A characteristic of human gastroenteropancreatic neuroendocrine tumors (GEP-NET) is a minute unobtrusive primary tumor which often cannot be detected by common physical examinations. It therefore remains unidentified until the tumor has spread and space-occupying metastases cause clinical symptoms leading to diagnosis. Cases in which the primary cannot be located are referred to as NET with CUP-syndrome (cancer of unknown primary syndrome). With the help of array-CGH (comparative genomic hybridization, Agilent 105K) and gene expression analysis (Agilent 44K), microdissected primaries and their metastases were compared to identify up- and down-regulated genes which can be used as a marker for tumor progression. In a next analysis step, a hierarchical clustering of 41.078 genes revealed three genes [C-type lectin domain family 13 member A (CD302), peptidylprolyl isomerase containing WD40 repeat (PPWD1) and abhydrolase domain containing 14B (ABHD14B)] which expression levels can categorize the metastases into three groups depending on the localization of their primary. Because cancer therapy is dependent on the localization of the primary, the gene expression level of these three genes are promising markers to unravel the CUP syndrome in NET.

In oral mucosa lesions it is frequently difficult to differentiate between precursor lesions and already manifest oral squamous cell carcinoma. Therefore, multiple scalpel biopsies are necessary to detect tumor cells already in early stages and to guarantee an accurate follow-up. We analyzed oral brush biopsies (n = 49) of normal mucosa, inflammatory and hyperproliferative lesions, and oral squamous cell carcinoma with ProteinChip Arrays (SELDI) as a non-invasive method to characterize putative tumor cells. Three proteins were found that differentiated between these three stages. These three proteins are able to distinguish between normal cells and tumor cells with a sensitivity of 100% and specificity of 91% and can distinguish inflammatory/hyperproliferative lesions from tumor cells with a sensitivity of up to 91% and specificity of up to 90%. Two of these proteins have been identified by immunodepletion as S100A8 and S100A9 and this identification was confirmed by immunocytochemistry. For the first time, brush biopsies have been successfully used for proteomic biomarker discovery. The identified protein markers are highly specific for the distinction of the three analyzed stages and therewith reflect the progression from normal to premalignant non-dysplastic and finally to tumor tissue. This knowledge could be used as a first diagnostic step in the monitoring of mucosal lesions.

Pheochromocytoma (PCC) in children is rare, genetically not well described, and often related to a poor prognosis. We detected genomic imbalances in all 14 tumors from children analyzed by comparative genomic hybridization. A combinatorial loss of chromatin from 3p and 11p was a common feature in 10 of 14 (72%) patients, which was a result of either a loss of a total chromosome 3 and a total chromosome 11 in 6 of 10 patients, or confined deletions of their p arms in 4 of 10 patients. All patients exhibiting a loss of 3p and 11p carried VHL mutations. The VHL mutations were constitutive in 9 cases and somatic and restricted to tumor DNA in the remaining tumor. On the other hand, VHL mutations were absent in 4 patients, 2 who had other familial syndromes (NF1, SDHD) and 2 with unknown etiology. Our data show that the pattern of imbalances in the tumor DNA of PCC patients strongly correlated with an underlying familial VHL mutation. Furthermore, we show that true sporadic PCC is rare in childhood. Thus, children with PCC should be checked for a related predisposing gene. This would also identify familial syndrome patients requiring long-term monitoring for other syndrome-related malignancies.

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Our study highlights the cellular transdifferentiation within the pleomorphic adenoma. It could be shown that spatial segmentation of MALDI imaging data is a promising approach in the emerging field of digital histological analysis and characterization of tumors.