Over the past 20 years, significant success in the therapy of certain cancer types has given rise to the hope that cancer will soon be curable. However, it is becoming evident that many tumor types, which were previously regarded as homogeneous disease entities, are composed of different subtypes with varying patient prognosis and survival rates. These findings may explain the varying degrees of success in cancer treatment. Since classical pathological parameters are often not sufficient to identify tumor subtypes, novel markers for tumor diagnosis and new targets for differential tumor therapies are required.

Adult renal cell carcinoma (RCC) is one of the 10 most common human malignancies in developed countries. Its global incidence has been increasing continuously over the past 30 years (1). Males are afflicted twice as often compared to females, and several genetic factors, such as the von Hippel Lindau (VHL) gene are known to play a role in a subset of RCC. Apart from these typical markers, other genes known to be involved in RCC include VEGF (2, 3), EGFR (4, 5), TGFA (6), c-myc proto-oncogene (7, 8) and VIM (9). RCC is divided into clear cell (ccRCC; 80% of all cases), papillary (pRCC, 10%), chromophobe (chRCC, 5%), and several other rare types. Although the histopathological diagnosis of kidney cancer is well established in the clinical routine, the molecular basis for the distinction of RCC types is poorly understood.

New technologies to examine tissue samples taken from cancer patients on a large scale have been developed in the genome projects. In particular, DNA microarrays have been applied to various kinds of human tumors (10-18) in order to find new cancer subclasses and to decipher their molecular basis. However, there is an important issue associated with the discovery of gene expression patterns to be used for diagnostic purposes. The number of available tumor samples usually is much smaller (10-300)

than the number of available probes (10 000-50 000). Therefore, special attention should be devoted to avoiding over-interpretation of microarray data. Analysis of differential gene expression has to account for multiple testing, and classification methods must address the problem of overfitting (see also Chapter 19). We propose the usage of various classification methods for microarray data analysis in order to reduce the risk of overinterpretation. We constructed RCC-specific cDNA microarrays encompassing 4207 cDNA clones and hybridized these with labeled cDNA derived from tumor samples of the three major RCC types. By using the microarray data of 35 RCC samples, we identified a set of 18 genes that are potentially useful for diagnosis and therapy of kidney tumors.

10 Ways To Fight Off Cancer

10 Ways To Fight Off Cancer

Learning About 10 Ways Fight Off Cancer Can Have Amazing Benefits For Your Life The Best Tips On How To Keep This Killer At Bay Discovering that you or a loved one has cancer can be utterly terrifying. All the same, once you comprehend the causes of cancer and learn how to reverse those causes, you or your loved one may have more than a fighting chance of beating out cancer.

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