Adipocyte Precursor-Derived NRG1 Promotes Resistance to FGFR Inhibition in Urothelial Carcinoma.

Aberrations of the fibroblast growth factor receptor (FGFR) family members are frequently observed in metastatic urothelial cancer (mUC), and blocking the FGF/FGFR signaling axis is used as a targeted therapeutic strategy for treating patients. Erdafitinib is a pan-FGFR inhibitor, which has recently been approved by the FDA for mUC with FGFR2/3 alterations. Although mUC patients show initial response to erdafitinib, acquired resistance rapidly develops. Here, we found that adipocyte precursors promoted resistance to erdafitinib in FGFR-dependent bladder and lung cancer in a paracrine manner. Moreover, neuregulin 1 (NRG1) secreted from adipocyte precursors was a mediator of erdafitinib resistance by activating human epidermal growth factor receptor 3 (ERBB3; also known as HER3) signaling, and knockdown of NRG1 in adipocyte precursors abrogated the conferred paracrine resistance. NRG1 expression was significantly downregulated in terminally differentiated adipocytes compared with their progenitors. Pharmacologic inhibition of the NRG1/HER3 axis using pertuzumab reversed erdafitinib resistance in tumor cells in vitro and prolonged survival of mice bearing bladder cancer xenografts in vivo. Remarkably, data from single-cell RNA sequencing revealed that NRG1 was enriched in platelet-derived growth factor receptor-A (PDGFRA) expressing inflammatory cancer-associated fibroblasts, which is also expressed on adipocyte precursors. Together, this work reveals a paracrine mechanism of anti-FGFR resistance in bladder cancer, and potentially other cancers, that is amenable to inhibition using available targeted therapies. SIGNIFICANCE: Acquired resistance to FGFR inhibition can be rapidly promoted by paracrine activation of the NRG1/HER3 axis mediated by adipocyte precursors and can be overcome by the combination of pertuzumab and erdafitinib treatment. See related commentary by Kolonin and Anastassiou, p. 648.

From Planning Stage Towards FAIR Data: A Practical Metadatasheet For Biomedical Scientists.

Datasets consist of measurement data and metadata. Metadata provides context, essential for understanding and (re-)using data. Various metadata standards exist for different methods, systems and contexts. However, relevant information resides at differing stages across the data-lifecycle. Often, this information is defined and standardized only at publication stage, which can lead to data loss and workload increase. In this study, we developed Metadatasheet, a metadata standard based on interviews with members of two biomedical consortia and systematic screening of data repositories. It aligns with the data-lifecycle allowing synchronous metadata recording within Microsoft Excel, a widespread data recording software. Additionally, we provide an implementation, the Metadata Workbook, that offers user-friendly features like automation, dynamic adaption, metadata integrity checks, and export options for various metadata standards. By design and due to its extensive documentation, the proposed metadata standard simplifies recording and structuring of metadata for biomedical scientists, promoting practicality and convenience in data management. This framework can accelerate scientific progress by enhancing collaboration and knowledge transfer throughout the intermediate steps of data creation.

AdipoQ-a simple, open-source software to quantify adipocyte morphology and function in tissues and in vitro.

The different adipose tissues (ATs) can be distinguished according to their function. For example, white AT stores energy in form of lipids, whereas brown AT dissipates energy in the form of heat. These functional differences are represented in the respective adipocyte morphology; whereas white adipocytes contain large, unilocular lipid droplets, brown adipocytes contain smaller, multilocular lipid droplets. However, an automated, image analysis pipeline to comprehensively analyze adipocytes in vitro in cell culture as well as ex vivo in tissue sections is missing. We here present AdipoQ, an open-source software implemented as ImageJ plugins that allows us to analyze adipocytes in tissue sections and in vitro after histological and/or immunofluorescent labeling. AdipoQ is compatible with different imaging modalities and staining methods, allows batch processing of large datasets and simple post-hoc analysis, provides a broad band of parameters, and allows combining multiple fluorescent readouts. Therefore AdipoQ is of immediate use not only for basic research but also for clinical diagnosis.