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Resistance to various antineoplastic agents is common in the clinical management of malignant melanoma. The biological mechanisms conferring these different drug-resistant phenotypes are still unclear. To identify potential factors mediating drug resistance to melanoma cells, the mRNA expression profiles of the parental drug-sensitive human melanoma cell line MeWo and four derived drug-resistant sublines with acquired resistance against four commonly used drugs for melanoma treatment (cisplatin, etoposide, fotemustine and vindesine) were analysed. We investigated cDNA arrays with 43,000 cDNA clones ( approximately 30,000 unique genes) to study the expression patterns of these cell lines. We were able to simultaneously extract new candidate genes associated with drug resistance in malignant melanoma and to correlate the present findings with previously described resistance-associated genes. Using hierarchical clustering and analysing the overlap of genes with altered expression, we detected similarities between the expression signatures related to cisplatin and fotemustine resistance. The resistance against vindesine required a minimal set of changes in gene expression relative to the parental MeWo cell line. Our study provides new data that may be used to obtain further insight into the resistance characteristics of malignant melanoma.

Many signal transduction processes converge on Ras proteins that serve as molecular switches to couple external stimuli with cytoplasmic and nuclear targets. Oncogenic mutations lock Ras proteins in their activated state. Cellular responses to permanent Ras activation such as the induction of neoplastic phenotypes are mediated by distinct transcriptional alterations. A number of studies have reported alterations of the genetic program because of short-term or long-term activation of Ras signaling pathways. However, a consistent pattern of Ras-related transcriptional alterations has not yet emerged, because currently available investigations were based on different methods for assessing mRNA expression profiles, on different types of cells, and on heterogeneous experimental conditions. Here we describe the "Ras signaling target array" (RASTA) representing approximately 300 Ras-responsive target genes. This customized oligonucleotide array is a universal tool for assessing transcriptional patterns of cells or tissues expressing oncogenic Ras genes, as well as upstream and downstream effectors. To validate the results obtained by array-based expression profiling, we have compared the data with those obtained by suppression subtractive hybridization and conventional expression analysis by Northern blotting. Target RNAs were prepared from preneoplastic rat ovarian surface epithelial cells (ROSE) and the KRAS-transformed derivative A2/5. By interrogating Ras signaling target arrays with mRNAs prepared from the same types of cells as hybridization target, we correctly recognized 85% of genes differentially expressed on conversion of normal ovarian epithelial cells to the Ras-transformed state.

Mutated genes of the RAS family encoding small GTP-binding proteins drive numerous cancers, including pancreatic, colon and lung tumors. Besides the numerous effects of mutant RAS gene expression on aberrant proliferation, transformed phenotypes, metabolism, and therapy resistance, the most striking consequences of chronic RAS activation are changes of the genetic program. By performing systematic gene expression studies in cellular models that allow comparisons of pre-neoplastic with RAS-transformed cells, we and others have estimated that 7 percent or more of all transcripts are altered in conjunction with the expression of the oncogene. In this context, the number of up-regulated transcripts approximates that of down-regulated transcripts. While up-regulated transcription factors such as MYC, FOSL1, and HMGA2 have been identified and characterized as RAS-responsive drivers of the altered transcriptome, the suppressed factors have been less well studied as potential regulators of the genetic program and transformed phenotype in the breadth of their occurrence. We therefore have collected information on downregulated RAS-responsive factors and discuss their potential role as tumor suppressors that are likely to antagonize active cancer drivers. To better understand the active mechanisms that entail anti-RAS function and those that lead to loss of tumor suppressor activity, we focus on the tumor suppressor HREV107 (alias PLAAT3 [Phospholipase A and acyltransferase 3], PLA2G16 [Phospholipase A2, group XVI] and HRASLS3 [HRAS-like suppressor 3]). Inactivating HREV107 mutations in tumors are extremely rare, hence epigenetic causes modulated by the RAS pathway are likely to lead to down-regulation and loss of function. [ABSTRACT FROM AUTHOR]

Because of the low overall response rates of 10–47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib at the clinically administered doses. A resistance matrix was determined, and gene expression profiles of the subsets of resistant vs. sensitive cell lines were compared. Triplicate gene expression signatures were obtained from the caArray project. Significance analysis of microarrays and rank products were applied for feature selection. Ninety-five genes were also measured by RT-PCR. In case of four sunitinib resistance associated genes, the results were validated in clinical samples by immunohistochemistry. A list of 63 top genes associated with resistance against the five tyrosine kinase inhibitors was identified. Quantitative RT-PCR analysis confirmed 45 of 63 genes identified by microarray analysis. Only two genes (ANXA3 and RAB25) were related to sensitivity against more than three inhibitors. The immunohistochemical analysis of sunitinib-treated metastatic renal cell carcinomas confirmed the correlation between RAB17, LGALS8, and EPCAM and overall survival. In summary, we determined predictive biomarkers for five tyrosine kinase inhibitors, and validated sunitinib resistance biomarkers by immunohistochemistry in an independent patient cohort. [ABSTRACT FROM AUTHOR]

Cellular signaling networks are subject to transcriptional and proteolytic regulation under both physiological and pathological conditions. For example, the expression of proteins subject to covalent modification by phosphorylation is known to be altered upon cellular differentiation or during carcinogenesis. However, it is unclear how moderate alterations in protein expression can bring about large changes in signal transmission as, for example, observed in the case of haploinsufficiency, where halving the expression of signaling proteins abrogates cellular function. By modeling a fundamental motif of signal transduction, the phosphorylation-dephosphorylation cycle, we show that minor alterations in the concentration of the protein subject to phosphorylation (or the phosphatase) can affect signal transmission in a highly ultrasensitive fashion. This "ultrasensitization" is strongly favored by substrate sequestration on the catalyzing enzymes, and can be observed with experimentally measured enzymatic rate constants. Furthermore, we show that coordinated transcription of multiple proteins (i.e., synexpression) within a protein kinase cascade results in even more pronounced all-or-none behavior with respect to signal transmission. Finally, we demonstrate that ultrasensitization can account for specificity and modularity in the regulation of cellular signal transduction. Ultrasensitization can result in all-or-none cell-fate decisions and in highly specific cellular regulation. Additionally, switch-like phenomena such as ultrasensitization are known to contribute to bistability, oscillations, noise reduction, and cellular heterogeneity. [ABSTRACT FROM AUTHOR]

To understand the relationship between oncogenic signaling and the reprogramming of gene expression, we performed transcriptional profiling in rat ovarian surface epithelial cells (ROSE), in which neoplastic transformation is driven by a mutated KRAS oncogene. We identified >200 genes whose expression was elevated or reduced following permanent KRAS expression. Deregulated KRAS-responsive genes encode transcriptional regulators, signaling effectors, proteases, extracellular matrix and adhesion proteins, transformation-suppressing proteins and negative growth regulators. Many of them have not been previously identified in cells expressing oncogenic RAS genes or in other well-studied models of oncogenic signaling. The number of critical genes related to the execution of anchorage-independent proliferation and epithelial-mesenchymal transition was narrowed down to 79 by selectively inhibiting the mitogen-activated protein kinase (MAPK/ERK) and phosphatidylinositol 3-kinase (PI3K) pathways. Blocking MAPK/ERK-signaling caused reversion to the normal epithelial phenotype in conjunction with the reversal of deregulated target transcription to pretransformation levels. In addition, silencing of the overexpressed transcriptional regulator Fra-1 by RNA interference resulted in growth reduction, suggesting that this factor partially contributes to, but is not sufficient for the proliferative capacity of KRAS-transformed epithelial cells.Oncogene (2004) 23, 4536-4555. doi:10.1038/sj.onc.1207585 Published online 5 April 2004 [ABSTRACT FROM AUTHOR]

The signal-transducing Ras proteins are important driving forces of diverse cellular processes such as proliferation, neoplastic transformation, differentiation and growth inhibition. As a step toward understanding the complex mechanisms underlying cellular responses, gene expression patterns were examined in two phenotypically normal fibroblast lines which differ in their sensitivity toward oncogene-mediated transformation. Suppression subtractive hybridization (SSH) was used to establish a subtracted cDNA library specific for the REF52 cell line which, like normal diploid fibroblasts, is refractory toward neoplastic transformation induced by mutated HRAS oncogenes. In contrast, rat 208F control cells can be efficiently transformed by HRAS. The nucleotide sequence of 549 subtracted cDNA clones (`REF52 minus 208F') was determined. We identified 93 preferentially expressed gene fragments in resistant REF52 cells as compared to 208F cells. Seventeen of the 52 known genes (32.6%) are capable of inhibiting cell proliferation or of adversely affecting oncogenic signal transduction pathways. These results suggest that the anti-oncogenic properties of resistant REF52 cells are determined by multiple negative growth regulators. The preneoplastic state expressed in 208F cells is characterized by impairment of unexpectedly redundant control mechanisms. Our results also demonstrate that SSH is a powerful method for identifying specific transcriptional patterns in closely related cell types. [ABSTRACT FROM AUTHOR]

The H-rev107 tumour suppressor was isolated as a gene specifically expressed in rat fibroblasts resistant toward malignant transformation by the activated HRAS gene (; ). Here we describe the human homologue of the rat H-rev107 gene. The predicted rat and human proteins are highly conserved exhibiting an overall amino acid identity of 83%. The H-REV107-1 gene is ubiquitously expressed with the exception of haematopoetic cells and tissues. In contrast, H-REV107-1 mRNA was found only in eight of 27 cell lines derived from mammary carcinoma, lung carcinoma, gastric carcinoma, kidney carcinoma, melanoma, neuroblastoma and other tumours. The H-REV107-1 protein was not detectable in any of these tumour cells. Loss of H-REV107-1 expression was not restricted to cultured human tumour cell lines, but also found in primary squamous cell carcinomas. Gross structural aberrations of the H-REV107-1 gene were absent in tumorigenic cell lines. Thus, the block to H-REV107-1 expression is achieved both at the level of transcription and translation. By fluorescence in situ hybridisation the human H-REV107-1 gene was localised to chromosome 11q11-12. [ABSTRACT FROM AUTHOR]