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Abstract Background In view of the fact that radiomics features have been reported as predictors of immunotherapy to various cancers, this study aimed to develop a prediction model to determine the response to anti‐programmed death‐1 (anti‐PD‐1) therapy in esophageal squamous cell carcinoma (ESCC) patients from contrast‐enhanced CT (CECT) radiomics features. Methods Radiomic analysis of images was performed retrospectively for image samples before and after anti‐PD‐1 treatment, and efficacy analysis was performed for the results of two different time node evaluations. A total of 68 image samples were included in this study. Quantitative radiomic features were extracted from the images, and the least absolute shrinkage and selection operator method was applied to select radiomic features. After obtaining selected features, three classification models were used to establish a radiomics model to predict the ESCC status and efficacy of therapy. A cross‐validation strategy utilizing three folds was employed to train and test the model. Performance evaluation of the model was done using the area under the curve (AUC) of receiver operating characteristic, sensitivity, specificity, and precision metric. Results Wavelet and area of gray level change (log‐sigma) were the most significant radiomic features for predicting therapy efficacy. Fifteen radiomic features from the whole tumor and peritumoral regions were selected and comprised of the fusion radiomics score. A radiomics classification was developed with AUC of 0.82 and 0.884 in the before and after‐therapy cohorts, respectively. Conclusions The combined model incorporating radiomic features and clinical CECT predictors helps to predict the response to anti‐PD‐1therapy in patients with ESCC.

Abstract Developing a multifunctional nanoplatform to achieve efficient theranostics of tumors through multi‐pronged strategies remains to be challenging. Here, the design of the intelligent redox‐responsive generation 3 (G3) poly(amidoamine) dendrimer nanogels (NGs) loaded with gold nanoparticles (Au NPs) and chemotherapeutic drug toyocamycin (Au/Toy@G3 NGs) for ultrasound‐enhanced cancer theranostics is showcased. The constructed hybrid NGs with a size of 193 nm possess good colloidal stability under physiological conditions, and can be dissociated to release Au NPs and Toy in the reductive glutathione‐rich tumor microenvironment (TME). The released Toy can promote the apoptosis of cancer cells through endoplasmic reticulum stress amplification and cause immunogenic cell death to maturate dendritic cells. The loaded Au NPs can induce the conversion of tumor‐associated macrophages from M2‐type to antitumor M1‐type to remodulate the immunosuppressive TME. Combined with antibody‐mediated immune checkpoint blockade, effective chemoimmunotherapy of a pancreatic tumor mouse model can be realized, and the chemoimmunotherapy effect can be further ultrasound enhanced due to the sonoporation‐improved tumor permeability of NGs. The developed Au/Toy@G3 NGs also enable Au‐mediated computed tomography imaging of tumors. The constructed responsive dendrimeric NGs tackle tumors through a multi‐pronged chemoimmunotherapy strategy targeting both cancer cells and immune cells, which hold a promising potential for clinical translations.