The detection and classification of oral mucosal lesions is a challenging task due to high heterogeneity and overlap in clinical appearance. Nevertheless, differentiating benign from potentially malignant lesions is essential for appropriate management. This study evaluated whether a deep learning model trained to discriminate 11 classes of oral mucosal lesions could exceed the performance of general dentists.

4,079 intraoral photographs of benign, potentially malignant and malignant oral lesions were labeled using bounding boxes and classified into 11 classes. The data were split 80:20 for training (n=3031) and validation (n=766), keeping an independent test dataset (n=282). The YOLOv8 computer vision model was implemented for image classification and object detection. Model performance was evaluated on the test dataset which was also assessed by six general dentists and three specialists in oral surgery. Evaluation metrics included sensitivity, specificity, F1-score, precision, area-under-the-receiver-operating-characteristics-curve (AUROC), and average precision (AP) at multiple thresholds of intersection over union.

In terms of classification, the highest F1-score (0.80) and AUROC (0.96) were observed for human papillomavirus (HPV)-related lesions, whereas the lowest F1-score (0.43) and AUROC (0.78) were obtained for keratosis. In terms of object detection, best results were achieved for HPV-related lesions (AP25=0.82) and proliferative verrucous leukoplakia (AP25=0.8; AP50=0.76), while the lowest values were noted for leukoplakia (AP25=0.36; AP50=0.2). Overall, the model performed comparable to specialists (p=0.93) and significantly better than general dentists (p<0.01).

The developed model performed as well as specialists in oral surgery, highlighting its potential as a valuable tool for oral lesion assessment.

By providing performance comparable to oral surgeons and superior to general dentists, the developed multi-class model could support the clinical evaluation of oral lesions, potentially enabling earlier diagnosis of potentially malignant disorders, enhancing patient management, and improving patient prognosis.

Appendiceal Goblet Cell Adenocarcinoma (GCA) is a renamed subtype of appendiceal adenocarcinoma. A proper management is required to improve the outcomes of the patients. We hereby reported a chance diagnosis of GCA presenting as acute appendicitis being teated by ileocecectomy plus partial right-hemicolectomy.

A 59-year old male complained of a right lower abdominal pain for 17 h on admission with a history of acute appendicitis. Physical examination revealed hyperactive bowel sound and right lower quadrant tenderness. CBC showed WBC and neutrophil elevation. Abdominal CT demonstrated an enlarged appendix with surrounding fat-stranding. A laparoscopic appendectomy was performed with the unexpected finding of GCA in the surgical specimen. Enhanced CT and colonoscopy were further performed to rule out metastasis. An ileocecectomy plus partial right-hemicolectomy was operated to resect the distal ileum and the proximal ascending colon both about 10 cm with the cecum. The pathology revealed that the ileocecal subserosa was invaded. The patient was then referred to the oncology department for 5-FU-based chemotherapy.

GCA requires proper treatment. The diagnosis can be challenging due to the unspecific clinical manifestations, and is depending on pathology in the cases of appendicitis after appendectomy. Though right-hemicolectomy should remain as the standard treatment, the enhanced CT and colonoscopy are necessary for further evaluation. Our case has chosen the ileocecectomy plus partial right-hemicolectomy based on the enhanced CT and colonoscopy ruling out metastasis.

The case highlights the ileocecectomy plus partial right-hemicolectomy to treat GCA on the specific preoperative evaluation ruling out metastasis and followed by the recommendation of 5-FU-based chemotherapy.

Large chromosomal copy number gains are ubiquitous throughout cancer types. However, which genes drive their selective advantage is not well established, and therefore they are hardly utilized in clinical practice. Our analysis of copy number patterns in pan-cancer datasets suggests that the selective advantage of copy number gains is largely driven by known oncogenes. Analysis of CRISPR screening data identifies a list of 101 genes that are likely to mediate the effect of these gains, which is highly enriched in annotated oncogenes but also contains genes that have not been implicated in cancer so far. Moreover, we show that specific gains are associated with drug sensitivity or resistance, with a strong enrichment of gains of oncogenes with increased sensitivity to inhibitors targeting these specific genes. Finally, we provide examples where gains can function as relevant clinical biomarkers for diagnosis and treatment. Thus, large copy number gains exert their selective advantage through known and novel oncogenes, and their systematic analysis could advance precision oncology.

Radioactive isotopes have underpinned radiation medicine and research since their discovery. From early interstitial applications of radium and 137Cs to modern application of 192Ir after-loaders and 125I seeds in brachytherapy, radioisotopes remain the standard of care for several prostate, gynecologic, and head and neck malignancies. However, the continuous emission and high specific activity of sealed sources impose substantial logistical, regulatory, and security burdens. International regulatory agencies therefore advocate minimizing reliance on high-activity sources where feasible. Advances in image-guided, energy-concentrating modalities have yielded clinically mature platforms capable of delivering ablative energy with steep dose gradients and normal-tissue sparing without the need for radioactivity. This review surveys five such modalities: (1) laser interstitial thermal therapy, an MR-thermography-guided laser ablation system; (2) intraoperative radiation therapy, using low-kV x rays or electrons; (3) MRI-guided linear accelerators (MR-LINAC); (4) ultra-high dose rate "FLASH" external-beam therapy; and (5) particle therapy using protons and heavy ions. Collectively, these technologies promise non-radioactive, highly conformal treatment options that leverage diverse radiobiological mechanisms to redefine therapeutic ratios in clinical practice.

Therapy-induced acquired resistance limits the clinical effectiveness of mutation-specific KRAS inhibitors in colorectal cancer (CRC). Here, we investigated whether broad-spectrum, active-state RAS inhibitors meet similar limitations. We found that KRAS-mutant CRC cell lines were sensitive to the RAS(ON) multiselective RAS inhibitor RMC-7977, given that treatment resulted in RAS-RAF-MEK-ERK pathway inhibition; halted proliferation; and, in some cases, induced apoptosis. RMC-7977 initially reduced the activity of a compartment-specific, dual-color reporter of ERK activity, with reporter reactivation emerging after long-term dose escalation. These drug-resistant cell populations exhibited distinct patterns of phospho-protein abundance, transcriptional activities, and genomic mutations, including a Y71H mutation in KRAS and an S257L mutation in RAF1. Transgenic expression of KRAS^{G13D, Y71H} or RAF1^S257L in drug-sensitive CRC cells induced resistance to RMC-7977. CRC cells that were resistant to RMC-7977 and harboring RAF1^S257L exhibited synergistic sensitivity to concurrent inhibition of RAS and RAF. Our findings demonstrate the power of reporter-assisted screening together with single-cell analyses for dissecting the complex landscape of therapy resistance. The strategy offers opportunities to develop clinically relevant combinatorial treatments to counteract the emergence of resistant cancer cells.

Castleman disease, a rare lymphoproliferative disorder with diverse features, is often misdiagnosed due to rarity and similarity to malignancies.

The study analyzed the clinicopathological characteristics, diagnostic challenges, and outcomes of head and neck Castleman disease (HNCD) to improve diagnostic accuracy and optimize management strategies.

Retrospective study of 21 HNCD patients treated at Beijing Tongren Hospital (2007-2024). Demographics, presentation, imaging, histopathology, treatment, and outcomes were analyzed using t-tests, Mann-Whitney U, and Fisher's exact tests.

Mean age 36.1; 52.4% female. Mainly painless cervical masses (95.2%). Histology: 85.7% hyaline vascular, 14.3% plasma cell. Imaging showing non-specific hypoechoic nodules (ultrasound) and homogeneous enhancement (CT/MRI). Surgical excision (85.7%) achieved 76.2% complete remission (mean follow-up: 85.2 months). Tumor size (34.6 ± 15.3 mm) didn't correlate with outcome (p = 0.756). One plasma cell patient (4.8%) died of unrelated causes. No recurrences or malignant transformations were observed.

HNCDs are predominantly unicentric and can be cured with complete surgical resection. Due to the lack of specificity of imaging and laboratory findings, diagnosis relies on histopathology. Collaborations among multiple centers and molecular studies are essential to advancing the precision treatment of HNCD.

Cancer cells exhibit a remarkable resilience to cytotoxic stress, often adapting through transcriptional changes linked to alterations in chromatin structure. In several types of cancer, these adaptations involve epigenetic modifications and restructuring of topologically associating domains. However, the underlying principles by which chromatin architecture facilitates such adaptability across different cancers remain poorly understood. To investigate the role of chromatin in this process, we developed a physics-based model that connects chromatin organization to cell fate decisions, such as survival following chemotherapy. Our model builds on the observation that chromatin forms packing domains, which influence transcriptional activity through macromolecular crowding. The model accurately predicts chemoevasion in vitro, suggesting that changes in packing domains affect the likelihood of survival. Consistent results across diverse cancer types indicate that the model captures fundamental principles of chromatin-mediated adaptation, independent of the specific cancer or chemotherapy mechanisms involved. Based on these insights, we hypothesized that compounds capable of modulating packing domains, termed Transcriptional Plasticity Regulators (TPRs), could prevent cellular adaptation to chemotherapy. We conducted a proof-of-concept compound screen using live-cell chromatin imaging to identify several TPRs that synergistically enhanced chemotherapy-induced cell death. The most effective TPR significantly improved therapeutic outcomes in a patient-derived xenograft model of ovarian cancer. These findings underscore the central role of chromatin in cellular adaptation to cytotoxic stress and present a framework for enhancing cancer therapies, with broad potential across multiple cancer types.

Tumor cell heterogeneity poses a significant challenge in the treatment of colorectal cancer, with dedifferentiation being a key factor in the emergence and maintenance of such heterogeneity. Does dedifferentiation necessarily promote colorectal cancer growth? What are its regulatory mechanisms in treatment response? These critical questions remain insufficiently understood. To investigate this issue, we develop a cancer cell population dynamics model. Our findings reveal that dedifferentiation impacts cancer growth in complex and varied patterns. Specifically, dedifferentiation can either facilitate or hinder cancer growth, with the outcomes depending on the dedifferentiation probability and the growth rates of different types of tumor cells. Subsequently, we consider the implications of dedifferentiation for various treatment strategies. Chemotherapy, which simultaneously promotes cell death and induces dedifferentiation, shows variable efficacy, potentially leading to tumor shrinkage or growth. In contrast, the combination of chemotherapy and high-intensity immunotherapy significantly enhances therapeutic outcomes, achieving more stable tumor control. These findings underscore the importance of incorporating dedifferentiation dynamics into colorectal cancer growth models and treatment designs, highlighting the advantages of combination therapy in overcoming the limitations of monotherapy.

Gastric cancer (GC), a widely recognized malignant neoplasm, poses significant treatment challenges. It is essential to pursue additional research to uncover novel therapeutic approaches and predictive methodologies. The phenomenon of disulfidptosis, recently identified as a distinct type of programmed cell death, offers intriguing possibilities for therapeutic applications.

This study performed differential analysis, GO analysis, KEGG, GSEA, and other analyses to investigate the relationship between disulfidptosis-related LncRNAs (DRLs) and TCGA GC data. The analysis included 373 gastric cancer samples and 32 normal gastric tissue samples, obtained from [specify data source, e.g., TCGA, GEO, or in-house cohorts]. Samples were rigorously screened based on [criteria, e.g., histopathological confirmation, RNA quality, or clinical completeness], and transcriptomic data were processed using [specific tools or pipelines] to ensure reproducibility. A new, more accurate predictive model was constructed, identifying potential therapeutic targets, signaling pathways, and sensitive drugs.

A refined prognostic signature associated with disulfidptosis in GC was developed through over 200 Lasso regression and MultiCox calculations. It was discovered that AL359182.1 and AC107021.2 could influence GC prognosis by modulating the MYH10/LIGHT JUNCTION or MYH10/REGULATION OF ACTIN CYTOSKELETON pathways. Notably, AL359182.1, newly identified as linked to GC prognosis, emerges as a potential novel therapeutic target. Furthermore, this study enhanced the accuracy of immunotherapy evaluations and screened for potential sensitive drugs.

Leveraging DRLs and TCGA GC data, this research identified highly precise prognostic signatures consisting of four LncRNAs: PINK1-AS, AC107021.2, AL359182.1, and AC009486.1. The discovery of two new signaling pathways could impact the prognosis of GC. AL359182.1 is proposed as a novel potential therapeutic target. The identified signature also effectively predicts the immunogenicity of GC and facilitates the screening of sensitive drugs. Further experimental validation is suggested to strengthen these conclusions.

As a key epigenetic regulator, E3 ubiquitin-ligase ubiquitin-like containing PHD and RING finger domains 1 (UHRF1) is essential for maintaining genomic stability. The aberrant activation of UHRF1 has been strongly implicated in cancer progression. Emerging evidence indicates that UHRF1 serves as a pivotal orchestrator of immune homeostasis. This review provides an overview of the impact of UHRF1 on both innate and adaptive immunity, highlighting its epigenetic and regulatory roles in the development and function of macrophages, T lymphocytes, and B lymphocytes. Crucially, the protective mechanisms of UHRF1 in autoimmune disorders while concurrently detailing its tumor-promoting functions are dissected. Finally, this review discusses the therapeutic challenges and future perspectives for targeting UHRF1 in autoimmune disorders and cancers.