Krishna R. Kalari

FKBP51 Affects Cancer Cell Response to Chemotherapy by Negatively Regulating Akt

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.

Multiple sclerosis patients have a distinct gut microbiota compared to healthy controls.

Multiple sclerosis (MS) is an immune-mediated disease, the etiology of which involves both genetic and environmental factors. The exact nature of the environmental factors responsible for predisposition to MS remains elusive; however, it’s hypothesized that gastrointestinal microbiota might play an important role in pathogenesis of MS. Therefore, this study was designed to investigate whether gut microbiota are altered in MS by comparing the fecal microbiota in relapsing remitting MS (RRMS) (n = 31) patients to that of age- and gender-matched healthy controls (n = 36). Phylotype profiles of the gut microbial populations were generated using hypervariable tag sequencing of the V3–V5 region of the 16S ribosomal RNA gene. Detailed fecal microbiome analyses revealed that MS patients had distinct microbial community profile compared to healthy controls. We observed an increased abundance of Psuedomonas, Mycoplana, Haemophilus, Blautia, and Dorea genera in MS patients, whereas control group showed increased abundance of Parabacteroides, Adlercreutzia and Prevotella genera. Thus our study is consistent with the hypothesis that MS patients have gut microbial dysbiosis and further study is needed to better understand their role in the etiopathogenesis of MS.

Integrated Analysis of Gene Expression, CpG Island Methylation, and Gene Copy Number in Breast Cancer Cells by Deep Sequencing

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.

Genomic Analysis Reveals That Immune Function Genes Are Strongly Linked to Clinical Outcome in the North Central Cancer Treatment Group N9831 Adjuvant Trastuzumab Trial

PURPOSE To develop a genomic signature that predicts benefit from trastuzumab in human epidermal growth factor receptor 2-positive breast cancer. PATIENTS AND METHODS DASL technology was used to quantify mRNA in samples from 1,282 patients enrolled onto the Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) adjuvant trastuzumab trial. Cox proportional hazard ratios (HRs), adjusted for significant clinicopathologic risk factors, were used to determine the association of each gene with relapse-free survival (RFS) for 433 patients who received chemotherapy alone (arm A) and 849 patients who received chemotherapy plus trastuzumab (arms B and C). Network and pathway analyses were used to identify key biologic processes linked to RFS. The signature was built by using a voting scheme. RESULTS Network and functional ontology analyses suggested that increased RFS was linked to a subset of immune function genes. A voting scheme model was used to define immune gene enrichment based on the expression of any nine or more of 14 immune function genes at or above the 0.40 quantile for the population. This model was used to identify immune gene-enriched tumors in arm A and arms B and C. Immune gene enrichment was linked to increased RFS in arms B and C (HR, 0.35; 95% CI, 0.22 to 0.55; P < .001), whereas arm B and C patients who did not exhibit immune gene enrichment did not benefit from trastuzumab (HR, 0.89; 95% CI, 0.62 to 1.28; P = .53). Enriched immune function gene expression as defined by our predictive signature was not associated with increased RFS in arm A (HR, 0.90; 95% CI, 0.60 to 1.37; P = .64). CONCLUSION Increased expression of a subset of immune function genes may provide a means of predicting benefit from adjuvant trastuzumab.

Radiation pharmacogenomics: A genome-wide association approach to identify radiation response biomarkers using human lymphoblastoid cell lines

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.

MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing

BackgroundAlthough 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.ResultsFor optimization of tools and parameters, MAP-RSeq was validated using both simulated and real datasets. MAP-RSeq workflow consists of six major modules such as alignment of reads, quality assessment of reads, gene expression assessment and exon read counting, identification of expressed single nucleotide variants (SNVs), detection of fusion transcripts, summarization of transcriptomics data and final report. This workflow is available for Human transcriptome analysis and can be easily adapted and used for other genomes. Several clinical and research projects at the Mayo Clinic have applied the MAP-RSeq workflow for RNA-Seq studies. The results from MAP-RSeq have thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients.ConclusionsOur software provides gene counts, exon counts, fusion candidates, expressed single nucleotide variants, mapping statistics, visualizations, and a detailed research data report for RNA-Seq. The workflow can be executed on a standalone virtual machine or on a parallel Sun Grid Engine cluster. The software can be downloaded from http://bioinformaticstools.mayo.edu/research/maprseq/.

Gemcitabine and Arabinosylcytosin Pharmacogenomics: Genome-Wide Association and Drug Response Biomarkers

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® 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 IC50 values for the cell lines. We then performed GWA studies with SNPs, gene expression and IC50 of these two drugs. This approach identified SNPs that were associated with gemcitabine or AraC IC50 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 IC50. 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.

Protein kinase Cι expression and oncogenic signaling mechanisms in cancer

Accumulating evidence demonstrates that PKCι is an oncogene and prognostic marker that is frequently targeted for genetic alteration in many major forms of human cancer. Functional data demonstrate that PKCι is required for the transformed phenotype of lung, pancreatic, ovarian, prostate, colon, and brain cancer cells. Future studies will be required to determine whether PKCι is also an oncogene in the many other cancer types that also overexpress PKCι. Studies of PKCι using genetically defined models of tumorigenesis have revealed a critical role for PKCι in multiple stages of tumorigenesis, including tumor initiation, progression, and metastasis. Recent studies in a genetic model of lung adenocarcinoma suggest a role for PKCι in transformation of lung cancer stem cells. These studies have important implications for the therapeutic use of aurothiomalate (ATM), a highly selective PKCι signaling inhibitor currently undergoing clinical evaluation. Significant progress has been made in determining the molecular mechanisms by which PKCι drives the transformed phenotype, particularly the central role played by the oncogenic PKCι‐Par6 complex in transformed growth and invasion, and of several PKCι‐dependent survival pathways in chemo‐resistance. Future studies will be required to determine the composition and dynamics of the PKCι‐Par6 complex, and the mechanisms by which oncogenic signaling through this complex is regulated. Likewise, a better understanding of the critical downstream effectors of PKCι in various human tumor types holds promise for identifying novel prognostic and surrogate markers of oncogenic PKCι activity that may be clinically useful in ongoing clinical trials of ATM. J. Cell. Physiol. 226: 879–887, 2011.

TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data

Summary: 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. Availability and implementation: TREAT is freely available to non-commercial users as either a stand-alone annotation and visualization tool, or as a comprehensive workflow integrating sequencing alignment and variant calling. The executables, instructions and the Amazon Cloud Images of TREAT can be downloaded at the website: http://ndc.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm Contact: Hossain.Asif@mayo.edu; Kocher.JeanPierre@mayo.edu Supplementary information: Supplementary data are provided at Bioinformatics online.

RNA Toxicity and Missplicing in the Common Eye Disease Fuchs Endothelial Corneal Dystrophy

Background: Expansion of intronic (CTG·CAG)n repeats in TCF4 is found in most Fuchs endothelial corneal dystrophy (FECD) patients. Results: RNA foci co-localizing with the splicing factor MBNL1 are found in FECD cells, and changes in mRNA splicing occur. Conclusion: Trinucleotide repeat expansion in FECD is associated with RNA focus formation and missplicing. Significance: RNA toxicity occurs in a disease affecting millions of patients. Fuchs endothelial corneal dystrophy (FECD) is an inherited degenerative disease that affects the internal endothelial cell monolayer of the cornea and can result in corneal edema and vision loss in severe cases. FECD affects ∼5% of middle-aged Caucasians in the United States and accounts for >14,000 corneal transplantations annually. Among the several genes and loci associated with FECD, the strongest association is with an intronic (CTG·CAG)n trinucleotide repeat expansion in the TCF4 gene, which is found in the majority of affected patients. Corneal endothelial cells from FECD patients harbor a poly(CUG)n RNA that can be visualized as RNA foci containing this condensed RNA and associated proteins. Similar to myotonic dystrophy type 1, the poly(CUG)n RNA co-localizes with and sequesters the mRNA-splicing factor MBNL1, leading to missplicing of essential MBNL1-regulated mRNAs. Such foci and missplicing are not observed in similar cells from FECD patients who lack the repeat expansion. RNA-Seq splicing data from the corneal endothelia of FECD patients and controls reveal hundreds of differential alternative splicing events. These include events previously characterized in the context of myotonic dystrophy type 1 and epithelial-to-mesenchymal transition, as well as splicing changes in genes related to proposed mechanisms of FECD pathogenesis. We report the first instance of RNA toxicity and missplicing in a common non-neurological/neuromuscular disease associated with a repeat expansion. The FECD patient population with this (CTG·CAG)n trinucleotide repeat expansion exceeds that of the combined number of patients in all other microsatellite expansion disorders.