Cancer-associated fibroblasts (CAFs) are a major constituent of the tumor microenvironment, although their origin and roles in shaping disease initiation, progression and treatment response remain unclear due to significant heterogeneity. Here, following a negative selection strategy combined with single-cell RNA sequencing of 768 transcriptomes of mesenchymal cells from a genetically engineered mouse model of breast cancer, we define three distinct subpopulations of CAFs. Validation at the transcriptional and protein level in several experimental models of cancer and human tumors reveal spatial separation of the CAF subclasses attributable to different origins, including the peri-vascular niche, the mammary fat pad and the transformed epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs and hold independent prognostic capability in clinical cohorts by association to metastatic disease. In conclusion, the improved resolution of the widely defined CAF population opens the possibility for biomarker-driven development of drugs for precision targeting of CAFs.

Aquaporins are water channel proteins belonging to the major intrinsic protein (MIP) superfamily of membrane proteins. More than 150 MIPs have been identified in organisms ranging from bacteria to animals and plants. In plants, aquaporins are present in the plasma membrane and in the vacuolar membrane where they are abundant constituents. Functional studies of aquaporins have hitherto mainly been performed by heterologous expression in Xenopus oocytes. A main issue is now to understand their role in the plant, where they are likely to be important both at the cellular and at the whole plant level. Plants contain a large number of aquaporin isoforms with distinct cell type- and tissue-specific expression patterns. Some of these are constitutively expressed, whereas the expression of others is regulated in response to environmental factors, such as drought and salinity. At the protein level, regulation of water transport activity by phosphorylation has been reported for some aquaporins.

BackgroundBreast cancer exhibits significant molecular, pathological, and clinical heterogeneity. Current clinicopathological evaluation is imperfect for predicting outcome, which results in overtreatment for many patients, and for others, leads to death from recurrent disease. Therefore, additional criteria are needed to better personalize care and maximize treatment effectiveness and survival.MethodsTo address these challenges, the Sweden Cancerome Analysis Network - Breast (SCAN-B) consortium was initiated in 2010 as a multicenter prospective study with longsighted aims to analyze breast cancers with next-generation genomic technologies for translational research in a population-based manner and integrated with healthcare; decipher fundamental tumor biology from these analyses; utilize genomic data to develop and validate new clinically-actionable biomarker assays; and establish real-time clinical implementation of molecular diagnostic, prognostic, and predictive tests. In the first phase, we focus on molecular profiling by next-generation RNA-sequencing on the Illumina platform.ResultsIn the first 3 years from 30 August 2010 through 31 August 2013, we have consented and enrolled 3,979 patients with primary breast cancer at the seven hospital sites in South Sweden, representing approximately 85% of eligible patients in the catchment area. Preoperative blood samples have been collected for 3,942 (99%) patients and primary tumor specimens collected for 2,929 (74%) patients. Herein we describe the study infrastructure and protocols and present initial proof of concept results from prospective RNA sequencing including tumor molecular subtyping and detection of driver gene mutations. Prospective patient enrollment is ongoing.ConclusionsWe demonstrate that large-scale population-based collection and RNA-sequencing analysis of breast cancer is feasible. The SCAN-B Initiative should significantly reduce the time to discovery, validation, and clinical implementation of novel molecular diagnostic and predictive tests. We welcome the participation of additional comprehensive cancer treatment centers.Trial registrationClinicalTrials.gov identifier NCT02306096.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-015-0131-9) contains supplementary material, which is available to authorized users.

The biochemistry of most metabolic pathways is conserved from bacteria to humans, although the control mechanisms are adapted to the needs of each cell type. Oxygen depletion commonly controls the switch from respiration to fermentation. However, Saccharomyces cerevisiae also controls that switch in response to the external glucose level. We have generated an S. cerevisiae strain in which glucose uptake is dependent on a chimeric hexose transporter mediating reduced sugar uptake. This strain shows a fully respiratory metabolism also at high glucose levels as seen for aerobic organisms, and switches to fermentation only when oxygen is lacking. These observations illustrate that manipulating a single step can alter the mode of metabolism. The novel yeast strain is an excellent tool to study the mechanisms underlying glucose-induced signal transduction.