The muscle stem cell (MuSC) population is recognized as functionally heterogeneous. Cranial muscle stem cells, which originate from head mesoderm, can have greater proliferative capacity in culture and higher regenerative potential in transplantation assays when compared to those in the limb. The existence of such functional differences in phenotypic outputs remain unresolved as a comprehensive understanding of the underlying mechanisms is lacking. We addressed this issue using a combination of clonal analysis, live imaging, and scRNA-seq, identifying critical biological features that distinguish extraocular (EOM) and limb (Tibialis anterior, TA) MuSC populations. Time-lapse studies using a Myogenin tdTomato reporter showed that the increased proliferation capacity of EOM MuSCs is accompanied by a differentiation delay in vitro . Unexpectedly, in vitro activated EOM MuSCs expressed a large array of distinct extracellular matrix (ECM) components, growth factors, and signaling molecules that are typically associated with mesenchymal non-muscle cells. These unique features are regulated by a specific set of transcription factors that constitute a coregulating module. This transcription factor network, which includes Foxc1 as one of the major players, appears to be hardwired to EOM identity as it is present in quiescent adult MuSCs, in the activated counterparts during growth and retained upon passages in vitro. These findings provide insights into how high-performing MuSCs regulate myogenic commitment by active remodeling of their local environment.

Abstract Introduction: MGMT gene promoter methylation status is today the only biomarker of survival for GBM patients and predicts favorable response to temozolomide (TMZ). Here we propose a deep learning-based model using histology data (H&E slides) to predict the prognosis of patients with Glioblastoma (GBM) treated by standard of care (SOC). Methods: We included TCGA GBM patients and selected only patients treated after 2005 (Stupp protocol start); compliant to WHO 2021 classification; treated by surgery and adjuvant therapy; with a follow-up superior to median overall survival (OS) (14.5 months). Short and long survivor labels were defined based on median OS cut-off. A deep learning pipeline was trained to predict these labels from the H&E slides (baseline surgery samples). First, the slides were automatically segmented into tissue and background, divided into a regular grid of tiles (112 × 112µm), and tiles were vectorized using a vision transformer-based feature extractor trained on H&E slides of 5,500 patients with 16 cancer subtypes (GBM excluded). In the second step, ABMIL deep learning model was trained to predict the survival category using the bag of tile features available from step 1 for each patient. The cohort was divided into five folds with even numbers of short and long survivors. For each fold, 50 ABMIL models were trained on the remaining folds and ensembled to predict the category of the patients in the fold. Training hyperparameters were tuned on a separated cohort excluding GBM patients. Results: After filtering, we analyzed n = 192 TCGA GBM patients including 154 patients with a known MGMT promoter methylation status. Our histology-based model had an accuracy of 0.661 and a ROC AUC of 0.706. It stratified the population into short and long survivors with an Hazard Ratio (HR) of 0.48 (95% CI 0.34-0.69). Our model outperformed the MGMT methylation status that had an HR of 0.57 (95% CI 0.40-0.83). Moreover, our model was independent of MGMT methylation status and the combination of both was able to further improve prognosis prediction: we applied our model independently to the 91 patients with an unmethylated MGMT status (predicted: 43 low, 48 high) and to the 63 patients with a methylated MGMT status (predicted: 30 low, 33 high), and obtained HR of 0.42 (95% CI 0.27-0.67) and 0.49 (95% CI 0.28-0.86) respectively. Conclusion: Having selected patients treated by the latest SOC and classified as GBM by the latest WHO criteria, we propose a model predicting survival based on histological specimens available in routine care, which outperformed the current unique biomarker MGMT methylation status. The combination of this status and our model improves prognosis predictions compared to each strategy alone. Citation Format: Lucas Fidon, Celine Thiriez, Alexandre Grimaldi, Omar Darwiche Domingues, Charles Maussion, Caroline Hoffmann. Histology-based prognosis prediction using deep learning outperforms and is independent of the MGMT methylation status in patients with glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7395.

The current view of hematopoiesis considers leukocytes on a continuum with distinct developmental origins, and which exert non-overlapping functions. However, there is less known about the function and phenotype of ontogenetically distinct neutrophil populations. In this work, using a photoconvertible transgenic zebrafish line; Tg(mpx:Dendra2), we selectively label rostral blood island-derived and caudal hematopoietic tissue-derived neutrophils in vivo during steady state or upon injury. By comparing the migratory properties and single-cell expression profiles of both neutrophil populations at steady state we show that rostral neutrophils show higher csf3b expression and migration capacity than caudal neutrophils. Upon injury, both populations share a core transcriptional profile as well as subset-specific transcriptional signatures. Accordingly, both rostral and caudal neutrophils are recruited to the wound independently of their distance to the injury. While rostral neutrophils respond uniformly, caudal neutrophils respond heterogeneously. Collectively, our results reveal that co-existing neutrophils populations with ontogenically distinct origin display functional differences.

How distinct cell fates are manifested by direct lineage ancestry from bipotent progenitors, or by specification of individual cell types is a key question for understanding the emergence of tissues. The interplay between skeletal muscle progenitors and associated connective tissue cells provides a model for examining how muscle functional units are established. Most craniofacial structures originate from the vertebrate-specific neural crest cells except in the dorsal portion of the head, where they arise from cranial mesoderm. Here, using multiple lineage-tracing strategies combined with single cell RNAseq and in situ analyses, we identify bipotent progenitors expressing Myf5 (an upstream regulator of myogenic fate) that give rise to both muscle and juxtaposed connective tissue. Following this bifurcation, muscle and connective tissue cells retain complementary signalling features and maintain spatial proximity. Disrupting myogenic identity shifts muscle progenitors to a connective tissue fate. The emergence of Myf5 -derived connective tissue is associated with the activity of several transcription factors, including Foxp2 . Interestingly, this unexpected bifurcation in cell fate was not observed in craniofacial regions that are colonised by neural crest cells. Therefore, we propose that an ancestral bi-fated program gives rise to muscle and connective tissue cells in skeletal muscles that are deprived of neural crest cells.

Cranial muscles have been the focus of many studies over the years because of their unique developmental programs and relative resistance to illnesses. In addition, head muscles possess clonal relationships with heart muscles and have been highly remodeled during vertebrate evolution. Here, we provide an overview of recent findings that have helped to redefine the boundaries and lineages of cranial mesoderm. These studies have important implications regarding the emergence of muscle connective tissues, which can share a common origin with skeletal muscle. We also highlight new regulatory networks of various muscle subgroups, particularly those derived from the most caudal arches, which remain poorly defined. Finally, we suggest future research avenues to characterize the nature of their intrinsic specificities and their emergence during evolution.

In vertebrates, head and trunk muscles develop from different mesodermal populations and are regulated by distinct genetic networks. Neck muscles at the head-trunk interface remain poorly defined due to their complex morphogenesis and dual mesodermal origins. Here, we use genetically modified mice to establish a 3D model that integrates regulatory genes, cell populations and morphogenetic events that define this transition zone. We show that the evolutionary conserved cucullaris-derived muscles originate from posterior cardiopharyngeal mesoderm, not lateral plate mesoderm, and we define new boundaries for neural crest and mesodermal contributions to neck connective tissue. Furthermore, lineage studies and functional analysis of Tbx1- and Pax3-null mice reveal a unique developmental program for somitic neck muscles that is distinct from that of somitic trunk muscles. Our findings unveil the embryological and developmental requirements underlying tetrapod neck myogenesis and provide a blueprint to investigate how muscle subsets are selectively affected in some human myopathies.

Craniofacial development depends on cell-cell interactions, coordinated cellular movement and differentiation under the control of regulatory gene networks, which include the distal-less (Dlx) gene family. However, the functional significance of Dlx5 in patterning the oropharyngeal region has remained unknown. Here, we show that loss of Dlx5 leads to a shortened soft palate and an absence of the levator veli palatini, palatopharyngeus and palatoglossus muscles that are derived from the 4th pharyngeal arch (PA); however, the tensor veli palatini, derived from the 1st PA, is unaffected. Dlx5-positive cranial neural crest (CNC) cells are in direct contact with myoblasts derived from the pharyngeal mesoderm, and Dlx5 disruption leads to altered proliferation and apoptosis of CNC and muscle progenitor cells. Moreover, the FGF10 pathway is downregulated in Dlx5-/- mice, and activation of FGF10 signaling rescues CNC cell proliferation and myogenic differentiation in these mutant mice. Collectively, our results indicate that Dlx5 plays crucial roles in the patterning of the oropharyngeal region and development of muscles derived from the 4th PA mesoderm in the soft palate, likely via interactions between CNC-derived and myogenic progenitor cells.

Distal‐less (Dll) genes belong to an evolutionarily conserved family of homeobox transcriptional regulators, which are important for the early embryonic development of bone in the limbs and craniofacial region. Mutations in human Dll orthologs, Dlx5/6, cause split‐hand/split‐foot type 1 malformation (SHFM1) associated with sensorineural deafness, cleft palate, developmental delay, and micrognathia. Dlx5 mutant mice have craniofacial abnormalities including cleft soft palate and micrognathia. However, the role of Dlx5 in the palatal‐pharyngeal development, which is important for speech, remains unclear. This study examines the role of Dlx5 in the formation of the soft palate, the Eustachian tube (ET), and the pharyngeal region. Gene expression analysis demonstrates that Dlx5 is expressed in muscles and osteogenic progenitor cells. Homozygous Dlx5 mutant mice lack soft palatal muscles including the levator veli palatini (LVP) and palatopharyngeus (PLP). The posterior regions of the hard palate and pterygoid plate are smaller in Dlx5−/− mice than in controls. Morphometric analyses of the premaxilla, maxilla, palatine bone, and mandible show that these bones are smaller in height, width, and length in Dlx5−/− mice compared to controls. Taken together, our data reveal that Dlx5−/− mice recapitulate craniofacial phenotypes similar to those of SHFM patients. Further studies of Dlx5 expression in the proximal region of the mandible, posterior palate, and pharyngeal region may reveal the mechanism responsible for the pharyngeal morphology. These studies hold potential for improving our understanding of the evolution of speech in the human lineage.Support or Funding InformationSupported by the NIDCR, NIH R37 DE012711

Disrupted ERK1/2 signaling is associated with several developmental syndromes in humans. To understand the function of ERK2 (MAPK1) in the postmigratory neural crest populating the craniofacial region, we studied two mouse models: Wnt1-Cre;Erk2(fl/fl) and Osr2-Cre;Erk2(fl/fl). Wnt1-Cre;Erk2(fl/fl) mice exhibited cleft palate, malformed tongue, micrognathia and mandibular asymmetry. Cleft palate in these mice was associated with delay/failure of palatal shelf elevation caused by tongue malposition and micrognathia. Osr2-Cre;Erk2(fl/fl) mice, in which the Erk2 deletion is restricted to the palatal mesenchyme, did not display cleft palate, suggesting that palatal clefting in Wnt1-Cre;Erk2(fl/fl) mice is a secondary defect. Tongues in Wnt1-Cre;Erk2(fl/fl) mice exhibited microglossia, malposition, disruption of the muscle patterning and compromised tendon development. The tongue phenotype was extensively rescued after culture in isolation, indicating that it might also be a secondary defect. The primary malformations in Wnt1-Cre;Erk2(fl/fl) mice, namely micrognathia and mandibular asymmetry, are linked to an early osteogenic differentiation defect. Collectively, our study demonstrates that mutation of Erk2 in neural crest derivatives phenocopies the human Pierre Robin sequence and highlights the interconnection of palate, tongue and mandible development. Because the ERK pathway serves as a crucial point of convergence for multiple signaling pathways, our study will facilitate a better understanding of the molecular regulatory mechanisms of craniofacial development.

Cleft palate is one of the most common congenital birth defects. Tremendous efforts have been made over the last decades towards understanding hard palate development. However, little is known about soft palate morphogenesis and myogenesis. Finding an appropriate surgical repair to restore physiological functions of the soft palate in patients with cleft palate is a major challenge for surgeons, and complete restoration is not always achievable. Here, we first analyzed the morphology, orientation and attachments of the four muscles of the murine soft palate and found that they are very similar to their counterparts in humans, validating the use of mus musculus as a model for future studies. Our data suggests that muscle differentiation extends from the lateral region to the midline following palatal fusion. We also detected an epithelial seam in the fusing soft palatal shelves, consistent with the process of fusion of the posterior palatal shelves, followed by degradation of the epithelial remnants. Innervation and vascularization are present mainly in the oral side of the soft palate, complementing the differentiated muscles. Cell lineage tracing using Wnt1-Cre;Zsgreenfl/fl mice indicated that all the tendons and mesenchyme embedding the soft palate muscles are neural crest-derived. We propose that the posterior attachment of the soft palate to the pharyngeal wall is an interface between the neural crest- and mesoderm-derived mesenchyme in the craniofacial region, and thus can serve as a potential model for the study of boundaries during development. Taken together, our study provides a comprehensive view of the development and morphology of the murine soft palate and serves as a reference for further molecular analyses.

Fondements régulatoires de la diversité des muscles faciaux : origines développementales de la résilience musculaire Les muscles squelettiques sont présents dans tout le corps et présentent un niveau surprenant d'hétérogénéité, dans leur susceptibilité aux maladies, potentiel de régénération ou capacités métaboliques. Cette diversité est également retrouvée au cours du développement embryonnaire où les cellules myogéniques et non myogéniques établissent le système musculo-squelettique. La tête et le cou sont constitués d'une grande variété de muscles qui remplissent des fonctions essentielles, mais nous en savons peu sur la biologie des muscles craniofaciaux. Ces structures sont associées à l'émergence de cellules de la crête neurale (CCN) qui donnent naissance à la plupart des tissus non myogéniques crâniens et qui sont cruciales à la formation des muscles. Cependant, certains muscles crâniens sont privés de CCN, et nous ignorons comment les cellules myogéniques et non myogéniques contribuent à ces domaines. Cette thèse fournit des preuves démontrant que les progéniteurs en amont du muscle se détournent du programme myogénique pour donner naissance au tissu conjonctif. Nous avons utilisé une approche de single-cell RNAseq non biaisée et restreinte avec différentes lignées transgéniques de souris à des stades embryonnaires distincts, des marquages in situ et de nouvelles méthodes analytiques, et avons montré que les progéniteurs bipotents issus du mésoderme exprimant le gène de détermination musculaire Myf5 donnent naissance au muscle squelettique et au tissu conjonctif anatomiquement associé dans les muscles partiellement privés de CCN. Cette transition est caractérisée par une complémentarité de signalisation de récepteurs tyrosine kinase entre les cellules musculaires et non musculaires, ainsi que par des modules régulateurs distincts. Les muscles crâniens proviennent également de différentes lignées qui impliquent l'activité de cascades de régulation génique spécifiques. Ici, nous avons utilisé une approche non biaisée et large pour découvrir des modules de régulation spécifiques qui sous-tendent différentes populations de cellules myogéniques dans la tête et à travers plusieurs stades de développement. Certaines de ces « tâches de naissance génétiques » uniques sont des facteurs de transcription spécifiques et sont conservées dans les cellules souches musculaires adultes, ce qui indique que leur importance potentielle est de fournir les propriétés uniques qui ont été signalées pour différentes populations de cellules souches musculaires. Enfin, ces études utilisent des méthodes analytiques inédites qui bénéficient des dernières avancées algorithmiques et offrent de nouvelles perspectives pour la découverte de processus biologiques à partir de données à haut débit.