Successful tumor development and progression involves the complex interplay of both pro- and anti-oncogenic signaling pathways. Genetic components balancing these opposing activities are likely to require tight regulation, because even subtle alterations in their expression may disrupt this balance with major consequences for various cancer-associated phenotypes. Here, we describe a cassette of cancer-specific genes exhibiting precise transcriptional control in solid tumors. Mining a database of tumor gene expression profiles from six different tissues, we identified 48 genes exhibiting highly restricted levels of gene expression variation in tumors (n = 270) compared to nonmalignant tissues (n = 71). Comprising genes linked to multiple cancer-related pathways, the restricted expression of this “Poised Gene Cassette” (PGC) was robustly validated across 11 independent cohorts of ∼1,300 samples from multiple cancer types. In three separate experimental models, subtle alterations in PGC expression were consistently associated with significant differences in metastatic and invasive potential. We functionally confirmed this association in siRNA knockdown experiments of five PGC genes (p53CSV, MAP3K11, MTCH2, CPSF6, and SKIP), which either directly enhanced the invasive capacities or inhibited the proliferation of AGS cancer cells. In primary tumors, similar subtle alterations in PGC expression were also repeatedly associated with clinical outcome in multiple cohorts. Taken collectively, these findings support the existence of a common set of precisely controlled genes in solid tumors. Since inducing small activity changes in these genes may prove sufficient to potently influence various tumor phenotypes such as metastasis, targeting such precisely regulated genes may represent a promising avenue for novel anti-cancer therapies.

Recurrent genomic amplifications and deletions are frequently observed in primary gastric cancers (GC). However, identifying specific oncogenes and tumor suppressor genes within these regions can be challenging, as they often cover tens to hundreds of genes. Here, we combined high-resolution array-based comparative genomic hybridization (aCGH) with gene expression profiling to target genes within focal high-level amplifications in GC cell lines, and identified RAB23 as an amplified and overexpressed Chr 6p11p12 gene in Hs746T cells. High RAB23 protein expression was also observed in some lines lacking RAB23 amplification, suggesting additional mechanisms for up-regulating RAB23 besides gene amplification. siRNA silencing of RAB23 significantly reduced cellular invasion and migration in Hs746T cells, whereas overexpression of RAB23 enhanced cellular invasion in AGS cells. RAB23 amplifications in primary gastric tumors were confirmed by both fluorescence in situ hybridization and genomic qPCR, and in two independent patient cohorts from Hong Kong and the United Kingdom RAB23 expression was significantly associated with diffuse-type GC (dGC) compared with intestinal-type GC (iGC). These results provide further evidence that dGC and iGC likely represent two molecularly distinct tumor types, and show that investigating focal chromosomal amplifications by combining highresolution aCGH with expression profiling is a powerful strategy for identifying novel cancer genes in regions of recurrent chromosomal aberration. [Cancer Res 2008;68(12): 4623-30]

The identification of specific oncogenes and tumor suppressor genes in regions of recurrent aneuploidy is a major challenge of molecular cancer research. Using both oligonucleotide single-nucleotide polymorphism and mRNA expression arrays, we integrated genomic and transcriptional information to identify and prioritize candidate cancer genes in regions of increased and decreased chromosomal copy number in a cohort of primary breast cancers. Confirming the validity of this approach, several regions of previously-known copy number (CN) alterations in breast cancer could be successfully reidentified. Focusing on regions of decreased CN, we defined a prioritized list of eighteen candidate genes, which included ARPIN, FBN1, and LZTS1, previously shown to be associated with cancers in breast or other tissue types, and novel genes such as P29, MORF4L1, and TBC1D5. One such gene, the RUNX3 transcription factor, was selected for further study. We show that RUNX3 is present at reduced CNs in proportion to the rest of the tumor genome and that RUNX3 CN reductions can also be observed in a breast cancer series from a different center. Using tissue microarrays, we demonstrate in an independent cohort of over 120 breast tissues that RUNX3 protein is expressed in normal breast epithelium but not fat and stromal tissue, and widely down-regulated in the majority of breast cancers (>85%). In vitro, RUNX3 overexpression suppressed the invasive potential of MDA-MB-231 breast cancer cells in a matrigel assay. Our results demonstrate the utility of integrative genomic approaches to identify novel potential cancer-related genes in primary tumors. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.