Autocrine TGF-β Signaling Maintains Tumorigenicity of Glioma-Initiating Cells through Sry-Related HMG-Box Factors

SummaryDespite aggressive surgery, radiotherapy, and chemotherapy, treatment of malignant glioma remains formidable. Although the concept of cancer stem cells reveals a new framework of cancer therapeutic strategies against malignant glioma, it remains unclear how glioma stem cells could be eradicated. Here, we demonstrate that autocrine TGF-β signaling plays an essential role in retention of stemness of glioma-initiating cells (GICs) and describe the underlying mechanism for it. TGF-β induced expression of Sox2, a stemness gene, and this induction was mediated by Sox4, a direct TGF-β target gene. Inhibitors of TGF-β signaling drastically deprived tumorigenicity of GICs by promoting their differentiation, and these effects were attenuated in GICs transduced with Sox2 or Sox4. Furthermore, GICs pretreated with TGF-β signaling inhibitor exhibited less lethal potency in intracranial transplantation assay. These results identify an essential pathway for GICs, the TGF-β-Sox4-Sox2 pathway, whose disruption would be a therapeutic strategy against gliomas

An Id-like molecule, HHM, is a synexpression group-restricted regulator of TGF-β signalling

Transforming growth factor (TGF)-β induces various cellular responses principally through Smad-dependent transcriptional regulation. Activated Smad complexes cooperate with transcription factors in regulating a group of target genes. The target genes controlled by the same Smad-cofactor complexes are denoted a synexpression group. We found that an Id-like helix-loop-helix protein, human homologue of Maid (HHM), is a synexpression group-restricted regulator of TGF-β signalling. HHM suppressed TGF-β-induced growth inhibition and cell migration but not epithelial–mesenchymal transition. In addition, HHM inhibited TGF-β-induced expression of plasminogen activator inhibitor-type 1 (PAI-1), PDGF-B, and p21WAF, but not Snail. We identified a basic-helix-loop-helix protein, Olig1, as one of the Smad-binding transcription factors affected by HHM. Olig1 interacted with Smad2/3 in response to TGF-β stimulation, and was involved in transcriptional activation of PAI-1 and PDGF-B. HHM, but not Id proteins, inhibited TGF-β signalling-dependent association of Olig1 with Smad2/3 through physical interaction with Olig1. HHM thus appears to regulate a subset of TGF-β target genes including the Olig1-Smad synexpression group. HHM is the first example of a cellular response-selective regulator of TGF-β signalling with clearly determined mechanisms

Identification of age-dependent features of human bronchi using explainable artificial intelligence

Background Ageing induces functional and structural alterations in organs, and age-dependent parameters have been identified in various medical data sources. However, there is currently no specific clinical test to quantitatively evaluate age-related changes in bronchi. This study aimed to identify age-dependent bronchial features using explainable artificial intelligence for bronchoscopy images. Methods The present study included 11 374 bronchoscopy images, divided into training and test datasets based on the time axis. We constructed convolutional neural network (CNN) models and evaluated these models using the correlation coefficient between the chronological age and the “bronchial age” calculated from bronchoscopy images. We employed gradient-weighted class activation mapping (Grad-CAM) to identify age-dependent bronchial features that the model focuses on. We assessed the universality of our model by comparing the distribution of bronchial age for each respiratory disease or smoking history. Results We constructed deep-learning models using four representative CNN architectures to calculate bronchial age. Although the bronchial age showed a significant correlation with chronological age in each CNN architecture, EfficientNetB3 achieved the highest Pearson's correlation coefficient (0.9617). The application of Grad-CAM to the EfficientNetB3-based model revealed that the model predominantly attended to bronchial bifurcation sites, regardless of whether the model accurately predicted chronological age or exhibited discrepancies. There were no significant differences in the discrepancy between the bronchial age and chronological age among different respiratory diseases or according to smoking history. Conclusion Bronchial bifurcation sites are universally important age-dependent features in bronchi, regardless of the type of respiratory disease or smoking history

Crystallization and preliminary X-ray diffraction analysis of GCIP/HHM transcriptional regulator

Native and selenomethionine-derivatized crystals of full-length human GCIP/HHM protein were obtained. The crystals belonged to space group P3221 and the best native crystal diffracted to 3.5 Å resolution