Objective To investigate the expression profile, prognostic value, gene co-expression network, and immunomodulatory role of BRF1 in a pan-cancer context, and to explore its biological functions and molecular regulatory mechanisms in esophageal squamous cell carcinoma (ESCC). Methods The pan-cancer dataset from The Cancer Genome Atlas (TCGA) was utilized to analyze the differential expression of BRF1 in tumor versus normal tissues, its association with patient survival, pathway enrichment for co-expressed genes, and immune features (including immune checkpoints, cytokines, and immune cell infiltration). The expression profile of BRF1 in ESCC was validated using the Gene Expression Omnibus (GEO) database. In vitro, BRF1 was knocked down in ESCC cells using siRNA. Cell proliferation and migration were assessed by MTT and Transwell assays, respectively. The expression levels of proliferation- and migration-related proteins were detected by Western blotting. The correlation between BRF1 and ferroptosis was analyzed using TCGA data. Results BRF1 was significantly upregulated in over 20 types of cancer, and its high expression was associated with poor prognosis in patients with adrenocortical carcinoma and prostate adenocarcinoma. BRF1 was found to positively regulate the T-cell-mediated cell death pathway in esophageal adenocarcinoma and was associated with the circadian rhythm regulation pathway in pancreatic adenocarcinoma. The correlation of BRF1 with immune checkpoints, cytokine networks, and immune cell infiltration was found to be cancer type-specific. In vitro experiments demonstrated that knocking down BRF1 significantly inhibited the proliferation of ESCC cells, accompanied by the downregulation of the proliferation marker PCNA. Cell migration was also significantly impaired, with decreased expression of Vimentin and MMPs and increased expression of E-cadherin. Furthermore, the expression of BRF1 was positively correlated with that of ferroptosis-antagonizing genes, such as GPX4, HSPA5, and SLC7A11. Conclusion BRF1 plays complex roles in pan-cancer, participating in the regulation of tumorigenesis, progression, and immune infiltration. BRF1 promotes the proliferation and migration of ESCC cells, a mechanism potentially associated with the regulation of ferroptosis resistance. These findings suggest that BRF1 could be a potential therapeutic target for ESCC.

Recent research from the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) indicates that breast cancer is the most prevalent malignant tumor among women, posing a significant threat to women's health. Surgery remains the primary therapeutic modality for breast cancer. Recently, endoscopic and robotic breast surgical techniques have gained acceptance among both surgeons and patients. However, considerable variation exists in surgical approaches and outcomes. To standardize these techniques, facilitate their broader clinical adoption, and ultimately improve patient care, the Endoscopic-robotic Breast Surgery Clinical Trials Consortium (ErBSCTC) of China has developed this guideline. This document encompasses the technologies and instrumentation utilized in endoscopic and robotic breast surgery, surgical techniques, perioperative management, complication handling, long-term follow-up, and oncologic outcomes, aiming to provide evidence-based guidance for healthcare professionals involved in the prevention, diagnosis, and treatment of breast diseases.

Breast cancer is the most common malignant tumor among women in China, with surgery being one of the primary treatment modalities. Endoscopic/robotic breast surgery (ErBS) is gaining widespread acceptance among patients and surgeons alike due to its advantages of minimal invasiveness, superior cosmetic outcomes, and accelerated recovery. However, substantial heterogeneity currently exists across China regarding patient selection, standardized operative techniques, perioperative management, and complication handling, underscoring the urgent need for evidence-based consensus guidelines. To promote standardization and ensure consistent quality of ErBS, the Chinese Endoscopic-Robotic Breast Surgery Clinical Trials Consortium (CErBSCTC) has systematically reviewed the latest high-quality evidence and formulated the "Protocol for China Endoscopic and Robotic Breast Surgery Guidelines (2026 edition)", which outlines a comprehensive methodology for guideline development.

This guideline, presented in three parts, details the core aspects of endoscopic/robotic breast surgery, including its techniques, equipment, surgical procedures, perioperative management, complication treatment, long-term follow-up, and outcomes. Part one offered a comprehensive overview of indications for endoscopic and robotic breast surgery, intraoperative techniques, surgical instrument choices, and common endoscopic and robotic breast reconstruction procedures. This part will cover other endoscopic breast procedures beyond immediate breast reconstruction and include perioperative management strategies, to provide healthcare professionals involved in endoscopic and robotic breast surgery with systematic operational guidelines and clinical decision-making references.

Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Objective To use imaging features of pulmonary nodules to predict the risk of lymph node metastasis in patients with cT1-stage non-small cell lung cancer (NSCLC), providing a reference for clinical decision-making. Methods A retrospective analysis was conducted on the imaging features and postoperative pathological results of cT1 NSCLC patients who underwent surgical treatment at Linyi People’s Hospital from July 2019 to July 2022. Patients were grouped and analyzed according to lymph node metastasis status. Results A total of 1 123 patients were included, comprising 471 males and 652 females, with a median age of 59 (52, 66) years. Comparative analysis revealed that sex, age, nodule location, nodule size on imaging, solid component size, consolidation tumor ratio (CTR), average CT value, and tumor proximity to the pleura all influenced lymph node metastasis. A nomogram was constructed, indicating that the probability of lymph node metastasis in cT1 NSCLC was positively correlated with solid component size, CTR, and average CT value of the pulmonary nodule, and negatively correlated with patient age. The area under the receiver operating characteristic curve was 0.929. Conclusion For cT1 NSCLC patients, the probability of lymph node metastasis can be predicted by measuring the solid component size, CTR, and average CT value of the pulmonary nodule, in conjunction with patient age. However, relying solely on pulmonary nodule imaging characteristics is insufficient to determine a specific lymph node dissection strategy.

Objective     To construct a radiomics model for identifying clinical high-risk carotid plaques. Methods     A retrospective analysis was conducted on patients with carotid artery stenosis in China-Japan Friendship Hospital from December 2016 to June 2022. The patients were classified as a clinical high-risk carotid plaque group and a clinical low-risk carotid plaque group according to the occurrence of stroke, transient ischemic attack and other cerebrovascular clinical symptoms within six months. Six machine learning models including eXtreme Gradient Boosting, support vector machine, Gaussian Naive Bayesian, logical regression, K-nearest neighbors and artificial neural network were established. We also constructed a joint predictive model combined with logistic regression analysis of clinical risk factors. Results    Finally 652 patients were collected, including 427 males and 225 females, with an average age of 68.2 years. The results showed that the prediction ability of eXtreme Gradient Boosting was the best among the six machine learning models, and the area under the curve (AUC) in validation dataset was 0.751. At the same time, the AUC of eXtreme Gradient Boosting joint prediction model established by clinical data and carotid artery imaging data validation dataset was 0.823. Conclusion     Radiomics features combined with clinical feature model can effectively identify clinical high-risk carotid plaques.

Background: Although trichorhinophalangeal syndrome type 1 (TRPS1) was initially thought to be highly sensitive and specific for carcinomas and mesenchymal tumors of mammary origin, more recent data suggest its expression is not limited to breast neoplasms but also can be seen in other cutaneous neoplasms, such as extramammary Paget disease and squamous cell carcinoma (SCC) in situ. Methods: Two-hundred cases of non-melanocytic cutaneous neoplasm, including basal cell carcinomas (BCCs) (n = 41), SCCs (n = 35), Merkel cell carcinomas (MCCs) (n = 25), and adnexal neoplasms (n = 99), were tested for TRPS1 expression using a monoclonal anti- TRPS1 rabbit anti-human antibody. Results: TRPS1 expression was present in almost all cases of SCC (94%), with a median H-score of 200, while it was either absent or only focally present in most BCCs (90%), with a median H-score of 5. The difference between BCCs and SCCs in H-score was significant (p < .001). All MCCs (100%) lacked TRPS1 expression. TRPS1 expression was frequently seen in most adnexal neoplasms, benign and malignant, in variable intensity and proportion but was consistently absent in apocrine carcinomas. All endocrine mucin-producing sweat gland carcinomas (EMPSGCs) (100%, 6/6) showed diffuse and strong TRPS1 immunoreactivity, with a median H-score of 300, which was significantly different (p < .001) than that of BCCs. Conclusions Our study shows that TRPS1 may be an effective discriminatory marker for BCCs and SCCs. It also has a role in distinguishing BCCs from EMPSGCs.

Humans ; Infant ; Female ; Breast Neoplasms ; Carcinoma