Citations

Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, and the activated B cell–like subtype (ABC-DLBCL) is associated with particularly poor outcome. Many ABC-DLBCLs harbor gain-of-function mutations that cause inappropriate assembly of the CARMA1-BCL10-MALT1 (CBM) signalosome, a cytoplasmic complex that drives downstream NF-κB signaling. MALT1 is the effector protein of the CBM signalosome such that its recruitment to the signalosome via interaction with BCL10 allows it to exert both protease and scaffolding activities that together synergize in driving NF-κB. Here, we demonstrate that a molecular groove located between two adjacent immunoglobulin-like domains within MALT1 represents a binding pocket for BCL10. Leveraging this discovery, we performed an in silico screen to identify small molecules that dock within this MALT1 groove and act as BCL10-MALT1 protein-protein interaction (PPI) inhibitors. We report the identification of M1i-124 as a first-in-class compound that blocks BCL10-MALT1 interaction, abrogates MALT1 scaffolding and protease activities, promotes degradation of BCL10 and MALT1 proteins, and specifically targets ABC-DLBCLs characterized by dysregulated MALT1. Our findings demonstrate that small-molecule inhibitors of BCL10-MALT1 interaction can function as potent agents to block MALT1 signaling in selected lymphomas, and provide a road map for clinical development of a new class of precision-medicine therapeutics.

Abstract Background: Although colorectal cancer survival rates are improving, the risk of incident type 2 diabetes mellitus (T2D) among Asian, Native Hawaiian, and Pacific Islander (ANHPI) ethnic groups is poorly understood. This study aims to identify high-risk groups and quantify the risk across different periods. Methods: Using the SEER–Medicare database, colorectal cancer survivors who were ANHPI were matched to non-Hispanic White (NHW) survivors at a ratio of 1:3. Multivariable Cox regression models computed HRs and 95% confidence intervals (CI) for incident T2D. Results: The study included 6,463 NHW and 2,901 ANHPI colorectal cancer survivors diagnosed between 2000 and 2017. Among them, 715 NHW and 484 ANHPI developed T2D during 39,097 and 10,769 person-years of follow-up, respectively. ANHPI colorectal cancer survivors had an elevated T2D risk compared with NHW across all follow-up periods (HRoverall: 1.84, 95% CI, 1.51–2.25; HR1–5 years: 1.83, 95% CI, 1.45–2.30). Southeast and East Asians demonstrated the highest T2D risks. Colon cancer was linked to early postdiagnosis T2D risk, whereas rectal cancer was associated with later risk. No significant association was observed for Native Hawaiians and Pacific Islanders. Conclusions: ANHPI colorectal cancer survivors face a greater risk of T2D, particularly among Southeast and East Asians. These findings highlight the need for evidence-based survivorship strategies to prevent T2D and reduce ethnic disparities. Impact: This is the first study to examine T2D risk among ANHPI colorectal cancer survivors, providing critical insights to inform tailored diabetes prevention and survivorship care.

Abstract Melanoma is characterized by its rapid progression and high mortality rates, making early and accurate detection essential for improving patient outcomes. This paper presents a comprehensive review of significant advancements in early melanoma detection, with a focus on integrating computer vision and deep learning techniques. This study investigates cutting-edge neural networks such as YOLO, GAN, Mask R-CNN, ResNet, and DenseNet to explore their application in enhancing early melanoma detection and diagnosis. These models were critically evaluated for their capacity to enhance dermatological imaging and diagnostic accuracy, crucial for effective melanoma treatment. Our research demonstrates that these AI technologies refine image analysis and feature extraction, and enhance processing capabilities in various clinical settings. Additionally, we emphasize the importance of comprehensive dermatological datasets such as PH2, ISIC, DERMQUEST, and MED-NODE, which are crucial for training and validating these sophisticated models. Integrating these datasets ensures that the AI systems are robust, versatile, and perform well under diverse conditions. The results of this study suggest that the integration of AI into melanoma detection marks a significant advancement in the field of medical diagnostics and is expected to have the potential to improve patient outcomes through more accurate and earlier detection methods. Future research should focus on enhancing these technologies further, integrating multimodal data, and improving AI decision interpretability to facilitate clinical adoption, thus transforming melanoma diagnostics into a more precise, personalized, and preventive healthcare service.

BACKGROUND: Data registries lack a definitive classification system that distinguishes different locations of colon cancer from one another. OBJECTIVE: To establish an international consensus on the definition of primary colon cancer segment locations. DESIGN: Between December 2022 and June 2023, Delphi survey study was conducted to seek opinions from relevant international experts and eventually develop a consensus definition of each colon cancer segment. SETTING: Three-round online-based Delphi survey study. INTERVENTIONS: Online survey included 17 questions. In the first two rounds, participating experts were asked to rank each statement on a scale of 1–9 (9 is the most relevant). Consensus statements and definitions were revised according to results, obtaining a consensus score of 7–9. During the third round and online meeting, definitions and statements reached a moderate or high consensus(above 4 in more than 70% of participants) were included. MAIN OUTCOME AND MEASURE: Primary goal of our project was focused on precisely localizing the specific segment affected by primary colon cancer, rather than to identify surgical treatment or type of resection needed for particular segment. RESULTS: The first round included 331 experts, 301 (91%) completed the second round, and 295 (98%) completed the final round. Experts strongly supported the use of a “10 cm rule” to describe colon cancer sites at the flexures and anatomical landmarks for other segments. Regarding the definition of rectosigmoid cancer, experts from America and Europe reached a high consensus that the term rectosigmoid as a colon cancer location must be abolished in contrast to experts from Asia. Description of cancers overlapping segments achieved a consensus of 64%. LIMITATIONS: Subjective decisions are based on individual expert clinical experience. CONCLUSIONS: This Delphi survey, the first internationally conducted consensus study, achieved a remarkable level of consensus among a panel of global experts. Ambiguity still exists regarding overlapping lesions. See Video Abstract .

Ovarian cancer (OC) has the highest mortality rate among gynecologic malignant tumors and is clinically difficult to cure. Traditional Chinese medicine (TCM) has shown unique advantages in the treatment of OC. However, there is currently a lack of normative guidance documents for the treatment of OC with integrated traditional Chinese and western medicine. The guidelines are the first comprehensive approach to diagnosing and treating OC by integrating TCM with western medicine. Adhering to evidence-based principles, the guidelines draw on the most recent advancements in OC treatment from both domestic and international researches. The guidelines formulate a variety of therapeutic methods, including oral Chinese herbal medicine, acupuncture, and external treatments, providing a treatment strategy for the combined use of TCM and western medicine in OC. Furthermore, the guidelines establish a diagnostic and treatment pathway for the holistic management of OC with TCM throughout the disease’s progression. The guidelines were officially published in the China Association of Chinese Medicine in January 2023, which provided a scientific basis for the formulation of clinical diagnosis and treatment strategies and promoted integration with international academic standards. This paper interpreted the features of the guidelines and the 7 PICO issues (Population, Intervention, Comparison, Outcome) in the whole TCM management of OC, aiming to help TCM and western medicine practitioners better understand and apply the guidelines, and provide better medical services for patients with OC.

Ophthalmic immune-related adverse events (Eye-irAEs) from immune checkpoint inhibitors can cause visual morbidity. The absence of standardized definitions for Eye-irAEs not only impedes the development of evidence-based treatments but also progress in translational research. The objective of this study was to develop consensus guidance for an approach to Eye-irAEs. Four ophthalmic physicians (uveitis specialists and neuro-ophthalmologists) drafted Eye-irAE consensus guidance and definitions, which were reviewed by the multidisciplinary Eye-irAE definition panel. The panel was divided into Group A (Neuro-ophthalmology/Orbital Disease) and Group B (Uveitis/Ocular Surface Disease). A modified Delphi consensus process was used, with two rounds of anonymous ratings by panelists and two meetings to discuss areas of controversy. For each disorder, five diagnostic components were evaluated: symptoms, examination findings, laboratory studies/imaging findings, diagnostic criteria, and treatment. Panelists rated content for usability, appropriateness and accuracy on 9-point scales in electronic surveys and provided free-text comments. Aggregated survey responses were incorporated into revised definitions. Consensus was based on numeric ratings using the RAND Corporation/ University of California Los Angeles Health Services Utilization Study (RAND/UCLA) Appropriateness Method with prespecified definitions. 29 panelists from 25 academic medical centers voted on 114 rating scales (66 neuro-ophthalmic/orbital disease components, 48 uveitis/ocular surface disease components); of these, 86.3% (57/66) in Group A and 89.6% (43/48) in Group B reached first-round consensus. After revisions, all items except 6.1% (4/66) in Group A and 1.6% (1/60) in Group B received second-round consensus. Consensus definitions were achieved for 10/11 neuro-ophthalmic/orbital disorders: optic neuritis, inflammatory optic disc edema, arteritic ischemic optic neuropathy, optic perineuritis, orbital inflammation, thyroid eye disease-like orbital inflammation, cavernous sinus syndrome, oculomotor mononeuritis, trochlear mononeuritis, and abducens mononeuritis. Consensus definitions were achieved for 9/10 uveitis/ocular surface disorders: anterior uveitis, intermediate uveitis, posterior uveitis, panuveitis, Vogt-Koyanagi-Harada-like syndrome, sarcoidosis-like syndrome, acute macular neuroretinopathy, dry eye disease, and scleritis. These disease definitions establish a standardized classification for Eye-irAE, highlighting differences between irAEs and other inflammatory disorders. Importantly, diagnostic certainty does not always align directly with the need to treat as an Eye-irAE. Given the consensus from this representative panel group, it is anticipated the definitions will be used broadly across clinical and research settings.