of ABT-199 into therapeutic regimens for MLL-rearranged leukemias.
•MLLr ALL blasts express high levels of BCL-2, BAX, and BIM•MLL/AF4 activates BCL2 through H3K79 methylation•MLLr ALL cells are exquisitely sensitive to BCL-2 antagonist ABT-199•ABT-199 treatment synergizes with H3K79 methylation inhibitors on MLLr samples
Therapies designed to exploit specific molecular pathways in aggressive cancers are an exciting area of research. Mutations in the MLL gene cause aggressive incurable leukemias. Benito et al. show that MLL leukemias are highly sensitive to BCL-2 inhibitors, especially when combined with drugs that target mutant MLL complex activity.
apoptosis pathways; leukemias; bcl-2 family members; MLL/AF4; DOT1L; H3K79 methylation
Increased availability of multi-platform genomics data on matched samples has sparked research efforts to discover how diverse molecular features interact both within and between platforms. In addition, simultaneous measurements of genetic and epigenetic characteristics illuminate the roles their complex relationships play in disease progression and outcomes. However, integrative methods for diverse genomics data are faced with the challenges of ultra-high dimensionality and the existence of complex interactions both within and between platforms.
We propose a novel modeling framework for integrative analysis based on decompositions of the large number of platform-specific features into a smaller number of latent features. Subsequently we build a predictive model for clinical outcomes accounting for both within- and between-platform interactions based on Bayesian model averaging procedures. Principal components, partial least squares and non-negative matrix factorization as well as sparse counterparts of each are used to define the latent features, and the performance of these decompositions is compared both on real and simulated data. The latent feature interactions are shown to preserve interactions between the original features and not only aid prediction but also allow explicit selection of outcome-related features. The methods are motivated by and applied to, a glioblastoma multiforme dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, microRNA, copy number and methylation data.
For the glioblastoma data, we find a high concordance between our selected prognostic genes and genes with known associations with glioblastoma. In addition, our model discovers several relevant cross-platform interactions such as copy number variation associated gene dosing and epigenetic regulation through promoter methylation. On simulated data, we show that our proposed method successfully incorporates interactions within and between genomic platforms to aid accurate prediction and variable selection. Our methods perform best when principal components are used to define the latent features.
Latent feature; genomic data; high-dimensional; interactions; integrative models; Bayesian model averaging
Studying mechanisms of malignant transformation of human pre-B cells, we found that acute activation of oncogenes induced immediate cell death in the vast majority of cells. Few surviving pre-B cell clones had acquired permissiveness to oncogenic signaling by strong activation of negative feedback regulation of Erk signaling. Studying negative feedback regulation of Erk in genetic experiments at three different levels, we found that Spry2, Dusp6 and Etv5 were essential for oncogenic transformation in mouse models for pre-B acute lymphoblastic leukemia (ALL). Interestingly, a small molecule inhibitor of DUSP6 selectively induced cell death in patient-derived pre-B ALL cells and overcame conventional mechanisms of drug-resistance.
TRIM62 is a putative tumor suppressor gene. We investigated the levels of expression of TRIM62 protein in 511 patients with acute myeloid leukemia (AML) by reverse-phase protein array technology. Low TRIM62 levels were associated with markedly poorer outcomes and improved the prognostic impact of NPM1 and FLT3 mutations. Low TRIM62 levels, therefore, is an independent adverse prognostic factor in AML.
Tripartite motif (TRIM)-62 is a putative tumor suppressor gene whose role in leukemia is unknown.
Materials and Methods
We evaluated the effect of TRIM62 protein expression in patients with acute myeloid leukemia (AML). We used reverse-phase protein array methodology to determine TRIM62 levels in leukemia-enriched protein samples from 511 patients newly diagnosed with AML.
TRIM62 levels in AML cells were significantly lower than in normal CD34-positive cells, suggesting that TRIM62 loss might be involved in leukemogenesis, but was not associated with specific karyotypic abnormalities or Nucleophosmin (NPM1), Fms-like Tyrosine Kinase-3 (FLT3), or rat sarcoma viral oncogene (RAS) mutational status. Low TRIM62 levels were associated with shorter complete remission duration and significantly shorter event-free and overall survival rates, particularly among patients with intermediate-risk cytogenetics. In that AML subgroup, age and TRIM62 levels were the most powerful independent prognostic factors for survival. TRIM62 protein levels further refined the risk associated with NPM1 and FLT3 mutational status. TRIM62 loss was associated with altered expression of proteins involved in leukemia stem cell homeostasis (β-catenin and Notch), cell motility, and adhesion (integrin-β3, ras-related C3 botulinum toxin substrate [RAC], and fibronectin), hypoxia (Hypoxia-inducible factor 1-alpha [HIF1α], egl-9 family hypoxia-inducible factor 1 [Egln1], and glucose-regulated protein, 78kDa [GRP78]), and apoptosis (B-cell lymphoma-extra large (BclXL) and caspase 9).
Low TRIM62 levels, consistent with a tumor suppressor role, represent an independent adverse prognostic factor in AML.
AML; Proteomics; Reverse phase protein array; RPPA; TRIM62
We recently discovered that the protein phosphatase 2A (PP2A) B55α subunit (PPP2R2A) is under-expressed in primary blast cells and is unfavorable for remission duration in AML patients. In this study, reverse phase protein analysis (RPPA) of 230 proteins in 511 AML patient samples revealed a strong correlation of B55α with a number of proteins including MYC, PKC α, and SRC. B55α suppression in OCI-AML3 cells by shRNA demonstrated that the B subunit is a PKCα phosphatase. B55α does not target SRC, but rather the kinase suppresses protein expression of the B subunit. Finally, the correlation between B55α and MYC levels reflected a complex stoichiometric competition between B subunits. Loss of B55α in OCI-AML3 cells did not change global PP2A activity and the only isoform that is induced is the one containing B56α. In cells containing B55α shRNA, MYC was suppressed with concomitant induction of the competing B subunit B56α (PPP2R5A). A recent study determined that FTY-720, a drug whose action involves the activation of PP2A, resulted in the induction of B55α In AML cells, and a reduction of the B subunit rendered these cells resistant to FTY-720. Finally, reduction of the B subunit resulted in an increase in the expression of miR-191-5p and a suppression of miR-142-3p. B55α regulation of these miRs was intriguing as high levels of miR-191 portend poor survival in AML, and miR-142-3p is mutated in 2% of AML patient samples. In summary, the suppression of B55α activates signaling pathways that could support leukemia cell survival.
B55α; AML; Relapse; Cell signaling; miR-142; miR-191
Leukemias are well suited to proteomic profiling by RPPA due to the ready accessibility of blasts from the blood or marrow. In this review, we review methodological and procedural issues that affect the quality of RPPA data. We recommend contact printers that minimize sample quantities and evaporation and maximize sample per slide. The impact of sample selection and handling is reviewed as well. Protein is best prepared fresh on the date of acquisition as cryopreservation changes protein expression levels in some diseases. Rapid processing is also required to avoid changes in phosphorylation over time. Sample source, blood vs. marrow does not seem to affect results as long as leukemic blast enrichment procedures are utilized. The choice of the correct “normal” control is important for comparing diseased to “normal” expression. Various means of normalizing the data are discussed.
Proteomics; Leukemia; RPPA; Reverse phase protein array
Reverse-phase protein array (RPPA) analysis is a powerful, relatively new platform that allows for high-throughput, quantitative analysis of protein networks. One of the challenges that currently limit the potential of this technology is the lack of methods that allow for accurate data modeling and identification of related networks and samples. Such models may improve the accuracy of biological sample classification based on patterns of protein network activation and provide insight into the distinct biological relationships underlying different types of cancer. Motivated by RPPA data, we propose a Bayesian sparse graphical modeling approach that uses selection priors on the conditional relationships in the presence of class information. The novelty of our Bayesian model lies in the ability to draw information from the network data as well as from the associated categorical outcome in a unified hierarchical model for classification. In addition, our method allows for intuitive integration of a priori network information directly in the model and allows for posterior inference on the network topologies both within and between classes. Applying our methodology to an RPPA data set generated from panels of human breast cancer and ovarian cancer cell lines, we demonstrate that the model is able to distinguish the different cancer cell types more accurately than several existing models and to identify differential regulation of components of a critical signaling network (the PI3K-AKT pathway) between these two types of cancer. This approach represents a powerful new tool that can be used to improve our understanding of protein networks in cancer.
Bayesian methods; protein signaling pathways; graphical models; mixture models
Acute myeloid leukemia (AML) patients with highly active AKT tend to do poorly. Cell cycle arrest and apoptosis are tightly regulated by AKT via phosphorylation of GSK3α and β isoforms which inactivates these kinases. In the current study we examine the prognostic role of AKT mediated GSK3 phosphorylation in AML.
We analyzed GSK3α/β phosphorylation by reverse phase protein analysis (RPPA) in a cohort of 511 acute myeloid leukemia (AML) patients. Levels of phosphorylated GSK3 were correlated with patient characteristics including survival and with expression of other proteins important in AML cell survival.
High levels of p-GSK3α/β correlated with adverse overall survival and a lower incidence of complete remission duration in patients with intermediate cytogenetics, but not in those with unfavorable cytogenetics. Intermediate cytogenetic patients with FLT3 mutation also fared better respectively when p-GSK3α/β levels were lower. Phosphorylated GSK3α/β expression was compared and contrasted with that of 229 related cell cycle arrest and/or apoptosis proteins. Consistent with p-GSK3α/β as an indicator of AKT activation, RPPA revealed that p-GSK3α/β positively correlated with phosphorylation of AKT, BAD, and P70S6K, and negatively correlated with β-catenin and FOXO3A. PKCδ also positively correlated with p-GSK3α/β expression, suggesting crosstalk between the AKT and PKC signaling pathways in AML cells.
These findings suggest that AKT-mediated phosphorylation of GSK3α/β may be beneficial to AML cell survival, and hence detrimental to the overall survival of AML patients. Intrinsically, p-GSK3α/β may serve as an important adverse prognostic factor for a subset of AML patients.
•Phospho-GSK3 is prognostic for poor survival in a subset of AML patients.•Phospho-GSK3 is a biomarker for active AKT in AML.•AKT is a PKCδ kinase in AML cells.
Leukemia; GSK3; AKT; PKC delta; RPPA; Signal transduction
Earlier work identified specific tumor-promoting abnormalities that are shared between lung cancers and adjacent normal bronchial epithelia. We sought to characterize the yet unknown global molecular and adjacent airway field cancerization (FC) in early-stage non–small cell lung cancer (NSCLC).
Whole-transcriptome expression profiling of resected early-stage (I–IIIA) NSCLC specimens (n = 20) with matched tumors, multiple cytologically controlled normal airways with varying distances from tumors, and uninvolved normal lung tissues (n = 194 samples) was performed using the Affymetrix Human Gene 1.0 ST platform. Mixed-effects models were used to identify differentially expressed genes among groups. Ordinal regression analysis was performed to characterize site-dependent airway expression profiles. All statistical tests were two-sided, except where noted.
We identified differentially expressed gene features (n = 1661) between NSCLCs and airways compared with normal lung tissues, a subset of which (n = 299), after gene set enrichment analysis, statistically significantly (P < .001) distinguished large airways in lung cancer patients from airways in cancer-free smokers. In addition, we identified genes (n = 422) statistically significantly and progressively differentially expressed in airways by distance from tumors that were found to be congruently modulated between NSCLCs and normal lung tissues. Furthermore, LAPTM4B, with statistically significantly increased expression (P < .05) in airways with shorter distance from tumors, was upregulated in human immortalized cells compared with normal bronchial epithelial cells (P < .001) and promoted anchorage-dependent and -independent lung cancer cell growth.
The adjacent airway FC comprises both site-independent profiles as well as gradient and localized airway expression patterns. Profiling of the airway FC may provide new insights into NSCLC oncogenesis and molecular tools for detection of the disease.
DNA methylation is associated with aberrant gene expression in cancer, and has been shown to correlate with therapeutic response and disease prognosis in some types of cancer. We sought to investigate the biological significance of DNA methylation in lung cancer.
We integrated the gene expression profiles and data of gene promoter methylation for a large panel of non-small cell lung cancer cell lines, and identified 578 candidate genes with expression levels that were inversely correlated to the degree of DNA methylation. We found these candidate genes to be differentially methylated in normal lung tissue versus non-small cell lung cancer tumors, and segregated by histologic and tumor subtypes. We used gene set enrichment analysis of the genes ranked by the degree of correlation between gene expression and DNA methylation to identify gene sets involved in cellular migration and metastasis. Our unsupervised hierarchical clustering of the candidate genes segregated cell lines according to the epithelial-to-mesenchymal transition phenotype. Genes related to the epithelial-to-mesenchymal transition, such as AXL, ESRP1, HoxB4, and SPINT1/2, were among the nearly 20% of the candidate genes that were differentially methylated between epithelial and mesenchymal cells. Greater numbers of genes were methylated in the mesenchymal cells and their expressions were upregulated by 5-azacytidine treatment. Methylation of the candidate genes was associated with erlotinib resistance in wild-type EGFR cell lines. The expression profiles of the candidate genes were associated with 8-week disease control in patients with wild-type EGFR who had unresectable non-small cell lung cancer treated with erlotinib, but not in patients treated with sorafenib.
Our results demonstrate that the underlying biology of genes regulated by DNA methylation may have predictive value in lung cancer that can be exploited therapeutically.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-1079) contains supplementary material, which is available to authorized users.
DNA methylation; Epithelial-mesenchymal transition; Erlotinib; Lung cancer
Motivation: With the expansion of high-throughput technologies, understanding different kinds of genome-level data is a common task. MicroRNA (miRNA) is increasingly profiled using high-throughput technologies (microarrays or next-generation sequencing). The downstream analysis of miRNA targets can be difficult. Although there are many databases and algorithms to predict miRNA targets, there are few tools to integrate miRNA–gene interaction data into high-throughput genomic analyses.
Results: We present targetHub, a CouchDB database of miRNA–gene interactions. TargetHub provides a programmer-friendly interface to access miRNA targets. The Web site provides RESTful access to miRNA–gene interactions with an assortment of gene and miRNA identifiers. It can be a useful tool to integrate miRNA target interaction data directly into high-throughput bioinformatics analyses.
Availability: TargetHub is available on the web at http://app1.bioinformatics.mdanderson.org/tarhub/_design/basic/index.html.
Investigate the mechanisms of regulation and role associated with EZH2 expression in lung cancer cells.
We investigated the mechanisms of EZH2 expression associated with the vascular endothelial growth factor (VEGF)/VEGF receptor 2 (VEGFR-2) pathway. Furthermore, we sought to determine the role of EZH2 in response of lung adenocarcinoma to platinum-based chemotherapy, as well as the effect of EZH2 depletion on VEGFR-2–targeted therapy in lung adenocarcinoma cell lines. Additionally, we characterized EZH2 expression in lung adenocarcinoma specimens and correlated it with patients’ clinical characteristics.
In this study, we demonstrate that VEGF/VEGFR-2 activation induces expression of EZH2 through the upregulation of E2F3 and HIF-1α, and downregulated expression of miR-101. EZH2 depletion by treatment with 3-deazaneplanocin A and knockdown by siRNA decreased the expression of EZH2 and H3K27me3, increased PARP-C level, reduced cell proliferation and migration, and increased sensitivity of the cells to treatment with cisplatin and carboplatin. Additionally, high EZH2 expression was associated with poor overall survival in patients who received platinum-based adjuvant therapy, but not in patients who did not receive this therapy. Furthermore, we demonstrated for the first time that the inhibition of EZH2 greatly increased the sensitivity of lung adenocarcinoma cells to the anti-VEGFR-2 drug AZD2171.
Our results suggest that VEGF/VEGFR-2 pathway plays a role in regulation of EZH2 expression via E2F3, HIF-1α and miR-101. EZH2 depletion decreases the malignant potential of lung adenocarcinoma and sensitivity of the cells to both platinum-based and VEGFR-2–targeted therapy.
EZH2; NSCLC; VEGF/VEGFR-2 pathway; DZNep
Lysophosphatidic acid (LPA) acts through high affinity G protein-coupled receptors to mediate a plethora of physiological and pathological activities associated with tumorigenesis. LPA receptors and autotaxin (ATX/LysoPLD), the primary enzyme producing LPA, are aberrantly expressed in multiple cancer lineages. However, the role of ATX and LPA receptors in the initiation and progression of breast cancer has not been evaluated. We demonstrate that expression of ATX or each Edg-family LPA receptor in mammary epithelium of transgenic mice is sufficient to induce a high frequency of late-onset, estrogen receptor (ER) positive, invasive and metastatic mammary cancer. Thus ATX and LPA receptors can contribute to the initiation and progression of breast cancer.
LPA; ATX; Transgenic mouse model; Breast cancer; Metastasis
Intrinsic resistance to agents targeting phosphatidylinositol-3-kinase (PI3K)/AKT pathway is one of the major challenges in cancer treatment with such agents. The objective of this study is to identify the genes or pathways that can be targeted to overcome the resistance of non-small cell lung cancer to the AKT inhibitor, MK2206, which is currently being evaluated in phase I and II clinical trials. Using a genome-wide small interfering RNA (siRNA) library screening and biological characterization we identified that inhibition of Thioredoxin Reductase-1 (TXNRD1), one of the key anti-oxidant enzymes, with siRNAs or its inhibitor, Auranofin, sensitized non-small cell lung cancer cells to MK2206 treatment in vitro and in vivo. We found that simultaneous inhibition of TXNRD1 and AKT pathways induced robust reactive oxygen species (ROS) production, which was involved in c-Jun N-terminal Kinase (JNK, MAPK8) activation and cell apoptosis. Furthermore we found that the synthetic lethality interaction between the TXNRD1 and AKT pathways occurred through the KEAP1/NRF2 cellular antioxidant pathway. Lastly, we found that synthetic lethality induced by TXNRD1 and AKT inhibitors relied on wild type KEAP1 function. Our study indicates that targeting the interaction between AKT and TXNRD1 antioxidant pathways with MK2206 and Auranofin, a FDA approved drug, is a rational strategy to treat lung cancer and that KEAP1 mutation status may offer a predicative biomarker for such combination approaches.
Synthetic lethality; AKT; TXNRD1; MK2206; KEAP1
The treatment of uveal melanoma with proton radiotherapy has provided excellent clinical outcomes. However, contemporary treatment planning systems use simplistic dose algorithms that limit the accuracy of relative dose distributions. Further, absolute predictions of absorbed dose per monitor unit are not yet available in these systems. The purpose of this study was to determine if Monte Carlo methods could predict dose per monitor unit (D/MU) value at the center of a proton spread-out Bragg peak (SOBP) to within 1% on measured values for a variety of treatment fields relevant to ocular proton therapy. The MCNPX Monte Carlo transport code, in combination with realistic models for the ocular beam delivery apparatus and a water phantom, was used to calculate dose distributions and D/MU values, which were verified by the measurements. Measured proton beam data included central-axis depth dose profiles, relative cross-field profiles and absolute D/MU measurements under several combinations of beam penetration ranges and range-modulation widths. The Monte Carlo method predicted D/MU values that agreed with measurement to within 1% and dose profiles that agreed with measurement to within 3% of peak dose or within 0.5 mm distance-to-agreement. Lastly, a demonstration of the clinical utility of this technique included calculations of dose distributions and D/MU values in a realistic model of the human eye. It is possible to predict D/MU values accurately for clinical relevant range-modulated proton beams for ocular therapy using the Monte Carlo method. It is thus feasible to use the Monte Carlo method as a routine absolute dose algorithm for ocular proton therapy.