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73 citation(s) found for "Zimmermann, B".

Abstract B46: Identification of biomarkers for stratification of Gleason score 7 patients using whole-transcriptome expression profiling
Erho, Nicholas , Sierocinski, Thomas , Davicioni, Elai , Jenkins, Robert B. , Gadhessi, Mercedeh, Buerki, Christine, Crisan, Anamaria, Haddad, Zaid , Zimmermann, Benedikt, Mitra, Anirban P., Vergara, Ismael A. , Triche, Timothy J. , Davicioni, Elai

Mayo Clinic

Cancer Research | May 9, 2013 | Volume: 72 | Issue: 4_Supplement | Pages: B46-B46

10.1158/1538-7445.prca2012-b46 Get It

Abstract Motivations: Gleason score is the most prognostic variable in prostate cancer pathology. Patients with high Gleason (8+) are the most likely to experience biochemical recurrence (BCR), clinical progression (CP) and prostate-cancer specific mortality (PCSM), whereas patients with Gleason ≤6 are expected to have excellent long-term outcomes. However, the majority of prostate cancer patients are diagnosed with Gleason score 7, a heterogeneous group in terms of patient outcomes. In the absence of adverse pathological factors (APF, such as preoperative PSA, SM+, ECE and SVI) most Gleason 7 patients will have excellent outcomes. In contrast, Gleason 7 patients with APF are considered at high-risk for recurrence and therefore are candidates for adjuvant therapy. In this study, we have investigated whether a classifier based on differentially expressed genomic features could be used to improve prognostication of Gleason 7 patients, independent of APF. Methods: Two whole-transcriptome (1.4 million feature) oligonucleotide microarray expression datasets from radical prostatectomy specimens were analyzed. The first one (GEO accession: GSE21032) consisted of 125 fresh frozen (FF) samples from the MSKCC Oncogenome Project and the second dataset had 545 formalin-fixed-paraffin- embedded (FFPE) samples from the Mayo Clinic tumor registry. For genomic feature selection, differential expression in the FF dataset between Gleason ≤6 (n=40) and ≥8 (n=15) was assessed with false discovery rate adjusted t-tests (p<0.05). Next, a k-nearest neighbor (KNN) classifier was trained and tuned using the selected features to predict clinical progression (i.e., positive bone or CT scans after BCR) in the FFPE dataset, again using samples with Gleason score ≤6 (n=63) and ≥8 (n=211). The KNN classifier was evaluated on Gleason score 7 (n=209) FFPE samples (not used for training) using multivariable logistic regression. Results: The KNN classifier segregated the Gleason 7 samples into high and low risk CP groups. The KNN odds ratios were 2.9 (p<0.005), 2.1 (p<0.05) and 2.8 (p<0.05) for BCR, CP and PCSM end-points, respectively when comparing high and low risk groups. Multivariable analysis revealed that the KNN classifier was independently prognostic. Conclusions: A KNN classifier developed using differentially expressed genomic features significantly stratified Gleason score 7 patients for several clinically relevant endpoints. Future validation studies will address the utility of this classifier in predicting pathological Gleason score from biopsy specimens, which may be particularly useful for evaluation of biopsy Gleason 6 cases. In these patients, deferring prostatectomy in favour of active surveillance is an appealing treatment option unless the ‘true’ Gleason of the index lesion is in fact a Gleason 7 or higher, where immediate surgery is likely a life-saving procedure. Citation Format: Nicholas Erho, Thomas Sierocinski, Elai Davicioni, Robert B. Jenkins, Mercedeh Gadhessi, Christine Buerki, Ismael A. Vergara, Anamaria Crisan, Zaid Haddad, Benedikt Zimmermann, Anirban Mitra, Timothy J. Triche. Identification of biomarkers for stratification of Gleason score 7 patients using whole-transcriptome expression profiling [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr B46.
Liver Cancer Protease Activity Profiles Support Therapeutic Options with Matrix Metalloproteinase–Activatable Oncolytic Measles Virus
Mühlebach, Michael D. , Schaser, Thomas , Armeanu, Sorin, Hanschmann, Kay-Martin O., Cattaneo, Roberto , Lauer, Ulrich M. , Cichutek, Klaus, Buchholz, Christian J. , Zimmermann, Martina , Bitzer, Michael

Mayo Clinic

Cancer Research | September 21, 2010 | Volume: 70 | Issue: 19 | Pages: 7620-7629

10.1158/0008-5472.can-09-4650 | PMID 20858718 Get It

Abstract Primary and secondary cancers of the liver are a significant health problem with limited treatment options. We sought here to develop an oncolytic measles virus (MV) preferentially activated in liver tumor tissue, thus reducing infection and destruction of healthy tissue. We documented that in primary tumor tissue, urokinase-type plasminogen activator and especially matrix metallproteinase-2 (MMP-2) are significantly more active than in adjacent nontumorous tissue. We then generated variants of the MV fusion protein by inserting different MMP substrate motifs at the protease cleavage site and identified the motif PQGLYA as the most efficient cleavage site as determined by syncytia formation on protease-positive tumor cells. The corresponding MMP-activatable oncolytic MV-MMPA1 virus was rescued and shown to be strongly restricted on primary human hepatocytes and healthy human liver tissue, while remaining as effective as the parental MV in the tumor tissue sections. Our findings underline the clinical potency of the MMP activation concept as a strategy to generate safer oncolytic viruses for the treatment of primary and secondary cancers of the liver. Cancer Res; 70(19); 7620–9. ©2010 AACR.