R. Pilchowski

Specific Protein Patterns Characterize Metastatic Potential of Advanced Bladder Cancer

PURPOSE The prognosis in patients with metastasized bladder cancer is still poor. Clinical and histopathological parameters have limited ability to predict the risk of tumor progression. Thus, we identified specific protein patterns associated with tumor progression to differentiate specimens with and without metastasis. MATERIALS AND METHODS We analyzed 46 metastasized and 42 nonmetastasized muscle invasive bladder cancers by ProteinChip® technology surface enhanced laser desorption/ionization time of flight mass spectrometry. Cell lysis was done after laser capture microdissection from cryostat sections to achieve high tumor cell purity. Surface enhanced laser desorption/ionization time of flight mass spectrometry was completed with 2 matrices (Q10 and CM10). Bioinformatic analysis was performed by XLMiner® clustering using the Fuzzy c-means method. Differentially expressed proteins were identified and verified by 2-dimensional gel electrophoresis, tryptic in gel digest, peptide mapping, immunodepletion assay and Western blot analysis. RESULTS By combining data on 2 chip surfaces (Q10 and CM10) results showed 86% sensitivity and 89% specificity in the training set, and 63% sensitivity and 88% specificity in the validation set. The relevant protein peaks 10.83, 14.68, 16.15 and 27.85 Da were identified as S100A8, MAP-1LC3, MUC-1S1 and GST-M1, respectively. CONCLUSIONS We defined specific protein patterns with ProteinChip technology using bioinformatic evaluation software, which allowed differentiation between nonmetastasized and metastasized bladder tumor samples with high sensitivity and specificity. We identified 4 differentially expressed proteins. Thus, it seems possible to identify patients at high metastasized risk even at a clinically localized stage, leading to individual therapy decisions.

Immunochemotherapy-associated protein patterns in tumour tissue and serum of patients with metastatic renal cell carcinoma.

Context: Systemic treatment of metastatic renal cell carcinoma (mRCC) with targeted therapies became widely accepted; however, there are few patients who greatly benefit from immunochemotherapy (ICT). It is crucial to recognize these patients for individual treatment. Objectives: Definition of protein patterns in tissue and serum from mRCC-patients to predict benefit from ICT. Materials and methods: Twenty-five tissue samples and 59 sera were analysed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Protein peaks of interest were identified by 2D-PAGE and peptide mass fingerprinting. Validation was carried out by Western Blot and ELISA. Results: Protein patterns associated with therapy response were determined. Caveolin-1 (CAV-1) and plasminogen activator inhibitor 1 (PAI-1) were identified in tissue; serum amyloid A (SAA) and transthyretin (TTR) were found in serum. Conclusion: Individual prediction of therapy benefit and selecting patients for ICT based on molecular biological profiles appear to be feasible in the future.

Molekulares Tumorprofiling von Nierenzelltumoren: Relevanz für Diagnostik und Therapie

ZusammenfassungMolekularbiologische Tumormarker und Prognoseparameter sind Voraussetzung für eine differenzierte Diagnostik und daraus resultierend für eine individuelle Prognosebewertung und Therapiewahl auch für Patienten mit Nierenzelltumoren (NZK). Es ist heute möglich, Tumoren sehr komplex unter Einsatz von Hochdurchsatzverfahren zu charakterisieren. Durch genetische Analysen konnten die einzelnen histopathologisch definierten Subtypen der Nierenzelltumoren als eigenständige Tumorentitäten definiert werden. Die genetischen Merkmale der einzelnen Subtypen können heute zur Diagnosesicherung am Tumormaterial, aber auch an der Biopsie eingesetzt werden. Darüber hinaus ist es möglich, metastasierungsspezifische molekulare Muster zu definieren, die zukünftig die Bewertung des Metastasierungspotenzials bereits am Primärtumor erlauben. Durch Proteomanalysen im Serum wurden spezifische Proteinmuster im Serum definiert und daraus ableitend erste Kandidatenproteine, die als Biomarker dienen könnten, identifiziert. Hierzu zählt das SAA-1, welches bei Patienten mit klarzelligen Nierenzellkarzinomen erhöht vorliegt. Da neue Therapeutika für Patienten mit metastasierten NZK zur Verfügung stehen, ist es notwendig, Patienten für die effektivste Therapie zu selektieren und frühzeitig das Therapieversagen zu erkennen. Es konnten Biomarker im Tumorgewebe und im Serum identifiziert werden, die mit dem Therapieansprechen korrelieren.AbstractMolecular biological tumor markers and prognostic parameters are necessary for differential diagnosis, individual prognosis, and therapy in patients with renal cell tumors. By using high throughput technologies, it is possible to characterize tumor samples comprehensively. Based on specific genetic alterations, histopathological subtypes were defined as independent tumor entities. Genetic characteristics can be used for diagnosis of primary tumor samples and also of biopsies. Furthermore, specific molecular patterns of metastatic tumors are known, allowing the determination of the primary tumor’s metastatic potential. The specific protein patterns of serum samples of tumor patients were analyzed, and several candidate proteins have been identified. One of these is SAA-1, which is elevated in patients with clear cell renal cell carcinomas (RCC). New therapeutic options are now available for patients with metastatic RCC. Therefore, it is necessary to select the best therapy for each patient and to detect therapy resistance very early. Biomarkers in tumor tissue and serum were found to correlate with therapy response.