Assessment of a low skeletal muscle mass (SM) is important for diagnosis of ageing and disease-associated sarcopenia and is hindered by heterogeneous methods and terminologies that lead to differences in diagnostic criteria among studies and even among consensus definitions. The aim of this review was to analyze and summarize previously published cut-offs for SM applied in clinical and research settings and to facilitate comparison of results between studies. Multiple published reference values for discrepant parameters of SM were identified from 64 studies and the underlying methodological assumptions and limitations are compared including different concepts for normalization of SM for body size and fat mass (FM). Single computed tomography or magnetic resonance imaging images and appendicular lean soft tissue by dual X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) are taken as a valid substitute of total SM because they show a high correlation with results from whole body imaging in cross-sectional and longitudinal analyses. However, the random error of these methods limits the applicability of these substitutes in the assessment of individual cases and together with the systematic error limits the accurate detection of changes in SM. Adverse effects of obesity on muscle quality and function may lead to an underestimation of sarcopenia in obesity and may justify normalization of SM for FM. In conclusion, results for SM can only be compared with reference values using the same method, BIA- or DXA-device and an appropriate reference population. Limitations of proxies for total SM as well as normalization of SM for FM are important content-related issues that need to be considered in longitudinal studies, populations with obesity or older subjects.

Introduction: Sphingosine-1-phosphate (S1P) is a signaling lipid that regulates pathophysiological processes involved in sepsis progression, including endothelial permeability, cytokine release, and vascular tone. The aim of this study was to investigate whether serum-S1P concentrations are associated with disease severity in patients with sepsis. Methods: This single-center prospective-observational study includes 100 patients with systemic inflammatory response syndrome (SIRS) plus infection (n = 40), severe sepsis (n = 30), or septic shock (n = 30) and 214 healthy blood donors as controls. Serum-S1P was measured by mass spectrometry. Blood parameters, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), lactate, and white blood cells (WBCs), were determined by routine assays. The Sequential Organ Failure Assessment (SOFA) score was generated and used to evaluate disease severity. Results: Serum-S1P concentrations were lower in patients than in controls (P < 0.01), and the greatest difference was between the control and the septic shock groups (P < 0.01). Serum-S1P levels were inversely correlated with disease severity as determined by the SOFA score (P < 0.01) as well as with IL-6, PCT, CRP, creatinine, lactate, and fluid balance. A receiver operating characteristic analysis for the presence or absence of septic shock revealed equally high sensitivity and specificity for S1P compared with the SOFA score. In a multivariate logistic regression model calculated for prediction of septic shock, S1P emerged as the strongest predictor (P < 0.001). Conclusions: In patients with sepsis, serum-S1P levels are dramatically decreased and are inversely associated with disease severity. Since S1P is a potent regulator of endothelial integrity, low S1P levels may contribute to capillary leakage, impaired tissue perfusion, and organ failure in sepsis.

Extracellular vesicles (EVs) are known for their important role in cancer progression and hold considerable potential as a source for tumor biomarkers. However, purification of tumor-specific EVs from patient plasma is still an urgent unmet need due to contamination by normal host cell-derived EVs, that results in compromised analytical sensitivity. Here we identified fatty acid synthase (FASN), a key lipogenic enzyme which is highly expressed in malignant glioma cells, to be elevated in CD63- and CD81-positive EVs in glioma patient plasma samples, opening vital opportunities to sort brain tumor-specific EVs.

Circulating tumor cells (CTCs) are promising tools for risk prediction and the monitoring of response to therapy in cancer patients. Within the EU/IMI CANCER-ID consortium, we validated CTC enrichment systems for future inclusion into clinical trials. Due to the known heterogeneity of markers expressed on CTCs, we tested the Parsortix^® system (ANGLE plc) which enables label-independent CTC enrichment from whole blood based on increased size and deformability of these tumor cells compared to leukocytes. We performed extensive comparisons both with spiked-in blood models (i.e., MDA-MB-468 tumor cell line cells spiked at very low concentration into blood from healthy donors) and validated the protocol on actual clinical samples from breast, lung, and gastrointestinal cancer patients to define optimal conditions for CTC enrichment. Multiple parameters including cassette gap, separation pressure, and cell fixatives were compared in parallel. Also, the compatibility of blood collection tubes with whole genome amplification of isolated tumor cells was demonstrated and we furthermore established a workflow for semi-automated CTC detection using a quantitative cell imager. The established workflow will contribute to supporting the use of size-based CTC enrichment platforms in clinical trials testing the clinical validity and utility of CTCs for personalized medicine.

Keratins are the main identification markers of circulating tumor cells (CTCs); however, whether their deregulation is associated with the metastatic process is largely unknown. Previously we have shown by in silico analysis that keratin 16 (KRT16) mRNA upregulation might be associated with more aggressive cancer. Therefore, in this study, we investigated the biological role and the clinical relevance of K16 in metastatic breast cancer. By performing RT-qPCR, western blot, and immunocytochemistry, we investigated the expression patterns of K16 in metastatic breast cancer cell lines and evaluated the clinical relevance of K16 expression in CTCs of 20 metastatic breast cancer patients. High K16 protein expression was associated with an intermediate mesenchymal phenotype. Functional studies showed that K16 has a regulatory effect on EMT and overexpression of K16 significantly enhanced cell motility (p < 0.001). In metastatic breast cancer patients, 64.7% of the detected CTCs expressed K16, which was associated with shorter relapse-free survival (p = 0.0042). Our findings imply that K16 is a metastasis-associated protein that promotes EMT and acts as a positive regulator of cellular motility. Furthermore, determining K16 status in CTCs provides prognostic information that helps to identify patients whose tumors are more prone to metastasize.

Despite remarkable progress in melanoma therapy, the exceptional heterogeneity of the disease has prevented the development of reliable companion biomarkers for the prediction or monitoring of therapy responses. Here, we show that difficulties in detecting blood-based markers, like circulating tumor cells (CTC), might arise from the translation of the mutational heterogeneity of melanoma cells towards their surface marker expression. We provide a unique method, which enables the molecular characterization of clinically relevant CTC subsets, as well as circulating tumor DNA (ctDNA), from a single blood sample. The study demonstrates the benefit of a combined analysis of ctDNA and CTC counts in melanoma patients, revealing that CTC subsets and ctDNA provide synergistic real-time information on the mutational status, RNA and protein expression of melanoma cells in individual patients, in relation to clinical outcome.