The ectonucleotidases CD39 and CD73 catalyze extracellular ATP to immunosuppressive adenosine, and as such, represent potential cancer targets. We investigated biological impacts of CD39 and CD73 in pancreatic ductal adenocarcinoma (PDAC) by studying clinical samples and experimental mouse tumors. Stromal CD39 and tumoral CD73 expression significantly associated with worse survival in human PDAC samples and abolished the favorable prognostic impact associated with the presence of tumor-infiltrating CD8+ T cells. In mouse transplanted KPC tumors, both CD39 and CD73 on myeloid cells, as well as CD73 on tumor cells, promoted polarization of infiltrating myeloid cells towards an M2-like phenotype, which enhanced tumor growth. CD39 on tumor-specific CD8+ T cells and pancreatic stellate cells also suppressed IFNγ production by T cells. Although therapeutic inhibition of CD39 or CD73 alone significantly delayed tumor growth in vivo, targeting of both ectonucleotidases exhibited markedly superior antitumor activity. CD73 expression on human and mouse PDAC tumor cells also protected against DNA damage induced by gemcitabine and irradiation. Accordingly, large-scale pharmacogenomic analyses of human PDAC cell lines revealed significant associations between CD73 expression and gemcitabine chemoresistance. Strikingly, increased DNA damage in CD73-deficient tumor cells associated with activation of the cGAS–STING pathway. Moreover, cGAS expression in mouse KPC tumor cells was required for antitumor activity of the CD73 inhibitor AB680 in vivo. Our study, thus, illuminates molecular mechanisms whereby CD73 and CD39 seemingly cooperate to promote PDAC progression.
The progression of chronic liver disease (CLD) is characterized by excessive extracellular matrix deposition, disrupting hepatic architecture and function. Upon liver injury, hepatic stellate cells (HSCs) differentiate towards myofibroblasts and become inflammatory, proliferative and fibrogenic. To date, it is still unclear whether HSC activation is driven by similar mechanisms in different aetiologies. HSCs from multiple publicly available single-cell RNA-sequencing datasets were annotated and merged into a single-cell HSC activation atlas. Spheroid co-cultures of primary mouse hepatocytes/HSCs (n = 5) and ELISAs on patient plasma samples (n = 80) were performed to validate the mechanistic insight obtained from the HSC atlas. We established an HSC activation atlas in which HSCs are clearly divided into three distinct transcriptomic profiles: quiescent HSCs, initiatory HSCs and myofibroblasts. These transcriptomic profiles are present in each of the investigated mouse liver injury models as well as in human CLDs, indicating that HSC activation is a conserved process. This activation process is driven by a core set of transcription factors independent of liver injury or species. Furthermore, we reveal novel ligands associated with activation of HSCs in multiple liver injury models and validate the profibrotic effect of parathyroid hormone. Finally, we identify COLEC10 as a conserved marker for quiescent HSCs and a biomarker of liver fibrosis in patients with different CLDs (p <0.0001). We reveal unexpected similarities in the regulatory mechanisms of HSCs across diverse liver injury settings and species. The HSC activation atlas has the potential to provide novel insights into liver fibrosis and steer novel treatment options. This study establishes a single-cell atlas of hepatic stellate cells across various liver injuries, highlighting a conserved activation process between different injuries and across species. The discovery of novel activating ligands and the biomarker COLEC10 in human plasma could be used to enhance diagnostic and therapeutic strategies. Additionally, the conserved activation process supports the use of any mouse model for mechanistic studies and testing of new anti-fibrotic compounds, streamlining preclinical research efforts.
Soccer players frequently experience acute and chronic groin pain. Sportsman’s hernia is a common injury in professional soccer players, that causes inguinal pain. The authors discuss their experience with the management of sportsman’s hernia in professional soccer players competing in national and international competition in a retrospective review of prospectively collected data. Between March 2004 and December 2009, seventy-one professional soccer players were surgically treated for sportsman’s hernia. Average age at surgery was 24 years, and average duration of symptoms from onset to surgical repair was 11 months. Conservative treatment improved symptoms temporarily or to some extent in 18 athletes. All athletes underwent a bilateral open hernia repair with concurrent adductor tendon release. Average follow-up was 4 years, and average time to return to competitive sport was 4 months. At final follow-up, 95% of soccer players were still active, 48 at the same level and 19 at a lower level. Four athletes had stopped their careers because of another injury (n=2) or recurrence (n=2). Sportsman’s hernia is a potentially career-ending injury in professional soccer players. Conservative management is often unsuccessful. An open surgical hernia repair combined with an adductor longus tenotomy relieves the symptoms caused by a sportsman’s hernia and restores activity in 95% of athletes. This study offers insight into the management of sportsman’s hernia and offers a successful treatment to salvage the careers of professional soccer players.
The lack of adequate human in vitro models that recapitulate the cellular composition and response of the human liver to injury hampers the development of anti-fibrotic drugs. The goal of this study was to develop a human spheroid culture model to study liver fibrosis by using induced pluripotent stem cell (iPSC)-derived liver cells. iPSCs were independently differentiated towards hepatoblasts (iHepatoblasts), hepatic stellate cells (iHSCs), endothelial cells (iECs) and macrophages (iMΦ), before assembly into free floating spheroids by culturing cells in 96-well U-bottom plates and orbital shaking for up to 21 days to allow further maturation. Through transcriptome analysis, we show further maturation of iECs and iMΦ, the differentiation of the iHepatoblasts towards hepatocyte-like cells (iHeps) and the inactivation of the iHSCs by the end of the 3D culture. Moreover, these cultures display a similar expression of cell-specific marker genes (CYP3A4, PDGFRβ, CD31 and CD68) and sensitivity to hepatotoxicity as spheroids made using freshly isolated primary human liver cells. Furthermore, we show the functionality of the iHeps and the iHSCs by mimicking liver fibrosis through iHep-induced iHSC activation, using acetaminophen. In conclusion, we have established a reproducible human iPSC-derived liver culture model that can be used to mimic fibrosis in vitro as a replacement of primary human liver derived 3D models. The model can be used to investigate pathways involved in fibrosis development and to identify new targets for chronic liver disease therapy.
In this scoping review, we delve into the transformative potential of artificial intelligence (AI) in addressing challenges inherent in whole-genome sequencing (WGS) analysis, with a specific focus on its implications in oncology. Unveiling the limitations of existing sequencing technologies, the review illuminates how AI-powered methods emerge as innovative solutions to surmount these obstacles. The evolution of DNA sequencing technologies, progressing from Sanger sequencing to next-generation sequencing, sets the backdrop for AI’s emergence as a potent ally in processing and analyzing the voluminous genomic data generated. Particularly, deep learning methods play a pivotal role in extracting knowledge and discerning patterns from the vast landscape of genomic information. In the context of oncology, AI-powered methods exhibit considerable potential across diverse facets of WGS analysis, including variant calling, structural variation identification, and pharmacogenomic analysis. This review underscores the significance of multimodal approaches in diagnoses and therapies, highlighting the importance of ongoing research and development in AI-powered WGS techniques. Integrating AI into the analytical framework empowers scientists and clinicians to unravel the intricate interplay of genomics within the realm of multi-omics research, paving the way for more successful personalized and targeted treatments.