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Tumor-suppressor genes (TSGs) have been classically defined as genes whose loss of function in tumor cells contributes to the formation and/or maintenance of the tumor phenotype. TSGs containing nonsense mutations may not be expressed because of nonsense-mediated RNA decay (NMD). We combined inhibition of the NMD process, which clears transcripts that contain nonsense mutations, with the application of high-density single-nucleotide polymorphism arrays analysis to discriminate allelic content in order to identify candidate TSGs in five breast cancer cell lines. We identified ARID1A as a target of NMD in the T47D breast cancer cell line, likely as a consequence of a mutation in exon-9, which introduces a premature stop codon at position Q944. ARID1A encodes a human homolog of yeast SWI1, which is an integral member of the hSWI/SNF complex, an ATP-dependent, chromatin-remodeling, multiple-subunit enzyme. Although we did not find any somatic mutations in 11 breast tumors, which show DNA copy-number loss at the 1p36 locus adjacent to ARID1A, we show that low ARID1A RNA or nuclear protein expression is associated with more aggressive breast cancer phenotypes, such as high tumor grade, in two independent cohorts of over 200 human breast cancer cases each. We also found that low ARID1A nuclear expression becomes more prevalent during the later stages of breast tumor progression. Finally, we found that ARID1A re-expression in the T47D cell line results in significant inhibition of colony formation in soft agar. These results suggest that ARID1A may be a candidate TSG in breast cancer.

Protein kinase C betaII (PKCβII) represents a novel potential target for anticancer therapies in breast cancer. In order to identify patient subgroups which might benefit from PKC-targeting therapies, we investigated the expression of PKCβII in human breast cancer cell lines and in a tissue microarray (TMA). We first screened breast cancer cell line representatives of breast cancer subtypes for PKCβII expression at the mRNA and at the protein levels. We analyzed a TMA comprising of tumors from 438 patients with a median followup of 15.4 years for PKCβII expression by immunohistochemistry along with other prognostic factors in breast cancer. Among a panel of human breast cancer cell lines, only MDA-MB-436, a triple negative basal cell line, showed overexpression for PKCβII both at the mRNA and at the protein levels. In breast cancer patients, cytoplasmic expression of PKCβII correlated positively with human epidermal growth factor receptor-2 (HER-2; P = 0.01) and Ki-67 (P = 0.016), while nuclear PKCβII correlated positively with estrogen receptor (ER; P = 0.016). The positive correlation of CK5/6 with cytoplasmic PKCβII (P = 0.033) lost statistical significance after adjusting for multiple comparisons (P = 0.198). Cytoplasmic PKCβII did not correlate with cyclooxygenase (COX-2; P = 0.925) and vascular endothelial growth factor (P = 1). There was no significant association between PKCβII staining and overall survival. Cytoplasmic PKCβII correlates with HER-2 and Ki-67, while nuclear PKCβII correlates with ER in breast cancer. Our study suggests the necessity for assessing the subcellular localization of PKCβII in breast cancer subtypes when evaluating the possible effectiveness of PKCβII-targeting agents.

A major focus of biology is determining the role that specific genes play within a cell. The ability to control gene expression is a powerful tool for biologists, and methods that facilitate the expression of genes in trans have been very useful in delineating gene function. However, methods that enable researchers to decease or inhibit gene expression in a controlled and specific manner have been lacking. A significant advancement in the field of gene silencing is the recent discovery of RNA interference (RNAi), a post-transcriptional gene silencing mechanism first described in C. elegansand Drosophilaand more recently shown to occur in mammals, including mouse and human cells. This chapter will examine several aspects of RNAi and its related gene silencing mechanisms and will discuss the impact that technologies based on these endogenous cellular processes have had on studies of gene function and on new approaches to the treatment of disease.

cDNA microarrays permit massively parallel gene expression analysis and have spawned a new paradigm in the study of molecular biology. One of the significant challenges in this genomic revolution is to develop sophisticated approaches to facilitate the visualization, analysis, and interpretation of the vast amounts of multi-dimensional gene expression data. We have applied self-organizing map (SOM) in order to meet these challenges. In essence, we utilize U-matrix and component planes in microarray data visualization and introduce general procedure for assessing significance for a cluster detected from U-matrix. Our case studies consist of two data sets. First, we have analyzed a data set containing 13,824 genes in 14 breast cancer cell lines. In the second case we show an example of the SOM in drug treatment of prostate cancer cells. Our results indicate that (1) SOM is capable of helping finding certain biologically meaningful clusters, (2) clustering algorithms could be used for finding a set of potential predictor genes for classification purposes, and (3) comparison and visualization of the effects of different drugs is straightforward with the SOM. In summary, the SOM provides an excellent format for visualization and analysis of gene microarray data, and is likely to facilitate extraction of biologically and medically useful information.

Androgen deprivation therapy for advanced prostate cancer is often effective, but not curative. Molecular pathways mediating the therapeutic response and those contributing to the subsequent hormone-refractory cell growth remain poorly understood. Here, cDNA microarray analysis of human CWR22 prostate cancer xenografts during the course of androgen deprivation therapy revealed distinct global gene expression profiles in primary, regressing and recurrent tumors. Elucidation of the genes involved in the transition between these states implicated specific molecular mechanisms in therapy failure and tumor progression. First, we identified a set of androgen-responsive genes whose expression decreased during the therapy response, but was then systematically restored in the recurrent tumors. In addition, altered expression of genes that encode known targets of rapamycin or that converge on the PI3K/AKT/FRAP pathway was observed in the recurrent tumors. Further suggestion for the involvement of these genes in hormone-refractory prostate cancer came from the observation that cells established from the recurrent xenografts were strongly inhibited in vitro by rapamycin. The results of this functional genomic analysis suggest that the combined effect of re-expression of androgen-responsive genes as well as the activation of rapamycin-sensitive signaling may drive prostate cancer progression, and contribute to the failure of androgen-deprivation therapy.

Background Ewing's sarcomas are aggressive musculoskeletal tumors occurring most frequently in the long and flat bones as a solitary lesion mostly during the teen-age years of life. With current treatments, significant number of patients relapse and survival is poor for those with metastatic disease. As part of novel target discovery in Ewing's sarcoma, we applied RNAi mediated phenotypic profiling to identify kinase targets involved in growth and survival of Ewing's sarcoma cells. Results Four Ewing's sarcoma cell lines TC-32, TC-71, SK-ES-1 and RD-ES were tested in high throughput-RNAi screens using a siRNA library targeting 572 kinases. Knockdown of 25 siRNAs reduced the growth of all four Ewing's sarcoma cell lines in replicate screens. Of these, 16 siRNA were specific and reduced proliferation of Ewing's sarcoma cells as compared to normal fibroblasts. Secondary validation and preliminary mechanistic studies highlighted the kinases STK10 and TNK2 as having important roles in growth and survival of Ewing's sarcoma cells. Furthermore, knockdown of STK10 and TNK2 by siRNA showed increased apoptosis. Conclusion In summary, RNAi-based phenotypic profiling proved to be a powerful gene target discovery strategy, leading to successful identification and validation of STK10 and TNK2 as two novel potential therapeutic targets for Ewing's sarcoma.

High-resolution CGH analysis on cDNA microarrays for direct identification of amplification target genes

Gene expression changes during hormonal therapy for prostate cancer reveal candidate diagnostic and drug targets