Overdispersed logistic regression for SAGE: Modelling multiple groups and covariates

BACKGROUND: Two major identifiable sources of variation in data derived from the Serial Analysis of Gene Expression (SAGE) are within-library sampling variability and between-library heterogeneity within a group. Most published methods for identifying differential expression focus on just the sampling variability. In recent work, the problem of assessing differential expression between two groups of SAGE libraries has been addressed by introducing a beta-binomial hierarchical model that explicitly deals with both of the above sources of variation. This model leads to a test statistic analogous to a weighted two-sample t-test. When the number of groups involved is more than two, however, a more general approach is needed. RESULTS: We describe how logistic regression with overdispersion supplies this generalization, carrying with it the framework for incorporating other covariates into the model as a byproduct. This approach has the advantage that logistic regression routines are available in several common statistical packages. CONCLUSIONS: The described method provides an easily implemented tool for analyzing SAGE data that correctly handles multiple types of variation and allows for more flexible modelling

Gene expression signature of estrogen receptor α status in breast cancer

BACKGROUND: Estrogens are known to regulate the proliferation of breast cancer cells and to modify their phenotypic properties. Identification of estrogen-regulated genes in human breast tumors is an essential step toward understanding the molecular mechanisms of estrogen action in cancer. To this end we generated and compared the Serial Analysis of Gene Expression (SAGE) profiles of 26 human breast carcinomas based on their estrogen receptor α (ER) status. Thus, producing a breast cancer SAGE database of almost 2.5 million tags, representing over 50,000 transcripts. RESULTS: We identified 520 transcripts differentially expressed between ERα-positive (+) and ERα-negative (-) primary breast tumors (Fold change ≥ 2; p < 0.05). Furthermore, we identified 220 high-affinity Estrogen Responsive Elements (EREs) distributed on the promoter regions of 163 out of the 473 up-modulated genes in ERα (+) breast tumors. In brief, we observed predominantly up-regulation of cell growth related genes, DNA binding and transcription factor activity related genes based on Gene Ontology (GO) biological functional annotation. GO terms over-representation analysis showed a statistically significant enrichment of various transcript families including: metal ion binding related transcripts (p = 0.011), calcium ion binding related transcripts (p = 0.033) and steroid hormone receptor activity related transcripts (p = 0.031). SAGE data associated with ERα status was compared with reported information from breast cancer DNA microarrays studies. A significant proportion of ERα associated gene expression changes was validated by this cross-platform comparison. However, our SAGE study also identified novel sets of genes as highly expressed in ERα (+) invasive breast tumors not previously reported. These observations were further validated in an independent set of human breast tumors by means of real time RT-PCR. CONCLUSION: The integration of the breast cancer comparative transcriptome analysis based on ERα status coupled to the genome-wide identification of high-affinity EREs and GO over-representation analysis, provide useful information for validation and discovery of signaling networks related to estrogen response in this malignancy

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

<p>Abstract</p> <p>Background</p> <p>Tumor-predominant splice isoforms were identified during comparative <it>in silico </it>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.</p> <p>Results</p> <p>In total, we confirmed 14 genes with glioma-specific splicing; seven were novel events identified by the exon expression array (<it>A2BP1, BCAS1, CACNA1G, CLTA, KCNC2, SNCB</it>, and <it>TPD52L2</it>). 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.</p> <p>Conclusion</p> <p>While 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 <it>in silico </it>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.</p

BRCA2 inhibition enhances cisplatin-mediated alterations in tumor cell proliferation, metabolism, and metastasis

Tumor cells have unstable genomes relative to non-tumor cells. Decreased DNA integrity resulting from tumor cell instability is important in generating favorable therapeutic indices, and intact DNA repair mediates resistance to therapy. Targeting DNA repair to promote the action of anti-cancer agents is therefore an attractive therapeutic strategy. BRCA2 is involved in homologous recombination repair. BRCA2 defects increase cancer risk but, paradoxically, cancer patients with BRCA2 mutations have better survival rates. We queried TCGA data and found that BRCA2 alterations led to increased survival in patients with ovarian and endometrial cancer. We developed a BRCA2-targeting second-generation antisense oligonucleotide (ASO), which sensitized human lung, ovarian, and breast cancer cells to cisplatin by as much as 60%. BRCA2 ASO treatment overcame acquired cisplatin resistance in head and neck cancer cells, but induced minimal cisplatin sensitivity in non-tumor cells. BRCA2 ASO plus cisplatin reduced respiration as an early event preceding cell death, concurrent with increased glucose uptake without a difference in glycolysis. BRCA2 ASO and cisplatin decreased metastatic frequency invivo by 77%. These results implicate BRCA2 as a regulator of metastatic frequency and cellular metabolic response following cisplatin treatment. BRCA2 ASO, in combination with cisplatin, is a potential therapeutic anti-cancer agent

Genome-Wide Hypomethylation in Head and Neck Cancer Is More Pronounced in HPV-Negative Tumors and Is Associated with Genomic Instability

Loss of genome-wide methylation is a common feature of cancer, and the degree of hypomethylation has been correlated with genomic instability. Global methylation of repetitive elements possibly arose as a defense mechanism against parasitic DNA elements, including retrotransposons and viral pathogens. Given the alterations of global methylation in both viral infection and cancer, we examined genome-wide methylation levels in head and neck squamous cell carcinoma (HNSCC), a cancer causally associated with human papilloma virus (HPV). We assayed global hypomethylation levels in 26 HNSCC samples, compared with their matched normal adjacent tissue, using Pyrosequencing-based methylation assays for LINE repeats. In addition, we examined cell lines derived from a variety of solid tumors for LINE and SINE (Alu) repeats. The degree of LINE and Alu hypomethylation varied among different cancer cell lines. There was only moderate correlation between LINE and Alu methylation levels, with the range of variation in methylation levels being greater for the LINE elements. LINE hypomethylation was more pronounced in HPV-negative than in HPV-positive tumors. Moreover, genomic instability, as measured by genome-wide loss-of-heterozygosity (LOH) single nucleotide polymorphism (SNP) analysis, was greater in HNSCC samples with more pronounced LINE hypomethylation. Global hypomethylation was variable in HNSCC. Its correlation with both HPV status and degree of LOH as a surrogate for genomic instability may reflect alternative oncogenic pathways in HPV-positive versus HPV-negative tumors