Management and outcomes of breast cancer patients with radiotherapy interruption.

Background: Many cancer patients have not received timely treatment or even had treatment interruptions due to the COVID-19 pandemic. The objective of this investigation was to evaluate whether the prognosis of patients with breast cancer after surgery was affected by any interruptions in radiotherapy. Methods: The healthcare documents for breast cancer patients experiencing radiotherapy interruption after surgery, including treatment-related characteristics, and time of interruption, type of disease progression, and survival status, were collected between January and April 2020 during the Wuhan blockade. Results: The final number of patients included was 148, and neither the Kaplan-Meier (KM) survival curve nor the cross-tabulation analysis found statistical significance. Cox regression analysis also did not identify risk factors associated with PFS. Conclusions: The prognosis of patients with postoperative breast cancer may not be significantly impacted by the interruption of radiotherapy, given its integration with additional treatments like targeted and endocrine therapies.

A novel predictor for dosimetry data of lung and the radiation pneumonitis incidence prior to SBRT in lung cancer patients.

Normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) in lung cancer patients with stereotactic body radiation therapy (SBRT), which based on dosimetric data from treatment planning, are limited to patients who have already received radiation therapy (RT). This study aims to identify a novel predictive factor for lung dose distribution and RP probability before devising actionable SBRT plans for lung cancer patients. A comprehensive correlation analysis was performed on the clinical and dose parameters of lung cancer patients who underwent SBRT. Linear regression models were utilized to analyze the dosimetric data of lungs. The performance of the regression models was evaluated using mean squared error (MSE) and the coefficient of determination (R2). Correlational analysis revealed that most clinical data exhibited weak correlations with dosimetric data. However, nearly all dosimetric variables showed "strong" or "very strong" correlations with each other, particularly concerning the mean dose of the ipsilateral lung (MI) and the other dosimetric parameters. Further study verified that the lung tumor ratio (LTR) was a significant predictor for MI, which could predict the incidence of RP. As a result, LTR can predict the probability of RP without the need to design an elaborate treatment plan. This study, as the first to offer a comprehensive correlation analysis of dose parameters, explored the specific relationships among them. Significantly, it identified LTR as a novel predictor for both dose parameters and the incidence of RP, without the need to design an elaborate treatment plan.

Rtt105 stimulates Rad51-ssDNA assembly and orchestrates Rad51 and RPA actions to promote homologous recombination repair.

Homologous recombination (HR) is essential for the maintenance of genome stability. During HR, Replication Protein A (RPA) rapidly coats the 3'-tailed single-strand DNA (ssDNA) generated by end resection. Then, the ssDNA-bound RPA must be timely replaced by Rad51 recombinase to form Rad51 nucleoprotein filaments that drive homology search and HR repair. How cells regulate Rad51 assembly dynamics and coordinate RPA and Rad51 actions to ensure proper HR remains poorly understood. Here, we identified that Rtt105, a Ty1 transposon regulator, acts to stimulate Rad51 assembly and orchestrate RPA and Rad51 actions during HR. We found that Rtt105 interacts with Rad51 in vitro and in vivo and restrains the adenosine 5' triphosphate (ATP) hydrolysis activity of Rad51. We showed that Rtt105 directly stimulates dynamic Rad51-ssDNA assembly, strand exchange, and D-loop formation in vitro. Notably, we found that Rtt105 physically regulates the binding of Rad51 and RPA to ssDNA via different motifs and that both regulations are necessary and epistatic in promoting Rad51 nucleation, strand exchange, and HR repair. Consequently, disrupting either of the interactions impaired HR and conferred DNA damage sensitivity, underscoring the importance of Rtt105 in orchestrating the actions of Rad51 and RPA. Our work reveals additional layers of mechanisms regulating Rad51 filament dynamics and the coordination of HR.

Prediction of Geometric Characteristics of Laser Cladding Layer Based on Least Squares Support Vector Regression and Crested Porcupine Optimization.

The morphology size of laser cladding is a crucial parameter that significantly impacts the quality and performance of the cladding layer. This study proposes a predictive model for the cladding morphology size based on the Least Squares Support Vector Regression (LSSVR) and the Crowned Porcupine Optimization (CPO) algorithm. Specifically, the proposed model takes three key parameters as inputs: laser power, scanning speed, and powder feeding rate, with the width and height of the cladding layer as outputs. To further enhance the predictive accuracy of the LSSVR model, a CPO-based optimization strategy is applied to adjust the penalty factor and kernel parameters. Consequently, the CPO-LSSVR model is established and evaluated against the LSSVR model and the Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP) model in terms of relative error metrics. The experimental results demonstrate that the CPO-LSSVR model can achieve a significantly improved relative error of no more than 2.5%, indicating a substantial enhancement in predictive accuracy compared to other methods and showcasing its superior predictive performance. The high accuracy of the CPO-LSSVR model can effectively guide the selection of laser cladding process parameters and thereby enhance the quality and efficiency of the cladding process.

Different trends of gastric cancer in China, Japan, Republic of Korea and United States of America.

Gastric cancer exerts a significant healthcare burden worldwide and is highly geographically heterogeneous. This study investigates the burden of gastric cancer in China from 1990 to 2019 and compares it with Japan, South Korea, and the United States. The results indicated a declining trend in ASIR and ASDR in four countries. However, the incidence and death rates in China remain disproportionately high. Significant gender disparities exist in the incidence and death rates, with males experiencing significantly higher rates than females. Incidence and death rates were found to increase with age in all studied countries. In China, a transient upward trend was observed in the period effect, whereas the cohort effect has been declining. In contrast, the remaining countries showed decreasing patterns in both period and cohort effects. The burden of disease remains high in China, therefore, broaden the scope of gastroscopy screening and concentrate on high-risk groups is vital.

Partial response to trastuzumab deruxtecan (DS8201) following progression in HER2-amplified breast cancer with pulmonary metastases managed with disitamab vedotin (RC48): a comprehensive case report and literature review.

Breast cancer remains one of the predominant malignancies worldwide. In the context of inoperable advanced or metastatic human epidermal growth factor receptor 2 (HER2)-positive breast cancer, systemic management primarily relies on HER2-targeting monoclonal antibodies. With the successful development of anti-HER2 antibody-drug conjugates (ADCs), these agents have been increasingly integrated into therapeutic regimens for metastatic breast cancer. Here, we present the case of a 42-year-old female patient with HER2-positive pulmonary metastatic breast cancer who underwent an extensive treatment protocol. This protocol included chemotherapy, radiation therapy, hormonal therapy, surgical intervention on the breast, and anti-HER2 therapies. The anti-HER2 therapies involved both singular and dual targeting strategies using trastuzumab and the ADC disitamab vedotin (RC48) over an 8-year period. After experiencing disease progression following HER2-targeted therapy with RC48, the patient achieved noticeable partial remission through a therapeutic regimen that combined trastuzumab deruxtecan (DS8201) and tislelizumab. The data suggest a promising role for DS8201 in managing advanced stages of HER2-amplified metastatic breast cancer, especially in cases that demonstrate progression after initial HER2-directed therapies using ADCs. Furthermore, its combination with anti-PD-1 agents enhances therapeutic efficacy by augmenting the anti-tumoral immune response.

Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies.

BACKGROUND: Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population. METHODS: To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants. RESULTS: Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose-response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32). CONCLUSIONS: Our comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.

Study on Gesture Recognition Method with Two-Stream Residual Network Fusing sEMG Signals and Acceleration Signals.

Currently, surface EMG signals have a wide range of applications in human-computer interaction systems. However, selecting features for gesture recognition models based on traditional machine learning can be challenging and may not yield satisfactory results. Considering the strong nonlinear generalization ability of neural networks, this paper proposes a two-stream residual network model with an attention mechanism for gesture recognition. One branch processes surface EMG signals, while the other processes hand acceleration signals. Segmented networks are utilized to fully extract the physiological and kinematic features of the hand. To enhance the model's capacity to learn crucial information, we introduce an attention mechanism after global average pooling. This mechanism strengthens relevant features and weakens irrelevant ones. Finally, the deep features obtained from the two branches of learning are fused to further improve the accuracy of multi-gesture recognition. The experiments conducted on the NinaPro DB2 public dataset resulted in a recognition accuracy of 88.25% for 49 gestures. This demonstrates that our network model can effectively capture gesture features, enhancing accuracy and robustness across various gestures. This approach to multi-source information fusion is expected to provide more accurate and real-time commands for exoskeleton robots and myoelectric prosthetic control systems, thereby enhancing the user experience and the naturalness of robot operation.

Patient's Healthy-Limb Motion Characteristic-Based Assist-As-Needed Control Strategy for Upper-Limb Rehabilitation Robots.

The implementation of a progressive rehabilitation training model to promote patients' motivation efforts can greatly restore damaged central nervous system function in patients. Patients' active engagement can be effectively stimulated by assist-as-needed (AAN) robot rehabilitation training. However, its application in robotic therapy has been hindered by a simple determination method of robot-assisted torque which focuses on the evaluation of only the affected limb's movement ability. Moreover, the expected effect of assistance depends on the designer and deviates from the patient's expectations, and its applicability to different patients is deficient. In this study, we propose a control method with personalized treatment features based on the idea of estimating and mapping the stiffness of the patient's healthy limb. This control method comprises an interactive control module in the task-oriented space based on the quantitative evaluation of motion needs and an inner-loop position control module for the pneumatic swing cylinder in the joint space. An upper-limb endpoint stiffness estimation model was constructed, and a parameter identification algorithm was designed. The upper limb endpoint stiffness which characterizes the patient's ability to complete training movements was obtained by collecting surface electromyographic (sEMG) signals and human-robot interaction forces during patient movement. Then, the motor needs of the affected limb when completing the same movement were quantified based on the performance of the healthy limb. A stiffness-mapping algorithm was designed to dynamically adjust the rehabilitation training trajectory and auxiliary force of the robot based on the actual movement ability of the affected limb, achieving AAN control. Experimental studies were conducted on a self-developed pneumatic upper limb rehabilitation robot, and the results showed that the proposed AAN control method could effectively estimate the patient's movement needs and achieve progressive rehabilitation training. This rehabilitation training robot that simulates the movement characteristics of the patient's healthy limb drives the affected limb, making the intensity of the rehabilitation training task more in line with the patient's pre-morbid limb-use habits and also beneficial for the consistency of bilateral limb movements.

Targeting O-GlcNAcylation in cancer therapeutic resistance: The sugar Saga continues.

O-linked-N-acetylglucosaminylation (O-GlcNAcylation), a dynamic post-translational modification (PTM), holds profound implications in controlling various cellular processes such as cell signaling, metabolism, and epigenetic regulation that influence cancer progression and therapeutic resistance. From the therapeutic perspective, O-GlcNAc modulates drug efflux, targeting and metabolism. By integrating signals from glucose, lipid, amino acid, and nucleotide metabolic pathways, O-GlcNAc acts as a nutrient sensor and transmits signals to exerts its function on genome stability, epithelial-mesenchymal transition (EMT), cell stemness, cell apoptosis, autophagy, cell cycle. O-GlcNAc also attends to tumor microenvironment (TME) and the immune response. At present, several strategies aiming at targeting O-GlcNAcylation are under mostly preclinical evaluation, where the newly developed O-GlcNAcylation inhibitors markedly enhance therapeutic efficacy. Here we systematically outline the mechanisms through which O-GlcNAcylation influences therapy resistance and deliberate on the prospects and challenges associated with targeting O-GlcNAcylation in future cancer treatments.

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks.

Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.

Deep-learning-driven dose prediction and verification for stereotactic radiosurgical treatment of isolated brain metastases.

Purpose: While deep learning has shown promise for automated radiotherapy planning, its application to the specific scenario of stereotactic radiosurgery (SRS) for brain metastases using fixed-field intensity modulated radiation therapy (IMRT) on a linear accelerator remains limited. This work aimed to develop and verify a deep learning-guided automated planning protocol tailored for this scenario. Methods: We collected 70 SRS plans for solitary brain metastases, of which 36 cases were for training and 34 for testing. Test cases were derived from two distinct clinical institutions. The envisioned automated planning process comprised (1): clinical dose prediction facilitated by deep-learning algorithms (2); transformation of the forecasted dose into executable plans via voxel-centric dose emulation (3); validation of the envisaged plan employing a precise dosimeter in conjunction with a linear accelerator. Dose prediction paradigms were established by engineering and refining two three-dimensional UNet architectures (UNet and AttUNet). Input parameters encompassed computed tomography scans from clinical plans and demarcations of the focal point alongside organs at potential risk (OARs); the ensuing output manifested as a 3D dose matrix tailored for each case under scrutiny. Results: Dose estimations rendered by both models mirrored the manual plans and adhered to clinical stipulations. As projected by the dual models, the apex and average doses for OARs did not deviate appreciably from those delineated in the manual plan (P-value≥0.05). AttUNet showed promising results compared to the foundational UNet. Predicted doses showcased a pronounced dose gradient, with peak concentrations localized within the target vicinity. The executable plans conformed to clinical dosimetric benchmarks and aligned with their associated verification assessments (100% gamma approval rate at 3 mm/3%). Conclusion: This study demonstrates an automated planning technique for fixed-field IMRT-based SRS for brain metastases. The envisaged plans met clinical requirements, were reproducible across centers, and achievable in deliveries. This represents progress toward automated paradigms for this specific scenario.

Single-cell and bulk RNA sequencing analysis of B cell marker genes in TNBC TME landscape and immunotherapy.

Objective: This study amied to investigate the prognostic characteristics of triple negative breast cancer (TNBC) patients by analyzing B cell marker genes based on single-cell and bulk RNA sequencing. Methods: Utilizing single-cell sequencing data from TNBC patients, we examined tumor-associated B cell marker genes. Transcriptomic data from The Cancer Genome Atlas (TCGA) database were used as the foundation for predictive modeling. Independent validation set was conducted using the GSE58812 dataset. Immune cell infiltration into the tumor was assessed through various, including XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA. The TIDE score was utilized to predict immunotherapy outcomes. Additional investigations were conducted on the immune checkpoint blockade gene, tumor mutational load, and the GSEA enrichment analysis. Results: Our analysis encompassed 22,106 cells and 20,556 genes in cancerous tissue samples from four TNBC patients, resulting in the identification of 116 B cell marker genes. A B cell marker gene score (BCMG score) involving nine B cell marker genes (ZBP1, SEL1L3, CCND2, TNFRSF13C, HSPA6, PLPP5, CXCR4, GZMB, and CCDC50) was developed using TCGA transcriptomic data, revealing statistically significant differences in survival analysis (P<0.05). Functional analysis demonstrated that marker genes were predominantly associated with immune-related pathways. Notably, substantial differences between the higher and lower- BCMG score groups were observed in terms of immune cell infiltration, immune cell activity, tumor mutational burden, TIDE score, and the expression of immune checkpoint blockade genes. Conclusion: This study has established a robust model based on B-cell marker genes in TNBC, which holds significant potential for predicting prognosis and response to immunotherapy in TNBC patients.

Genome-wide association analysis of left ventricular imaging-derived phenotypes identifies 72 risk loci and yields genetic insights into hypertrophic cardiomyopathy.

Left ventricular regional wall thickness (LVRWT) is an independent predictor of morbidity and mortality in cardiovascular diseases (CVDs). To identify specific genetic influences on individual LVRWT, we established a novel deep learning algorithm to calculate 12 LVRWTs accurately in 42,194 individuals from the UK Biobank with cardiac magnetic resonance (CMR) imaging. Genome-wide association studies of CMR-derived 12 LVRWTs identified 72 significant genetic loci associated with at least one LVRWT phenotype (P < 5 × 10-8), which were revealed to actively participate in heart development and contraction pathways. Significant causal relationships were observed between the LVRWT traits and hypertrophic cardiomyopathy (HCM) using genetic correlation and Mendelian randomization analyses (P < 0.01). The polygenic risk score of inferoseptal LVRWT at end systole exhibited a notable association with incident HCM, facilitating the identification of high-risk individuals. The findings yield insights into the genetic determinants of LVRWT phenotypes and shed light on the biological basis for HCM etiology.

Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation.

Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the physicians' experience and the patient's characteristics. And the training should have high accuracy on the premise of safety. Therefore, trajectory customization, optimization, and tracking control algorithms are conducted based on a new upper limb rehabilitation robot. First, joint friction and initial load were identified and compensated. The admittance algorithm was used to realize the trajectory customization. Second, the improved butterfly optimization algorithm (BOA) was used to optimize the nonuniform rational B-spline fitting curve (NURBS). Then, a variable gain control strategy is designed, which enables the robot to track the trajectory well with small human-robot interaction (HRI) forces and to comply with a large HRI force to ensure safety. Regarding the return motion, an error subdivision method is designed to slow the return movement. The results showed that the customization force is less than 6 N. The trajectory tracking error is within 12 mm without a large HRI force. The control gain starts to decrease in 0.5 s periods while there is a large HRI force, thereby improving safety. With the decrease in HRI force, the real position can return to the desired trajectory slowly, which makes the patient feel comfortable.

Dosimetric impact of hollow intraoral stents for head and neck cancer radiotherapy: A phantom study.

PURPOSE: To investigate the dosimetric impact of the calculation boundaries and dose calculation algorithms of radiotherapy in head and neck cancer patients with an opened oral cavity connected to the exterior by a hollow intraoral positioning stent. METHODS AND MATERIALS: A homemade silicone phantom with an opened oral cavity was placed in a CIRS head phantom to model head and neck cancer patients with a hollow intraoral positioning stent. 3D-CRT plans were designed on CT images of the phantom in Monaco and Pinnacle3 treatment planning systems (TPSs) with the same beam parameters. The default boundary and manually extrapolated boundary were both adopted in these two TPSs to explore the dosimetric impact on treatment plans. The nanoDot™ optically stimulated luminescence dosimeters (OSLDs) were chosen to measure the planned dose surrounding the oral cavity of the head phantom after calibration. RESULT: The doses in the air cavity and two measuring points at the joint area were dramatically changed from 0.0, 92.4 and 148.8 cGy to 177.8, 244.2 and 244.1 cGy in Monaco after adopting the extrapolated boundary. While the calculated doses at the same place were changed from 61.2, 143.7 and 198.3 cGy to 175.4, 234.7 and 233.2 cGy in Pinnacle3 with a similar calculation boundary. For the Monaco TPS, the relative errors compared to the OSLD measured doses were 2.94 ± 1.93%, 0.53 ± 8.64%, 2.65 ± 1.87% and 3.93 ± 1.69% at 4 measuring positions. In contrast, the relative errors 4.03 ± 1.93%, 4.85 ± 8.64%, 7.61 ± 1.87% and 5.61 ± 1.69% were observed in Pinnacle3 . CONCLUSION: The boundary setting of an opened oral cavity in TPSs has a significant dosimetric impact on head and neck cancer radiotherapy. An extrapolated boundary should be manually set up to include the whole oral cavity in the dose calculation domain to avoid major dose deviations.

New treatment insights into pancreatic acinar cell carcinoma: case report and literature review.

Pancreatic acinar cell carcinoma (PACC) is a rare pancreatic malignancy with unique clinical, molecular, and morphologic features. The long-term survival of patients with PACC is substantially better than that of patients with ductal adenocarcinoma of the pancreas. Surgical resection is considered the first choice for treatment; however, there is no standard treatment option for patients with inoperable disease. The patient with metastatic PACC reported herein survived for more than 5 years with various treatments including chemotherapy, radiotherapy, antiangiogenic therapy and combined immunotherapy.

Bre1/RNF20 promotes Rad51-mediated strand exchange and antagonizes the Srs2/FBH1 helicases.

Central to homologous recombination (HR) is the assembly of Rad51 recombinase on single-strand DNA (ssDNA), forming the Rad51-ssDNA filament. How the Rad51 filament is efficiently established and sustained remains partially understood. Here, we find that the yeast ubiquitin ligase Bre1 and its human homolog RNF20, a tumor suppressor, function as recombination mediators, promoting Rad51 filament formation and subsequent reactions via multiple mechanisms independent of their ligase activities. We show that Bre1/RNF20 interacts with Rad51, directs Rad51 to ssDNA, and facilitates Rad51-ssDNA filament assembly and strand exchange in vitro. In parallel, Bre1/RNF20 interacts with the Srs2 or FBH1 helicase to counteract their disrupting effect on the Rad51 filament. We demonstrate that the above functions of Bre1/RNF20 contribute to HR repair in cells in a manner additive to the mediator protein Rad52 in yeast or BRCA2 in human. Thus, Bre1/RNF20 provides an additional layer of mechanism to directly control Rad51 filament dynamics.

Effect of radiotherapy interruption on nasopharyngeal cancer.

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from the epithelial cells of the nasopharynx with a unique geographic distribution, and is particularly prevalent in East and Southeast Asia. Due to its anatomical location, the surgery is difficult to access and the high sensitivity of nasopharyngeal cancer to radiotherapy (RT) makes it the main treatment modality. Radical radiotherapy is the first-line treatment for early-stage nasopharyngeal carcinoma and the cornerstone of multidisciplinary treatment for patients with locally advanced nasopharyngeal carcinoma. Nevertheless, radiotherapy interruption is inevitable as a consequence of unavoidable factors such as public holidays, machine malfunction, patient compliance, and adverse response to treatment, which in turn leads to a reduction in bioactivity and causes sublethal loss of tumor cells to repair. Unirradiated tumor cells are more likely to repopulate at or near their original fastest growth rate during this interval. If no measures are taken after the radiotherapy interruption, such as increasing the dose of radiotherapy and systemic therapy, the tumor is most likely to go uncontrolled and then progress. This review describes the effects of radiotherapy interruption on nasopharyngeal carcinoma, the mechanism of the effect, and explores the measures that can be taken in response to such interruption.

Co-profiling reveals distinct patterns of genomic chromatin accessibility and gene expression in pulmonary hypertension caused by chronic hypoxia.

INTRODUCTION: Aberrant gene expression is a key mechanism underlying pulmonary hypertension (PH) development. The alterations of genomic chromatin accessibility and their relationship with the aberrant gene expressions in PH are poorly understood. We used bulk Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) and RNA sequencing (RNA-seq) in pulmonary artery smooth muscle cells (PASMCs) of chronic hypoxia-exposed rats mimicking group 3 human PH. METHODS: Adult Sprague Dawley rats were commercially obtained from Hunan SJA (Hunan SJA Laboratory Animal Co., Changsha, China) and randomizedly allocated into four groups exposing to nomobaric hypoxia or normoxia for 1 or 28 days respectively. After the assessment of pulmonary hemodynamics, smooth muscle cells were isolated from intralobular arteries and simultaneously subjected to bulk Assay of ATAC-seq and RNA-seq. RESULTS: Hypoxic exposure for continuous 28-days, but not for 1-day, induced established PH phenotypes in rats. ATAC-seq revealed a major distribution of differential accessibility regions (DARs) annotated to the genome in out-of-promoter regions, following 1-day or 28-days hypoxia. 1188 DAR-associated genes and 378 differentially expressed genes (DEGs) were identified in rats after exposure to 1-day hypoxia, while 238 DAR-associated genes and 452 DEGs for 28-days hypoxia. Most of the DAR-associated genes or DEGs in 1-day did not overlap with that of 28-days hypoxia. A Pearson correlation analysis indicated no significant correlation between ATAC-seq and RNA-seq. CONCLUSIONS: The alterations in genomic chromatin accessibility and genes expression of PASMCs in the initial stage of hypoxia are distinct from the established stage of hypoxia-induced PH. The genomic differential accessibility regions may not be the main mechanisms directly underlying the differentially expressed genes observed either in the initial or established stages of PH. Thus the time-course alterations of gene expression and their possible indirect link with genomic chromatin accessibility warrant more attention in mechanistic study of pulmonary hypertension.