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Loss of fat mass is a key feature of cancer cachexia and has been attributed to increased adipocyte lipolysis. The mechanism behind this alteration is unknown and was presently investigated. We studied mature s.c. fat cells and differentiated preadipocytes from 26 cancer patients with and without cachexia. Hormone-induced lipolysis and expression of lipolysis-regulating genes were determined together with body composition and in vivo lipolytic activity (fasting plasma glycerol or fatty acids related to body fat). Body fat was reduced by 40% and in vivo lipolytic activity was 2-fold increased in cachexia (P = 0.001). In mature adipocytes, the lipolytic effects of catecholamines and natriuretic peptide were 2- to 3-fold increased in cachexia (P < 0.001). This was completely counteracted by inhibiting the rate-limiting lipolysis enzyme hormone-sensitive lipase (HSL). In cachexia, the expression levels of HSL mRNA and protein were increased by 50% and 100%, respectively (P = 0.005–0.03), which strongly correlated with in vitro lipolytic stimulation (r = 0.7–0.9). The antilipolytic effect of insulin in mature fat cells and the stimulated lipolytic effect in differentiated preadipocytes were unaltered in cachexia. Patients who lost weight due to other factors than cancer cachexia had no change in adipocyte lipolysis. In conclusion, adipocyte lipolysis is increased in cancer cachexia not due to nonepigenic factors or to weight loss per se, but most probably because of enhanced expression and function of adipocyte HSL. The selective inhibition of this enzyme may prevent fat loss in cancer patients. [Cancer Res 2007;67(11):5531–7]

Background. For many tumors, therapeutic options are sparse beyond the guidelines, especially for pancreatic cancer. At the same time, more and more biomarkers are known, informing about or supporting treatment decisions. Finally, tumor DNA analysis with next generation sequencing (NGS) is quickly becoming a routine test, at least for tumors. However, to analyse the vast amount of data and provide concrete, evidence-based treatment recommendations has been a challenge. Methods. Applying NGS in a quality controlled set-up together with the newly developed evidence-based software tool EngineusGUIDETM (CE-marked). Results. During the time from Oct 2013 until Oct 2015, 87 patients were analysed with EngineusGUIDE. In 7 cases, more than one tumor was investigated. NGS was performed (WXS = 48; panel/paired = 16, panel = 23). Sequencing could be performed in all but one patient (Whole Exome; bone metastasis). Sequencing quality was insufficient for analysis in 3 cases (paired panel), sequencing revealed insufficient tumor content in the sample for one patient (Whole Exome) leaving 82 patients. The indication was: Pancreatic Neoplasms = 21 cases; Colorectal Neoplasms = 12; Breast Neoplasms = 5; CUP = 6; NSCLC = 3; 2 cases each for Bronchial Neoplasms, Adenoid Cystic Carcinoma, Common Bile Duct Neoplasms, Glioblastoma, Multiple Myeloma, Prostatic Neoplasms and 1 case each for Adenocarcinoma, Duodenal Neoplasms, Endometrial Neoplasms, Hemangiosarcoma, Hypopharyngeal Neoplasms, Leukemia (Lymphocytic, Chronic, B-Cell), Liposarcoma, Liver Neoplasms, Lung Neoplasms, B-Cell Lymphoma, Mantle-Cell Lymphoma, Meningioma, Oropharyngeal Neoplasms, Ovarian Neoplasms, Paranasal Sinus Neoplasms, Parathyroid Neoplasms, Sarcoma, Sigmoid Neoplasms, Squamous Cell Neoplasms, Stomach Neoplasms, Thyroid Neoplasms, Urinary Bladder Neoplasms, Uveal melanoma. In 67/82 patients, druggable targets (response biomarkers) could be identified (range 0-8; median 2). In 45/82 patients (range 0-5; median 1) biomarkers indicated lack of efficacy (e.g. KRAS mutation in CRC). In 65/82 patients, biomarkers indicated increased toxicity (range 0-7; median 2), in 19/82 patients FDA-approved biomarkers for toxicity were detected (28 biomarkers). Of the positive biomarkers, 40 biomarkers in 26 patients indicated drugs approved in the indication, 75 biomarkers in 45 patients indicated approved drugs, and 58 biomarkers in 39 patients indicated experimental drugs (pre-clinical and phase I - III). Six patients have already received drugs recommended by EngineusGUIDE. In 11 patients, toxicity markers may explain observed toxicity during previous treatment. We are currently collecting the outcome parameters of EngineusGUIDE recommendations. Citation Format: Matthias Löhr, Katrin Stecker, Caroline Huelsewig, Sandra Morandell, Isin Ertongur, Sarah Luke-Glaser, Anna Laib, Linnéa Malgerud, Carlos Fernández Moro, Masoud Karimi, Johan Permert, Rainer Heuchel, Johan Lindberg, Valtteri Wirta, Alexander Picker, Marco Del Chiaro, Stephan L. Haas, Caroline S. Verbek, Lars Engstrand, Jens Siveke, David Jackson, Henrik Grönberg, Dirk Jäger, Stephan Brock. An evidence-based software tool for personalized cancer medicine to recommend therapeutic options and avoid toxicity. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3165.