scholarly journals Transcriptomic analysis of temporal shifts in berry development between two grapevine cultivars of the Pinot family reveals potential ripening-regulative genes

2021 ◽  
Author(s):  
Jens Theine ◽  
Daniela Holtgräwe ◽  
Katja Herzog ◽  
Florian Schwander ◽  
Anna Kicherer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Regulatory Genes ◽  
Pinot Noir ◽  
Differentially Expressed ◽  
Berry Development ◽  
Ripening Time ◽  
Berry Ripening

Background Grapevine cultivars of the Pinot family represent in the broader sense clonally propagated mutants with clear-cut phenotypes, such as different color or shifted ripening time, that result in major phenotypic and physiological differences as well as changes in important viticultural traits. Specifically, the cultivars 'Pinot Noir' (PN) and 'Pinot Noir Precoce' (PNP, early ripening) flower at the same time, but vary for the beginning of berry ripening (véraison) and consequently for the harvest time. Apart from the genotype, seasonal climatic conditions (i.e. high temperatures) also affect ripening times. To reveal possible ripening-regulatory genes affecting the timing of the start of ripening, we investigated differences in gene expression profiles between PN and PNP throughout berry development with a closely meshed time series and in two years. Results The difference in the duration of berry formation between PN and PNP was quantified to be about two weeks under the growth conditions applied, using plant material with a proven clonal relationship of PN and PNP. Clusters of co-expressed genes and differentially expressed genes (DEGs) were detected which reflect the shift in the beginning of ripening at the level of gene expression profiles. Functional annotation of these DEGs fits to phenotypic and physiological changes during berry development. In total, we observed between PN and PNP 3,342 DEGs in 2014 and 2,745 DEGs in 2017. The intersection of both years comprises 1,923 DEGs. Among these, 388 DEGs were identified as véraison-specific and 12 were considered as candidates for a regulatory effect on berry ripening time. The expression profiles revealed two candidate genes for Ripening Time Control, designated VviRTIC1 and VviRTIC2 (VIT_210s0071g01145 and VIT_200s0366g00020, respectively) that may contribute to controlling the phenotypic difference between PN and PNP. Conclusions Many of the 1,923 DEGs identified show highly similar expression profiles in both cultivars as far as accelerated berry formation of PNP is concerned. Putative ripening-regulatory genes differentially expressed between PNP and PN as well as véraison-specific genes were identified. We point out potential connections of these genes to molecular events during berry development and discuss potential ripening time controlling candidate genes, two of which are already differentially expressed in the early berry development phase. Several down-regulated genes are annotated to encode auxin response factors / ARFs. Conceivably, changes in auxin signaling may realize the earlier ripening phenotype of PNP.

scholarly journals Transcriptomic analysis of temporal shifts in berry development between two grapevine cultivars of the Pinot family reveals potential genes controlling ripening time

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jens Theine ◽  
Daniela Holtgräwe ◽  
Katja Herzog ◽  
Florian Schwander ◽  
Anna Kicherer ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Expression Profiles ◽  
Climatic Conditions ◽  
Pinot Noir ◽  
Differentially Expressed ◽  
Auxin Signaling ◽  
Potential Candidate ◽  
Berry Development ◽  
Ripening Time ◽  
Berry Ripening

Abstract Background Grapevine cultivars of the Pinot family represent clonally propagated mutants with major phenotypic and physiological differences, such as different colour or shifted ripening time, as well as changes in important viticultural traits. Specifically, the cultivars ‘Pinot Noir’ (PN) and ‘Pinot Noir Precoce’ (PNP, early ripening) flower at the same time, but vary in the beginning of berry ripening (veraison) and, consequently, harvest time. In addition to genotype, seasonal climatic conditions (i.e. high temperatures) also affect ripening times. To reveal possible regulatory genes that affect the timing of veraison onset, we investigated differences in gene expression profiles between PN and PNP throughout berry development with a closely meshed time series and over two separate years. Results The difference in the duration of berry formation between PN and PNP was quantified to be approximately two weeks under the growth conditions applied, using plant material with a proven PN and PNP clonal relationship. Clusters of co-expressed genes and differentially expressed genes (DEGs) were detected which reflect the shift in the timing of veraison onset. Functional annotation of these DEGs fit to observed phenotypic and physiological changes during berry development. In total, we observed 3,342 DEGs in 2014 and 2,745 DEGs in 2017 between PN and PNP, with 1,923 DEGs across both years. Among these, 388 DEGs were identified as veraison-specific and 12 were considered as berry ripening time regulatory candidates. The expression profiles revealed two candidate genes for ripening time control which we designated VviRTIC1 and VviRTIC2 (VIT_210s0071g01145 and VIT_200s0366g00020, respectively). These genes likely contribute the phenotypic differences observed between PN and PNP. Conclusions Many of the 1,923 DEGs show highly similar expression profiles in both cultivars if the patterns are aligned according to developmental stage. In our work, putative genes differentially expressed between PNP and PN which could control ripening time as well as veraison-specific genes were identified. We point out connections of these genes to molecular events during berry development and discuss potential candidate genes which may control ripening time. Two of these candidates were observed to be differentially expressed in the early berry development phase. Several down-regulated genes during berry ripening are annotated as auxin response factors / ARFs. Conceivably, general changes in auxin signaling may cause the earlier ripening phenotype of PNP.

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

263 USE OF PORCINE PARTHENOTES AND GENE EXPRESSION PROFILING USING MICROARRAYS FOR IDENTIFICATION OF IMPRINTED GENES

2006 ◽  
Vol 18 (2) ◽  
pp. 239
Author(s):  
J. Piedrahita ◽  
S. Bischoff ◽  
J. Estrada ◽  
B. Freking ◽  
D. Nonneman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Expression Profiles ◽  
Mammalian Species ◽  
Polar Body ◽  
Gene Expression Profiles ◽  
Tissue Type ◽  
Imprinted Genes

Genomic imprinting arises from differential epigenetic markings including DNA methylation and histone modifications and results in one allele being expressed in a parent-of-origin specific manner. For further insight into the porcine epigenome, gene expression profiles of parthenogenetic (PRT; two maternally derived chromosome sets) and biparental embryos (BP; one maternal and one paternal set of chromosomes) were compared using microarrays. Comparison of the expression profiles of the two tissue types permits identification of both maternally and paternally imprinted genes and thus the degree of conservation of imprinted genes between swine and other mammalian species. Diploid porcine parthenogenetic fetuses were generated using follicular oocytes (BOMED, Madison, WI, USA). Oocytes with a visible polar body were activated using a single square pulse of direct current of 50 V/mm for 100 �s and diploidized by culture in 10 �g/mL cycloheximide for 6 h to limit extrusion of the second polar body. Following culture, BP embryos obtained by natural matings, and PRT embryos, were surgically transferred to oviducts on the first day of estrus. Fetuses recovered at 28-30 days of gestation were dissected to separate viscera including brain, liver, and placenta; the visceral tissues were then flash-frozen in liquid nitrogen. Porcine fibroblast tissue was obtained from the remaining carcass by mincing, trypsinization, and plating cells in �-MEM. Total RNA was extracted from frozen tissue or cell culture using RNA Aqueous kit (Ambion, Austin, TX, USA) according to the manufacturer's protocol. Gene expression differences between BP and PRT tissues were determined using the GeneChip� Porcine Genome Array (Affymetrix, Santa Clara, CA) containing 23 256 transcripts from Sus scrofa and representing 42 genes known to be imprinted in human and/or mice. Triplicate arrays were utilized for each tissue type, and for PRT versus BP combination. Significant differential gene expression was identified by a linear mixed model analysis using SAS 5.0 (SAS Institute, Cary, NC, USA). Storey's q-value method was used to correct for multiple testing at q d 0.05. The following genes were classified as imprinted on the basis of their expression profiles: In fibroblasts, ARHI, HTR2A, MEST, NDN, NNAT, PEG3, PLAGL1, PEG10, SGCE, SNRPN, and UBE3A; in liver, IGF2, PEG3, PLAGL1, PEG10, and SNRPN; in placenta, HTR2A, IGF2, MEST, NDN, NNAT, PEG3, PLAGL1, PEG10, and SNRPN; and in brain, none. Additionally, several genes not known to be imprinted in humans/mice were highly differentially expressed between the two tissue types. Overall, utilizing the PRT models and gene expression profiles, we have identified thirteen genes where imprinting is conserved between swine and humans/mice, and several candidate genes that represent potentially imprinted genes. Presently, our efforts are focused in the identification of single nucleotide polymorphisms (SNPs) to more carefully evaluate the behavior of these genes in normal and abnormal gestations and to test whether the candidate genes are indeed imprinted. This research was supported by USDA-CSREES grant 524383 to J. P. and B. F.

171 THE EFFECT OF TRICHOSTATIN A ON THE DEVELOPMENT AND THE GLOBAL GENE EXPRESSION PATTERNS IN MOUSE EMBRYOS DEVELOPING IN VITRO

2008 ◽  
Vol 20 (1) ◽  
pp. 165
Author(s):  
X. S. Cui ◽  
X. Y. Li ◽  
T. Kim ◽  
N.-H. Kim
Keyword(s):  
Gene Expression ◽  
Trichostatin A ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Mouse Embryos ◽  
Differentially Expressed ◽  
Gene Expression Patterns ◽  
Cell Stage

Trichostatin A (TSA) is an inhibitor of histone deacetylase and is able to alter gene expression patterns by interfering with the removal of acetyl groups from histones. The aim of this study was to determine the effect of TSA treatment on the development and gene expression patterns of mouse zygotes developing in vitro. The addition of 100 nm TSA to the culture medium did not affect the cleavage of mouse embryos (TSA treatment, 148/150 (99%) v. control, 107/107 (100%)); however, embryos that were treated with TSA arrested at the 2-cell stage (145/148, 98%). We estimated the number of nuclei in control and TSA-treated embryos by propidium iodide staining, taking into account the presence of any cells with two or more nuclei. At 62–63 h post-hCG stimulation, control zygotes had developed to the 4-cell stage and exhibited one nucleus in each blastomere, indicative of normal development. In contrast, we observed tetraploid nuclei in at least one blastomere in 20.8% (11/53) of the embryos that had been treated with TSA. At 28–29 h post-hCG stimulation (metaphase of the 1-cell stage), there was no difference in the mitotic index (as determined by analyzing the microtubule configuration) in the TSA group compared to the control group. At the 2-cell stage, however, we did not observe mitotic spindles and metaphase chromatin in embryos in the TSA treatment group compared to the controls. Interestingly, when embryos were cultured in TSA-free medium from 35 h post-hCG stimulation (S- or early G2-phase of the 2-cell stage) onward, almost all of them (47/50) developed to the blastocyst stage. In contrast, when embryos were cultured in TSA-free medium from 42 h post-hCG stimulation (middle G2-phase of the 2-cell stage) onward, they did not develop to the 4-cell stage. We used Illumina microarray technology to analyze the gene expression profiles in control and TSA-treated late 2-cell-stage embryos. Applied Biosystems Expression System software was used to extract assay signals and assay signal-to-noise ratio values from the microarray images. Our data showed that 897 genes were significantly (P < 0.05; 2-sample t-test) up- or down-regulated by TSA treatment compared to controls. Analysis using the PANTHER classification system (https://panther.appliedbiosystems.com) revealed that the 575 genes that were differentially expressed in the TSA group compared to the control were classified as being associated with putative biological processes or molecular function. Overall, in terms of putative biological processes, more nucleoside, nucleotide, and nucleic acid metabolism, protein metabolism and modification, signal transduction, developmental process, and cell cycle genes were differentially expressed between the TSA and control groups. In terms of putative molecular function, more nucleic acid-binding transcription factor and transferase genes were differentially expressed between the groups. The results collectively suggest that inhibition of histone acetylation in mouse embryos affects gene expression profiles at the time of zygotic genome activation, and this subsequently affects further development.

Integrated Transcriptomic Analysis of Necrosis-related Gene in Diffuse Gliomas

2019 ◽  
Vol 80 (04) ◽  
pp. 240-249
Author(s):  
Jiajia Wang ◽  
Jie Ma
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Prognostic Index ◽  
Gene Expression Profiles ◽  
Risk Groups ◽  
Low Risk ◽  
Differentially Expressed ◽  
Low Grade

Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.

scholarly journals Integrated analysis of the aging brain transcriptome and proteome in tauopathy

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Carl Grant Mangleburg ◽  
Timothy Wu ◽  
Hari K. Yalamanchili ◽  
Caiwei Guo ◽  
Yi-Chen Hsieh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Mutant Form ◽  
Brain Gene Expression ◽  
Brain Transcriptome ◽  
Age Dependent

Abstract Background Tau neurofibrillary tangle pathology characterizes Alzheimer’s disease and other neurodegenerative tauopathies. Brain gene expression profiles can reveal mechanisms; however, few studies have systematically examined both the transcriptome and proteome or differentiated Tau- versus age-dependent changes. Methods Paired, longitudinal RNA-sequencing and mass-spectrometry were performed in a Drosophila model of tauopathy, based on pan-neuronal expression of human wildtype Tau (TauWT) or a mutant form causing frontotemporal dementia (TauR406W). Tau-induced, differentially expressed transcripts and proteins were examined cross-sectionally or using linear regression and adjusting for age. Hierarchical clustering was performed to highlight network perturbations, and we examined overlaps with human brain gene expression profiles in tauopathy. Results TauWT induced 1514 and 213 differentially expressed transcripts and proteins, respectively. TauR406W had a substantially greater impact, causing changes in 5494 transcripts and 697 proteins. There was a ~ 70% overlap between age- and Tau-induced changes and our analyses reveal pervasive bi-directional interactions. Strikingly, 42% of Tau-induced transcripts were discordant in the proteome, showing opposite direction of change. Tau-responsive gene expression networks strongly implicate innate immune activation. Cross-species analyses pinpoint human brain gene perturbations specifically triggered by Tau pathology and/or aging, and further differentiate between disease amplifying and protective changes. Conclusions Our results comprise a powerful, cross-species functional genomics resource for tauopathy, revealing Tau-mediated disruption of gene expression, including dynamic, age-dependent interactions between the brain transcriptome and proteome.

scholarly journals Genomewide Expression Profile Analysis of the Candida glabrata Pdr1 Regulon

2010 ◽  
Vol 10 (3) ◽  
pp. 373-383 ◽  
Author(s):  
Kelly E. Caudle ◽  
Katherine S. Barker ◽  
Nathan P. Wiederhold ◽  
Lijing Xu ◽  
Ramin Homayouni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Candida Glabrata ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Resistant Isolate ◽  
Content Type ◽  
Activating Mutations ◽  
Zinc Cluster

ABSTRACTThe ABC transportersCandida glabrataCdr1 (CgCdr1), CgPdh1, and CgSnq2 are known to mediate azole resistance in the pathogenic fungusC. glabrata. Activating mutations inCgPDR1, a zinc cluster transcription factor, result in constitutive upregulation of these ABC transporter genes but to various degrees. We examined the genomewide gene expression profiles of two matched azole-susceptible and -resistantC. glabrataclinical isolate pairs. Of the differentially expressed genes identified in the gene expression profiles for these two matched pairs, there were 28 genes commonly upregulated withCgCDR1in both isolate sets includingYOR1,LCB5,RTA1,POG1,HFD1, and several members of theFLOgene family of flocculation genes. We then sequencedCgPDR1from each susceptible and resistant isolate and found two novel activating mutations that conferred increased resistance when they were expressed in a common background strain in whichCgPDR1had been disrupted. Microarray analysis comparing these reengineered strains to their respective parent strains identified a set of commonly differentially expressed genes, includingCgCDR1,YOR1, andYIM1, as well as genes uniquely regulated by specific mutations. Our results demonstrate that while CgPdr1 activates a broad repertoire of genes, specific activating mutations result in the activation of discrete subsets of this repertoire.

Integration of expression profiles and genetic mapping data to identify candidate genes in intracranial aneurysm

2007 ◽  
Vol 32 (1) ◽  
pp. 45-57 ◽  
Author(s):  
Shantel Weinsheimer ◽  
Guy M. Lenk ◽  
Monique van der Voet ◽  
Susan Land ◽  
Antti Ronkainen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Intracranial Aneurysm ◽  
Genetic Mapping ◽  
Candidate Genes ◽  
Expression Profiles ◽  
Adherens Junction ◽  
Gene Expression Profiles ◽  
Mapping Data ◽  
Positional Candidate ◽  
Genetic Mapping Data

Intracranial aneurysm (IA) is a complex genetic disease for which, to date, 10 loci have been identified by linkage. Identification of the risk-conferring genes in the loci has proven difficult, since the regions often contain several hundreds of genes. An approach to prioritize positional candidate genes for further studies is to use gene expression data from diseased and nondiseased tissue. Genes that are not expressed, either in diseased or nondiseased tissue, are ranked as unlikely to contribute to the disease. We demonstrate an approach for integrating expression and genetic mapping data to identify likely pathways involved in the pathogenesis of a disease. We used expression profiles for IAs and nonaneurysmal intracranial arteries (IVs) together with the 10 reported linkage intervals for IA. Expressed genes were analyzed for membership in Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathways. The 10 IA loci harbor 1,858 candidate genes, of which 1,561 (84%) were represented on the microarrays. We identified 810 positional candidate genes for IA that were expressed in IVs or IAs. Pathway information was available for 294 of these genes and involved 32 KEGG biological function pathways represented on at least 2 loci. A likelihood-based score was calculated to rank pathways for involvement in the pathogenesis of IA. Adherens junction, MAPK, and Notch signaling pathways ranked high. Integration of gene expression profiles with genetic mapping data for IA provides an approach to identify candidate genes that are more likely to function in the pathology of IA.

Molecular Determinants of Lymph Node Microenvironment Induced Host Immune Tolerance In CLL: Role for CAV1, PTPN6, and PKCβ In the Process

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1367-1367
Author(s):  
Christine Gilling ◽  
Amit Mittal ◽  
Vincent Nganga ◽  
Vicky Palmer ◽  
Dennis D. Weisenburger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mouse Model ◽  
Immune Tolerance ◽  
Conflicts Of Interest ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Receptor ◽  
Differentially Expressed ◽  
Expression Levels ◽  
Aggressive Disease

Abstract Abstract 1367 Previously, we have shown that gene expression profiles (GEP) of CLL cells from lymph nodes (LN), bone marrow (BM), and peripheral blood (PB) are significantly different from each other. Among the major pathways associated with differential gene expression, a “tolerogenic signature” involved in host immune tolerance is significant in regulating CLL progression. The genes associated with the tolerogenic signature are significantly differentially expressed in patient LN-CLL compared to BM-CLL and PB-CLL, suggesting that LN-CLL cells induce this immune tolerance. From 83 differentially expressed genes identified by GEP that are associated with immune dysregulation, we selected eleven genes (CAV1, PTPN6, PKCb, ZWINT, IL2Ra, CBLC, CDC42, ZNF175, ZNF264, IL10, and HLA-G) for validation studies to determine whether these genes are also dysregulated in the Emu-TCL1 mouse model of CLL. The results demonstrate a trend of upregulation of these genes as determined by qRT-PCR in the LN-tumor microenvironment. To further evaluate the kinetics of selected gene expression during tumor progression, we determined the expression levels of Cav1, Ptpn6, and Pkcb at 12, 24, and 36 weeks of CLL development in the Em-TCL1 mouse model. We found that the expression of all three genes increased as a function of age, indicating a correlation of gene expression with disease progression. In addition, as CLL progressed in these mice there was a marked decrease in CD4+ and CD8+ T cells. The murine data were further validated using CLL cells from the same patients with indolent versus aggressive disease indicating a similar trend in expression as CLL progressed (n=4). Furthermore, patient data analyzed by Kaplan Meier analyses of the expression levels of the selected genes indicated a significant association between down-regulation of PTPN6 (p=0.031) and up-regulation of ZWINT (p<0.001) with clinical outcome as determined by a shorter time to treatment (p<0.05). Functional analysis by knockdown of CAV1 and PKCb in primary patient CLL cells determined by MTT assay showed a decrease in proliferation following knockdown of these genes (p<0.005). Protein-interaction modeling revealed regulation of CAV1 and PTPN6 by one another. Additionally, the PTPN6 protein regulates B cell receptor (BCR) signaling and subsequently the BCR regulates PKCb. Therefore, these data from both mice and humans with CLL, argue that an aggressive disease phenotype is paralleled by expression of genes associated with immune suppression. In particular, evidence presented here suggests, dysregulation of CAV1, PTPN6, ZWINT, and PKCb expression promotes CLL progression. Disclosures: No relevant conflicts of interest to declare.

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