NetrinG1+ cancer-associated fibroblasts generate unique extracellular vesicles that support the survival of pancreatic cancer cells under nutritional stress

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Abstract

It is projected that in 5 years, pancreatic cancer will become the second deadliest cancer in the United States. A unique aspect of pancreatic ductal adenocarcinoma (PDAC) is its stroma; rich in cancer-associated fibroblasts (CAFs) and a dense CAF-generated extracellular matrix (ECM). These pathogenic stroma CAF/ECM units cause the collapse of local blood vessels rendering the tumor microenvironment nutrient-poor. PDAC cells are able to survive this state of nutrient stress via support from CAF-secreted material, which includes small extracellular vesicles (sEVs). The tumor-supportive CAFs possess a distinct phenotypic profile, compared to normal-like fibroblasts, expressing NetrinG1 (NetG1) at the plasma membrane, and active Integrin α5β1 localized to the multivesicular bodies; traits indicative of poor patient survival. We herein report that NetG1+ CAFs secrete sEVs that stimulate Akt-mediated survival in nutrient-deprived PDAC cells, protecting them from undergoing apoptosis. Further, we show that NetG1 expression in CAFs is required for the pro-survival properties of sEVs. Additionally, we report that the above-mentioned CAF markers are secreted in distinct subpopulations of EVs; with NetG1 being enriched in exomeres, and Integrin α5β1 being enriched in exosomes. Finally, we found that NetG1 and Integrin α5β1 were detected in sEVs collected from plasma of PDAC patients, while their levels were significantly lower in plasma-derived sEVs of sex/age-matched healthy donors. The discovery of these tumor-supporting CAF-EVs elucidates novel avenues in tumor-stroma interactions and pathogenic stroma detection.

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Fiji: an open-source platform for biological-image analysis.

Johannes Schindelin, Ignacio Arganda-Carreras, Erwin Frise … (2020)

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

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Cancer statistics, 2022

Rebecca Siegel, Kimberly D Miller, Hannah Fuchs … (2022)

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes. Incidence data (through 2018) were collected by the Surveillance, Epidemiology, and End Results program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2019) were collected by the National Center for Health Statistics. In 2022, 1,918,030 new cancer cases and 609,360 cancer deaths are projected to occur in the United States, including approximately 350 deaths per day from lung cancer, the leading cause of cancer death. Incidence during 2014 through 2018 continued a slow increase for female breast cancer (by 0.5% annually) and remained stable for prostate cancer, despite a 4% to 6% annual increase for advanced disease since 2011. Consequently, the proportion of prostate cancer diagnosed at a distant stage increased from 3.9% to 8.2% over the past decade. In contrast, lung cancer incidence continued to decline steeply for advanced disease while rates for localized-stage increased suddenly by 4.5% annually, contributing to gains both in the proportion of localized-stage diagnoses (from 17% in 2004 to 28% in 2018) and 3-year relative survival (from 21% to 31%). Mortality patterns reflect incidence trends, with declines accelerating for lung cancer, slowing for breast cancer, and stabilizing for prostate cancer. In summary, progress has stagnated for breast and prostate cancers but strengthened for lung cancer, coinciding with changes in medical practice related to cancer screening and/or treatment. More targeted cancer control interventions and investment in improved early detection and treatment would facilitate reductions in cancer mortality.

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Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

Yingyao Zhou, Bin Zhou, Lars Pache … (2019)

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.