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Fluorophores with donor-acceptor-donor groups with the emission spanning the second near-infrared window (NIR-II) have recently received great attention for biomedical application. Yet, the mechanism underlying the equilibrium between fluorescence (radiative decay) and photothermal effect (non-radiative decay) of these fluorophores remains elusive. Here, we demonstrate that a lipophilic NIR-II fluorophore, BPBBT, possesses both twisted intramolecular charge transfer (TICT) and aggregation-induced emission (AIE) characteristics. Human serum albumin (HSA) binds to BPBBT, which changes the planarity of the fluorophore and restricts its intramolecular rotation. The binding results in alteration to the equilibrium between AIE and TICT state of BPBBT, tailoring its fluorescence and photothermal efficiency. Under the guidance of intraoperative NIR-II fluorescence image, the prepared HSA-bound BPBBT nanoparticles delineate primary orthotopic mouse colon tumor and metastatic lesions with dimensions as small as 0.5 mm × 0.3 mm, and offer photothermal ablation therapy with optimized timing, dosing and area of the laser irradiation. There is a balance between the fluorescence and photothermal properties of fluorescent molecules. Here, the authors report on an NIR-II fluorophore which binds with human serum albumin changing the equilibrium, increasing the photothermal efficiency, and demonstrate application of this for tumour ablation.

PurposePathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) is commonly accepted as the gold standard to assess outcome after NAC in breast cancer patients. 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) has unique value in tumor staging, predicting prognosis, and evaluating treatment response. Our aim was to determine if we could identify radiomic predictors from PET/CT in breast cancer patient therapeutic efficacy prior to NAC.MethodsThis retrospective study included 100 breast cancer patients who received NAC; there were 2210 PET/CT radiomic features extracted. Unsupervised and supervised machine learning models were used to identify the prognostic radiomic predictors through the following: (1) selection of the significant (p < 0.05) imaging features from consensus clustering and the Wilcoxon signed-rank test; (2) selection of the most discriminative features via univariate random forest (Uni-RF) and the Pearson correlation matrix (PCM); and (3) determination of the most predictive features from a traversal feature selection (TFS) based on a multivariate random forest (RF). The prediction model was constructed with RF and then validated with 10-fold cross-validation for 30 times and then independently validated. The performance of the radiomic predictors was measured in terms of area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).ResultsThe PET/CT radiomic predictors achieved a prediction accuracy of 0.857 (AUC = 0.844) on the training split set and 0.767 (AUC = 0.722) on the independent validation set. When age was incorporated, the accuracy for the split set increased to 0.857 (AUC = 0.958) and 0.8 (AUC = 0.73) for the independent validation set and both outperformed the clinical prediction model. We also found a close association between the radiomic features, receptor expression, and tumor T stage.ConclusionRadiomic predictors from pre-treatment PET/CT scans when combined with patient age were able to predict pCR after NAC. We suggest that these data will be valuable for patient management.

Background Predictive biomarkers are needed to identify oestrogen receptor-positive, human epidermal growth factor receptor 2-negative (ER + /HER2-) metastatic breast cancer (MBC) patients who would likely benefit from cyclin-dependent kinase 4 and 6 inhibitors combined with endocrine therapy. Therefore, we performed an exploratory study to evaluate the tumour heterogeneity parameters based on 16α- 18 F-fluoro-17β-oestradiol ( 18 F-FES)-PET imaging as a potential marker to predict progression-free survival (PFS) in MBC patients receiving palbociclib combined with endocrine therapy. Methods Fifty-six ER + MBC patients underwent 18 F-FES-PET/CT before the initiation of palbociclib. 18 F-FES uptake was quantified and expressed as the standardized uptake value (SUV). Interlesional heterogeneity was qualitatively identified according to the presence or absence of 18 F-FES-negative lesions. Intralesional heterogeneity was measured by the SUV-based heterogeneity index (HI = SUVmax/SUVmean). Association with survival was evaluated using the Cox proportional hazards model. Results A total of 551 metastatic lesions were found in 56 patients: 507 lesions were identified as 18 F-FES-positive, 38 lesions were distributed across 10 patients without 18 F-FES uptake, and the remaining 6 were liver lesions. Forty-three patients obtained a clinical benefit, and 13 developed progressive disease (PD) within 24 weeks. Nine out of 10 patients with an 18 F-FES-negative site developed PD, and the median PFS was only 2.4 months. Among 46 patients with only 18 F-FES-positive lesions, only four patients had PD, and the median PFS was 23.6 months. There were statistically significant differences between the two groups ( P  < 0.001). For the subgroup of patients with only 18 F-FES-positive lesions, low FES-HI patients experienced substantially longer PFS times than those with high FES-HI (26.5 months vs. 16.5 months, P  = 0.004). Conclusions 18 F-FES-PET may provide a promising method for identifying and selecting candidate ER + /HER2- MBC patients who would most likely benefit from palbociclib combined with endocrine treatment and could serve as a predictive marker for treatment response. Trial registration NCT04992156, Date of registration: August 5, 2021 (retrospectively registered).

Multimodal combinatorial therapy merges different modes of therapies in one platform, which can overcome several clinical challenges such as premature drug loss during blood circulation and significantly improve treatment efficiency. Here we report a combinatorial therapy nanoplatform that enables dual photothermal therapy and pH-stimulus-responsive chemotherapy. By super-assembly of mesoporous silica nanoparticles (MSN) with metal-phenolic networks (MPN), anti-cancer drugs can be loaded in the MSN matrix, while the outer MPN coating allows dual photothermal and pH-responsive properties. Upon near-infrared light irradiation, the MSN@MPN nanoplatform exhibits excellent photothermal effect, and demonstrates outstanding pH-triggered drug release property. In vitro cell experiments suggest the MSN@MPN system exhibits superior biocompatibility and can effectively kill tumor cells after loading anti-cancer drugs. Consequently, the MSN@MPN system shows promising prospects in clinical application for tumor therapy.

BACKGROUNDImproving and predicting tumor response to immunotherapy remains challenging. Combination therapy with a transforming growth factor-β receptor (TGF-βR) inhibitor that targets cancer-associated fibroblasts (CAFs) is promising for the enhancement of efficacy of immunotherapies. However, the effect of this approach in clinical trials is limited, requiring in vivo methods to better assess tumor responses to combination therapy.METHODSWe measured CAFs in vivo using the 68Ga-labeled fibroblast activation protein inhibitor-04 (68Ga-FAPI-04) for PET/CT imaging to guide the combination of TGF-β inhibition and immunotherapy. One hundred thirty-one patients with metastatic colorectal cancer (CRC) underwent 68Ga-FAPI and 18F-fluorodeoxyglucose (18F-FDG) PET/CT imaging. The relationship between uptake of 68Ga-FAPI and tumor immunity was analyzed in patients. Mouse cohorts of metastatic CRC were treated with the TGF-βR inhibitor combined with KN046, which blocks programmed death ligand 1 (PD-L1) and CTLA-4, followed by 68Ga-FAPI and 18F-FDG micro-PET/CT imaging to assess tumor responses.RESULTSPatients with metastatic CRC demonstrated high uptake rates of 68Ga-FAPI, along with suppressive tumor immunity and poor prognosis. The TGF-βR inhibitor enhanced tumor-infiltrating T cells and significantly sensitized metastatic CRC to KN046. 68Ga-FAPI PET/CT imaging accurately monitored the dynamic changes of CAFs and tumor response to combined the TGF-βR inhibitor with immunotherapy.CONCLUSION68Ga-FAPI PET/CT imaging is powerful in assessing tumor immunity and the response to immunotherapy in metastatic CRC. This study supports future clinical application of 68Ga-FAPI PET/CT to guide precise TGF-β inhibition plus immunotherapy in CRC patients, recommending 68Ga-FAPI and 18F-FDG dual PET/CT for CRC management.TRIAL REGISTRATIONCFFSTS Trial, ChiCTR2100053984, Chinese Clinical Trial Registry.FUNDINGNational Natural Science Foundation of China (82072695, 32270767, 82272035, 81972260).

Objective The aim of this study was to investigate the potential value of dual tracers 18 F-FDG and 18 F-FES PET/CT in predicting response to Cyclin-Dependent 4/6 Kinase (CDK4/6) inhibitors combined with endocrine therapy for metastatic estrogen receptor (ER)-positive breast cancer patients. Methods This retrospective study enrolled 38 ER-positive metastatic breast cancer patients from our center who underwent both 18 F-FDG and 18 F-FES PET/CT scans within 1 month before CDK4/6 inhibitors combined with endocrine therapy. The extracted parameters comprised the maximum standardized uptake value (SUVmax) for both FDG and FES PET, as well as the ratio between FES and FDG SUVmax. Each parameter was dichotomized based on its median threshold. The primary endpoint was progression-free survival (PFS), which was estimated using the Kaplan–Meier method and compared by the log-rank test. Results After a median follow-up of 15.6 months, progressive disease was observed in 23 out of 38 patients, and the median PFS for the whole cohort was 21.0 months [95% confidence interval (CI) 12.7–29.3]. FES and FDG PET identified 6 patients (15.8%) with FES-negative lesions, suggesting ER heterogeneity in metastatic lesions. The median PFS of these patients was only 5.3 months (95% CI 1.7–8.9), which was substantially shorter than that of patients with 100% FES-positive lesions (median PFS 22.9 months, 95% CI 17.1–28.7, P  < 0.001). Patients with 100% FES-positive lesions who had high FES/FDG showed significantly shorter PFS compared to those with low FES/FDG (14.9 vs. 30.5 months, P  = 0.003). Conclusions This study shows that FDG and FES PET imaging may serve as valuable tools for patient selection in the context of CDK4/6 inhibitor therapy combined with endocrine treatment, and have the potential to function as prognostic biomarkers.

Combinations of immune checkpoint therapies show encouraging results in the treatment of many human cancers. However, the higher costs and greater side effects of such combinations compared with single‐agent immunotherapies limit their further applications. In this work, a novel smart agent, KN046@19F‐ZIF‐8, is developed to overcome these limitations. KN046 is a novel recombinant humanized PD‐L1/CTLA‐4 bispecific single‐domain antibody‐Fc fusion protein, which can bind to both PD‐L1 and CTLA‐4 effectively. ZIF‐8 is a smart delivery system, which can safely and effectively deliver KN406 to a tumor. In vitro and in vivo results demonstrate that the smart agent KN046@19F‐ZIF‐8 not only improves the immune response rate of the antibody drug in treatment of tumors but also reduces its toxic side effects, thereby achieving excellent antitumor efficacy. This study provides an engineering strategy for clinical applications of a more effective immunotherapy. A novel smart agent is engineered by coating a tumor microenvironment responsive ZIF‐8 on the novel recombinant humanized PD‐L1/CTLA‐4 bispecific single‐domain antibody‐Fc fusion protein to overcome the higher costs and greater side effects of single‐agent immunotherapies.

Background To develop and validate a survival model with clinico-biological features and 18 F- FDG PET/CT radiomic features via machine learning, and for predicting the prognosis from the primary tumor of colorectal cancer. Methods A total of 196 pathologically confirmed patients with colorectal cancer (stage I to stage IV) were included. Preoperative clinical factors, serum tumor markers, and PET/CT radiomic features were included for the recurrence-free survival analysis. For the modeling and validation, patients were randomly divided into the training (n = 137) and validation (n = 59) set, while the 78 stage III patients [training (n = 55), and validation (n = 23)] was divided for the further experiment. After selecting features by the log-rank test and variable-hunting methods, random survival forest (RSF) models were built on the training set to analyze the prognostic value of selected features. The performance of models was measured by C-index and was tested on the validation set with bootstrapping. Feature importance and the Pearson correlation were also analyzed. Results Radiomics signature (containing four PET/CT features and four clinical factors) achieved the best result for prognostic prediction of 196 patients (C-index 0.780, 95% CI 0.634–0.877). Moreover, four features (including two clinical features and two radiomics features) were selected for prognostic prediction of the 78 stage III patients (C-index was 0.820, 95% CI 0.676–0.900). K–M curves of both models significantly stratified low-risk and high-risk groups ( P  < 0.0001). Pearson correlation analysis demonstrated that selected radiomics features were correlated with tumor metabolic factors, such as SUVmean, SUVmax. Conclusion This study presents integrated clinico-biological-radiological models that can accurately predict the prognosis in colorectal cancer using the preoperative 18 F-FDG PET/CT radiomics in colorectal cancer. It is of potential value in assisting the management and decision making for precision treatment in colorectal cancer. Trial registration The retrospectively registered study was approved by the Ethics Committee of Fudan University Shanghai Cancer Center (No. 1909207-14-1910) and the data were analyzed anonymously.

Background The aim of this study was to evaluate the efficacy of fluorine 18 ( 18 F) labeled fibroblast activation protein inhibitor (FAPI) in identifying mediastinal and hilar lymph node metastases and to develop a model to quantitatively and repeatedly identify lymph node status. Methods Twenty-seven patients with 137 lymph nodes were identified by two PET/CT images. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of lymph node status were analyzed, and the optimal cut-off value was identified by ROC analysis. Results The SUVmax of metastatic lymph nodes on 18 F-FAPI was higher than that on 18 F-FDG PET/CT (10.87 ± 7.29 vs 6.08 ± 5.37, p  < 0.001). 18 F-FAPI presented much greater lymph node detection sensitivity, specificity, accuracy, PPV and NPV than 18 F-FDG PET/CT (84% vs. 71%; 92% vs. 67%; 90% vs. 69%, 84% vs. 52%, and 92% vs. 83%, respectively). Additionally, the diagnostic effectiveness of 18 F-FAPI in small lymph nodes was greater than that of 18 F-FDG PET/CT (specificity: 96% vs. 72%; accuracy: 93% vs. 73%; PPV: 77% vs. 33%, respectively). Notably, the optimal cut-off value for specificity and PPV of 18 F-FAPI SUVmax was 5.3; the optimal cut-off value for sensitivity and NPV was 2.5. Conclusion 18 F-FAPI showed promising diagnostic efficacy in metastatic mediastinal and hilar lymph nodes from lung cancer patients, with a higher SUVmax, especially in small metastatic nodes, compared with 18 F-FDG. In addition, this exploratory work recommended optimal SUVmax cutoff values to distinguish between nonmetastatic and metastatic lymph nodes, thereby advancing the development of image-guided radiation. Trial registration ClinicalTrials.gov identifier: ChiCTR2000036091.