Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6-96.8% precision and 91.6-95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/.
Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome.
Two cytidine analogues, gemcitabine and cytosine arabinoside (AraC), are widely used in the treatment of a variety of cancers with a large individual variation in response. To identify potential genetic biomarkers associated with response to these two drugs, we used a human lymphoblastoid cell line (LCL) model system with extensive genomic data, including 1.3 million SNPs and 54,000 basal expression probesets to perform genome-wide association studies (GWAS) with gemcitabine and AraC IC50 values.
Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs. The UTRs, however, are known to have many sequence and structural motifs that can regulate translational and transcriptional efficiency and stability of mRNAs through interaction with RNA-binding proteins and other non-coding RNAs like microRNAs (miRNAs). In a recent study, transcriptomes of tumor cells harboring mutant and wild-type KRAS (V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) genes in patients with non-small cell lung cancer (NSCLC) have been sequenced to identify single nucleotide variations (SNVs). About 40% of the total SNVs (73,717) identified were mapped to UTRs, but omitted in the previous analysis. To meet this obvious demand for analysis of the UTRs, we designed a comprehensive pipeline to predict the effect of SNVs on two major regulatory elements, secondary structure and miRNA target sites. Out of 29,290 SNVs in 6462 genes, we predict 472 SNVs (in 408 genes) affecting local RNA secondary structure, 490 SNVs (in 447 genes) affecting miRNA target sites and 48 that do both. Together these disruptive SNVs were present in 803 different genes, out of which 188 (23.4%) were previously known to be cancer-associated. Notably, this ratio is significantly higher (one-sided Fisher's exact test p-value?=?0.032) than the ratio (20.8%) of known cancer-associated genes (n?=?1347) in our initial data set (n?=?6462). Network analysis shows that the genes harboring disruptive SNVs were involved in molecular mechanisms of cancer, and the signaling pathways of LPS-stimulated MAPK, IL-6, iNOS, EIF2 and mTOR. In conclusion, we have found hundreds of SNVs which are highly disruptive with respect to changes in the secondary structure and miRNA target sites within UTRs. These changes hold the potential to alter the expression of known cancer genes or genes linked to cancer-associated pathways.
Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlations of >0.94 and >0.80 with NanoString and ScriptSeq protocols, respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively, p<2x10(-16). Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transcriptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries, but detection of eSNV and fusion transcripts was less sensitive.
Our goal in these analyses was to use genomic features from a test set of primary breast tumors to build an integrated transcriptome landscape model that makes relevant hypothetical predictions about the biological and/or clinical behavior of HER2-positive breast cancer. We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel. These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set. The generality of the model was confirmed by the observation that several key pathways were enriched in HER2-positive TCGA breast tumors. The ability of this model to make relevant predictions about the biology of breast cancer cells was established by the observation that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset. Additional modules from the HER2 transcriptome model, including ubiquitin-mediated proteolysis, TGF-beta signaling, RHO-family GTPase signaling, and M-phase progression, were linked to response to lapatinib and paclitaxel in vitro and/or risk of relapse in the N9831 dataset. These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.
The sequencing by the PolyA selection is the most common approach for library preparation. With limited amount or degraded RNA, alternative protocols such as the NuGEN have been developed. However, it is not yet clear how the different library preparations affect the downstream analyses of the broad applications of RNA sequencing.
TREAT (Targeted RE-sequencing Annotation Tool) is a tool for facile navigation and mining of the variants from both targeted resequencing and whole exome sequencing. It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways.
The most common male malignancy in the United States is prostate cancer; however its rate of occurrence varies significantly among ethnic groups. In a previous cDNA microarray study on CaP tumors from African American (AA) and Caucasian (CA) patients, we identified 97 candidate genes that exhibited opposite gene expression polarity with respect to race groups; genes up-regulated in AA were simultaneously down-regulated in CA.
Gemcitabine is a cytidine analogue used in the treatment of various solid tumors. Little is known about how gemcitabine and its metabolites are transported out of cells. We set out to study the efflux of gemcitabine and the possible consequences of that process in cancer cells. We observed the efflux of gemcitabine and its deaminated metabolite, 2,2-difluorodeoxyuridine (dFdU) using high performance liquid chromatography and tandem mass spectrometry (LC-MS/MS) after gemcitabine treatment. Non-selective ABCC-transport inhibition with probenecid significantly increased intracellular dFdU concentrations, with a similar trend observed with verapamil, a non-selective ABCB1 and ABCG2 transport inhibitor. Neither probenecid nor verapamil altered intracellular gemcitabine levels after the inhibition of deamination with tetrahydrourudine, suggesting that efflux of dFdU, but not gemcitabine, was mediated by ABC transporters. MTS assays showed that probenecid increased sensitivity to gemcitabine. While dFdU displayed little cytotoxicity, intracellular dFdU accumulation inhibited cytidine deaminase, resulting in increased gemcitabine levels and enhanced cytotoxicity. Knockdown of ABCC3, ABCC5 or ABCC10 individually did not significantly increase gemcitabine sensitivity, suggesting the involvement of multiple transporters. In summary, ABCC-mediated efflux may contribute to gemcitabine resistance through increased dFdU efflux that allows for the continuation of gemcitabine deamination. Reversing efflux-mediated gemcitabine resistance may require broad-based efflux inhibition.
SnowShoes-FTD, developed for fusion transcript detection in paired-end mRNA-Seq data, employs multiple steps of false positive filtering to nominate fusion transcripts with near 100% confidence. Unique features include: (i) identification of multiple fusion isoforms from two gene partners; (ii) prediction of genomic rearrangements; (iii) identification of exon fusion boundaries; (iv) generation of a 5-3 fusion spanning sequence for PCR validation; and (v) prediction of the protein sequences, including frame shift and amino acid insertions. We applied SnowShoes-FTD to identify 50 fusion candidates in 22 breast cancer and 9 non-transformed cell lines. Five additional fusion candidates with two isoforms were confirmed. In all, 30 of 55 fusion candidates had in-frame protein products. No fusion transcripts were detected in non-transformed cells. Consideration of the possible functions of a subset of predicted fusion proteins suggests several potentially important functions in transformation, including a possible new mechanism for overexpression of ERBB2 in a HER-positive cell line. The source code of SnowShoes-FTD is provided in two formats: one configured to run on the Sun Grid Engine for parallelization, and the other formatted to run on a single LINUX node. Executables in PERL are available for download from our web site: http://mayoresearch.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm.
Accumulating evidence demonstrates that PKC? is an oncogene and prognostic marker that is frequently targeted for genetic alteration in many major forms of human cancer. Functional data demonstrate that PKC? is required for the transformed phenotype of lung, pancreatic, ovarian, prostate, colon, and brain cancer cells. Future studies will be required to determine whether PKC? is also an oncogene in the many other cancer types that also overexpress PKC?. Studies of PKC? using genetically defined models of tumorigenesis have revealed a critical role for PKC? in multiple stages of tumorigenesis, including tumor initiation, progression, and metastasis. Recent studies in a genetic model of lung adenocarcinoma suggest a role for PKC? in transformation of lung cancer stem cells. These studies have important implications for the therapeutic use of aurothiomalate (ATM), a highly selective PKC? signaling inhibitor currently undergoing clinical evaluation. Significant progress has been made in determining the molecular mechanisms by which PKC? drives the transformed phenotype, particularly the central role played by the oncogenic PKC?-Par6 complex in transformed growth and invasion, and of several PKC?-dependent survival pathways in chemo-resistance. Future studies will be required to determine the composition and dynamics of the PKC?-Par6 complex, and the mechanisms by which oncogenic signaling through this complex is regulated. Likewise, a better understanding of the critical downstream effectors of PKC? in various human tumor types holds promise for identifying novel prognostic and surrogate markers of oncogenic PKC? activity that may be clinically useful in ongoing clinical trials of ATM.
We used deep sequencing technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+) and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER- cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5 kb of the 5 end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations.
Acetaminophen is the leading cause of acute hepatic failure in many developed nations. Acetaminophen hepatotoxicity is mediated by the reactive metabolite N-acetyl-p-benzoquinonimine (NAPQI). We performed a "discovery" genome-wide association study using a cell line-based model system to study the possible contribution of genomics to NAPQI-induced cytotoxicity. A total of 176 lymphoblastoid cell lines from healthy subjects were treated with increasing concentrations of NAPQI. Inhibiting concentration 50 values were determined and were associated with "glutathione pathway" gene single nucleotide polymorphisms (SNPs) and genome-wide basal messenger RNA expression, as well as with 1.3 million genome-wide SNPs. A group of SNPs in linkage disequilibrium on chromosome 3 was highly associated with NAPQI toxicity. The p value for rs2880961, the SNP with the lowest p value, was 1.88 × 10(-7). This group of SNPs mapped to a "gene desert," but chromatin immunoprecipitation assays demonstrated binding of several transcription factor proteins including heat shock factor 1 (HSF1) and HSF2, at or near rs2880961. These chromosome 3 SNPs were not significantly associated with variation in basal expression for any of the genome-wide genes represented on the Affymetrix U133 Plus 2.0 GeneChip. We have used a cell line-based model system to identify a SNP signal associated with NAPQI cytotoxicity. If these observations are validated in future clinical studies, this SNP signal might represent a potential biomarker for risk of acetaminophen hepatotoxicity. The mechanisms responsible for this association remain unclear.
Betaine-homocysteine methyltransferase (BHMT) catalyzes the remethylation of homocysteine. BHMT is highly expressed in the human liver. In the liver, BHMT catalyzes up to 50% of homocysteine metabolism. Understanding the relationship between BHMT genetic polymorphisms and function might increase our understanding of the role of this reaction in homocysteine remethylation and in S-adenosylmethionine-dependent methylation. To help achieve those goals, we measured levels of BHMT enzyme activity and immunoreactive protein in 268 human hepatic surgical biopsy samples from adult subjects as well as 73 fetal hepatic tissue samples obtained at different gestational ages. BHMT protein levels were correlated significantly (p<0.001) with levels of enzyme activity in both fetal and adult tissues, but both were decreased in fetal tissue when compared with levels in the adult hepatic biopsies. To determine possible genotype-phenotype correlations, 12 tag SNPs for BHMT and the closely related BHMT2 gene were selected from SNPs observed during our own gene resequencing studies as well as from HapMap. These SNPs data were used to genotype DNA from the adult hepatic surgical biopsy samples, and genotype-phenotype association analysis was performed. Three SNPs (rs41272270, rs16876512, and rs6875201), located 28kb upstream, in the 5-UTR and in intron 1 of BHMT, respectively, were significantly correlated with both BHMT activity (p=3.41E-8, 2.55E-9 and 2.46E-10, respectively) and protein levels (p=5.78E-5, 1.08E-5 and 6.92E-6, respectively). We also imputed 230 additional SNPs across the BHMT and BHMT2 genes, identifying an additional imputed SNP, rs7700790, that was also highly associated with hepatic BHMT enzyme activity and protein. However, none of the 3 genotyped or one imputed SNPs displayed a "shift" during electrophoretic mobility shift assays. These observations may help us to understand individual variation in the regulation of BHMT in the human liver and its possible relationship to variation in methylation.
Radiation therapy is used to treat half of all cancer patients. Response to radiation therapy varies widely among patients. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers to help predict radiation response using 277 ethnically defined human lymphoblastoid cell lines (LCLs). Basal gene expression levels and 1.3 million genome-wide single nucleotide polymorphism (SNP) markers from both Affymetrix and Illumina platforms were assayed for all 277 human LCLs. MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium] assays for radiation cytotoxicity were also performed to obtain area under the curve (AUC) as a radiation response phenotype for use in the association studies. Functional validation of candidate genes, selected from an integrated analysis that used SNP, expression, and AUC data, was performed with multiple cancer cell lines using specific siRNA knockdown, followed by MTS and colony-forming assays. A total of 27 loci, each containing at least two SNPs within 50 kb with P-values less than 10(-4) were associated with radiation AUC. A total of 270 expression probe sets were associated with radiation AUC with P < 10(-3). The integrated analysis identified 50 SNPs in 14 of the 27 loci that were associated with both AUC and the expression of 39 genes, which were also associated with radiation AUC (P < 10(-3)). Functional validation using siRNA knockdown in multiple tumor cell lines showed that C13orf34, MAD2L1, PLK4, TPD52, and DEPDC1B each significantly altered radiation sensitivity in at least two cancer cell lines. Studies performed with LCLs can help to identify novel biomarkers that might contribute to variation in response to radiation therapy and enhance our understanding of mechanisms underlying that variation.
Thiopurine drugs such as 6-mercaptopurine (6-MP) and 6-thioguanine (6-TG) are used to treat acute lymphoblastic leukemia of childhood. To test the hypothesis that variation in the expression of genes within the "thiopurine pathway" might influence 6-MP and 6-TG sensitivity, we generated basal gene expression profiles and IC(50) values for both of these thiopurine drugs using a model system consisting of 194 Human Variation Panel lymphoblastoid cell lines. Association analysis showed that thiopurine S-methyltransferase, ecto-5-nucleotidase (NT5E), and multidrug resistance protein 4 (ABCC4) expression were correlated with thiopurine cytotoxicity. Those observations suggested the possible existence of a "thiopurine cellular circulation" involving nucleotide efflux by ABCC4, hydrolysis of thiopurine nucleotide monophosphates outside of the cell by NT5E, and subsequent transport of thiopurine nucleosides back into the cell by nucleoside transporters. The existence of this cellular circulation was confirmed by a series of functional experiments performed with cultured cells stably or transiently transfected with ABCC4 and/or NT5E. Because of the central role of NT5E in this cellular circulation, the NT5E gene was resequenced using 287 DNA samples from three ethnic groups, with the identification of 68 single nucleotide polymorphisms (SNPs), 46 of which were novel. Several SNPs in the 5-flanking region of NT5E were highly correlated with expression, rs9450278 having the lowest p value (p = 2.4 × 10(-10), R = -0.376). The thiopurine cellular circulation and genetic polymorphisms for genes encoding the proteins involved should be incorporated into future studies of thiopurine drug therapy and effect.
The human genome displays extensive copy-number variation (CNV). Recent discoveries have shown that large segments of DNA, ranging in size from hundreds to thousands of nucleotides, are either deleted or duplicated. This CNV may encompass genes, leading to a change in phenotype, including drug response phenotypes. Gemcitabine and 1-beta-D-arabinofuranosylcytosine (AraC) are cytidine analogues used to treat a variety of cancers. Previous studies have shown that genetic variation may influence response to these drugs. In the present study, we set out to test the hypothesis that variation in copy number might contribute to variation in cytidine analogue response phenotypes.
CD38 is an ecto-enzyme that hydrolyzes NAD. Its expression is a prognostic marker for chronic lymphocytic leukemia. We have characterized individual variation in CD38 expression in lymphoblastoid cell lines from 288 healthy subjects of three ethnicities. Expression varied widely, with significant differences among ethnic groups, and was correlated significantly with CD38 enzymatic activity and protein levels. The CD38 gene was then resequenced using DNA from the same cell lines, with the identification of 53 single nucleotide polymorphisms (SNPs) and one indel, 39 novel. One SNP, rs1130169, was significantly associated with CD38 mRNA expression and explained a portion of the difference in expression among ethnic groups. EMS assay showed nuclear protein binding at or near this SNP. We also determined that variation in CD38 expression in these cell lines was associated with variation in antineoplastic drug sensitivity. These results represent a step toward understanding mechanisms involved in CD38 expression.
5-Nucleotidases play a critical role in nucleotide pool balance and in the metabolism of nucleoside analogs such as gemcitabine and cytosine arabinoside (AraC). We previously performed an expression array association study with gemcitabine and AraC cytotoxicity using 197 human lymphoblastoid cell lines. One gene that was significantly associated with gemcitabine cytotoxicity was a nucleotidase family member, NT5C3. Very little is known with regard to the pharmacogenomics of this family of enzymes.
S-Adenosylhomocysteine hydrolase (AHCY) is the only mammalian enzyme known to catalyze the hydrolysis of S-adenosylhomocysteine. We have used a genotype-to-phenotype strategy to study this important enzyme by resequencing AHCY in 240 DNA samples from four ethnic groups. Thirty-nine polymorphisms were identified - 28 of which were novel. Functional genomic studies for wild type AHCY and the three variant allozymes identified showed that two variant allozymes had slight, but significant decreases in enzyme activity, but with no significant differences in levels of immunoreactive protein. Luciferase reporter gene assays for common 5-flanking region haplotypes revealed that one haplotype with a frequency of approximately 2% in Caucasian-American subjects displayed a decreased ability to drive transcription. The variant nucleotide at 5-flanking region single nucleotide polymorphism (SNP) (-34) in that haplotype altered the DNA-protein binding pattern during electrophoresis mobility shift assay. Finally, an AHCY genotype-phenotype association study for expression in lymphoblastoid cells identified four SNPs that were associated with decreased expression. For the IVS6 (intervening sequence 6, i.e., intron 6) G56 > C SNP among those four, electrophoresis mobility shift assay showed that a C > G nucleotide change resulted in an additional shifted band. These results represent a step toward understanding the functional consequences of common genetic variation in AHCY for the regulation of neurotransmitter, drug and macromolecule methylation.
Cancer patients show large individual variation in their response to chemotherapeutic agents. Gemcitabine (dFdC) and AraC, two cytidine analogues, have shown significant activity against a variety of tumors. We previously used expression data from a lymphoblastoid cell line-based model system to identify genes that might be important for the two drug cytotoxicity. In the present study, we used that same model system to perform a genome-wide association (GWA) study to test the hypothesis that common genetic variation might influence both gene expression and response to the two drugs. Specifically, genome-wide single nucleotide polymorphisms (SNPs) and mRNA expression data were obtained using the Illumina 550K(R) HumanHap550 SNP Chip and Affymetrix U133 Plus 2.0 GeneChip, respectively, for 174 ethnically-defined "Human Variation Panel" lymphoblastoid cell lines. Gemcitabine and AraC cytotoxicity assays were performed to obtain IC(50) values for the cell lines. We then performed GWA studies with SNPs, gene expression and IC(50) of these two drugs. This approach identified SNPs that were associated with gemcitabine or AraC IC(50) values and with the expression regulation for 29 genes or 30 genes, respectively. One SNP in IQGAP2 (rs3797418) was significantly associated with variation in both the expression of multiple genes and gemcitabine and AraC IC(50). A second SNP in TGM3 (rs6082527) was also significantly associated with multiple gene expression and gemcitabine IC50. To confirm the association results, we performed siRNA knock down of selected genes with expression that was associated with rs3797418 and rs6082527 in tumor cell and the knock down altered gemcitabine or AraC sensitivity, confirming our association study results. These results suggest that the application of GWA approaches using cell-based model systems, when combined with complementary functional validation, can provide insights into mechanisms responsible for variation in cytidine analogue response.
The human glucocorticoid receptor alpha (GRalpha) is a nuclear hormone receptor that regulates multiple physiological and pathophysiological processes. There are large variations in both physiological and therapeutic response to glucocorticoids. Multiple previous studies suggested that genetic polymorphisms in GRalpha (NR3C1) might play an important role.
Akt is a central regulator of cell growth. Its activity can be negatively regulated by the phosphatase PHLPP that specifically dephosphorylates the hydrophobic motif of Akt (Ser473 in Akt1). However, how PHLPP is targeted to Akt is not clear. Here we show that FKBP51 (FK506-binding protein 51) acts as a scaffolding protein for Akt and PHLPP and promotes dephosphorylation of Akt. Furthermore, FKBP51 is downregulated in pancreatic cancer tissue samples and several cancer cell lines. Decreased FKBP51 expression in cancer cells results in hyperphosphorylation of Akt and decreased cell death following genotoxic stress. Overall, our findings identify FKBP51 as a negative regulator of the Akt pathway, with potentially important implications for cancer etiology and response to chemotherapy.
Fatty liver induced by alcohol abuse is a major worldwide health hazard leading to morbidity and mortality. Previous studies indicate antifatty liver properties of garlic. This study investigated the molecular mechanisms of garlic oil (GO) or diallyl disulfide (DADS) imparted hepatoprotection against alcohol induced fatty liver in C57BL/6 mice using microarray-based global gene expression analysis. Alcohol liquid diet resulted in severe fatty liver with increased levels of serum aspartate aminotransferease and alanine aminotransferease as well as triglycerides and decreased levels of liver glutathione and antioxidant enzymes. The major canonical pathways implicated by alcohol treatment are the metabolisms of xenobiotics by cytochrome P450, glutathione, and arachidonic acid. Treatment with DADS or GO normalized the serum aminotransferease levels and liver antioxidant enzymes and reduced the contents of triglycerides and cholesterol. The canonical pathways involved in the amelioration of liver include arachidonic acid metabolism, altered T cell and B cell signaling, tryptophan metabolism, antigen presentation pathway for DADS, metabolism of xenobiotics, mitotic roles of Polo-like kinase, fatty acid metabolism, LPS/IL-1 mediated inhibition of RXR function, and C21-steroid hormone metabolism for GO.
Taxane is one of the first line treatments of lung cancer. In order to identify novel single nucleotide polymorphisms (SNPs) that might contribute to taxane response, we performed a genome-wide association study (GWAS) for two taxanes, paclitaxel and docetaxel, using 276 lymphoblastoid cell lines (LCLs), followed by genotyping of top candidate SNPs in 874 lung cancer patient samples treated with paclitaxel.
KRAS mutations are highly prevalent in non-small cell lung cancer (NSCLC), and tumors harboring these mutations tend to be aggressive and resistant to chemotherapy. We used next-generation sequencing technology to identify pathways that are specifically altered in lung tumors harboring a KRAS mutation. Paired-end RNA-sequencing of 15 primary lung adenocarcinoma tumors (8 harboring mutant KRAS and 7 with wild-type KRAS) were performed. Sequences were mapped to the human genome, and genomic features, including differentially expressed genes, alternate splicing isoforms and single nucleotide variants, were determined for tumors with and without KRAS mutation using a variety of computational methods. Network analysis was carried out on genes showing differential expression (374 genes), alternate splicing (259 genes), and SNV-related changes (65 genes) in NSCLC tumors harboring a KRAS mutation. Genes exhibiting two or more connections from the lung adenocarcinoma network were used to carry out integrated pathway analysis. The most significant signaling pathways identified through this analysis were the NF?B, ERK1/2, and AKT pathways. A 27 gene mutant KRAS-specific sub network was extracted based on gene-gene connections from the integrated network, and interrogated for druggable targets. Our results confirm previous evidence that mutant KRAS tumors exhibit activated NF?B, ERK1/2, and AKT pathways and may be preferentially sensitive to target therapeutics toward these pathways. In addition, our analysis indicates novel, previously unappreciated links between mutant KRAS and the TNFR and PPAR? signaling pathways, suggesting that targeted PPAR? antagonists and TNFR inhibitors may be useful therapeutic strategies for treatment of mutant KRAS lung tumors. Our study is the first to integrate genomic features from RNA-Seq data from NSCLC and to define a first draft genomic landscape model that is unique to tumors with oncogenic KRAS mutations.
Fusion genes and fusion gene products are widely employed as biomarkers and therapeutic targets in hematopoietic cancers, but their applications have yet to be appreciated in solid tumors. Here, we report the use of SnowShoes-FTD, a powerful new analytic pipeline that can identify fusion transcripts and assess their redundancy and tumor subtype-specific distribution in primary tumors. In a study of primary breast tumors, SnowShoes-FTD was used to analyze paired-end mRNA-Seq data from a panel of estrogen receptor (ER)(+), HER2(+), and triple-negative primary breast tumors, identifying tumor-specific fusion transcripts by comparison with mRNA-Seq data from nontransformed human mammary epithelial cell cultures plus the Illumina Body Map data from normal tissues. We found that every primary breast tumor that was analyzed expressed one or more fusion transcripts. Of the 131 tumor-specific fusion transcripts identified, 86 were "private" (restricted to a single tumor) and 45 were "redundant" (distributed among multiple tumors). Among the redundant fusion transcripts, 7 were unique to ER(+) tumors and 8 were unique to triple-negative tumors. In contrast, none of the redundant fusion transcripts were unique to HER2(+) tumors. Both private and redundant fusion transcripts were widely expressed in primary breast tumors, with many mapping to genomic loci implicated in breast carcinogenesis and/or risk. Our finding that some fusion transcripts are tumor subtype-specific suggests that these entities may be critical determinants in the etiology of breast cancer subtypes, useful as biomarkers for tumor stratification, or exploitable as cancer-specific therapeutic targets.
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