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Angiogenesis plays an important role in cancer growth and metastasis, and it is considered a therapeutic target to control tumour growth following anti‐angiogenic therapy. However, it is still unclear when tissues initiate angiogenesis during malignant transformation from premalignant condition and whether this premalignant condition could be a therapeutic target of anti‐angiogenic therapy. In this study, we aimed to analyse the onset of angiogenesis by evaluating morphological and functional alterations of microvessels during oral multistep carcinogenesis using a 4‐nitroquinoline 1‐oxide (4NQO)‐induced oral carcinogenesis mouse model. In the study, we initially confirmed that with the use of 4NQO, oral lesions develop in a stepwise manner from normal mucosa through oral epithelial dysplasia (OED) to oral squamous cell carcinoma (OSCC). Evaluation of CD31‐immunostained specimens revealed that microvessel density (MVD) increases in a stepwise manner from OEDs. Histological and functional analyses revealed the structural abnormalities and leakage of blood vessels had already taken place in OED. Then we evaluated the expression profiles of Hif1a and Vegfa along with hypoxic status and found that OED exhibited increased Vegfa expression under hypoxic conditions. Finally, we tested the possibility of OEDs as a target of anti‐angiogenic therapy and found that anti‐VEGFR2 neutralising antibody in OED slowed the disease progression from OED to OSCC. These data indicate that an angiogenic switch occurs at the premalignant stage and morphological, and functional alterations of microvessels already exist in OED. These findings also elucidate the tumour microenvironment, which gradually develops along with carcinogenic processes, and highlight usefulness of the 4NQO‐induced carcinogenesis model in the study of epithelial and stromal components, which will support epithelial carcinogenesis. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Adenosquamous carcinoma (ASC) is a rare variant of squamous cell carcinoma (SCC). It is thought to be more aggressive with poorer prognosis than conventional SCCs. Therefore, accurate preoperative diagnosis is crucial for adequate treatment strategy. In this report, we will present a case of ASC arising in left mandibular gingiva of 76-year-old male. Histological examination revealed both SCC component and adenocarcinoma (AdC) component. Also, transition from AdC to short spindle-shaped and pleomorphic cells, which is known as sarcomatoid change, was observed. Immunohistochemical study revealed that SCC component was positive for p40 and negative for Cytokeratin 7 (CK7), whereas, AdC component was negative for p40 and positive for CK7. In area with sarcomatoid change, immunohistochemical analysis revealed that negative expression of both CK7 and E-cadherin but positive expression of Vimentin and nuclear Snail/Slug, indicating the possible role of epithelial-mesenchymal transition (EMT) in AdC to sarcomatoid transition. [ABSTRACT FROM AUTHOR]

Background: Although cervical lymph node metastasis is an important prognostic factor for oral cancer, occult metastases remain undetected even by diagnostic imaging. We developed a learning model to predict lymph node metastasis in resected specimens of tongue cancer by classifying the level of immunohistochemical (IHC) staining for angiogenesis‐ and lymphangiogenesis‐related proteins using a multilayer perceptron neural network (MNN). Methods: We obtained a dataset of 76 patients with squamous cell carcinoma of the tongue who had undergone primary tumor resection. All 76 specimens were IHC stained for the six types shown above (VEGF‐C, VEGF‐D, NRP1, NRP2, CCR7, and SEMA3E) and 456 slides were prepared. We scored the staining levels visually on all slides. We created virtual slides (4560 images) and the accuracy of the MNN model was verified by comparing it with a hue–saturation (HS) histogram, which quantifies the manually determined visual information. Results: The accuracy of the training model with the MNN was 98.6%, and when the training image was converted to grayscale, the accuracy decreased to 52.9%. This indicates that our MNN adequately evaluates the level of staining rather than the morphological features of the IHC images. Multivariate analysis revealed that CCR7 staining level and T classification were independent factors associated with the presence of cervical lymph node metastasis in both HS histograms and MNN. Conclusion: These results suggest that IHC assessment using MNN may be useful for identifying lymph node metastasis in patients with tongue cancer. [ABSTRACT FROM AUTHOR]

Diagnostic methods of oral squamous cell carcinoma (SCC) using artificial intelligence (AI) and digital-histopathologic images have been developed. However, previous AI training methods have focused on the cellular atypia given by the training of high-magnification images, and little attention has been paid to structural atypia provided by low-power wide fields. Since oral SCC has histopathologic types with bland cytology, both cellular atypia and structural atypia must be considered as histopathologic features. This study aimed to investigate AI ability to judge oral SCC in a novel training method considering cellular and structural atypia and their suitability. We examined digitized histological whole-slide images from 90 randomly selected patients with tongue SCC who attended a dental hospital. Image patches of 1000 × 1000 pixels were cut from whole-slide images at 0.3125-, 1.25-, 5-, and 20-fold magnification, and 90,059 image patches were used for training and evaluation. These image patches were resized into 224 × 224, 384 × 384, 512 × 512, and 768 × 768 pixels, and the differences in input size were analyzed. EfficientNet B0 was utilized as the convolutional neural network model. Gradient-weighted class activation mapping (Grad-CAM) was used to elucidate its validity. The proposed method achieved a peak accuracy of 99.65% with an input size of 512 × 512 pixels. Grad-CAM suggested that AI focused on both cellular and structural atypia of SCC, and tended to focus on the region surrounding the basal layer. Training AI regarding both cellular and structural atypia using various magnification images simultaneously may be suitable for the diagnosis of oral SCC. [ABSTRACT FROM AUTHOR]

Proinflammatory cytokines play critical roles in the pathogenesis of joint diseases. Using a mass spectrometry–based cloning approach, we identified Semaphorin 4D (Sema4D) as an inflammatory cytokine that directly promoted cartilage destruction. Sema4d-deficient mice showed less cartilage destruction than wild-type mice in a model of rheumatoid arthritis. Sema4D induced a proinflammatory response in mouse articular chondrocytes characterized by the induction of proteolytic enzymes that degrade cartilage, such as matrix metalloproteinases (MMPs) and aggrecanases. The activation of Mmp13 and Mmp3 expression in articular chondrocytes by Sema4D did not depend on RhoA, a GTPase that mediates Sema4D-induced cytoskeletal rearrangements. Instead, it required NF-κB signaling and Ras-MEK-Erk1/2 signaling downstream of the receptors Plexin-B2 and c-Met and depended on the transcription factors IκBζ and C/EBPδ. Genetic and pharmacological blockade of these Sema4D signaling pathways inhibited MMP induction in chondrocytes and cartilage destruction in femoral head organ culture. Our results reveal a mechanism by which Sema4D signaling promotes cartilage destruction. Sema4D as cartilage destroyer: Various classical proinflammatory cytokines contribute to cartilage destruction in joint diseases. Murakami et al. found that Semaphorin 4D (Sema4D) was released by inflamed macrophages and stimulated cartilage begin{bmatrix} degradation in articular chondrocytes and cartilage explants. In a mouse model of inflammatory arthritis, Sema4D was increased in synovial fluid, and loss of Sema4D protected against cartilage degeneration. Sema4D elicited these effects by stimulating the expression of transcripts encoding begin{bmatrix}-degrading enzymes downstream of the receptors Plexin-B2 and c-Met and intracellular signaling pathways distinct from those by which Sema4D regulates cell morphology and motility. These findings identify Sema4D as a proinflammatory cytokine in joints and contribute to a broader understanding of the factors that drive joint degeneration. [ABSTRACT FROM AUTHOR]

Using a study on mice, the roles of transcription factors, Runx2 and Cbfbeta, in embryonic skeletal development are analyzed.