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G protein-coupled receptors (GPCRs) are one of the largest protein families in mammals. They mediate signal transduction across cell membranes and are important targets for the pharmaceutical industry. The G Protein-Coupled Receptors-Sequence Analysis and Statistics (GPCR-SAS) web application provides a set of tools to perform comparative analysis of sequence positions between receptors, based on a curated structural-informed multiple sequence alignment. The analysis tools include: (i) percentage of occurrence of an amino acid or motif and entropy at a position or range of positions, (ii) covariance of two positions, (iii) correlation between two amino acids in two positions (or two sequence motifs in two ranges of positions), and (iv) snake-plot representation for a specific receptor or for the consensus sequence of a group of selected receptors. The analysis of conservation of residues and motifs across transmembrane (TM) segments may guide the design of more selective ligands or help to rationalize activation mechanisms, among others. As an example, here we analyze the amino acids of the "transmission switch", that initiates receptor activation following ligand binding. The tool is freely accessible at http://lmc.uab.cat/gpcrsas/., Competing Interests: The authors have declared that no competing interests exist.

Epithelial ovarian cancer is a highly heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Therapeutic approaches need to account for inter-patient and intra-tumoural heterogeneity and detailed characterization of in vitro models representing the different histological and molecular ovarian cancer subtypes is critical to enable reliable preclinical testing. There are approximately 100 publicly available ovarian cancer cell lines but their cellular and molecular characteristics are largely undescribed. We have characterized 39 ovarian cancer cell lines under uniform conditions for growth characteristics, mRNA/microRNA expression, exon sequencing, drug response for clinically-relevant therapeutics and collated all available information on the original clinical features and site of origin. We tested for statistical associations between the cellular and molecular features of the lines and clinical features. Of the 39 ovarian cancer cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes: Epithelial (n = 21), Round (n = 7) and Spindle (n = 12) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes in the Spindle subtype. Comparison with the original clinical data showed association of the spindle-like tumours with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the expression profiles of Spindle, Round and Epithelial morphologies clustered with the previously described C1-stromal, C5-mesenchymal and C4 ovarian subtype expression profiles respectively. Comprehensive profiling of 39 ovarian cancer cell lines under controlled, uniform conditions demonstrates clinically relevant cellular and genomic characteristics. This data provides a rational basis for selecting models to develop specific treatment approaches for histological and molecular subtypes of ovarian cancer.