High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification.

BACKGROUND: High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterogeneity, but the lack of strong prognostic or predictive correlations with these subtypes currently hinders their clinical implementation. Stromal admixture profoundly affects the prognostic impact of the molecular subtypes, but the contribution of stromal cells to each subtype has poorly been characterised. Increasing the transcriptomic resolution of the molecular subtypes based on single-cell RNA sequencing (scRNA-seq) may provide insights in the prognostic and predictive relevance of these subtypes. METHODS: We performed scRNA-seq of 18,403 cells unbiasedly collected from 7 treatment-naive HGSTOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. We explored which phenotypic clusters correlated with overall survival based on expression of these transcriptomic markers in microarray data of 1467 tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype. RESULTS: We identified 11 cancer and 32 stromal cell phenotypes in HGSTOC tumours. Of these, the relative frequency of myofibroblasts, TGF-ß-driven cancer-associated fibroblasts, mesothelial cells and lymphatic endothelial cells predicted poor outcome, while plasma cells correlated with more favourable outcome. Moreover, we identified a clear cell-like transcriptomic signature in cancer cells, which correlated with worse overall survival in HGSTOC patients. Stromal cell phenotypes differed substantially between molecular subtypes. For instance, the mesenchymal, immunoreactive and differentiated signatures were characterised by specific fibroblast, immune cell and myofibroblast/mesothelial cell phenotypes, respectively. Cell phenotypes correlating with poor outcome were enriched in molecular subtypes associated with poor outcome. CONCLUSIONS: We used scRNA-seq to identify stromal cell phenotypes predicting overall survival in HGSTOC patients. These stromal features explain the association of the molecular subtypes with outcome but also the latter's weakness of clinical implementation. Stratifying patients based on marker genes specific for these phenotypes represents a promising approach to predict prognosis or response to therapy.

Transplacental transport of paracetamol and its phase II metabolites using the ex vivo placenta perfusion model.

In Europe, 50-60% of pregnant women uses paracetamol (PCM), also known as acetaminophen. While it was considered to be safe, recent studies have shown an association between prenatal exposure to PCM and increased incidences of autism, cryptorchidism, asthma and ADHD. In this study the transplacental transfer of PCM and its metabolites was investigated using an ex vivo human placenta perfusion model (closed circuit; n = 38). Maternal-to-foetal (M-F) and foetal-to-maternal (F-M) transplacental transfer was determined at a concentration correlating with the maximum and steady state concentration in normal clinical use. Antipyrine (AP) was added as reference compound. Samples of the foetal and maternal perfusion medium were taken until 210 (PCM) or 360 min (paracetamol sulphate (PCM-S) and paracetamol glucuronide (PCM-G). PCM and AP concentrations reached an equilibrium between foetal and maternal compartments within the duration of the perfusion experiment and irrespective of the transfer direction. The percentage placental transfer of PCM was 45% (M-F and F-M). For PCM-S, transfer was 39% (M-F) and 28% (F-M), while the PCM-G transfer was 34% (M-F) and 25% (F-M). During placenta perfusions with the metabolites slight conversion (3.5-4.1%) to PCM was observed. In conclusion, PCM crosses the placental barrier rapidly via passive diffusion. Differences in flow rate and villous placental structure explain the significantly faster M-F transfer than F-M transfer of PCM. The larger and more hydrophilic molecules PCM-S and PCM-G cross the placenta at a significantly lower rate. Moreover, their F-M transport is about 40% slower than M-F transport, suggesting involvement of a transporter.