Spiridon Tsavachidis

Splicing factors PTBP1 and PTBP2 promote proliferation and migration of glioma cell lines

Polypyrimidine tract-binding protein 1 (PTBP1) is a multi-functional RNA-binding protein that is aberrantly overexpressed in glioma. PTBP1 and its brain-specific homologue polypyrimidine tract-binding protein 2 (PTBP2) regulate neural precursor cell differentiation. However, the overlapping and non-overlapping target transcripts involved in this process are still unclear. To determine why PTBP1 and not PTBP2 would promote glial cell-derived tumours, both PTBP1 and PTBP2 were knocked down in the human glioma cell lines U251 and LN229 to determine the role of these proteins in cell proliferation, migration, and adhesion. Surprisingly, removal of both PTBP1 and PTBP2 slowed cell proliferation, with the double knockdown having no additive effects. Decreased expression of both proteins individually and in combination inhibited cell migration and increased adhesion of cells to fibronectin and vitronectin. A global survey of differential exon expression was performed following PTBP1 knockdown in U251 cells using the Affymetrix Exon Array to identify PTBP1-specific splicing targets that enhance gliomagenesis. In the PTBP1 knockdown, previously determined targets were unaltered in their splicing patterns. A single gene, RTN4 (Nogo) had significantly enhanced inclusion of exon 3 when PTBP1 was removed. Overexpression of the splice isoform containing exon 3 decreased cell proliferation to a similar degree as the removal of PTBP1. These results provide the first evidence that RNA-binding proteins affect the invasive and rapid growth characteristics of glioma cell lines. Its actions on proliferation appear to be mediated, in part, through alternative splicing of RTN4.

Global analysis of aberrant pre-mRNA splicing in glioblastoma using exon expression arrays.

BackgroundTumor-predominant splice isoforms were identified during comparative in silico sequence analysis of EST clones, suggesting that global aberrant alternative pre-mRNA splicing may be an epigenetic phenomenon in cancer. We used an exon expression array to perform an objective, genome-wide survey of glioma-specific splicing in 24 GBM and 12 nontumor brain samples. Validation studies were performed using RT-PCR on glioma cell lines, patient tumor and nontumor brain samples.ResultsIn total, we confirmed 14 genes with glioma-specific splicing; seven were novel events identified by the exon expression array (A2BP1, BCAS1, CACNA1G, CLTA, KCNC2, SNCB, and TPD52L2). Our data indicate that large changes (> 5-fold) in alternative splicing are infrequent in gliomagenesis (< 3% of interrogated RefSeq entries). The lack of splicing changes may derive from the small number of splicing factors observed to be aberrantly expressed.ConclusionWhile we observed some tumor-specific alternative splicing, the number of genes showing exclusive tumor-specific isoforms was on the order of tens, rather than the hundreds suggested previously by in silico mining. Given the important role of alternative splicing in neural differentiation, there may be selective pressure to maintain a majority of splicing events in order to retain glial-like characteristics of the tumor cells.

Critical and Distinct Roles of p16 and Telomerase in Regulating the Proliferative Life Span of Normal Human Prostate Epithelial Progenitor Cells

Normal human prostate (NHP) epithelial cells undergo senescence in vitro and in vivo, but the underlying molecular mechanisms remain obscure. Here we show that the senescence of primary NHP cells, which are immunophenotyped as intermediate basal-like cells expressing progenitor cell markers CD44, α2β1, p63, hTERT, and CK5/CK18, involves loss of telomerase expression, up-regulation of p16, and activation of p53. Using genetically defined manipulations of these three signaling pathways, we show that p16 is the primary determinant of the NHP cell proliferative capacity and that hTERT is required for unlimited proliferative life span. Hence, suppression of p16 significantly extends NHP cell life span, but both p16 inhibition and hTERT are required to immortalize NHP cells. Importantly, immortalized NHP cells retain expression of most progenitor markers, demonstrate gene expression profiles characteristic of proliferating progenitor cells, and possess multilineage differentiation potential generating functional prostatic glands. Our studies shed important light on the molecular mechanisms regulating the proliferative life span of NHP progenitor cells.

Molecular signatures of metastasis in head and neck cancer.

Metastases are the primary cause of cancer treatment failure and death, yet metastatic mechanisms remain incompletely understood.

Dicarbonyl/L-xylulose reductase: a potential biomarker identified by laser-capture microdissection-micro serial analysis of gene expression of human prostate adenocarcinoma.

To identify genes involved in prostate carcinogenesis, we used laser-capture microdissection-micro serial analysis of gene expression to construct libraries of paired cancer and normal cells from human tissue samples. After computational comparison of the two libraries, we identified dicarbonyl/l-xylulose reductase (DCXR), an enzyme that catalyzes α-dicarbonyl and l-xylulose, as being significantly up-regulated in prostate cancer cells. The specificity of DCXR up-regulation for prostate cancer tissues was confirmed by quantitative real-time reverse transcriptase-PCR, virtual Northern blot, and Western blot analyses. Furthermore, DCXR expression at the protein level was assessed using fresh-frozen tissues and a tissue microarray consisting of 46 cases of organ-confined early-stage prostate cancer and 29 cases of chemohormonally treated prostate cancer. In most normal prostate epithelial cells, DCXR was expressed at low levels and was localized predominantly in the cytoplasmic membrane. In contrast, in virtually all grades of early-stage prostate cancer and in all chemohormonally treated cases, DCXR was strikingly overexpressed and was localized predominantly in the cytoplasm and nucleus. In all samples, the stromal cells were completely devoid of DCXR expression. Based on these findings, we suggest that DCXR overexpression has the potential to be an additional useful biomarker for prostate cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(12):2615–22)

Combined laser capture microdissection and serial analysis of gene expression from human tissue samples

Cell-specific gene expression profiling from heterogeneous human tissues is confounded by cell purification limitations. Here, we describe a technique to generate gene expression profiles of pure populations of prostate cancer cells obtained from fresh-frozen prostatectomy specimens and small initial quantities of RNA by combining laser capture microdissection and microserial analysis of gene expression (LCM–microSAGE). Two microSAGE libraries were obtained from approximately 100 000 laser pulses, estimated to contain fewer than 3 × 105 cells and 20–30 ng mRNA. Two libraries were sequenced to a depth of 10 111 and 10 463 unique tags from normal and cancer cells, representing 6453 and 6923 genes, respectively. Most transcripts were expressed at similar levels, but cancer cells compared with normal cells had increased expression of 385 tags and decreased expression of 389 tags. A total of 20 genes were differentially expressed (P<0.05); five of these genes were upregulated and 15 were downregulated in cancer cells. Quantitative reverse transcriptase-polymerase chain reaction results from three selected genes corroborated the existence of cell-specific gene expression in LCM–microSAGE-derived libraries. In conclusion, the LCM–microSAGE approach demonstrates that large-scale expression profiles of known and unknown transcripts can be generated from pure populations of target cells obtained from human tissue samples comprised of heterogeneous mixtures of cell types.

Rapamycin-regulated gene expression signature determines prognosis in breast cancer.

CTRC-AACR San Antonio Breast Cancer Symposium: 2008 Abstracts Abstract #3072 Background: Mammalian target of rapamycin (mTOR) is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes) may also be used to simulate a biologic process or effects of a drug treatment. In this study, we tested the hypothesis that the gene-expression signature regulated by rapamycin could predict disease outcome for patients with breast cancer. Methods: MDA-MB-468 breast cancer cell line is triple negative and PTEN null. Sensitivity of MDA-MB-468 breast cancer cell line to rapamycin was determined by in vitro growth assays and in vivo tumor studies. Total RNA was extracted from cell lines treated with rapamycin or DMSO for 24 hours and xenografts treated with DMSO or rapamycin for 1 or 22 days. Total RNA was used for expression profiling and hybridized to Affymetrix HG-U133 Plus 2.0 arrays. We used two well-described primary breast cancer datasets of 251 (Miller et al, Proc. Natl. Acad. Sci. USA 2005;102:13550) and 286 (Wang et al, Lancet. 2005;365:671) patients from the public domain and assessed the prognostic capability of rapamycin-regulated gene expression signatures. Results: Colony formation and sulforhodazine B (IC50 < 1 nM) assays, and xenograft animals showed that MDA-MB-468 cells were sensitive to treatment with rapamycin. The comparison of in vitro and in vivo gene expression data identified a 31-gene expression signature that was up- regulated by rapamycin treatment in vitro as well as in vivo (FDR of 0.1). From the 31 genes on HG-U133 Plus 2.0 array, 20 that were included on HG-U133A array were used for analysis. In the Miller dataset, rapamycin metagene index (RMI) did not correlate with tumor size or lymph node status. High (0.75 percentile) RMI was significantly associated with longer survival (P=0.015). On multivariate analysis, RMI (P=0.029), tumor size (P=0.015) and lymph node status (P=0.001) were prognostic. In the Wang dataset, RMI predicted time to disease relapse (P=0.009). Conclusion: Rapamycin-regulated gene expression signature predicts clinical outcome in breast cancer. This supports the central role of mTOR signaling in breast cancer biology and provides further impetus to pursue mTOR-targeted therapies for breast cancer treatment. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 3072.

Abstract 04: Using family-based genome-wide data to evaluate imprinting and maternal genetic effects: A pilot study of glioma risk.

Abstract Introduction: Glioma is the most common malignant brain tumor, however only a few established risk factors have been identified. Recent evidence from a genome-wide linkage scan using a high-density array of single-nucleotide polymorphisms (SNPs) suggests glioma susceptibility is influenced by several genetic loci. While most studies focus on the role of alleles in genes carried by affected individuals (i.e., case genetic effects), other biological mechanisms may also be involved. As some cancer phenotypes may arise in utero, one such mechanism involves maternally mediated genetic effects. Specifically, the mother not only contributes half of her genome to the offspring, she also provides the intrauterine environment of the developing fetus. Variation in the mothers genome could affect the intrauterine environment essential to the normal development. Imprinting effects, where the effect of inherited DNA depends on whether it is transmitted from the mother or the father, may be another biological mechanism important in the etiology of glioma. While these unconventional biological mechanisms may be hard to study with a case-control design, they can be tested using case-parent triads, where affected cases and their parents are genotyped. Methods: Glioma cases and families were recruited from the Gliogene Consortium through The University of Texas MD Anderson Cancer Center, Houston, Texas. DNA samples were genotyped at Baylor College of Medicine using the Human 610-Quad Bead Chip or the Hap370K Bead Chip (Illumina, San Diego, CA). Genotype data were available on a total of 57 complete and incomplete case-parent triads. For this exploratory analysis, we evaluated the 12 “top hits” from a recent assessment of glioma susceptibility among familial glioma cases: PRL rs2064193; LOC389370 rs16886628; PRMT8 rs17780102; STYK1 rs2418087; GRIN2B rs7961199; SOX5 rs7305773; LOC728762 rs9303521; WNT9B rs1530364; SPOP rs6504618; LOC729430 rs1879145; MS12 rs868728; and NFATC1 rs7236492. We applied log-linear models to investigate whether polymorphisms of maternal genes or imprinting effects influence risk of glioma in cases. Results: Three of the 12 SNPs previously identified in a larger study of familial glioma risk also had significant maternal genetic effects, even after adjusting for the case genetic effects. Specifically, maternal genotypes for GRIN2B rs7961199 A>G (OR = 2.45, p = 0.04), NFATC1 rs7236492 C>T (OR = 4.67, p = 0.01), and LOC729430 rs1879145 C>T (OR = 7.86, p = 0.002) were associated with glioma risk. Interestingly, the variant at LOC729430 is located on 17q22-23.2, which appears to be important in familial glioma. Imprinting analyses are currently underway. Conclusions: To our knowledge, this is the first assessment of maternal genetic effects in the context of glioma risk. Furthermore, we employed a family-based design, which allows the assessment of imprinting effects. As the genetic architecture of glioma susceptibility is complex, involving the co-inheritance of multiple risk variants, epistatic interactions, and gene-environment interactions, it is important to explore alternative biological mechanisms using the whole human genome. Our findings suggest that maternal genetic variation may be relevant in the etiology of glioma risk. This work was supported by the National Institutes of Health (R01CA119215). Citation Format: Philip J. Lupo, Michael E. Scheurer, Georgina N. Armstrong, Spiridon Tsavachidis, Yanhong Liu, Ching C. Lau, The Gliogene Consortium, Sanjay Shete, Melissa L. Bondy. Using family-based genome-wide data to evaluate imprinting and maternal genetic effects: A pilot study of glioma risk. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 04.