Globally, there are over half a million new patients with head and neck squamous cell carcinomas (HNSCC) every year. The current therapeutic approaches to HNSCC are surgery and adjuvant radiotherapy. These approaches carry a high incidence of metastasis or recurrence from HNSCC cells’ radioresistance. Recent studies have revealed that a combination with radiosensitizers can be used to improve the radioresistance in HNSCC; however, few agents are approved as radiosensitizers. The constitutive activation of phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway is a vitally oncogenic type of signaling that promotes tumorigenesis, metastasis, and radiotherapy resistance in HNSCC. Pharmacological targeting of PI3K/AKT/mTOR signaling pathway is considered a promising strategy of radiosensitization in HNSCC. In this review, we summarize the oncogenic significance of PI3K/AKT/mTOR signaling in HNSCC with radiotherapy resistance and highlight the therapeutic potential of small molecule inhibitors against PI3K/AKT/mTOR signaling for the radiosensitization in HNSCC treatment. It provides a mechanistic framework for the development of new drugs for radiosensitization in HNSCC radiotherapy via targeting PI3K/AKT/mTOR signaling pathway.

This study explores integrating clinical features with radiomic and dosiomic characteristics into AI models to enhance the prediction accuracy of radiation dermatitis (RD) in breast cancer patients undergoing volumetric modulated arc therapy (VMAT). This study involved a retrospective analysis of 120 breast cancer patients treated with VMAT at Kaohsiung Veterans General Hospital from 2018 to 2023. Patient data included CT images, radiation doses, Dose-Volume Histogram (DVH) data, and clinical information. Using a Treatment Planning System (TPS), we segmented CT images into Regions of Interest (ROIs) to extract radiomic and dosiomic features, focusing on intensity, shape, texture, and dose distribution characteristics. Features significantly associated with the development of RD were identified using ANOVA and LASSO regression (p-value < 0.05). These features were then employed to train and evaluate Logistic Regression (LR) and Random Forest (RF) models, using tenfold cross-validation to ensure robust assessment of model efficacy. In this study, 102 out of 120 VMAT-treated breast cancer patients were included in the detailed analysis. Thirty-two percent of these patients developed Grade 2+ RD. Age and BMI were identified as significant clinical predictors. Through feature selection, we narrowed down the vast pool of radiomic and dosiomic data to 689 features, distributed across 10 feature subsets for model construction. In the LR model, the J subset, comprising DVH, Radiomics, and Dosiomics features, demonstrated the highest predictive performance with an AUC of 0.82. The RF model showed that subset I, which includes clinical, radiomic, and dosiomic features, achieved the best predictive accuracy with an AUC of 0.83. These results emphasize that integrating radiomic and dosiomic features significantly enhances the prediction of Grade 2+ RD. Integrating clinical, radiomic, and dosiomic characteristics into AI models significantly improves the prediction of Grade 2+ RD risk in breast cancer patients post-VMAT. The RF model analysis demonstrates that a comprehensive feature set maximizes predictive efficacy, marking a promising step towards utilizing AI in radiation therapy risk assessment and enhancing patient care outcomes.

Nasopharyngeal cancer shows a good response to intensity-modulated radiotherapy. However, there is no clear evidence for the benefits of routine use of image-guided radiotherapy. The purpose of this study was to perform a retrospective investigation of the treatment outcomes, treatment-related complications and prognostic factors for nasopharyngeal cancer treated with intensity-modulated radiotherapy and image-guided radiotherapy techniques. Retrospective analysis was performed on 326 consecutive nasopharyngeal cancer patients treated between 2004 and 2015. Potentially significant patient-related and treatment-related variables were analyzed. Radiation-related complications were recorded. The 5-year overall survival and disease-free survival rates of these patients were 77.9% and 70.5%, respectively. Age, AJCC (American Joint Committee on Cancer) stage, retropharyngeal lymphadenopathy, treatment interruption and body mass index were independent prognostic factors for overall survival. Age, AJCC stage, retropharyngeal lymphadenopathy, image-guided radiotherapy and body mass index were independent prognostic factors for disease-free survival. In conclusion, intensity-modulated radiotherapy significantly improves the treatment outcomes of nasopharyngeal cancer. With the aid of image-guided radiotherapy, the advantage of intensity-modulated radiotherapy might be further amplified.

The aim of this study was to evaluate the role of radiotherapy in the treatment of hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVT) and to determine the prognostic factors for overall survival. Altogether, 106 patients with HCC and PVT referred for radiotherapy between 2004 and 2009 were retrospectively reviewed. A total of 60 Gy in 30 daily fractions was delivered with intensity-modulated radiotherapy techniques. Patient-related and treatment-related factors were analyzed to evaluate their prognostic significance for the overall survival rate. Complete response was noted in 10 patients and partial response in 55 patients. The liver lesions had become resectable after the completion of radiotherapy in 12 patients, and surgery was subsequently performed. One or two courses of transarterial chemoembolization (TACE) were administered to 19 patients following radiotherapy. The 1-year and 2-year overall survival rates were 34.7% and 11%, respectively, and the median survival was 7 months for the entire cohort of patients. Post-radiotherapy treatment modality, response to radiotherapy and JIS score were demonstrated as independent prognostic factors for overall survival (P = 0.003, P < 0.001, P < 0.001, respectively). For patients who received surgical intervention after radiotherapy, the median survival was 30 months and the 2-year overall survival rate was 67%. Radiotherapy achieved a 61.5% objective response rate and prolonged survival in patients with PVT. The liver tumors had become resectable after radiotherapy in 11% of patients. Our results suggested that radiotherapy could offer survival benefits and should be considered as a treatment option for patients with PVT. Radiotherapy could also be considered as a preoperative treatment modality in patients with HCC and PVT.

Machine learning algorithms were used to analyze the odds and predictors of complications of thyroid damage after radiation therapy in patients with head and neck cancer. This study used decision tree (DT), random forest (RF), and support vector machine (SVM) algorithms to evaluate predictors for the data of 137 head and neck cancer patients. Candidate factors included gender, age, thyroid volume, minimum dose, average dose, maximum dose, number of treatments, and relative volume of the organ receiving X dose (X: 10, 20, 30, 40, 50, 60 Gy). The algorithm was optimized according to these factors and tenfold cross-validation to analyze the state of thyroid damage and select the predictors of thyroid dysfunction. The importance of the predictors identified by the three machine learning algorithms was ranked: the top five predictors were age, thyroid volume, average dose, V50 and V60. Of these, age and volume were negatively correlated with thyroid damage, indicating that the greater the age and thyroid volume, the lower the risk of thyroid damage; the average dose, V50 and V60 were positively correlated with thyroid damage, indicating that the larger the average dose, V50 and V60, the higher the risk of thyroid damage. The RF algorithm was most accurate in predicting the probability of thyroid damage among the three algorithms optimized using the above factors. The Area under the receiver operating characteristic curve (AUC) was 0.827 and the accuracy (ACC) was 0.824. This study found that five predictors (age, thyroid volume, mean dose, V50 and V60) are important factors affecting the chance that patients with head and neck cancer who received radiation therapy will develop hypothyroidism. Using these factors as the prediction basis of the algorithm and using RF to predict the occurrence of hypothyroidism had the highest ACC, which was 82.4%. This algorithm is quite helpful in predicting the probability of radiotherapy complications. It also provides references for assisting medical decision-making in the future.

Neutrophilic inflammation, characterized by dysregulated neutrophil activation, triggers a variety of inflammatory responses such as chemotactic infiltration, oxidative bursts, degranulation, neutrophil extracellular traps (NETs) formation, and delayed turnover. This type of inflammation is pivotal in the pathogenesis of acute respiratory distress syndrome (ARDS) and psoriasis. Despite current treatments, managing neutrophil-associated inflammatory symptoms remains a significant challenge. This review emphasizes the role of cyclin-dependent kinases (CDKs) in neutrophil activation and inflammation. It aims to highlight the therapeutic potential of repurposing CDK inhibitors to manage neutrophilic inflammation, particularly in ARDS and psoriasis. Additionally, it discusses the necessary precautions for the clinical application of these inhibitors due to potential off-target effects and the need for dose optimization. CDKs regulate key neutrophilic functions, including chemotactic responses, degranulation, NET formation, and apoptosis. Repurposing CDK inhibitors, originally developed for cancer treatment, shows promise in controlling neutrophilic inflammation. Clinical anticancer drugs, palbociclib and ribociclib, have demonstrated efficacy in treating neutrophilic ARDS and psoriasis by targeting off-label pathways, phosphoinositide 3-kinase (PI3K) and phosphodiesterase 4 (PDE4), respectively. While CDK inhibitors offer promising therapeutic benefits, their clinical repurposing requires careful consideration of off-target effects and dose optimization. Further exploration and clinical trials are necessary to ensure their safety and efficacy in treating inflammatory conditions.