p63 and p73 in human cancer: defining the network.

The p53-related genes p63 and p73 exhibit significant structural homology to p53; however, they do not function as classical tumor suppressors and are rarely mutated in human cancers. Both p63 and p73 exhibit tissue-specific roles in normal development and a complex contribution to tumorigenesis that is due to their expression as multiple protein isoforms. The predominant p63/p73 isoforms expressed both in normal development and in many tumors lack the conserved transactivation (TA) domain; these isoforms instead exhibit a truncated N-terminus (DeltaN) and function at least in part as transcriptional repressors. p63 and p73 isoforms are regulated through both transcriptional and post-translational mechanisms, and they in turn regulate diverse cellular functions including proliferation, survival and differentiation. The net effect of p63/p73 expression in a given context depends on the ratio of TA/DeltaN isoforms expressed, on physical interaction between p63 and p73 isoforms, and on functional interactions with p53 at the promoters of specific downstream target genes. These multifaceted interactions occur in diverse ways in tumor-specific contexts, demonstrating a functional 'p53 family network' in human tumorigenesis. Understanding the regulation and mechanistic contributions of p63 and p73 in human cancers may ultimately provide new therapeutic opportunities for a variety of these diseases.

Cancer gene discovery using digital differential display.

The Cancer Gene Anatomy Project database of the National Cancer Institute has thousands of expressed sequences, both known and novel, in the form of expressed sequence tags (ESTs). These ESTs, derived from diverse normal and tumor cDNA libraries, offer an attractive starting point for cancer gene discovery. Using a data-mining tool called Digital Differential Display (DDD) from the Cancer Gene Anatomy Project database, ESTs from six different solid tumor types (breast, colon, lung, ovary, pancreas, and prostate) were analyzed for differential expression. An electronic expression profile and chromosomal map position of these hits were generated from the Unigene database. The hits were categorized into major classes of genes including ribosomal proteins, enzymes, cell surface molecules, secretory proteins, adhesion molecules, and immunoglobulins and were found to be differentially expressed in these tumorderived libraries. Genes known to be up-regulated in prostate, breast, and pancreatic carcinomas were discovered by DDD, demonstrating the utility of this technique. Two hundred known genes and 500 novel sequences were discovered to be differentially expressed in these select tumor-derived libraries. Test genes were validated for expression specificity by reverse transcription-PCR, providing a proof of concept for gene discovery by DDD. A comprehensive database of hits can be accessed at http:// www.fau.edu/cmbb/publications/cancergenes. htm. This solid tumor DDD database should facilitate target identification for cancer diagnostics and therapeutics.