DDR2 expression in cancer-associated fibroblasts promotes ovarian cancer tumor invasion and metastasis through periostin-ITGB1

Ovarian cancer has the highest mortality of all gynecologic malignancies. As such, there is a need to identify molecular mechanisms that underlie tumor metastasis in ovarian cancer. Increased expression of receptor tyrosine kinase, DDR2, has been associated with worse patient survival. Identifying downstream targets of DDR2 may allow specific modulation of ovarian cancer metastatic pathways. Additionally, stromal cells play a critical role in metastasis. The crosstalk between tumor and stromal cells can lead to tumor progression. We first identified that tumor cells co-cultured with DDR2-expressing fibroblasts had lower periostin expression when compared to tumor cells co-cultured with DDR2-depleted fibroblasts. We confirmed that DDR2 regulates POSTN expression in ovarian cancer-associated fibroblasts (CAFs). We found that mesothelial cell clearance and invasion by tumor cells were enhanced three-fold when DDR2 and POSTN-expressing CAFs were present compared to DDR2 and POSTN-depleted CAFs. Furthermore, DDR2-depleted and POSTN-overexpressing CAFs co-injected with ovarian tumor cells had increased tumor burden compared to mice injected with tumor cells and DDR2 and POSTN-depleted CAFs. Furthermore, we demonstrated that DDR2 regulates periostin expression through integrin B1 (ITGB1). Stromal DDR2 is highly correlated with stromal POSTN expression in ovarian cancer patient tumors. Thus, DDR2 expression in CAFs regulates the steps of ovarian cancer metastasis through periostin

DDR2 Expression in Cancer-Associated Fibroblasts Promotes Ovarian Cancer Tumor Invasion and Metastasis through Periostin-ITGB1

Ovarian cancer has the highest mortality of all gynecologic malignancies. As such, there is a need to identify molecular mechanisms that underlie tumor metastasis in ovarian cancer. Increased expression of receptor tyrosine kinase, DDR2, has been associated with worse patient survival. Identifying downstream targets of DDR2 may allow specific modulation of ovarian cancer metastatic pathways. Additionally, stromal cells play a critical role in metastasis. The crosstalk between tumor and stromal cells can lead to tumor progression. We first identified that tumor cells co-cultured with DDR2-expressing fibroblasts had lower periostin expression when compared to tumor cells co-cultured with DDR2-depleted fibroblasts. We confirmed that DDR2 regulates POSTN expression in ovarian cancer-associated fibroblasts (CAFs). We found that mesothelial cell clearance and invasion by tumor cells were enhanced three-fold when DDR2 and POSTN-expressing CAFs were present compared to DDR2 and POSTN-depleted CAFs. Furthermore, DDR2-depleted and POSTN-overexpressing CAFs co-injected with ovarian tumor cells had increased tumor burden compared to mice injected with tumor cells and DDR2 and POSTN-depleted CAFs. Furthermore, we demonstrated that DDR2 regulates periostin expression through integrin B1 (ITGB1). Stromal DDR2 is highly correlated with stromal POSTN expression in ovarian cancer patient tumors. Thus, DDR2 expression in CAFs regulates the steps of ovarian cancer metastasis through periostin

Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO).

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills

Identification of genetic elements in metabolism by high-throughput mouse phenotyping

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome

Correction: The 5th edition of The World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms (vol 36, pg 1720, 2022)

10.1038/s41375-023-01962-5LEUKEMIA3791944-195