Anatomical and dosimetric variations during volumetric modulated arc therapy in patients with locally advanced nasopharyngeal carcinoma after induction therapy: Implications for adaptive radiation therapy.

Purpose: To investigate anatomical and dosimetric changes during volumetric modulated arc therapy (VMAT) in patients with locally advanced nasopharyngeal carcinoma (LA-NPC) after induction therapy (IT) and explore characteristics of patients with notable variations. Materials and methods: From July 2021 to June 2023, 60 LA-NPC patients undergoing VMAT after IT were retrospectively recruited. Adaptive computed tomography (aCT), reconstructed from weekly cone-beam computed tomography(CBCT), facilitates recontouring and planning transplantation. Volume, dice similarity coefficients, and dose to target volumes and organs at risk(OARs) on planning CT(pCT) and aCT were compared to identify changing patterns. Multivariate logistic regression was used to investigate risk factors. Results: The volumes of PGTVnasopharynx (PGTVp), PGTVnode (PGTVn), ipsilateral and contralateral parotid glands decreased during VMAT, with reductions of 2.25 %, 6.98 %, 20.09 % and 18.00 %, respectively, at 30 fractions from baseline (P < 0.001). After 25 fractions, D99 and D95 of PGTVn decreased by 7.94 % and 4.18 % from baseline, respectively, while the Dmean of ipsilateral and contralateral parotid glands increased by 7.80 % and 6.50 %, marking the peak rates of dosimetric variations (P < 0.001). The dosimetric fluctuations in PGTVp, the brainstem, and the spinal cord remained within acceptable limits. Furthermore, an initial BMI ≥ 23.5 kg/m2 and not-achieving objective response (OR) after IT were regarded as risk factors for a remarkable PGTVn dose reduction in the later stages of VMAT. Conclusions: Replanning for post-IT LA-NPC patients appears reasonable at 25F during VMAT. Patients with an initial BMI ≥ 23.5 kg/m2 and not-achieving OR after IT should be considered for adaptive radiation therapy to stabilize the delivered dose.

A self-assembled, genetically engineered, irradiated tumor cell debris vaccine.

Vaccine-based therapeutics for cancers face several challenges including lack of immunogenicity and tumor escape pathways for single antigen targets. It has been reported that radiotherapy has an in situ vaccine effect that provides tumor antigens following irradiation, helping to activate antigen-presenting cells (APCs). Herein, a new vaccine approach is developed by combining genetically engineered irradiated tumor cell debris (RTD) and hyaluronic acid (HA), termed HA@RTD. A cancer cell line is developed that overexpresses granulocyte-macrophage colony-stimulating factor (GM-CSF). A hydrogel was developed by covalent conjugation of HA with RTD proteins that acted as a potent vaccine system, the effects which were probed with T cell receptor sequencing. The engineered vaccine activated antitumor immunity responses and prevented tumor growth in mice even with a single immunization. HA@RTD vaccine efficacy was also assessed in therapeutic settings with established tumors and in combination with immune checkpoint blockade.

Systemic longitudinal immune profiling identifies proliferating Treg cells as predictors of immunotherapy benefit: biomarker analysis from the phase 3 CONTINUUM and DIPPER trials.

The identification of predictors for immunotherapy is often hampered by the absence of control groups in many studies, making it difficult to distinguish between prognostic and predictive biomarkers. This study presents biomarker analyses from the phase 3 CONTINUUM trial (NCT03700476), the first to show that adding anti-PD-1 (aPD1) to chemoradiotherapy (CRT) improves event-free survival (EFS) in patients with locoregionally advanced nasopharyngeal carcinoma. A dynamic single-cell atlas was profiled using mass cytometry on peripheral blood mononuclear cell samples from 12 pairs of matched relapsing and non-relapsing patients in the aPD1-CRT arm. Using a supervised representation learning algorithm, we identified a Ki67+ proliferating regulatory T cells (Tregs) population expressing high levels of activated and immunosuppressive molecules including FOXP3, CD38, HLA-DR, CD39, and PD-1, whose abundance correlated with treatment outcome. The frequency of these Ki67+ Tregs was significantly higher at baseline and increased during treatment in patients who relapsed compared to non-relapsers. Further validation through flow cytometry (n = 120) confirmed the predictive value of this Treg subset. Multiplex immunohistochemistry (n = 249) demonstrated that Ki67+ Tregs in tumors could predict immunotherapy benefit, with aPD1 improving EFS only in patients with low baseline levels of Ki67+ Tregs. These findings were further validated in the multicenter phase 3 DIPPER trial (n = 262, NCT03427827) and the phase 3 OAK trial of anti-PD-L1 immunotherapy in NSCLC, underscoring the predictive value of Ki67+ Treg frequency in identifying the beneficiaries of immunotherapy and potentially guiding personalized treatment strategies.

Targeting the Cascade Amplification of Macrophage Colony-stimulating Factor to Alleviate the Immunosuppressive Effects Following Radiotherapy.

Radiotherapy (RT) serves as the primary treatment for solid tumors. Its potential to incite an immune response against tumors both locally and distally profoundly impacts clinical outcomes. However, RT may also promote the accumulation of immunosuppressive cytokines and immunosuppressive cells, greatly impeding the activation of antitumor immune responses and substantially limiting the effectiveness of RT. Therefore, regulating post-RT immunosuppression to steer the immune milieu toward heightened activation potentially enhances RT's therapeutic potential. Cytokines, potent orchestrators of diverse cellular responses, play a pivotal role in regulating this immunosuppressive response. Identifying and promptly neutralizing early released immunosuppressive cytokines are a crucial development in augmenting RT's immunomodulatory effects. To this end, we conducted a screen of immunosuppressive cytokines following RT and identified macrophage colony-stimulating factor (MCSF) as an early up-regulated and persistent immune suppressor. Single-cell sequencing revealed that the main source of up-regulated MCSF derived from tumor cells. Mechanistic exploration revealed that irradiation-dependent phosphorylation of the p65 protein facilitated its binding to the MCSF gene promoter, enhancing transcription. Knockdown and chemical inhibitor experiments conclusively demonstrated that suppressing tumor cell-derived MCSF amplifies RT's immune-activating effects, with optimal results achieved by early MCSF blockade after irradiation. Additionally, we validated that MCSF acted on macrophages, inducing the secretion of a large number of inhibitory cytokines. In summary, we propose a novel approach to enhance the immune activation effects of RT by blocking the MCSF-CSF1R signaling pathway early after irradiation.

Sequence-specific nanoparticle barcode strategy for multiplex human enterovirus typing.

Human enteroviruses (HEV) can cause a range of diseases from mild to potentially life-threatening. Identification and genotyping of HEV are crucial for disease management. Existing typing methods, however, have inherent limitations. Developing alternative methods to detect HEV with more virus types, high accuracy, and sensitivity in an accessible manner presents a technological and analytical challenge. Here, a sequence-specific nanoparticle barcode (SSNB) method is presented for simultaneous detection of 10 HEV types. This method significantly increases sensitivity, enhancing detection by 10-106 times over the traditional multiplex hybrid genotyping (MHG) method, by resolving cross-interference between the multiple primer sets. Furthermore, the SSNB method demonstrates a 100% specificity in accurately distinguishing between 10 different HEV types and other prevalent clinical viruses. In an analysis of 70 clinical throat swab samples, the SSNB method shows slightly higher detection rate for positive samples (50%) compared to the RT-PCR method (48.6%). Additionally, further assessment of the typing accuracy for samples identified as positive by SSNB using sequencing method reveals a concordance rate of 100%. The combined high sensitivity and specificity level of the methodology, together with the capability for multiple type analysis and compatibility with clinical workflow, make this approach a promising tool for clinical settings.

Proton spot dose estimation based on positron activity distributions with neural network.

BACKGROUND: Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy. PURPOSE: This study evaluates the effectiveness of three classical neural network models, recurrent neural network (RNN), U-Net, and Transformer, for proton dose estimating. It also investigates the characteristics of these models, providing valuable insights for selecting the appropriate model in clinical practice. METHODS: Proton dose calculations for spot beams were simulated using Geant4. Computed tomography (CT) images from four head cases were utilized, with three for training neural networks and the remaining one for testing. The neural networks were trained with one-dimensional (1D) positron activity distributions as inputs and generated 1D dose distributions as outputs. The impact of the number of training samples on the networks was examined, and their dose prediction performance in both homogeneous brain and heterogeneous nasopharynx sites was evaluated. Additionally, the effect of positron activity distribution uncertainty on dose prediction performance was investigated. To quantitatively evaluate the models, mean relative error (MRE) and absolute range error (ARE) were used as evaluation metrics. RESULTS: The U-Net exhibited a notable advantage in range verification with a smaller number of training samples, achieving approximately 75% of AREs below 0.5 mm using only 500 training samples. The networks performed better in the homogeneous brain site compared to the heterogeneous nasopharyngeal site. In the homogeneous brain site, all networks exhibited small AREs, with approximately 90% of the AREs below 0.5 mm. The Transformer exhibited the best overall dose distribution prediction, with approximately 92% of MREs below 3%. In the heterogeneous nasopharyngeal site, all networks demonstrated acceptable AREs, with approximately 88% of AREs below 3 mm. The Transformer maintained the best overall dose distribution prediction, with approximately 85% of MREs below 5%. The performance of all three networks in dose prediction declined as the uncertainty of positron activity distribution increased, and the Transformer consistently outperformed the other networks in all cases. CONCLUSIONS: Both the U-Net and the Transformer have certain advantages in the proton dose estimation task. The U-Net proves well suited for range verification with a small training sample size, while the Transformer outperforms others at dose-guided proton therapy.

A novel fast robust optimization algorithm for intensity-modulated proton therapy with minimum monitor unit constraint.

BACKGROUND: Intensity-modulated proton therapy (IMPT) optimizes spot intensities and position, providing better conformability. However, the successful application of IMPT is dependent upon addressing the challenges posed by range and setup uncertainties. In order to address the uncertainties in IMPT, robust optimization is essential. PURPOSE: This study aims to develop a novel fast algorithm for robust optimization of IMPT with minimum monitor unit (MU) constraint. METHODS AND MATERIALS: The study formulates a robust optimization problem and proposes a novel, fast algorithm based on the alternating direction method of multipliers (ADMM) framework. This algorithm enables distributed computation and parallel processing. Ten clinical cases were used as test scenarios to evaluate the performance of the proposed approach. The robust optimization method (RBO-NEW) was compared with plans that only consider nominal optimization using CTV (NMO-CTV) without handling uncertainties and PTV (NMO-PTV) to handle the uncertainties, as well as with conventional robust-optimized plans (RBO-CONV). Dosimetric metrics, including D95, homogeneity index, and Dmean, were used to evaluate the dose distribution quality. The area under the root-mean-square dose (RMSD)-volume histogram curves (AUC) and dose-volume histogram (DVH) bands were used to evaluate the robustness of the treatment plan. Optimization time cost was also assessed to measure computational efficiency. RESULTS: The results demonstrated that the RBO plans exhibited better plan quality and robustness than the NMO plans, with RBO-NEW showing superior computational efficiency and plan quality compared to RBO-CONV. Specifically, statistical analysis results indicated that RBO-NEW was able to reduce the computational time from 389.70 ± 207.40 $389.70\pm 207.40$ to 228.60 ± 123.67 $228.60\pm 123.67$ s ( p < 0.01 $p<0.01$ ) and reduce the mean organ-at-risk (OAR) dose from 9.38 ± 12.80 $9.38\pm 12.80$ % of the prescription dose to 9.07 ± 12.39 $9.07\pm 12.39$ % of the prescription dose ( p < 0.05 $p<0.05$ ) compared to RBO-CONV. CONCLUSION: This study introduces a novel fast robust optimization algorithm for IMPT treatment planning with minimum MU constraint. Such an algorithm is not only able to enhance the plan's robustness and computational efficiency without compromising OAR sparing but also able to improve treatment plan quality and reliability.

Biological-equivalent-dose-based integrated optimization framework for fast-energy-switching Bragg peak FLASH-RT using single-beam-per-fraction.

BACKGROUNDS: When comparing the delivery of all beams per fraction (ABPF) to single beam per fraction (SBPF), it is observed that SBPF not only helps meet the FLASH dose threshold but also mitigates the uncertainty with beam switching in the FLASH effect. However, SBPF might lead to a higher biological equivalent dose in 2 Gy (EQD2) for normal tissues. PURPOSE: This study aims to develop an EQD2-based integrated optimization framework (EQD2-IOF), encompassing robust dose, delivery efficiency, and beam orientation optimization (BOO) for Bragg peak FLASH plans using the SBPF treatment schedule. The EQD2-IOF aims to enhance both dose sparing and the FLASH effect. METHODS: A superconducting gantry was employed for fast energy switching within 27 ms, while universal range shifters were utilized to improve beam current in the implementation of FLASH plans with five Bragg peak beams. To enhance dose delivery efficiency while maintaining plan quality, a simultaneous dose and spot map optimization (SDSMO) algorithm for single field optimization was incorporated into a Bayesian optimization-based auto-planning algorithm. Subsequently, a BOO algorithm based on Tabu search was developed to select beam angle combinations (BACs) for 10 lung cases. To simultaneously consider dose sparing and FLASH effect, a quantitative model based on dose-dependent dose modification factor (DMF) was used to calculate FLASH-enhanced dose distribution. The EQD2-IOF plan was compared to the plan optimized without SDSMO using BAC selected by a medical physicist (Manual plan) in the SBPF treatment schedule. Meanwhile, the mean EQD2 in the normal tissue was evaluated for the EQD2-IOF plan in both SBPF and ABPF treatment schedules. RESULTS: No significant difference was found in D2% and D98% of the target between EQD2-IOF plans and Manual Plans. When using a minimum DMF of 0.67 and a dose threshold of 4 Gy, EQD2-IOF plans showed a significant reduction in FLASH-enhanced EQD2mean of the ipsilateral lung and normal tissue by 10.5% and 11.5%, respectively, compared to Manual plans. For normal tissues that received a dose greater than 70% of the prescription dose, using a minimum DMF of 0.7 for FLASH sparing compensated for the increase in EQD2mean resulting from replacing ABPF with SBPF schedules. CONCLUSIONS: The EQD2-IOF can automatically optimize SBPF FLASH-RT plans to achieve optimal sparing of normal tissues. With an energy switching time of 27 ms, the loss of fractionate repairing using SBPF schedules in high-dose regions can be compensated for by the FLASH effect. However, when an energy switching time of 500 ms is utilized, the SBPF schedule needs careful consideration, as the FLASH effect diminishes with longer irradiation time.

Final analysis of a phase II trial of neoadjuvant chemoimmunotherapy for locoregionally advanced head and neck squamous cell carcinoma.

OBJECTIVES: Neoadjuvant chemoimmunotherapy has shown promising results for resectable, locoregionally advanced (LA) head and neck squamous cell carcinoma (L/A HNSCC). We published the first phase II trial of neoadjuvant camrelizumab combined with chemotherapy in resectable, L/A HNSCC, demonstrating it was safe and feasible with favorable pathological complete response (pCR). Here, we report the final analysis results for neoadjuvant chemoimmunotherapy in L/A HNSCC (minimum 2.0 years of follow-up). MATERIALS AND METHODS: Three cycles of chemoimmunotherapy were administered before surgery to patients with L/A HNSCC. Two-year disease-free survival (DFS), overall survival (OS) and quality of life (QOL) were reported. RESULTS: The overall two-year DFS and OS rates were 90 % and 100 %, respectively. With a median follow-up of 33.7 months, 9 of 10 (90 %) patients with pCR were alive and disease free. Patients with TNM stage (II/III) or < 20 % of residual viable tumor trended toward improved DFS; hazard ratio (HR), 0.44 [95 % confidence interval (CI), 0.04-5.28] and HR, 0.26 (95 % CI, 0.03-2.36), respectively. All QLQ-C30 functioning and symptom scales other than nausea and vomiting were resolved at 2 years after the completion of radiotherapy. CONCLUSION: Neoadjuvant camrelizumab in combination with chemotherapy provided encouraging clinical outcomes for patients with L/A HNSCC. Further studies with longer follow-up and larger samples are warranted. TRIAL REGISTRATION: Chictr.org.cn, ChiCTR1900025303. Registered Aug 22, 2019. https://www.chictr.org.cn/showproj.html?proj=41380.

BL-B01D1, a first-in-class EGFR-HER3 bispecific antibody-drug conjugate, in patients with locally advanced or metastatic solid tumours: a first-in-human, open-label, multicentre, phase 1 study.

BACKGROUND: Antibody-drug conjugates have promising clinical activity in the treatment of solid tumours. BL-B01D1 is a first-in-class EGFR-HER3 bispecific antibody-drug conjugate. We aimed to assess the safety and preliminary antitumour activity of BL-B01D1 in patients with locally advanced or metastatic solid tumours. METHODS: This first-in-human, open-label, multicentre, dose-escalation and dose-expansion phase 1 trial was conducted in seven hospitals in China, enrolling patients aged 18-75 years (dose escalation; phase 1a) or older than 18 years (dose expansion; phase 1b), with a life expectancy of at least 3 months, an Eastern Cooperative Oncology Group performance status of 0-1, and histologically or cytologically confirmed locally advanced or metastatic solid tumours that had progressed on current standard treatment. In the phase 1a i3+3 design, patients received intravenous BL-B01D1 at three different schedules: 0·27 mg/kg, 1·5 mg/kg, and 3·0 mg/kg weekly; 2·5 mg/kg, 3·0 mg/kg, and 3·5 mg/kg on days 1 and 8 of each cycle every 3 weeks; or 5·0 mg/kg and 6·0 mg/kg on day 1 of each cycle every 3 weeks. The primary objectives of phase 1a were to identify the safety, maximum tolerated dose, and dose-limiting toxicity. In phase 1b, patients were treated in two schedules: 2·5 and 3·0 mg/kg on days 1 and 8 every 3 weeks, or 4·5, 5·0, and 6·0 mg/kg on day 1 every 3 weeks. The primary objectives of phase 1b were to assess the safety and recommended phase 2 dose of BL-B01D1, and objective response rate was a key secondary endpoint. Safety was analysed in all patients with safety records who received at least one dose of BL-B01D1. Antitumour activity was assessed in the activity analysis set which included all patients who received at least one dose of BL-B01D1 every 3 weeks. This trial is registered with China Drug Trials, CTR20212923, and ClinicalTrials.gov, NCT05194982, and recruitment is ongoing. FINDINGS: Between Dec 8, 2021, and March 13, 2023, 195 patients (133 [65%] men and 62 [32%] women; 25 in phase 1a and 170 in phase 1b) were consecutively enrolled, including 113 with non-small-cell lung cancer, 42 with nasopharyngeal carcinomas, 13 with small-cell lung cancer, 25 with head and neck squamous cell carcinoma, one with thymic squamous cell carcinoma, and one with submandibular lymphoepithelioma-like carcinoma. In phase 1a, four dose-limiting toxicities were observed (two at 3·0 mg/kg weekly and two at 3·5 mg/kg on days 1 and 8 every 3 weeks; all were febrile neutropenia), thus the maximum tolerated dose was reached at 3·0 mg/kg on days 1 and 8 every 3 weeks and 6·0 mg/kg on day 1 every 3 weeks. Grade 3 or worse treatment-related adverse events occurred in 139 (71%) of 195 patients; the most common of which were neutropenia (91 [47%]), anaemia (76 [39%]), leukopenia (76 [39%]), and thrombocytopenia (63 [32%]). 52 (27%) patients had a dose reduction and five (3%) patients discontinued treatment due to treatment-related adverse events. One patient was reported as having interstitial lung disease. Treatment-related deaths occurred in three (2%) patients (one due to pneumonia, one due to septic shock, and one due to myelosuppression). In 174 patients evaluated for activity, median follow-up was 6·9 months (IQR 4·5-8·9) and 60 (34%; 95% CI 27-42) patients had an objective response. INTERPRETATION: Our results suggest that BL-B01D1 has preliminary antitumour activity in extensively and heavily treated advanced solid tumours with an acceptable safety profile. Based on the safety and antitumour activity data from both phase 1a and 1b, 2·5 mg/kg on days 1 and 8 every 3 weeks was selected as the recommended phase 2 dose in Chinese patients. FUNDING: Sichuan Baili Pharmaceutical. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Induction-concurrent chemoradiotherapy with or without sintilimab in patients with locoregionally advanced nasopharyngeal carcinoma in China (CONTINUUM): a multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial.

BACKGROUND: Anti-PD-1 therapy and chemotherapy is a recommended first-line treatment for recurrent or metastatic nasopharyngeal carcinoma, but the role of PD-1 blockade remains unknown in patients with locoregionally advanced nasopharyngeal carcinoma. We assessed the addition of sintilimab, a PD-1 inhibitor, to standard chemoradiotherapy in this patient population. METHODS: This multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial was conducted at nine hospitals in China. Adults aged 18-65 years with newly diagnosed high-risk non-metastatic stage III-IVa locoregionally advanced nasopharyngeal carcinoma (excluding T3-4N0 and T3N1) were eligible. Patients were randomly assigned (1:1) using blocks of four to receive gemcitabine and cisplatin induction chemotherapy followed by concurrent cisplatin radiotherapy (standard therapy group) or standard therapy with 200 mg sintilimab intravenously once every 3 weeks for 12 cycles (comprising three induction, three concurrent, and six adjuvant cycles to radiotherapy; sintilimab group). The primary endpoint was event-free survival from randomisation to disease recurrence (locoregional or distant) or death from any cause in the intention-to-treat population. Secondary endpoints included adverse events. This trial is registered with ClinicalTrials.gov (NCT03700476) and is now completed; follow-up is ongoing. FINDINGS: Between Dec 21, 2018, and March 31, 2020, 425 patients were enrolled and randomly assigned to the sintilimab (n=210) or standard therapy groups (n=215). At median follow-up of 41·9 months (IQR 38·0-44·8; 389 alive at primary data cutoff [Feb 28, 2023] and 366 [94%] had at least 36 months of follow-up), event-free survival was higher in the sintilimab group compared with the standard therapy group (36-month rates 86% [95% CI 81-90] vs 76% [70-81]; stratified hazard ratio 0·59 [0·38-0·92]; p=0·019). Grade 3-4 adverse events occurred in 155 (74%) in the sintilimab group versus 140 (65%) in the standard therapy group, with the most common being stomatitis (68 [33%] vs 64 [30%]), leukopenia (54 [26%] vs 48 [22%]), and neutropenia (50 [24%] vs 46 [21%]). Two (1%) patients died in the sintilimab group (both considered to be immune-related) and one (<1%) in the standard therapy group. Grade 3-4 immune-related adverse events occurred in 20 (10%) patients in the sintilimab group. INTERPRETATION: Addition of sintilimab to chemoradiotherapy improved event-free survival, albeit with higher but manageable adverse events. Longer follow-up is necessary to determine whether this regimen can be considered as the standard of care for patients with high-risk locoregionally advanced nasopharyngeal carcinoma. FUNDING: National Natural Science Foundation of China, Key-Area Research and Development Program of Guangdong Province, Natural Science Foundation of Guangdong Province, Overseas Expertise Introduction Project for Discipline Innovation, Guangzhou Municipal Health Commission, and Cancer Innovative Research Program of Sun Yat-sen University Cancer Center. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy.

Objective.To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Approach.Two 3D UNets were established to predict photon and proton doses. A dataset of 95 patients with localized prostate cancer was randomly partitioned into 55, 10, and 30 for training, validation, and testing, respectively. We selected NTCP models for late rectum bleeding and acute urinary urgency of grade 2 or higher to quantify the benefit of proton therapy. Propagated uncertainties of predicted ΔNTCPs resulting from the dose prediction errors were calculated. Patient selection accuracies for a single endpoint and a composite evaluation were assessed under different ΔNTCP thresholds.Main results.Our deep learning-based dose prediction technique can reduce the time spent on plan comparison from approximately 2 days to as little as 5 seconds. The expanded uncertainty of predicted ΔNTCPs for rectum and bladder endpoints propagated from the dose prediction error were 0.0042 and 0.0016, respectively, which is less than one-third of the acceptable tolerance. The averaged selection accuracies for rectum bleeding, urinary urgency, and composite evaluation were 90%, 93.5%, and 93.5%, respectively.Significance.Our study demonstrates that deep learning dose prediction and NTCP evaluation scheme could distinguish the NTCP differences between photon and proton treatment modalities. In addition, the dose prediction uncertainty does not significantly influence the decision accuracy of NTCP-based patient selection for proton therapy. Therefore, automated deep learning dose prediction and NTCP evaluation schemes can potentially be used to screen large patient populations and to avoid unnecessary delays in the start of prostate cancer radiotherapy in the future.

In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network: a feasibility study.

We proposed a deep learning approach to classify various error types in daily VMAT treatment of head and neck cancer patients based on EPID dosimetry, which could provide additional information to support clinical decisions for adaptive planning. 146 arcs from 42 head and neck patients were analyzed. Anatomical changes and setup errors were simulated in 17,820 EPID images of 99 arcs obtained from 30 patients using in-house software for model training, validation, and testing. Subsequently, 141 clinical EPID images from 47 arcs belonging to the remaining 12 patients were utilized for clinical testing. The hierarchical convolutional neural network (HCNN) model was trained to classify error types and magnitudes using EPID dose difference maps. Gamma analysis with 3%/2 mm (dose difference/distance to agreement) criteria was also performed. The F1 score, a combination of precision and recall, was utilized to evaluate the performance of the HCNN model and gamma analysis. The adaptive fractioned doses were calculated to verify the HCNN classification results. For error type identification, the overall F1 score of the HCNN model was 0.99 and 0.91 for primary type and subtype identification, respectively. For error magnitude identification, the overall F1 score in the simulation dataset was 0.96 and 0.70 for the HCNN model and gamma analysis, respectively; while the overall F1 score in the clinical dataset was 0.79 and 0.20 for the HCNN model and gamma analysis, respectively. The HCNN model-based EPID dosimetry can identify changes in patient transmission doses and distinguish the treatment error category, which could potentially provide information for head and neck cancer treatment adaption.

Induction of therapeutic immunity and cancer eradication through biofunctionalized liposome-like nanovesicles derived from irradiated-cancer cells.

Immunotherapy has revolutionized the treatment of cancer. However, its efficacy remains to be optimized. There are at least two major challenges in effectively eradicating cancer cells by immunotherapy. Firstly, cancer cells evade immune cell killing by down-regulating cell surface immune sensors. Secondly, immune cell dysfunction impairs their ability to execute anti-cancer functions. Radiotherapy, one of the cornerstones of cancer treatment, has the potential to enhance the immunogenicity of cancer cells and trigger an anti-tumor immune response. Inspired by this, we fabricate biofunctionalized liposome-like nanovesicles (BLNs) by exposing irradiated-cancer cells to ethanol, of which ethanol serves as a surfactant, inducing cancer cells pyroptosis-like cell death and facilitating nanovesicles shedding from cancer cell membrane. These BLNs are meticulously designed to disrupt both of the aforementioned mechanisms. On one hand, BLNs up-regulate the expression of calreticulin, an "eat me" signal on the surface of cancer cells, thus promoting macrophage phagocytosis of cancer cells. Additionally, BLNs are able to reprogram M2-like macrophages into an anti-cancer M1-like phenotype. Using a mouse model of malignant pleural effusion (MPE), an advanced-stage and immunotherapy-resistant cancer model, we demonstrate that BLNs significantly increase T cell infiltration and exhibit an ablative effect against MPE. When combined with PD-1 inhibitor (α-PD-1), we achieve a remarkable 63.6% cure rate (7 out of 11) among mice with MPE, while also inducing immunological memory effects. This work therefore introduces a unique strategy for overcoming immunotherapy resistance.

Irradiated tumour cell-derived microparticles upregulate MHC-I expression in cancer cells via DNA double-strand break repair pathway.

Radiotherapy (RT) is used for over 50 % of cancer patients and can promote adaptive immunity against tumour antigens. However, the underlying mechanisms remain unclear. Here, we discovered that RT induces the release of irradiated tumour cell-derived microparticles (RT-MPs), which significantly upregulate MHC-I expression on the membranes of non-irradiated cells, enhancing the recognition and killing of these cells by T cells. Mechanistically, RT-MPs induce DNA double-strand breaks (DSB) in tumour cells, activating the ATM/ATR/CHK1-mediated DNA repair signalling pathway, and upregulating MHC-I expression. Inhibition of ATM/ATR/CHK1 reversed RT-MP-induced upregulation of MHC-I. Furthermore, phosphorylation of STAT1/3 following the activation of ATM/ATR/CHK1 is indispensable for the DSB-dependent upregulation of MHC-I. Therefore, our findings reveal the role of RT-MP-induced DSBs and the subsequent DNA repair signalling pathway in MHC-I expression and provide mechanistic insights into the regulation of MHC-I expression after DSBs.

Microglia and macrophage metabolism: a regulator of cerebral gliomas.

Reciprocal interactions between the tumor microenvironment (TME) and cancer cells play important roles in tumorigenesis and progression of glioma. Glioma-associated macrophages (GAMs), either of peripheral origin or representing brain-intrinsic microglia, are the majority population of infiltrating immune cells in glioma. GAMs, usually classified into M1 and M2 phenotypes, have remarkable plasticity and regulate tumor progression through different metabolic pathways. Recently, research efforts have increasingly focused on GAMs metabolism as potential targets for glioma therapy. This review aims to delineate the metabolic characteristics of GAMs within the TME and provide a summary of current therapeutic strategies targeting GAMs metabolism in glioma. The goal is to provide novel insights and therapeutic pathways for glioma by highlighting the significance of GAMs metabolism.

Metabolism, digestion, and horizontal transfer: potential roles and interaction of symbiotic bacteria in the ladybird beetle Novius pumilus and their prey Icerya aegyptiaca.

In this study, we first time sequenced and analyzed the 16S rRNA gene data of predator ladybird beetles Novius pumilus and globally distributed invasive pest Icerya aegyptiaca at different stages, and combined data with bacterial genome sequences in N. pumilus to explored the taxonomic distribution, alpha and beta diversity, differentially abundant bacteria, co-occurrence network, and putative functions of their microbial community. Our finding revealed that Candidatus Walczuchella, which exhibited a higher abundance in I. aegyptiaca, possessed several genes in essential amino acid biosynthesis and seemed to perform roles in providing nutrients to the host, similar to other obligate symbionts in scale insects. Lactococcus, Serratia, and Pseudomonas, more abundant in N. pumilus, were predicted to have genes related to hydrocarbon, fatty acids, and chitin degradation, which may assist their hosts in digesting the wax shell covering the scale insects. Notably, our result showed that Lactococcus had relatively higher abundances in adults and eggs compared to other stages in N. pumilus, indicating potential vertical transmission. Additionally, we found that Arsenophonus, known to influence sex ratios in whitefly and wasp, may also function in I. aegyptiaca, probably by influencing nutrient metabolism as it similarly had many genes corresponding to vitamin B and essential amino acid biosynthesis. Also, we observed a potential horizontal transfer of Arsenophonus between the scale insect and its predator, with a relatively high abundance in the ladybirds compared to other bacteria from the scale insects.IMPORTANCEThe composition and dynamic changes of microbiome in different developmental stages of ladybird beetles Novius pumilus with its prey Icerya aegyptiaca were detected. We found that Candidatus Walczuchella, abundant in I. aegyptiaca, probably provide nutrients to their host based on their amino acid biosynthesis-related genes. Abundant symbionts in N. pumilus, including Lactococcus, Serratia, and Pseudophonus, may help the host digest the scale insects with their hydrocarbon, fatty acid, and chitin degrading-related genes. A key endosymbiont Arsenophonus may play potential roles in the nutrient metabolisms and sex determination in I. aegyptiaca, and is possibly transferred from the scale insect to the predator.

Tumor cell senescence-induced macrophage CD73 expression is a critical metabolic immune checkpoint in the aging tumor microenvironment.

Background: The role of senescent cells in the tumor microenvironment (TME) is usually bilateral, and diverse therapeutic approaches, such as radiotherapy and chemotherapy, can induce cellular senescence. Cellular interactions are widespread in the TME, and tumor cells reprogram immune cells metabolically by producing metabolites. However, how senescent cells remodel the metabolism of TME remains unclear. This study aimed to explore precise targets to enhance senescent cells-induced anti-tumor immunity from a metabolic perspective. Methods: The in vivo senescence model was induced by 8 Gy×3 radiotherapy or cisplatin chemotherapy, and the in vitro model was induced by 10 Gy-irradiation or cisplatin treatment. Metabonomic analysis and ELISA assay on tumor interstitial fluid were performed for metabolites screening. Marker expression and immune cell infiltration in the TME were analyzed by flow cytometry. Cell co-culture system and senescence-conditioned medium were used for crosstalk validation in vitro. RNA sequencing and rescue experiments were conducted for mechanism excavation. Immunofluorescence staining and single-cell transcriptome profiling analysis were performed for clinical validation. Results: We innovatively reveal the metabolic landscape of the senescent TME, characterized with the elevation of adenosine. It is attributed to the senescent tumor cell-induced CD73 upregulation of tumor-associated macrophages (TAMs). CD73 expression in TAMs is evoked by SASP-related pro-inflammatory cytokines, especially IL-6, and regulated by JAK/STAT3 pathway. Consistently, a positive correlation between tumor cells senescence and TAMs CD73 expression is identified in lung cancer clinical specimens and databases. Lastly, blocking CD73 in a senescent background suppresses tumors and activates CD8+ T cell-mediated antitumor immunity. Conclusions: TAMs expressed CD73 contributes significantly to the adenosine accumulation in the senescent TME, suggesting targeting CD73 is a novel synergistic anti-tumor strategy in the aging microenvironment.

In situ vaccination caused by diverse irradiation-driven cell death programs.

Interest surrounding the effect of irradiation on immune activation has exponentially grown within the last decade. This includes work regarding mechanisms of the abscopal effect and the success achieved by combination of radiotherapy and immunotherapy. It is hypothesized that irradiation triggers the immune system to eliminate tumors by inducing tumor cells immunogenic cell death (ICD) in tumor cells. Activation of the ICD pathways can be exploited as an in situ vaccine. In this review, we provide fundamental knowledge of various forms of ICD caused by irradiation, describe the relationship between various cell death pathways and the immune activation effect driven by irradiation, and focus on the therapeutic value of exploiting these cell death programs in the context of irradiation. Furthermore, we summarize the immunomodulatory effect of different cell death programs on combinative radiotherapy and immunotherapy. In brief, differences in cell death programs significantly impact the irradiation-induced immune activation effect. Evaluating the transition between them will provide clues to develop new strategies for radiotherapy and its combination with immunotherapy.