CD205 is an endocytic receptor that is expressed at high levels by cortical thymic epithelial cells and by dendritic cell (DC) subsets, including the splenic CD8+ DC population that is responsible for cross-presentation of apoptotic cell-derived antigens. Antigen endocytosed via CD205 enters the MHC class I and MHC class II antigen presentation pathways and is subsequently presented to both CD4+ and CD8+ T cells. Despite the known role of CD205 in antigen uptake, the nature of the ligands bound by CD205 has not been determined, and most studies have relied on the use of monoclonal antibodies as surrogate ligands. To go beyond this approach, we created a panel of CD205-IgG fusion proteins spanning the extracellular portion of CD205 and used these to identify the physiological distribution of CD205 ligands. Our data demonstrate that two areas of the CD205 molecule, within C-type lectin-like domains (CTLDs) 3+4 and 9+10, recognise ligands expressed during apoptosis and necrosis of multiple cell types, and are additionally expressed by live cells of the dendritic cell line DC2.4. Thus, CD205 acts as a recognition receptor for dying cells, potentially providing an important pathway for the uptake of self-antigen in intrathymic and peripheral tolerance.

Extranodal NK/T cell lymphoma, nasal type (ENKTL) is an aggressive malignancy with a dismal prognosis. Although l-asparaginase-based chemotherapy has resulted in improved response rates, relapse occurs in up to 50% of patients with disseminated disease. There is hence an urgent need for effective targeted therapy, especially for patients with relapsed or refractory disease. Novel insights gleaned from high-throughput molecular and genomic profiling studies in recent years have contributed significantly to the understanding of the molecular biology of ENKTL, which exemplifies many of the hallmarks of cancer. Deregulated pro-proliferative signaling pathways, such as the Janus-associated kinase/signal transducer and activator of transcription (JAK/STAT), platelet-derived growth factor (PDGF), Aurora kinase, MYC, and NF-κB, have been identified as potential therapeutic targets. The discovery of the non-canonical function of EZH2 as a pro-proliferative transcriptional co-activator has shed further light on the pathogenesis of ENKTL. Loss of key tumor suppressor genes located on chromosome 6q21 also plays an important role. The best-studied examples include PR domain zinc finger protein 1(PRDM1), protein tyrosine phosphatase kappa (PTPRK), and FOXO3. Promoter hypermethylation has been shown to result in the downregulation of other tumor suppressor genes in ENKTL, which may be potentially targeted through hypomethylating agents. Deregulation of apoptosis through p53 mutations and upregulation of the anti-apoptotic protein, survivin, may provide a further growth advantage to this tumor. A deranged DNA damage response as a result of the aberration of ataxia telangiectasia-related (ATR) kinases can lead to significant genomic instability and may contribute to chemoresistance of ENKTL. Recently, immune evasion has emerged as a critical pathway for survival in ENKTL and may be a consequence of HLA dysregulation or STAT3-driven upregulation of programmed cell death ligand 1 (PD-L1). Immunotherapy via inhibition of programmed cell death 1 (PD-1)/PD-L1 checkpoint signaling holds great promise as a novel therapeutic option. In this review, we present an overview of the key molecular and pathogenic pathways in ENKTL, organized using the framework of the “hallmarks of cancer” as described by Hanahan and Weinberg, with a focus on those with the greatest translational potential.

Summary: CD205 (DEC‐205) is a member of the macrophage mannose receptor family of C‐type lectins. These molecules are known to mediate a wide variety of biological functions including the capture and internalization of ligands for subsequent processing and presentation by dendritic cells. Although its ligands await identification, the endocytic properties of CD205 make it an ideal target for those wishing to design vaccines and targeted immunotherapies. We present a detailed analysis of CD205 expression, distribution and endocytosis in human monocyte‐derived dendritic cells undergoing lipopolysaccharide‐induced maturation. Unlike other members of the macrophage mannose receptor family, CD205 was up‐regulated upon dendritic cell maturation. This increase was a result of de novo synthesis as well as a redistribution of molecules from endocytic compartments to the cell surface. Furthermore, the endocytic capacity of CD205 was abrogated and small amounts of the recently identified CD205–DCL‐1 fusion protein were detected in mature DC. Our results suggest that CD205 has two distinct functions – one as an endocytic receptor on immature dendritic cells and a second as a non‐endocytic molecule on mature dendritic cells – and further highlight its potential as an immuno‐modulatory target for vaccine and immunotherapy development.

Background: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability.Methods: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI.Results: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance.Conclusions: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.