Martin Braun

BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.

Prostate cancer (PCa) is the most prevalent cancer in men. Hyperactive STAT3 is thought to be oncogenic in PCa. However, targeting of the IL-6/STAT3 axis in PCa patients has failed to provide therapeutic benefit. Here we show that genetic inactivation of Stat3 or IL-6 signalling in a Pten-deficient PCa mouse model accelerates cancer progression leading to metastasis. Mechanistically, we identify p19(ARF) as a direct Stat3 target. Loss of Stat3 signalling disrupts the ARF-Mdm2-p53 tumour suppressor axis bypassing senescence. Strikingly, we also identify STAT3 and CDKN2A mutations in primary human PCa. STAT3 and CDKN2A deletions co-occurred with high frequency in PCa metastases. In accordance, loss of STAT3 and p14(ARF) expression in patient tumours correlates with increased risk of disease recurrence and metastatic PCa. Thus, STAT3 and ARF may be prognostic markers to stratify high from low risk PCa patients. Our findings challenge the current discussion on therapeutic benefit or risk of IL-6/STAT3 inhibition.

// Tim Müller 1, * , Martin Braun 1, * , Dimo Dietrich 1 , Seher Aktekin 1 , Simon Höft 1 , Glen Kristiansen 1 , Friederike Göke 2 , Andreas Schröck 2 , Johannes Brägelmann 3 , Stefanie A.E. Held 3 , Friedrich Bootz 2, * and Peter Brossart 3, * 1 Institute of Pathology, University Hospital Bonn, Bonn, Germany 2 Department of Otorhinolaryngology/Head and Neck Surgery, University Hospital Bonn, Bonn, Germany 3 Department of Oncology, Hematology and Rheumatology, University Hospital Bonn, Bonn, Germany * These authors have contributed equally to this work Correspondence to: Peter Brossart, email: Peter.Brossart@ukb.uni-bonn.de Keywords: PD-L1, prognostic biomarker, head and neck squamous cell carcinoma, immunohistochemistry Received: December 14, 2016     Accepted: March 17, 2017     Published: May 02, 2017 ABSTRACT Background: The PD-1 receptor and its ligands PD-L1 and PD-L2 are known to be significantly involved in T-cell regulation. Recent studies suggest that PD-L1 expression in malignant tumors contributes to an immunosuppressive microenvironment and disruption of antitumoral immune response. Drugs targeting this pathway are already tested in clinical trials against several tumor entities with promising results. However, until now comprehensive data with regard to PD-L1 and PD-L2 expression in head and neck squamous cell carcinoma (HNSCC) is still lacking. Patients and methods: We assessed PD-L1 and PD-L2 expression via immunohistochemistry in two independent cohorts of 293 HNSCC patients. Results: A significant subset of HNSCC showed high expression levels of PD-L1. Most remarkable, we detected a strong correlation between PD-L1 expression and overall survival time in both HNSCC cohorts. Further, in multivariate cox proportional hazard models, PD-L1 dominates as the strongest prognostic factor of patient’s outcome in HNSCC, leaving even tumor stage and distant metastasis behind. Moreover, strong PD-L1 expression was associated with the presence of distant metastases in a subset of cases. Conclusions: In summary, while the significance of PD-L2 in HNSCC seems to minor, we show that PD-L1 expression is common in HNSCC and, more importantly, a both robust and strong prognostic biomarker. In this respect, our results provide hints on further application of therapies targeting the PD-1/PD-L1 pathway in HNSCC. Investigation of response and outcome of patients receiving anti-PD-1/PD-L1 containing therapies in correlation with PD-L1 expression analysis should be an important task for the future. STATEMENT OF TRANSLATIONAL RELEVANCE In spite of improved treatment options and increasing knowledge of molecular alterations in HNSCC, the survival rate has not been dramatically changed in the past decades. Pies are missing in HNSCC. One promising candidate in cancer immune therapy is PD-L1. Drugs targeting PD-L1 or its receptor PD-1 are subject of several clinical studies in different cancer entities. However, comprehensive data about PD-L1 expression in HNSCC and therefore a rational basis for anti PD-L1/PD-1 therapy in HNSCC is lacking. Here, we provide wide-ranging data about PD-L1 expression in HNSCC of all major localizations. We observed a strong correlation between expression of PD-L1 and reduced overall survival time. Furthermore, high PD-L1 expression was identified as a strong prognostic factor of patient’s outcome when verified together with recognized prognostic factors.