National Clinical Research

This study aimed to establish matched patient-derived organoids from oral squamous cell carcinoma (PDO-T) and adjacent normal mucosa (PDO-N), characterize their distinct features, and evaluate their impact on drug response. PDOs were generated from primary OSCC tissues and matched adjacent normal mucosa obtained from 18 patients. Morphological and histological characteristics were assessed using brightfield microscopy and phalloidin staining. Immunohistochemistry was performed to evaluate differential marker expression. Drug response assays were conducted in paired PDO-T and PDO-N to assess chemotherapeutic sensitivity. We successfully established 5 PDO-T and 15 PDO-N lines, with PDO-N exhibiting a higher success rate (∼80 %). Morphological analysis showed that PDO-N formed spherical structures with a central cavity and polarity, while PDO-T displayed irregular structures with heterogeneous cell arrangements. Immunohistochemistry revealed broad distribution of Ki-67, p63 and YAP/TAZ in PDO-T, contrasting with their basal layer restriction in PDO-N. p53 was strongly positive in PDO-T. CK5 and CK13 exhibited a stratified pattern in PDO-N. Importantly, drug testing in paired PDO-T and PDO-N revealed divergent responses, with PDO-N generally more resistant and able to maintain morphological integrity under high-dose treatment. Our comparative analysis delineates distinct features between PDO-T and PDO-N in morphology, biomarker expression, and drug response. These findings provide an intuitive framework for their identification, thereby improving the accuracy of drug screening and enhancing the translational value of PDOs.

We thank Professor Taha for the insightful Editorial on our study addressing hepatocellular carcinoma (HCC) risk prediction after hepatitis B surface antigen (HBsAg) seroclearance [1, 2]. His comments appropriately highlight emerging priorities in the future management of HCC, particularly the need for refined risk stratification and stage-shifting surveillance strategies [3]. We are encouraged that the clinical relevance of our model, particularly its capacity to identify early-stage HCC, has been recognized. Our study was designed to address a clinically under-recognized population, patients achieving HBsAg seroclearance, who retain a measurable but heterogeneous residual risk of HCC [4]. By focusing specifically on this population, our model integrates six routinely available clinical parameters to provide a simple and clinically implementable tool for risk stratification. We acknowledge that the CAMP-B model has also demonstrated robust performance in this setting [5]. Our model builds upon these prior efforts by further refining risk stratification in this population and offering complementary clinical value. Importantly, the limitations highlighted in the Editorial also point towards several directions for future research. The absence of detailed viral factors, performance status, and potentially protective exposures reflects inherent constraints of real-world retrospective datasets, but also underscores the need for prospective cohorts with more comprehensive phenotyping. In the context of HBsAg seroclearance, viral replication is typically minimal or undetectable, as serum HBsAg levels are thought to reflect intrahepatic cccDNA transcriptional activity and HBV DNA integration-derived transcripts [6]. However, this suggests that traditional virological markers may have limited ability to capture the underlying biological heterogeneity in this setting, thereby necessitating the exploration of alternative biomarkers. Importantly, HBV DNA integration can persist within the host genome even after effective viral suppression, and the burden of viral integration—particularly the number of integration breakpoints—has been shown to correlate with the likelihood of HBsAg loss [7]. These findings highlight that integration-related heterogeneity may contribute to differential clinical outcomes following seroclearance. In addition, performance status, such as Eastern Cooperative Oncology Group score, has been well established as a prognostic factor in oncology [8]. However, in real-world outpatient cohorts with regular follow-up, there may be an inherent selection towards patients with preserved functional status. Future studies are therefore warranted to clarify the role of functional status in both HBsAg seroclearance and subsequent HCC risk. Furthermore, metabolic comorbidities, including diabetes, metabolic associated fatty liver disease, and hypertension, have been increasingly recognized as contributors to hepatocarcinogenesis [9]. Correspondingly, medications targeting these conditions may exert protective effects on HCC development in patients after HBsAg seroclearance, although robust evidence remains limited. This highlights an important avenue for future investigation, particularly in relation to optimizing long-term management strategies in this population. From a translational perspective, our findings support a shift towards risk-adapted surveillance strategies. Further external validation and prospective studies will be essential to confirm its clinical utility and to facilitate its integration into routine practice. Combining clinical risk scores with emerging machine learning approaches or multi-omics data may offer opportunities to refine individualized prediction and improve early detection. In conclusion, our findings provide a pragmatic framework for risk stratification after HBsAg seroclearance. Yan Lou: conceptualization, writing – original draft, writing – review and editing, project administration, supervision. Shuaibing Ying: conceptualization, writing – original draft. Yunqing Qiu: conceptualization, supervision, project administration, writing – original draft, writing – review and editing. The authors' declarations of personal and financial interests are unchanged from those in the original article [2]. This article is linked to Ying et al. papers. To view these articles, visit https://doi.org/10.1111/apt.70637 and https://doi.org/10.1111/apt.70644. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

To identify the research status, major contributors, and emerging frontiers in acupuncture randomized controlled trials (RCTs) through bibliometric analysis, assisting clinicians, researchers, and policymakers in rapidly capturing valuable research hotspots and potential directions. Articles related to acupuncture RCTs published between January 1, 2010, and December 31, 2024, were retrieved 1,908 articles from the Web of Science Core Collection and Scopus. Multiple software tools (Origin 2021, CiteSpace, and VOSviewer) have been integrated to comprehensively visualize relationships among authors, journals, keywords, institutions, and countries. The number of acupuncture RCTs grew steadily from 59 articles in 2010 to a peak of 205 in 2022, later stabilizing at 160. China led in output (1,096 articles), followed by the United States (263) and South Korea (216). Leading institutions included Beijing University of Chinese Medicine (166 articles; 2,084 citations) and Kyung Hee University (112 articles; top non-Chinese institution). Chinese scholars Liu Zhishun (most publications) and Liu Cunzhi (most citations) were the most prolific and highly cited researchers, respectively. The keywords of greatest interest were "Acupuncture" (1,188 times) and "Randomized Controlled Trial" (439 times). The next three most frequent keywords were "Electroacupuncture" (409 times), "Management" (291 times), and "Pain" (277 times). Burst keywords were "guidelines," "sleep," and "diagnosis" (2021-2022). Trials (274 articles) and Acupuncture in Medicine (H-index 26/2,099 citations) were the primary publishing journals. This study conducted a multidimensional analysis of the current state of acupuncture RCT research, revealing key research domains, hotspots, and potential trends. Building on these findings, we propose the following directions for future investigations: (1) identifying potential conditions for acupuncture through four classification approaches: conditions with conflicting research findings, conditions for which a body of evidence is emerging but has not yet reached a broad consensus, conditions for which modern medicine currently has no superior treatment options, and conditions where acupuncture can further expand its application; (2) key factors influencing acupuncture efficacy, such as acupoint prescription, core acupuncture parameters and the dose-effect relationship should be explored; (3) research quality and reliability should be ensured by adhering to rigorous methodological design and reporting standards, including appropriate selection of control groups and outcome measures.