Study of retinoic acid signaling in cancer cells: Cloning and characterization of retinoic acid responsive genes

Retinoids such as all-trans-retinoic acid (ATRA) are promising agents for cancer chemoprevention and therapy. ATRA can cause growth inhibition, induction of differentiation and apoptosis of a variety of cancer cells. These effects are thought to be mediated by nuclear retinoids receptors which are involved in ligand-dependent transcriptional activation of downstream target genes. Using differential display, we identified several retinoic acid responsive genes in the head and neck squamous carcinoma cells and lung cancer cells, including tissue type transglutaminase, cytochrome P450-related retinoic acid hydroxylase, and a novel gene, designated RAIG1. RAIG1 has two transcripts of 2.4 and 6.8 kbp, respectively, that are generated by alternative selection of polyadenylation sites. Both transcripts have the same open reading frame that encodes a protein comprised of 357 amino acid residues. The deduced RAIG1 protein sequence contains seven transmembrane domains, a signature structure of G protein-coupled receptors. RAIG1 mRNA is expressed at high level in fetal and adult lung tissues. Induction of RAIG1 expression by ATRA is rapid and dose-dependent. A fusion protein of RAIG1 and the green fluorescent protein was localized in the cell surface membrane and perinuclear vesicles in transiently transfected cells. The locus for RAIG1 gene was mapped to a region between D12S358 and D12S847 on chromosome 12p12.3-p13. Our study of the novel retinoic acid induced gene RAIG1 provide evidence for a possible interaction between retinoid and G protein signaling pathways.^ We further examined RAIG1 expression pattern in a panel of 84 cancer cell lines of different origin. The expression level varies greatly from very high to non-detectable. We selected a panel of different cancer cells to study the effects of retinoids and other differentiation agents. We observed: (1) In most cases, retinoids (including all-trans retinoic acid, 4HPR, CD437) could induce the expression of RAIG-1 in cells from cancers of the breast, colon, head and neck, lung, ovarian and prostate. (2) Compare to retinoids, butyrate is often a more potent inducer of RAIG-1 expression in many cancer cells. (3) Butyrate, Phenylacetate butyrate, (R)P-Butyrate and (S)P-Butyrate have different impact on RAIG1 expression which varies among different cell lines. Our results indicate that retinoids could restore RAIG1 expression that is down-regulated in many cancer cells.^ A mouse homologous gene, mRAIG1, was cloned by 5$\sp\prime$ RACE reaction. mRAIG1 cDNA has 2105 bp and shares 63% identity with RAIG1 cDNA. mRAIG1 encodes a polypeptide of 356 amino acid which is 76% identity with RAIG1 protein. mRAIG1 protein also has seven transmembrane domains which are structurally identical to those of RAIG1 protein. Only one 2.2 kbp mRAIG1 transcript could be detected. The mRAIG1 mRNA is also highly expressed in lung tissue. The expression of mRAIG1 gene could be induced by ATRA in several mouse embryonal carcinoma cells. The induction of mRAIG1 expression is associated with retinoic acid-induced neuroectoderm differentiation of P19 cells. Similarity in cDNA and protein sequence, secondary structure, tissue distribution and inducible expression by retinoic acid strongly suggest that the mouse gene is the homologue of the human RAIG1 gene. ^

Identification and characterization of cellular genes differentially expressed in a subset of tumors with non -functional WT1

Wilms tumor (WT) or nephroblastoma is a genetically heterogeneous pediatric renal tumor that accounts for 6–7% of all childhood cancers in the U.S. WT1, located at 11p13, is the sole WT gene cloned to date. Additional genomic regions containing genes that play a role in the development of Wilms tumor include 11p15, 7p, 16q, 1p, 17q and 19q. This heterogeneity has made it extremely difficult to develop an understanding of the pathways involved in the development of WT, even in the 5–20% of tumors that show mutations at the WT1 locus. My research addresses this gap in our current comprehension of the development of WT. ^ I have used two complementary approaches to extend the current understanding of molecular changes involved in the development of WT. In order to minimize complexities due to genetic heterogeneity, I confined my analysis to the WT1 pathway by assessing those genetically defined tumors that carry WT1 mutations. WT1 encodes a zinc finger transcription factor, and in vitro studies have identified many genes that are potentially regulated in vivo by WT1. However, there is very little in vivo data that suggests that they are transcriptionally regulated endogenously by WT1. In one approach I assessed the role of WT1 in the in vivo regulation of PDGFA and IGF2, two genes that are strong contenders for endogenous regulation by WT1. Using primary tissue samples, I found no correlation between the level of RNA expression of WT1 with either PDGFA or IGF2, suggesting that WT1 does not play a critical role in their expression in either normal kidney or WT. ^ In a parallel strategy, using differential display analysis I compared global gene expression in a subset of tumors with known homozygous inactivating WT1 mutations (WT1-tumors) to the gene expression in a panel of appropriate control tissues (fetal kidney, normal kidney, rhabdoid tumor and pediatric renal cell carcinoma). Transcripts that are aberrantly expressed in this subset of Wilms tumors are candidates for endogenous transcriptional regulation by WT1 as well as for potentially functioning in the development of WT. By this approach I identified several differentially expressed transcripts. I further characterized two of these transcripts, identifying a candidate WT gene in the process. I then performed a detailed analysis of this WT candidate gene, which maps to 7p. Future studies will shed more light on the role of these differentially expressed genes in WT. ^

Statistical Methods for Differential Expressions of Genes Detected in Multiple-Condition Experiment of Microarray

Most studies of differential gene-expressions have been conducted between two given conditions. The two-condition experimental (TCE) approach is simple in that all genes detected display a common differential expression pattern responsive to a common two-condition difference. Therefore, the genes that are differentially expressed under the other conditions other than the given two conditions are undetectable with the TCE approach. In order to address the problem, we propose a new approach called multiple-condition experiment (MCE) without replication and develop corresponding statistical methods including inference of pairs of conditions for genes, new t-statistics, and a generalized multiple-testing method for any multiple-testing procedure via a control parameter C. We applied these statistical methods to analyze our real MCE data from breast cancer cell lines and found that 85 percent of gene-expression variations were caused by genotypic effects and genotype-ANAX1 overexpression interactions, which agrees well with our expected results. We also applied our methods to the adenoma dataset of Notterman et al. and identified 93 differentially expressed genes that could not be found in TCE. The MCE approach is a conceptual breakthrough in many aspects: (a) many conditions of interests can be conducted simultaneously; (b) study of association between differential expressions of genes and conditions becomes easy; (c) it can provide more precise information for molecular classification and diagnosis of tumors; (d) it can save lot of experimental resources and time for investigators.^