BNC1 regulates cell heterogeneity in human pluripotent stem cell-derived epicardium.

The murine developing epicardium heterogeneously expresses the transcription factors TCF21 and WT1. Here, we show that this cell heterogeneity is conserved in human epicardium, regulated by BNC1 and associated with cell fate and function. Single cell RNA sequencing of epicardium derived from human pluripotent stem cells (hPSC-epi) revealed that distinct epicardial subpopulations are defined by high levels of expression for the transcription factors BNC1 or TCF21. WT1+ cells are included in the BNC1+ population, which was confirmed in human foetal hearts. THY1 emerged as a membrane marker of the TCF21 population. We show that THY1+ cells can differentiate into cardiac fibroblasts (CFs) and smooth muscle cells (SMCs), whereas THY1- cells were predominantly restricted to SMCs. Knocking down BNC1 during the establishment of the epicardial populations resulted in a homogeneous, predominantly TCF21high population. Network inference methods using transcriptomic data from the different cell lineages derived from the hPSC-epi delivered a core transcriptional network organised around WT1, TCF21 and BNC1. This study unveils a list of epicardial regulators and is a step towards engineering subpopulations of epicardial cells with selective biological activities.

[The first data challenge of the french society of pathology: An international competition in 2020, a research tool in A.I. for the future?] / Le premier data challenge organisé par la Société Française de Pathologie : une compétition internationale en 2020, un outil de recherche en intelligence artificielle pour l'avenir ?

The french society of pathology (SFP) organized in 2020 its first data challenge with the help of Health Data Hub (HDH). The organisation of this event first consisted in recruiting almost 5000 slides of uterus cervical biopsies obtained in 20 pathology centers. After having made sure that patients did not refuse to include their slides in the project, the slides were anonymised, digitized and annotated by expert pathologists, and were finally uploaded on a data challenge platform for competitors all around the world. Competitors teams had to develop algorithms that could distinguish among four diagnostic classes in epithelial lesions of uterine cervix. Among many submissions by competitors, the best algorithms obtained an overall score close to 95%. The best 3 teams shared 25k€ prizes during a special session organised during the national congress of the SFP. The final part of the competition lasted only 6 weeks and the goal of SFP and HDH is now to allow for the collection to be published in open access. This final step will allow data scientists and pathologists to further develop artificial intelligence algorithms in this medical area.

Meet-U: Educating through research immersion.

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.

Can AI predict epithelial lesion categories via automated analysis of cervical biopsies: The TissueNet challenge?

The French Society of Pathology (SFP) organized its first data challenge in 2020 with the help of the Health Data Hub (HDH). The organization of this event first consisted of recruiting nearly 5000 cervical biopsy slides obtained from 20 pathology centers. After ensuring that patients did not refuse to include their slides in the project, the slides were anonymized, digitized, and annotated by expert pathologists, and finally uploaded to a data challenge platform for competitors from around the world. Competing teams had to develop algorithms that could distinguish 4 diagnostic classes in cervical epithelial lesions. Among the many submissions from competitors, the best algorithms achieved an overall score close to 95%. The final part of the competition lasted only 6 weeks, and the goal of SFP and HDH is now to allow for the collection to be published in open access for the scientific community. In this report, we have performed a "post-competition analysis" of the results. We first described the algorithmic pipelines of 3 top competitors. We then analyzed several difficult cases that even the top competitors could not predict correctly. A medical committee of several expert pathologists looked for possible explanations for these erroneous results by reviewing the images, and we present their findings here targeted for a large audience of pathologists and data scientists in the field of digital pathology.

Autoimmunity affecting the biliary tract fuels the immunosurveillance of cholangiocarcinoma.

Cholangiocarcinoma (CCA) results from the malignant transformation of cholangiocytes. Primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) are chronic diseases in which cholangiocytes are primarily damaged. Although PSC is an inflammatory condition predisposing to CCA, CCA is almost never found in the autoimmune context of PBC. Here, we hypothesized that PBC might favor CCA immunosurveillance. In preclinical murine models of cholangitis challenged with syngeneic CCA, PBC (but not PSC) reduced the frequency of CCA development and delayed tumor growth kinetics. This PBC-related effect appeared specific to CCA as it was not observed against other cancers, including hepatocellular carcinoma. The protective effect of PBC was relying on type 1 and type 2 T cell responses and, to a lesser extent, on B cells. Single-cell TCR/RNA sequencing revealed the existence of TCR clonotypes shared between the liver and CCA tumor of a PBC host. Altogether, these results evidence a mechanistic overlapping between autoimmunity and cancer immunosurveillance in the biliary tract.