Search

Tumor heterogeneity, which is associated with poor outcomes, has not been exhibited in the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade and Necrosis (SSIGN) scores. Radiomics allows an in-depth characterization of heterogeneity across the tumor, but its incremental value to the existing prognostic models for clear cell renal cell carcinoma (ccRCC) outcome is unknown. The purpose of this study was to evaluate the association between the radiomics-based tumor heterogeneity and postoperative risk of recurrence in localized ccRCC, and to assess its incremental value to UISS and SSIGN.A multicenter 866 ccRCC patients derived from 12 Chinese hospitals were studied. The endpoint was recurrence-free survival (RFS). A CT-based radiomics signature (RS) was developed and assessed in the whole cohort and in the subgroups stratified by UISS and SSIGN. Two combined nomograms, the R-UISS (combining RS and UISS) and R-SSIGN (combining RS and SSIGN), were developed. The incremental value of RS to UISS and SSIGN in RFS prediction was evaluated. R statistical software was used for statistics.Patients with low radiomics scores were 4.44 times more likely to experience recurrence than those with high radiomics scores (P0.001). Stratified analysis suggested the association is significant among low- and intermediate-risk patients identified by UISS and SSIGN. The R-UISS and R-SSIGN showed better predictive capability than UISS and SSIGN did with higher C-indices (R-UISS vs. UISS, 0.74 vs. 0.64; R-SSIGN vs. SSIGN, 0.78 vs. 0.76) and higher clinical net benefit.The radiomics-based tumor heterogeneity can predict outcome and add incremental value to the existing prognostic models in localized ccRCC patients. Incorporating radiomics-based tumor heterogeneity in ccRCC prognostic models may provide the opportunity to better surveillance and adjuvant clinical trial design.

Purpose To investigate the prognostic value of baseline 18F-FDG PET/CT in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive (chemo)radiotherapy. Methods A total of 98 ESCC patients with cTNM stage T1-4, N1-3, M0 who received definitive (chemo)radiotherapy after 18F-FDG PET/CT examination from December 2013 to December 2020 were retrospectively analyzed. Clinical factors included age, sex, histologic differentiation grade, tumor location, clinical stage, and treatment strategies. Parameters obtained by 18F-FDG PET/CT included SUVmax of primary tumor (SUVTumor), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax of lymph node (SUVLN), PET positive lymph nodes (PLNS) number, the shortest distance between the farthest PET positive lymph node and the primary tumor in three-dimensional space after the standardization of the patient BSA (SDmax(LN-T)). Univariate and multivariate analysis was conducted by Cox proportional hazard model to explore the significant factors affecting overall survival (OS) and progression-free survival (PFS) in ESCC patients. Results Univariate analysis showed that tumor location, SUVTumor, MTV, TLG, PLNS number, SDmax (LN-T) were significant predictors of OS and tumor location, and clinical T stage, SUVTumor, MTV, TLG, SDmax (LN-T) were significant predictors of PFS (all p max (LN-T) were independent prognostic factors for OS (HR = 1.018, 95% CI 1.006–1.031; p = 0.005; HR = 6.988, 95% CI 2.119–23.042; p = 0.001) and PFS (HR = 1.019, 95% CI 1.005–1.034; p = 0.009; HR = 5.819, 95% CI 1.921–17.628; p = 0.002). Combined with independent prognostic factors MTV and SDmax (LN-T), we can further stratify patient risk. Conclusions Before treatment, 18F-FDG PET/CT has important prognostic value for patients with ESCC treated with definitive (chemo)radiotherapy. The lower the value of MTV and SDmax (LN-T), the better the prognosis of patients.

Programmed cell death protein-1 (PD-1)-mediated immunosuppression has been proposed to contribute to the limited clinical efficacy of chimeric antigen receptor T (CAR-T) cells in solid tumors. We generated PD-1 and T cell receptor (TCR) deficient mesothelin-specific CAR-T (MPTK-CAR-T) cells using CRISPR-Cas9 technology and evaluated them in a dose-escalation study. A total of 15 patients received one or more infusions of MPTK-CAR-T cells without prior lymphodepletion. No dose-limiting toxicity or unexpected adverse events were observed in any of the 15 patients. The best overall response was stable disease (2/15 patients). Circulating MPTK-CAR-T cells peaked at days 7–14 and became undetectable beyond 1 month. TCR-positive CAR-T cells rather than TCR-negative CAR-T cells were predominantly detected in effusion or peripheral blood from three patients after infusion. We further confirmed the reduced persistence of TCR-deficient CAR-T cells in animal models. Our results establish the preliminary feasibility and safety of CRISPR-engineered CAR-T cells with PD-1 disruption and suggest that the natural TCR plays an important role in the persistence of CAR-T cells when treating solid tumors.

[18F]AlF-NOTA-octreotide was evaluated for its biodistribution and dosimetry and demonstrated good safety, good tolerance, in vivo pharmacokinetics, and specific uptake in somatostatin receptor 2 (SSTR2)-positive tumors. This study aimed to improve the automated radiolabeling of NOTA-octreotide with [18F]AlF2+ and optimize the radiochemical yield (RCY) of [18F]AlF-NOTA-octreotide. The labeling procedure was optimized by changing the amounts of peptide and AlCl3, the labeling buffers. To simplify the process of preparing the solution, the reagent of the precursor (NOTA-octreotide 0.2 mg) and AlCl3·6H2O (27 µL 4 mM) were made into freeze-dried kit in advance. NOTA-octreotide was labeled with [18F]AlF2+ with a 55% yield in 40 min. This method can be used to effectively improve RCY and meet clinical requirements.

To construct an FDG PET/CT metabolic parameter-based model to predict early recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT). A total of 62 patients with HCC after LT were enrolled with a follow-up period of 1 year. Basic clinical, pathology, and laboratory data, CT features (CPLC), and PET metabolic parameters (CPLCP) were collected for model construction. A CPLC nomogram without metabolic parameters and a CPLCP nomogram with metabolic parameters were established. The net reclassification index (NRI) and integrated discrimination improvement (IDI) of the two models were calculated. The constructed model was compared with Milan criteria and University of California San Francisco (UCSF) criteria. The time-dependent area under the receiver operating characteristic curve (time-AUC) was used to compare the efficiency of the models, and the bootstrap method was used to for verification. Harrell’s concordance index (C-index) was used to evaluate the performance of these models. Decision curve analysis (DCA) was used to evaluate the clinical practicability of each model. Thirty out of 62 patients experienced a recurrence during the 1-year follow-up. BCLC stage (P = 0.009), MVI (P = 0.032), AFP (P = 0.004), CTdmax (P = 0.033), and MTV (P = 0.039) were the independent predictors. The CPLC nomogram and the CPLCP nomogram were established. Compared with the CPLC nomogram, the NRI of the CPLCP nomogram increased by 38.98% (95% CI = −18.77–60.43%) and the IDI increased by 4.40% (95% CI = −1.00–16.62%). The AUC value of the CPLCP nomogram was higher than those of Milan criteria and UCSF criteria in the time-AUC curve. Moreover, the CPLCP nomogram had a higher C-index (0.774) than other models. Finally, the DCA curve showed that clinical practicability of the CPLCP nomogram outperformed the Milan criteria and UCSF criteria. The CPLCP nomogram combining basic clinical data, pathology data, laboratory data, CT features, and PET metabolic parameters showed good efficacy and high clinical practicability in predicting the early recurrence of HCC after LT.

Lymphovascular invasion (LVI) impairs surgical outcomes in lung adenocarcinoma (LAC) patients. Preoperative prediction of LVI is challenging by using traditional clinical and imaging parameters. The purpose of this study was to investigate the value of the radiomics nomogram integrating clinical factors, CT features, and maximum standardized uptake value (SUVmax) to predict LVI and outcome in LAC and to evaluate the additional value of the SUVmax to the PET/CT-based radiomics nomogram.A total of 272 LAC patients (87 LVI-present LACs and 185 LVI-absent LACs) with PET/CT scans were retrospectively enrolled, and 160 patients with SUVmax ≥ 2.5 of them were used for PET radiomics analysis. Clinical data and CT features were analyzed to select independent LVI predictors. The performance of the independent LVI predictors and SUVmax was evaluated. Two-dimensional (2D) and three-dimensional (3D) CT radiomics signatures (RSs) and PET-RS were constructed with the least absolute shrinkage and selection operator algorithm and radiomics scores (Rad-scores) were calculated. The radiomics nomograms, incorporating Rad-score and independent clinical and CT factors, with SUVmax (RNWS) or without SUVmax (RNWOS) were built. The performance of the models was assessed with respect to calibration, discrimination, and clinical usefulness. All the clinical, PET/CT, pathologic, therapeutic, and radiomics parameters were assessed to identify independent predictors of progression-free survival (PFS).CT morphology was the independent LVI predictor. SUVmax provided better discrimination capability compared with CT morphology in the training set (P 0.001) and test set (P = 0.042). A total of 1409 CT and PET radiomics features were extracted and reduced to 8, 8, and 10 features to build the 2D CT-RS, 3D CT-RS, and the PET-RS, respectively. There was no significant difference in AUC between the 2D-RS and 3D-RS (P 0.05), and 2D CT-RS showed a relatively higher AUC than 3D CT-RS. The CT-RS, the CT-RNWOS, and the CT-RNWS showed good discrimination in the training set (AUC [area under the curve], 0.799, 0.796, and 0.851, respectively) and the test set (AUC, 0.818, 0.822, and 0.838, respectively). There was significant difference in AUC between the CT-RNWS and CT-RNWOS (P = 0.044) in the training set. Decision curve analysis (DCA) demonstrated the CT-RNWS outperformed the CT-RS and the CT-RNWOS in terms of clinical usefulness. Furthermore, DCA showed the PETCT-RNWS provided the highest net benefit compared with the PET-RNWS and CT-RNWS. PFS was significantly different between the pathologic and RNWS-predicted LVI-present and LVI-absent patients (P 0.001). Carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), pathologic LVI, histologic subtype, and SUVmax were independent predictors of PFS in the 244 CT-RNWS-predicted cohort; and CA125, NSE, pathologic LVI, and SUVmax were the independent predictors of PFS in the 141 PETCT-RNWS-predicted cohort.The radiomics nomogram, incorporating Rad-score, clinical and PET/CT parameters, shows favorable predictive efficacy for LVI status in LAC. Pathologic LVI and SUVmax are associated with LAC prognosis.

Butyrylcholinesterase (BChE) can modulate the expression level of cholinesterase, which emerges as an important clinical diagnose index. However, the currently reported assays for BChE are suffering from the problem of interferences. A ratiometric fluorescence assay was developed based on the MnO2 nanosheet (NS)–modulated fluorescence of sulfur quantum dots (S-dots) and o-phenylenediamine (OPD). MnO2 NS can not only quench the fluorescence of blue emissive S-dots, but also enhance the yellow emissive OPD by catalyzing its oxidation reactions. Upon introducing BChE and substrate into the system, their hydrolysate can reduce MnO2 into Mn2+, leading to the fluorescence recovery of S-dots and failure of OPD oxidation. BChE activity can be quantitatively detected by recording the change of fluorescence signals in the blue and yellow regions. A linear relationship is observed between the ratio of F435/F560 and the concentration of BChE in the range 30 to 500 U/L, and a limit of detection of 17.8 U/L has been calculated. The ratiometric fluorescence assay shows an excellent selectivity to acetylcholinesterase and tolerance to various other species. The method developed provides good detection performances in human serum medium and for screening of inhibitors.

To develop and validate a radiomics nomogram for preoperative differentiating renal angiomyolipoma without visible fat (AML.wovf) from homogeneous clear cell renal cell carcinoma (hm-ccRCC). Ninety-nine patients with AML.wovf (n = 36) and hm-ccRCC (n = 63) were divided into a training set (n = 80) and a validation set (n = 19). Radiomics features were extracted from corticomedullary phase and nephrographic phase CT images. A radiomics signature was constructed and a radiomics score (Rad-score) was calculated. Demographics and CT findings were assessed to build a clinical factors model. Combined with the Rad-score and independent clinical factors, a radiomics nomogram was constructed. Nomogram performance was assessed with respect to calibration, discrimination, and clinical usefulness. Fourteen features were used to build the radiomics signature. The radiomics signature showed good discrimination in the training set (AUC [area under the curve], 0.879; 95%; confidence interval [CI], 0.793–0.966) and the validation set (AUC, 0.846; 95% CI, 0.643–1.000). The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.896; 95% CI, 0.810–0.983) and the validation set (AUC, 0.949; 95% CI, 0.856–1.000) and showed better discrimination capability (p

Luminescent copper nanoclusters (Cu NCs) are chosen to functionalize Ti3C2Tx MXene flakes to form a new kind of nanohybrid. It was applied to the determination of glutathione (GSH) via photoluminescence (PL). The Cu NCs and MXene flakes are in close contact, and the blue PL of the Cu NCs (with excitation/emission peaks at 380/425 nm) is quenched. The addition of GSH triggers the separation of the nanohybrid. This results in the recovery of PL. GSH also promotes the PL of Cu NCs via host-guest interactions. Thus, target recognition, corresponding signal output and further magnification are accomplished in a single step. Under optimum conditions, the nanohybrid can detect GSH in the 5.0 to 100 μM concentration range and with a 3.0 μM detection limit. The assay is very specific and shows high selectivity towards metal ions, small biomolecules, amino acids, and thiol containing molecules.