Radiotherapy produces excessive reactive oxygen species (ROS), which can lead to DNA damage and apoptosis in tumor cells, thereby killing malignant cells. Chlorogenic acid (CGA) is a well‐known antioxidant in coffee due to its strong ability to remove ROS. However, the effect of CGA on radiotherapeutic efficacy remains unclear. In this study, we showed that CGA could hinder the therapeutic effect of radiotherapy by inhibiting radiation‐induced apoptosis and DNA damage via scavenging excessive ROS and activating the NF‐E2‐related factor 2 (Nrf2) antioxidant system in hepatocellular carcinoma (HCC) cells and a murine model. The knockdown of Nrf2 reversed CGA‐mediated radiation resistance in HCC cells. In conclusion, CGA might be a potential tumor‐protective compound upon irradiation and reduce the efficacy of radiotherapy via ROS scavenging and Nrf2 activation.

Introduction: TRIpartite motif (TRIM) proteins are important members of the Really Interesting New Gene‐finger‐containing E3 ubiquitin‐conjugating enzyme and are involved in the progression of hepatocellular carcinoma (HCC). However, the diverse expression patterns of TRIMs and their roles in prognosis and immune infiltrates in HCC have yet to be analyzed.Materials: Combined with previous research, we used an Oncomine database and the Human Protein Atlas to compare TRIM family genes' transcriptional levels between tumor samples and normal liver tissues, as verified by the Gene Expression Profiling Interactive Analysis database. We investigated the patient survival data of TRIMs from the Kaplan–Meier plotter database. Clinicopathologic characteristics associations and potential diagnostic and prognostic values were validated with clinical and expressional data collected from the cancer genome atlas.Results: We identified TRIM28, TRIM37, TRIM45, and TRIM59 as high‐priority members of the TRIMs family that modulates HCC. Low expression of TRIM28 was associated with shorter overall survival (OS) than high expression (log‐rank p = 0.009). The same trend was identified for TRIM37 (p = 0.001), TRIM45 (p = 0.013), and TRIM59 (p = 0.011). Multivariate analysis indicated that the level of TRIM37 was a significant independent prognostic factor for both OS (p = 0.043) and progression‐free interval (p = 0.044). We performed expression and mutation analysis and functional pathways and tumor immune infiltration analysis of the changes in TRIM factors.Conclusion: These data suggested that TRIM28, TRIM37, TRIM45, and TRIM59 could serve as efficient prognostic biomarkers and therapeutic targets in HCC.

This study evaluates ChatGPT‐4's potential as a decision‐support tool in the treatment of recurrent or metastatic head and neck squamous cell carcinoma (HNSCC). The study involved 12 retrospectively chosen patients with detailed clinical, tumor, treatment history, imaging, pathology, and symptomatic data. ChatGPT‐4, along with six experts and 10 junior oncologists, assessed these cases. The AI model applied the 8th edition AJCC TNM criteria for tumor staging and proposed treatment strategies. Performance was quantitatively rated on a 0–100 scale by both expert and junior oncologists, with further analysis through statistical scoring and intraclass correlation coefficients. Findings revealed that ChatGPT‐4 achieved an 83.3% accuracy rate in tumor staging with two instances of mis‐staging. Junior doctors rated its staging performance highly, showing strong consensus on language capabilities and moderate on learning assistance. Experts rated ChatGPT‐4's treatment strategy: high agreement on subject knowledge (median 86, mean 84.7), logical reasoning (median 83, mean 82), and analytical skills (median 85, mean 82); moderate on ChatGPT‐4's usefulness for treatment decision (median 80, mean 77) and its recommendations (median 80, mean 76.8). Junior doctors rated ChatGPT‐4 higher in treatment strategy (medians above 85) with limited consensus (subject knowledge: median 88, mean 84.5; logical reasoning: median 90, mean 83.2; analytical skills: median 90, mean 82.5; usefulness: median 85, mean 81.8; agreements for: median 85, mean 80.4). ChatGPT is proficient in tumor staging but moderately effective in treatment recommendations. Nonetheless, it shows promise as a supportive tool for clinicians, particularly for those with less experience, in making informed treatment decisions.