A novel planning framework for efficient spot-scanning proton arc therapy via particle swarm optimization (SPArc-particle swarm).

Objective.Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm).Approach.SPArc-particle swarmdivided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated.Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarmcompared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%-26% reduction of the beam delivery time (BDT) in the SPArc treatment.Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation.

Comprehensive Treatment Uncertainty Analysis and PTV Margin Estimation for Fiducial Tracking in Robotic Liver Stereotactic Body Radiation Therapy.

OBJECTIVE: This study aims to quantify the uncertainties of CyberKnife Synchrony fiducial tracking for liver stereotactic body radiation therapy (SBRT) cases, and evaluate the required planning target volume (PTV) margins. METHODS: A total of 11 liver tumor patients with a total of 57 fractions, who underwent SBRT with synchronous fiducial tracking, were enrolled for the present study. The correlation/prediction model error, geometric error, and beam targeting error were quantified to determine the patient-level and fraction-level individual composite treatment uncertainties. The composite uncertainties and multiple margin recipes were compared for scenarios with and without rotation correction during treatment. RESULTS: The correlation model error-related uncertainty was 4.3±1.8, 1.4±0.5 and 1.8±0.7 mm in the superior-inferior (SI), left-right, and anterior-posterior directions, respectively. These were the primary contributors among all uncertainty sources. The geometric error significantly increased for treatments without rotation correction. The fraction-level composite uncertainties had a long tail distribution. Furthermore, the generally used 5-mm isotropic margin covered all uncertainties in the left-right and anterior-posterior directions, and only 75% of uncertainties in the SI direction. In order to cover 90% of uncertainties in the SI direction, an 8-mm margin would be needed. For scenarios without rotation correction, additional safety margins should be added, especially in the superior-inferior and anterior-posterior directions. CONCLUSION: The present study revealed that the correlation model error contributes to most of the uncertainties in the results. Most patients/fractions can be covered by a 5-mm margin. Patients with large treatment uncertainties might need a patient-specific margin.

Exosomal miR-22-3p from Mesenchymal Stem Cells Inhibits the Epithelial-Mesenchymal Transition (EMT) of Melanoma Cells by Regulating LGALS1.

BACKGROUND: The mortality rate from melanoma has been rising and hence new therapeutic approaches for this disease have received extensive attention, especially the search for novel therapeutic targets. The aim of this study was to find new targets for the treatment of melanoma through a bioinformatics and experimental approach. METHODS: First, we screened for differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between melanoma and normal tissues using the TCGA-SKCM, GTEX, and GSE24996 datasets. Next, we identified epithelial-mesenchymal transition (EMT)-related DEGs and analyzed their expression levels and association with patient survival. The expression level of DEGs was then confirmed in normal human melanocytes and melanoma cells. Bioinformatics analysis was used to identify miRNAs that targeted the most highly expressed DEG, LGALS1, and their binding confirmed using dual luciferase. Enriched pathways for the LGALS1 target miR-22-3p were also analyzed. miR-22-3p was overexpressed in cells in order to investigate changes in cell activity and in related genes and proteins. Exosomes from human bone marrow mesenchymal stem cells (MSCs) were coated with miR-22-3p to examine its effect on EMT. RESULTS: The expression levels of LGALS1, CPXM1, and APLNR were higher in melanoma than in normal tissues and were associated with worse patient survival. The differential expression of these genes was confirmed using normal human skin melanocytes (PIG1) and human melanoma cells (WM-266-4). LGALS1 was the most differentially expressed gene between WM-266-4 and PIG1 cells, and was also predicted to be a target for miR-22-3p. The results of dual luciferase experiments confirmed that miR-22-3p could bind to LGALS1. Following the overexpression of miR-22-3p in WM-266-4 cells, the cell viability decreased, the expression levels of LGALS1, VIM and SNAI2 decreased, the expression level of CDH1 increased, and cell apoptosis increased. Transfection of miR-22-3p using exosomes resulted in similar effects. CONCLUSIONS: We identified three genes (LGALS1, CPXM1, APLNR) that showed a high level of differential expression in melanoma. LGALS1 is a target for miR-22-3p binding and this can inhibit the EMT of melanoma cells, thereby preventing the development of melanoma. Moreover, exosomes secreted by MSCs can be loaded with miR-22-3p, thus regulating the EMT process in melanoma cells.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma.

PURPOSE: Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC. PATIENTS AND METHODS: Various statistical methods such as Kaplan-Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1. RESULTS: QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages. CONCLUSION: Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.

NEDD4 Induces K48-Linked Degradative Ubiquitination of Hepatitis B Virus X Protein and Inhibits HBV-Associated HCC Progression.

Neural precursor cell expressed developmentally downregulated gene 4 (NEDD4) plays two opposite roles in carcinogenesis. It has been reported that NEDD4 inhibits hepatocellular carcinoma (HCC) progression; however, little is known about its potential function and molecular mechanism in HCC in the context of hepatitis B virus (HBV) infection. In this study, we analyzed NEDD4 expression in 199 HCC specimens with or without HBV infection and observed that NEDD4 expression was unrelated to HBV exposure in HCC tumor tissue but that high NEDD4 expression conferred better overall survival (OS) and progression-free survival (PFS) than low NEDD4 expression in patients with HBV-associated HCC. Upregulation of NEDD4 inhibited proliferation, migration and invasion in HBV-related HCC cell lines. We demonstrated that NEDD4 interacts with HBV X protein (HBx) and that HBx upregulation could reverse the suppression of proliferation and mobility induced by NEDD4 overexpression. Furthermore, we confirmed that NEDD4 induced the degradation of HBx in a ubiquitin/proteasome-dependent manner via K48-linked ubiquitination. Our findings suggest that NEDD4 exerts a tumor-suppressive effect in HBV-associated HCC by acting as an E3 ubiquitin ligase for HBx degradation and provide new insights into the function of NEDD4.

Elevation of plasma tRNA fragments as a promising biomarker for liver fibrosis in nonalcoholic fatty liver disease.

Fibrotic tissue remodelling in nonalcoholic fatty liver disease (NAFLD) will probably emerge as the leading cause of end-stage liver disease in the coming decades, but the ability to diagnose liver fibrosis in NAFLD patients noninvasively is limited. The abnormal expression of tRNA-derived small RNA (tsRNA) in plasma provides a novel idea for noninvasive diagnosis of various diseases, however, the relationship between tsRNAs and NAFLD is still unknown. Here, we took advantage of small RNA-Seq technology to profile tsRNAs in NAFLD patients and found the ubiquitous presence of hepatic tsRNAs secreted into circulating blood. Verification in a cohort of 114 patients with NAFLD and 42 patients without NAFLD revealed that three tsRNAs (tRF-Val-CAC-005, tiRNA-His-GTG-001, and tRF-Ala-CGC-006) were significantly elevated in the plasma of NAFLD patients, and the expression level are associated with NAFLD activity score (calculated from 0 to 8) and fibrosis stage (scored from 0 to 4). In mouse models, we further found that increased plasma levels of these three tsRNAs were positively correlated with the degree of liver fibrosis. Our study potentially identifies a new class of NAFLD biomarkers and reveal the possible existence of tsRNAs in the blood that can be used to predict fibrogenesis risk in patients diagnosed with NAFLD.

TIGIT/PVR and LncRNA ANRIL dual-targetable PAMAM polymeric nanoparticles efficiently inhibited the hepatoma carcinoma by combination of immunotherapy and gene therapy.

Herein, a novel polymeric nanoparticle was designed to inhibit hepatoma carcinoma by simultaneously targeting the T cell immunoreceptor with Ig and ITIM domains (TIGIT)/poliovirus receptor (PVR) and long noncoding RNAs antisense noncoding RNA in the INK4 locus (LncRNA ANRIL). Firstly, the siANRIL-loaded nanoparticles (NP-siANRIL) was developed by methoxy-poly (ethylene glycol)-polyamidoamine (mPEG-PAMAM) and polyamidoamine-poly (ethylene glycol)-disulphide bond-carboxyl (PAMAM-PEG-S2-COOH) using the self-assembly method. Then the DTBP-3 peptide, a newly developed identified peptide which could occupy the binding interface and effectively block the interaction of TIGIT with its ligand PVR, was further conjugated on the surface of NP-siANRIL via the glutathione (GSH)-sensitive disulphide linkage. In this way, the binding ability of DTBP-3 to TIGIT was remained once they were entrapped into the tumour tissues which were abundant of GSH. The present study demonstrated that DTBP-3NP-siANRIL exhibited an excellent anti-tumour effect on hepatoma carcinoma in vivo by simultaneously inhibited the expression of miR-203a and its downstream genes and increased the percentages of NK cells and T cells. In a word, the present study has presented a novel strategy for treatment of hepatoma carcinoma by simultaneously targeting of TIGIT/PVR and LncRNA ANRIL.

Artificial intelligence-based framework in evaluating intrafraction motion for liver cancer robotic stereotactic body radiation therapy with fiducial tracking.

PURPOSE: This study aimed to design a fully automated framework to evaluate intrafraction motion using orthogonal x-ray images from CyberKnife. METHODS: The proposed framework includes three modules: (a) automated fiducial marker detection, (b) three-dimensional (3D) position reconstruction, and (c) intrafraction motion evaluation. A total of 5927 images from real patients treated with CyberKnife fiducial tracking were collected. The ground truth was established by labeling coarse bounding boxes manually, and binary mask images were then obtained by applying a binary threshold and filter. These images and labels were used to train a detection model using a fully convolutional network (fCN). The output of the detection model can be used to reconstruct the 3D positions of the fiducial markers and then evaluate the intrafraction motion via a rigid transformation. For a patient test, the motion amplitudes, rotations, and fiducial cohort deformations were calculated used the developed framework for 13 patients with a total of 52 fractions. RESULTS: The precision and recall of the fiducial marker detection model were 98.6% and 95.6%, respectively, showing high model performance. The mean (±SD) centroid error between the predicted fiducial markers and the ground truth was 0.25 ± 0.47 pixels on the test data. For intrafraction motion evaluation, the mean (±SD) translations in the superior-posterior (SI), left-right (LR), and anterior-posterior (AP) directions were 13.1 ± 2.2 mm, 2.0 ± 0.4 mm, and 5.2 ± 1.4 mm, respectively, and the mean (±SD) rotations in the roll, pitch and yaw directions were 2.9 ± 1.5°, 2.5 ± 1.5°, and 3.1 ± 2.2°. Seventy-one percent of the fractions had rotations larger than the system limitations. With rotation correction during rigid registration, only 2 of the 52 fractions had residual errors larger than 2 mm in any direction, while without rotation correction, the probability of large residual errors increased to 46.2%. CONCLUSION: We developed a framework with high performance and accuracy for automatic fiducial marker detection, which can be used to evaluate intrafraction motion using orthogonal x-ray images from CyberKnife. For liver patients, most fractions have fiducial cohort rotations larger than the system limitations; however, the fiducial cohort deformation is small, especially for the scenario with rotation correction.