Radiation-induced lung injury (RILI) is one of the most common complications of thoracic radiotherapy, seriously affecting patients' quality of life and survival. The mechanisms underlying RILI and its therapeutic strategies have long been major focuses of research. Interleukin-17A (IL-17A), an important pro-inflammatory cytokine, has recently attracted increasing attention in studies of RILI. IL-17A regulates immune responses through multiple signaling pathways-not only promoting the recruitment of neutrophils during the acute phase of RILI, but also accelerating pulmonary fibrosis during the chronic phase by enhancing the activity of fibrogenic factors. Thus, IL-17A is considered a promising new therapeutic target for RILI. This review summarizes the mechanisms of IL-17A in RILI, discusses the prospects and challenges of targeting IL-17A for RILI treatment, and provides a theoretical basis for optimizing clinical intervention strategies.

Objective:To evaluate the effect of the radiation dose of thoracic cage bone structure on clinical prognosis in patients with locally advanced non‐small cell lung cancer (LA‐NSCLC) receiving chemoradiotherapy, and to develop and verify a combined model combining the radiation dose of bone structure, the estimated radiation dose of immune cells (EDRIC) and other related factors to predict the prognosis of LA‐NSCLC.Methods:Clinical data of 197 patients with LA‐NSCLC who underwent chemoradiotherapy were retrospectively analyzed. All patients were randomly divided into the training set and testing set at a ratio of 7:3 using computer random partitioning. The EDRIC value was calculated using the model developed by Jin et al. and modified by Ladbury et al. The scope of the thoracic cage structure includes the ribs, sternal manubrium, sternal body, thoracic vertebral body, thoracic vertebral appendages, and thoracic vertebrae. The tumor volume, ERDIC, and average bone structure dose (D mean) were categorized into two groups using the P25, P50, P75 value from the quartile method. Univariate and multivariate Cox proportional hazards regression were used to analyze the influencing factors of overall survival (OS), local progression‐free survival (LPFS), and distant metastasis‐free survival (DMFS) for predicting the outcome, and significant correlated variables were retained to construct a combined prediction model with EDRIC. The receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curves were plotted for subjects at the 2‐year time point of the combined model to evaluate the predictive performance. The model was visualized through a nomograph. Results:In the thoracic cage bone structure, D mean > 47.3 Gy of the sternal manubrium was an independent risk factor of OS, LPFS, and DMFS of LA-NSCLC patients. D mean > 23.1 Gy of thoracic vertebral body was an independent risk factor of OS, and D mean > 14.4 Gy of thoracic vertebral body was an independent risk factor of DMFS. Among other variables, gross tumor volume (GTV) >50.2 cm 3 was a risk factor for OS, and GTV >87.0 cm 3 was a risk factor for LPFS. Planning target volume >571.9 cm 3 was a risk factor for DMFS. A combined prediction model for OS, LPFS, and DMFS was established with EDRIC using features significantly associated with these three predicted outcomes. The area under the ROC curve (AUC) of OS combined model in the training set and test set were 0.708 and 0.696, respectively, and the AUC of DMFS combined model were 0.675 and 0.639, respectively. The calibration curve and DCA curve of the two prediction endpoints showed that the combined model had good prediction accuracy and clinical benefit. However, the LPFS model was not good in accuracy and clinical applicability. Conclusions:The radiation dose of sternal manubrium and thoracic vertebral body in the thoracic cage bone structure is an independent influencing factor for the prognosis of LA‐NSCLC patients after chemoradiotherapy. The combined model has good predictive performance for OS and DMFS.

Objective:To evaluate the efficacy and safety of radiotherapy combined with sintilimab and bevacizumab (anti-angiogenic agent) in patients with unresectable advanced hepatocellular carcinoma (HCC).Methods:Clinical data of 80 patients with unresectable advanced HCC admitted to Shanghai Mengchao Cancer Hospital from January 2021 to September 2023 were retrospectively analyzed. All patients were divided into two groups based on treatment regimens: the systemic therapy group ( n=41) receiving sintilimab combined with bevacizumab, and combined radiotherapy group ( n=39) receiving radiotherapy plus sintilimab and bevacizumab. Efficacy was evaluated using the response evaluation criteria in solid tumors (RECIST) 1.1 version and modified RECIST for HCC. Treatment-related adverse events (TRAE) were assessed by the common terminology criteria for adverse events (CTCAE) 4.03 version. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Secondary endpoints included objective response rate (ORR), disease control rate (DCR), and TRAE. Independent sample t-test was used for normally distributed quantitative data, and Chi-square test for qualitative data. Survival analysis was performed via Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression models were applied to analyze prognostic factors. Results:In terms of efficacy, no patient obtained complete response (CR) in the systemic therapy group, while 2 cases achieved CR in the combined radiotherapy group. The ORR was 22% (9/41) in the systemic therapy group and 59% (23/39) in the combined radiotherapy group ( P=0.001). The DCR was 85% (35/41) and 97% (38/39) in the two groups ( P=0.130), with the incidence of progressive disease of 15% (6/41) and 3% (1/39) ( P=0.130), respectively. The median PFS was 8.0 months (95% CI=6.8-9.2 months) in the combined radiotherapy group and 4.4 months (95% CI=4.1-4.7 months) in the systemic therapy group ( P=0.002). The median OS was 19.0 months (95% CI=15.5-22.5 months) in the combined radiotherapy group and 12.5 months (95% CI=9.4-15.6 months) in the systemic therapy group ( P=0.006). Radiotherapy was an independent protective factor for both PFS ( HR=0.474, 95% CI=0.289-0.778, P=0.003) and OS ( HR=0.403, 95% CI=0.218-0.744, P=0.004). The number of tumors >3 was an independent risk factor for both PFS ( HR=2.658, 95% CI=1.485-4.755, P=0.001) and OS ( HR=3.245, 95% CI=1.773-5.939, P=0.001). There was no significant difference in TRAE between two groups ( P > 0.05). Conclusions:Radiotherapy combined with sintilimab and bevacizumab shows high efficacy and acceptable safety in patients with unresectable advanced HCC.

Objective:To investigate the clinical characteristics of cervical adenocarcinoma and analyze the survival status and related prognostic factors.Methods:The data of 229 patients with cervical adenocarcinoma who were diagnosed pathologically in the General Hospital of Ningxia Medical University from January 2013 to October 2022 were retrospectively analyzed. Among them, 198 early stage patients were mainly treated with surgery, and 31 locally advanced stage patients were mainly treated with chemoradiotherapy. The overall survival (OS) and progression-free survival (PFS) rates in the whole cohort of patients and different treatment subgroups were calculated. Kaplan‐Meier method and log‐rank test were used for survival analysis, and Cox proportional hazards model was used for univariate and multivariate survival analyses.Results:Among the 229 patients, there were 11 subtypes of pathological classifications, predominantly of the usual‐type. At the end of follow‐up, 57 patients (24.9%) relapsed. The 3‐ and 5‐year OS rates were 86.4% and 79.3%, respectively, and the 3‐ and 5‐year PFS rates were 81.6% and 73.6%, respectively. Multivariate analysis showed that International Federation of Gynecology and Obstetrics (FIGO) staging of stages Ⅲ‐Ⅳ was an independent prognostic factor for OS and PFS ( HR=2.033, 95% CI=1.456‐2.839, P<0.001; HR=1.701, 95% CI=1.251‐2.313, P=0.001). Lymph node metastasis was an independent risk factor for PFS ( HR=1.610,95% CI=1.021‐2.539, P=0.041). Subgroup analysis of 198 patients with surgical treatment: the 3‐ and 5‐year OS rates were 90.0% and 84.9%, and the 3‐ and 5‐year PFS rates were 82.7% and 76.7%, respectively. Multivariate analysis showed that lymph node metastasis and deep invasion depth were the main risk factors for OS ( HR=6.893, 95% CI=2.592‐18.327, P<0.001; HR=1.952, 95% CI=1.164‐3.272, P=0.011) and PFS ( HR=5.507, 95% CI=2.569‐11.805, P<0.001; HR=1.638, 95% CI=1.09‐2.461, P=0.018). Ovarian preservation was an independent risk factor for PFS ( HR=3.364, 95% CI=1.115‐10.151, P=0.031). Conclusions:The pathological types of cervical adenocarcinoma are complex and diverse. Local recurrence and distant metastasis are the main reasons for treatment failure. FIGO stage, lymph node metastasis and postoperative depth of invasion are the main prognostic factors of cervical adenocarcinoma.

Prostate cancer (PC) is one of the common malignant tumors among men, and its incidence has been increased in China across these years. Radiotherapy is the mainstay therapy for PC. Due to the special biological characteristics of PC and the development of precision radiotherapy technology, hypofractionated regimens of radiotherapy are progressing rapidly, which has been increasingly applied in clinical practice and extensively studied by more and more researchers. In this review, the biological mechanisms of hypofractionated regimens, related clinical research, and practical applications of hypofractionated radiotherapy (such as definitive radiotherapy, postoperative adjuvant / salvage radiotherapy, oligometastasis radiotherapy, and pelvic lymph node radiotherapy) were summarized and its efficacy and toxicity profiles were analyzed, aiming to provide reference for scientific promotion of short‐course, hypofractionated precision radiotherapy for PC in China.

Malignant tumor is a major health problem plaguing the world. It metastasizes to the bone through complex ways, leading to a series of complications. In recent years, with the continuous progress of radiotherapy technology, the importance of radiotherapy has been ever strengthened. In this article, the application effect of radiotherapy in the treatment of bone metastases was evaluated by illustrating the types, metastasis principle and clinical manifestations of bone metastases, and different advantages of external irradiation, stereotactic radiotherapy and radionuclide therapy were elucidated, aiming to provide reference for comparing the differences in response to radiotherapy among different types of bone metastases and achieve the optimal treatment effect.

Glioblastoma (GBM) is the most aggressive malignant tumor of the adult central nervous system, with limited treatment options and poor prognosis. Radiotherapy (RT) remains a cornerstone of GBM treatment; however, tumor cell resistance to RT severely limits its efficacy. Recently, metabolic reprogramming (MR) has gained widespread attention as a critical mechanism enabling GBM cells to evade RT‐induced stress. In this review, the central roles of glucose, lipid, and amino acid metabolic reprogramming in GBM's resistance to RT were outlined, highlighting how GBM remodels metabolic pathways to enhance DNA damage repair, antioxidant defenses, and immune evasion after RT. Although combining metabolic inhibitors with RT has shown potential in improving GBM treatment outcomes, challenges such as overcoming the blood‐brain barrier and addressing tumor heterogeneity remain. The integration of nanomedicine‐based delivery systems and immunotherapy offers new hope for GBM treatment. Future research should focus on developing multidimensional, personalized metabolic targeting strategies, combined with immunotherapy and emerging technologies, to further improve therapeutic outcomes and survival rates for GBM patients.

Objective:To explore the predictive value of models based on clinical parameters, deep learning radiomics (DLR) from CT images, and traditional handcrafted radiomics (HCR) in assessing pathological complete response (pCR) after neoadjuvant radiotherapy combined with medical therapy in patients with esophageal cancer.Methods:A retrospective study was conducted on 130 patients with locally advanced esophageal cancer who underwent neoadjuvant radiotherapy combined with medical therapy followed by surgery at the First Affiliated Hospital of the University of Science and Technology of China from August 1, 2018, to August 31, 2024. Patients were randomly divided into a training set ( n=91) and a validation set ( n=39) at a ratio of 7:3. Logistic regression analysis was performed to identify clinical independent risk factors associated with pCR. DLR and HCR features were extracted from the tumor and the 5 mm peritumoral region on planning CT images. Features for modeling were selected using t-test, Mann-Whitney U test or Fisher exact probability method, least absolute shrinkage and selection operator (LASSO) regression to calculate the radiomics score (Rad-score). A nomogram was then constructed by integrating the clinical risk factors. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical benefits. Results:Multivariate logistic regression analysis identified body weight ( OR=1.101, 95% CI: 1.029-1.177, P=0.005) and lymph node positivity ( OR=0.100, 95% CI: 0.014-0.727, P=0.023) as independent predictors of pCR. The peritumoral DLR-HCR model showed superior predictive performance, with AUCs of 0.870 (95% CI: 0.799-0.942) in the training set and 0.866 (95% CI: 0.750-0.982) in the validation set. The combined model incorporating clinical parameters achieved the best performance, with AUCs of 0.903 (95% CI: 0.845-0.962) and 0.888 (95% CI: 0.782-0.994) in the training and validation sets, respectively. Conclusions:The combined model integrating peritumoral DLR-HCR features with clinical parameters provides excellent predictive value for pCR after neoadjuvant radiotherapy combined with medical therapy in esophageal cancer and offers valuable guidance for personalized treatment strategies.

Radiotherapy plays a critical role in the management of borderline resectable and unresectable locally advanced pancreatic cancer. Conventional radiotherapy improves local control in pancreatic cancer but has not significantly enhanced overall survival. Stereotactic body radiotherapy (SBRT), which employs single high-dose fractions or a hypofractionated regimen, enhances the biologically effective dose and has demonstrated remarkable efficacy in cancer treatment combined with systemic therapy. Due to the extremely high precision requirements of SBRT for spatial tumor targeting, precise organ motion management and image-guided radiotherapy technologies are essential for its successful implementation. The integration of MR-guided online adaptive radiotherapy with SBRT enables real-time assessment of anatomical changes during each treatment session, allowing online adaptive replanning to optimize dose delivery. This approach significantly improves treatment accuracy. The comprehensive application of these cutting-edge radiotherapy technologies holds promise for establishing groundbreaking therapeutic paradigms in pancreatic cancer.

Artificial intelligence (AI) technologies are being widely applied in radiotherapy. However, the integration of AI into clinical workflows of radiotherapy faces a series of challenges, such as poor model interpretability, domain shifts between clinical application and training data, and the inherent model uncertainties. Therefore, case-specific quality assurance (QA) is essential before deploying AI models in clinical practice. This paper reviews and summarizes QA methodologies for the application of AI models in radiotherapy across four key areas: image registration, image generation, region of interest segmentation, and treatment planning.