Using high-repeatable radiomic features improves the cross-institutional generalization of prognostic model in esophageal squamous cell cancer receiving definitive chemoradiotherapy.

OBJECTIVES: Repeatability is crucial for ensuring the generalizability and clinical utility of radiomics-based prognostic models. This study aims to investigate the repeatability of radiomic feature (RF) and its impact on the cross-institutional generalizability of the prognostic model for predicting local recurrence-free survival (LRFS) and overall survival (OS) in esophageal squamous cell cancer (ESCC) receiving definitive (chemo) radiotherapy (dCRT). METHODS: Nine hundred and twelve patients from two hospitals were included as training and external validation sets, respectively. Image perturbations were applied to contrast-enhanced computed tomography to generate perturbed images. Six thousand five hundred ten RFs from different feature types, bin widths, and filters were extracted from the original and perturbed images separately to evaluate RF repeatability by intraclass correlation coefficient (ICC). The high-repeatable and low-repeatable RF groups grouped by the median ICC were further analyzed separately by feature selection and multivariate Cox proportional hazards regression model for predicting LRFS and OS. RESULTS: First-order statistical features were more repeatable than texture features (median ICC: 0.70 vs 0.42-0.62). RFs from LoG had better repeatability than that of wavelet (median ICC: 0.70-0.84 vs 0.14-0.64). Features with smaller bin widths had higher repeatability (median ICC of 8-128: 0.65-0.47). For both LRFS and OS, the performance of the models based on high- and low-repeatable RFs remained stable in the training set with similar C-index (LRFS: 0.65 vs 0.67, p = 0.958; OS: 0.64 vs 0.65, p = 0.651), while the performance of the model based on the low-repeatable group was significantly lower than that based on the high-repeatable group in the external validation set (LRFS: 0.61 vs 0.67, p = 0.013; OS: 0.56 vs 0.63, p = 0.013). CONCLUSIONS: Applying high-repeatable RFs in modeling could safeguard the cross-institutional generalizability of the prognostic model in ESCC. CRITICAL RELEVANCE STATEMENT: The exploration of repeatable RFs in different diseases and different types of imaging is conducive to promoting the proper use of radiomics in clinical research. KEY POINTS: The repeatability of RFs impacts the generalizability of the radiomic model. The high-repeatable RFs safeguard the cross-institutional generalizability of the model. Smaller bin width helps improve the repeatability of RFs.

Pseudo-CT synthesis in adaptive radiotherapy based on a stacked coarse-to-fine model: Combing diffusion process and spatial-frequency convolutions.

BACKGROUND: Cone beam computed tomography (CBCT) provides critical anatomical information for adaptive radiotherapy (ART), especially for tumors in the pelvic region that undergo significant deformation. However, CBCT suffers from inaccurate Hounsfield Unit (HU) values and lower soft tissue contrast. These issues affect the accuracy of pelvic treatment plans and implementation of the treatment, hence requiring correction. PURPOSE: A novel stacked coarse-to-fine model combining Denoising Diffusion Probabilistic Model (DDPM) and spatial-frequency domain convolution modules is proposed to enhance the imaging quality of CBCT images. METHODS: The enhancement of low-quality CBCT images is divided into two stages. In the coarse stage, the improved DDPM with U-ConvNeXt architecture is used to complete the denoising task of CBCT images. In the fine stage, the deep convolutional network model jointly constructed by fast Fourier and dilated convolution modules is used to further enhance the image quality in local details and global imaging. Finally, the accurate pseudo-CT (pCT) images consistent with the size of the original data are obtained. Two hundred fifty paired CBCT-CT images from cervical and rectal cancer, combined with 200 public dataset cases, were used collectively for training, validation, and testing. RESULTS: To evaluate the anatomical consistency between pCT and real CT, we have used the mean(std) of structure similarity index measure (SSIM), peak signal to noise ratio (PSNR), and normalized cross-correlation (NCC). The numerical results for the above three metrics comparing the pCT synthesized by the proposed model against real CT for cervical cancer cases were 87.14% (2.91%), 34.02 dB (1.35 dB), and 88.01% (1.82%), respectively. For rectal cancer cases, the corresponding results were 86.06% (2.70%), 33.50 dB (1.41 dB), and 87.44% (1.95%). The paired t-test analysis between the proposed model and the comparative models (ResUnet, CycleGAN, DDPM, and DDIM) for these metrics revealed statistically significant differences (p < 0.05). The visual results also showed that the anatomical structures between the real CT and the pCT synthesized by the proposed model were closer. For the dosimetric verification, mean absolute error of dosimetry (MAEdoes) values for the maximum dose (Dmax), the minimum dose (Dmin), and the mean dose (Dmean) in the planning target volume (PTV) were analyzed, with results presented as mean (lower quartile, upper quartile). The experimental results show that the values of the above three dosimetry indexes (Dmin, Dmax, and Dmean) for the pCT images synthesized by the proposed model were 0.90% (0.48%, 1.29%), 0.82% (0.47%, 1.17%), and 0.57% (0.44%, 0.67%). Compared with 10 cases of the original CBCT image by Mann-Whitney test (p < 0.05), it also proved that pCT can significantly improve the accuracy of HU values for the dose calculation. CONCLUSION: The pCT synthesized by the proposed model outperforms the comparative models in numerical accuracy and visualization, promising for ART of pelvic cancers.

Curcumin and nanodelivery systems: New directions for targeted therapy and diagnosis of breast cancer.

As the global incidence of breast cancer continues to surge, the pursuit of novel, low-toxicity, and highly efficacious therapeutic strategies has emerged as a pivotal research focus. Curcumin (CUR), an active constituent of traditional Chinese medicine (TCM) renowned for its antimicrobial, anti-inflammatory, antioxidant, and antitumor properties, exhibits immense potential in breast cancer therapy. Nevertheless, CUR's poor water solubility, chemical instability, and unfavorable pharmacokinetics have impeded its clinical utilization. To address these challenges, nano-delivery systems have been extensively exploited for CUR administration, enhancing its in vivo stability and bioavailability, and facilitating precise targeting of breast cancer lesions. Therefore, we elaborate on CUR's chemical foundations, drug metabolism, and safety profile, and elucidate its potential mechanisms in breast cancer therapy, encompassing inducing apoptosis and autophagy, blocking cell cycle, inhibiting breast cancer metastasis, regulating tumor microenvironment and reversing chemotherapy resistance. The review primarily emphasizes recent advancements in CUR-based nano-delivery systems for the treatment and diagnosis of breast cancer. Liposomes, nanoparticles (encompassing polymer nanoparticles, solid lipid nanoparticles, mesoporous silica particles, metal/metal oxide nanoparticles, graphene nanomaterials, albumin nanoparticles, etc.), nanogels, and nanomicelles can serve as delivery carriers for CUR, exhibiting promising anti-breast cancer effects in both in vivo and in vitro experiments. Furthermore, nano-CUR can be integrated with fluorescence imaging, magnetic resonance imaging, computed tomography imaging, ultrasound, and other techniques to achieve precise localization and diagnosis of breast cancer masses. While this article has summarized the clinical studies of nano-curcumin, it is noteworthy that the research literature on nano-CUR applied to breast cancer diagnosis and the translation of nano-CUR clinical studies in BC patients remain limited. Therefore, future research should intensify exploration in this direction.

Novel insights: crosstalk with non-puerperal mastitis and immunity.

The two primary types of non-puerperal mastitis (NPM) are granulomatous lobular mastitis (GLM) and plasma cell mastitis (PCM). Existing research indicates that immune inflammatory response is considered to be the core of the pathogenesis of GLM and PCM, and both innate and adaptive immune responses play an important role in the pathophysiology of PCM and GLM. However, the regulatory balance between various immune cells in these diseases is still unclear. Consequently, we present a comprehensive summary of the immune-related variables and recent advances in GLM and PCM.

A2HTL: An Automated Hybrid Transformer Based Learning for Predicting Survival of Esophageal Cancer Using CT Images.

Esophageal cancer is a common malignant tumor, precisely predicting survival of esophageal cancer is crucial for personalized treatment. However, current region of interest (ROI) based methodologies not only necessitate prior medical knowledge for tumor delineation, but may also cause the model to be overly sensitive to ROI. To address these challenges, we develop an automated Hybrid Transformer based learning that integrates a Hybrid Transformer size-aware U-Net with a ranked survival prediction network to enable automatic survival prediction for esophageal cancer. Specifically, we first incorporate the Transformer with shifted windowing multi-head self-attention mechanism (SW-MSA) into the base of the UNet encoder to capture the long-range dependency in CT images. Furthermore, to alleviate the imbalance between the ROI and the background in CT images, we devise a size-aware coefficient for the segmentation loss. Finally, we also design a ranked pair sorting loss to more comprehensively capture the ranked information inherent in CT images. We evaluate our proposed method on a dataset comprising 759 samples with esophageal cancer. Experimental results demonstrate the superior performance of our proposed method in survival prediction, even without ROI ground truth.

A 3-year follow-up analysis of renal function in elderly patients with type 2 diabetes mellitus and an estimated glomerular filtration rate <90 mL/min/1.73m2: A retrospective cohort study.

Type 2 diabetes mellitus (T2DM) is a risk factor for patients with impaired renal function. The onset of T2DM-induced diabetic kidney disease (DKD) is frequently sub-clinical, potentially culminating in end-stage renal disease. In the current study the factors influencing DKD in elderly patients diagnosed with T2DM were determined. A retrospective cohort study was conducted involving patients ≥60 years of age with T2DM from June 2019 to December 2022. The Cockcroft-Gault formula was used to estimate the glomerular filtration rate. The clinical information and biochemical indicators of patients with an estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73m2 were collected. Patients were grouped based on a 3-year eGFR decline < 15% and ≥ 15%. The differences between the two groups were compared and the factors influencing the 3-year eGFR decline ≥ 15% were analyzed. A total of 242 patients were included, including 154 in the group with a 3-year eGFR decline < 15% and 88 in the group with a three-year eGFR decline ≥ 15%. Univariate logistic regression analysis showed that smoking cigarettes, and triglycerides (TG) and high-density lipoprotein levels were related to a 3-year eGFR decline ≥ 15% (P = .039, P < .001, and P = .011, respectively). Multivariate logistic regression analysis showed that the TG level was independently related to a 3-year eGFR decline ≥ 15% (P = .004; OR = 2.316). There was a significant linear relationship between the eGFR decline and TG level (P = .002). Patients with a TG concentration > 1.7 mmol/L had a more apparent decrease in the eGFR (P < .05). For elderly patients with T2DM and an eGFR < 90 mL/min/1.73m2, the TG level may be an important risk factor for deteriorating renal function that warrants actively intervention.

Proteomic Identification of Small Extracellular Vesicle Proteins LAMB1 and Histone H4 for Prostate Cancer Diagnosis and Risk Stratification.

Diagnosis and stratification of prostate cancer (PCa) patients using the prostate-specific antigen (PSA) test is challenging. Extracellular vesicles (EVs), as a new star of liquid biopsy, has attracted interest to complement inaccurate PSA screening and invasiveness of tissue biopsy. In this study, a panel of potential small EV (sEV) protein biomarkers is identified from PCa cell lines using label-free LC-MS/MS proteomics. These biomarkers underwent further validation with plasma and urine samples from different PCa stages through parallel reaction monitoring-based targeted proteomics, western blotting, and ELISA. Additionally, a tissue microarray containing cancerous and noncancerous tissues is screened to provide additional evidence of selected sEV proteins associated with cancer origin. Results indicate that sEV protein LAMB1 is highly expressed in human plasma of metastatic PCa patients compared with localised PCa patients and control subjects, while sEV protein Histone H4 is highly expressed in human urine of high-risk PCa patients compared to low-risk PCa patients and control subjects. These two sEV proteins demonstrate higher specificity and sensitivity than the PSA test and show promise for metastatic PCa diagnosis, progression monitoring, and risk stratification.

Clinical-radiomics nomogram for the risk prediction of esophageal fistula in patients with esophageal squamous cell carcinoma treated with intensity-modulated radiation therapy or volumetric-modulated arc therapy.

Background: Esophageal fistula (EF) is a serious adverse event as a result of radiotherapy in patients with esophageal cancer (EC). We aimed to identify the predictive factors and establish a prediction model of EF in patients with esophageal squamous cell carcinoma (ESCC) who underwent intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT). Methods: Patients with ESCC treated with IMRT or VMAT from January 2013 to December 2020 at Xijing Hospital were retrospectively analyzed. Ultimately, 43 patients with EF and 129 patients without EF were included in the analysis and propensity-score matched in a 1:3 ratio. The clinical characteristics and radiomics features were extracted. Univariate and multivariate stepwise logistic regression analyses were used to determine the risk factors associated with EF. Results: The median follow-up time was 24.0 months (range, 1.3-104.9 months), and the median overall survival (OS) was 13.1 months in patients with EF. A total of 1,158 radiomics features were extracted, and eight radiomics features were selected for inclusion into a model for predicting EF, with an area under the receiver operating characteristic curve (AUC) value of 0.794. Multivariate analysis showed that tumor length, tumor volume, T stage, lymphocyte rate (LR), and grade IV esophagus stenosis were related to EF, and the AUC value of clinical model for predicting EF was 0.849. The clinical-radiomics model had the best performance in predicting EF with an AUC value of 0.896. Conclusions: The clinical-radiomics nomogram can predict the risk of EF in ESCC patients and is helpful for the individualized treatment of EC.

[Research progress on structures, activities, and biosynthesis of blazeispirol compounds from Agaricus blazei].

Agaricus blazei is a rare medicinal and edible fungus with a crispy taste and delicious flavor. Both fruiting body and mycelium are rich in polysaccharides, sterols, terpenoids, peptides, lipids, polyphenols, and other active ingredients, which have strong pharmacological activities such as anti-tumor, lipid-lowering, glucose-lowering, immunomodulation, optimization of intestinal flora, and anti-oxidation. Therefore, it is a kind of fungal resource with a great prospect of edible and medicinal development. Among the reported chemical components of A. blazei, blazeispirol is a series of sterol compounds unique to A. blazei, which has a spiral structure and is different from classical steroids. It is an important active ingredient found in the mycelium of A. blazei and has significant hepatoprotective activity. It can be used as a phylogenetic and chemotaxonomic marker of A. blazei strains and is considered an excellent lead compound for drug development. According to the skeleton structure characteristics, the 17 discovered blazeispirol compounds can be divided into two types: blazeispirane and problazeispirane. In order to further explore the resource of blazeispirol compounds of A. blazei, the discovery, isolation, structure, biological activity, and biosynthetic pathways of blazeispirol compounds of A. blazei were systematically reviewed. Besides, the metabolic regulation strategies related to the fermentation synthesis of blazeispirol A by A. blazei were discussed. This review could provide a reference for the efficient synthesis and development of blazeispirol compounds, the research and development of related drugs and functional foods, and the quality improvement of A. blazei and other medicinal and edible fungi resources and derivatives.

A novel GARP humanized mouse model for efficacy assessment of GARP-targeting therapies.

Although breakthroughs have been achieved with immune checkpoint inhibitors (ICI) therapy, some tumors do not respond to those therapies due to primary or acquired resistance. GARP, a type I transmembrane cell surface docking receptor mediating latent transforming growth factor-ß (TGF-ß) and abundantly expressed on regulatory T lymphocytes and platelets, is a potential target to render these tumors responsive to ICI therapy, and enhancing anti-tumor response especially combined with ICI. To facilitate these research efforts, we developed humanized mouse models expressing humanized GARP (hGARP) instead of their mouse counterparts, enabling in vivo assessment of GARP-targeting agents. We created GARP-humanized mice by replacing the mouse Garp gene with its human homolog. Then, comprehensive experiments, including expression analysis, immunophenotyping, functional assessments, and pharmacologic assays, were performed to characterize the mouse model accurately. The Tregs and platelets in the B-hGARP mice (The letter B is the first letter of the company's English name, Biocytogen.) expressed human GARP, without expression of mouse GARP. Similar T, B, NK, DCs, monocytes and macrophages frequencies were identified in the spleen and blood of B-hGARP and WT mice, indicating that the humanization of GARP did not change the distribution of immune cell in these compartments. When combined with anti-PD-1, monoclonal antibodies (mAbs) against GARP/TGF-ß1 complexes demonstrated enhanced in vivo anti-tumor activity compared to monotherapy with either agent. The novel hGARP model serves as a valuable tool for evaluating human GARP-targeting antibodies in immuno-oncology, which may enable preclinical studies to assess and validate new therapeutics targeting GARP. Furthermore, intercrosses of this model with ICI humanized models could facilitate the evaluation of combination therapies.

Pseudo-medical image-guided technology based on 'CBCT-only' mode in esophageal cancer radiotherapy.

Purpose To minimize the various errors introduced by image-guided radiotherapy (IGRT) in the application of esophageal cancer treatment, this study proposes a novel technique based on the 'CBCT-only' mode of pseudo-medical image guidance. Methods The framework of this technology consists of two pseudo-medical image synthesis models in the CBCT→CT and the CT→PET direction. The former utilizes a dual-domain parallel deep learning model called AWM-PNet, which incorporates attention waning mechanisms. This model effectively suppresses artifacts in CBCT images in both the sinogram and spatial domains while efficiently capturing important image features and contextual information. The latter leverages tumor location and shape information provided by clinical experts. It introduces a PRAM-GAN model based on a prior region aware mechanism to establish a non-linear mapping relationship between CT and PET image domains.  As a result, it enables the generation of pseudo-PET images that meet the clinical requirements for radiotherapy. Results The NRMSE and multi-scale SSIM (MS-SSIM) were utilized to evaluate the test set, and the results were presented as median values with lower quartile and upper quartile ranges. For the AWM-PNet model, the NRMSE and MS-SSIM values were 0.0218 (0.0143, 0.0255) and 0.9325 (0.9141, 0.9410), respectively. The PRAM-GAN model produced NRMSE and MS-SSIM values of 0.0404 (0.0356, 0.0476) and 0.9154 (0.8971, 0.9294), respectively. Statistical analysis revealed significant differences (p < 0.05) between these models and others. The numerical results of dose metrics, including D98 %, Dmean, and D2 %, validated the accuracy of HU values in the pseudo-CT images synthesized by the AWM-PNet. Furthermore, the Dice coefficient results confirmed statistically significant differences (p < 0.05) in GTV delineation between the pseudo-PET images synthesized using the PRAM-GAN model and other compared methods. Conclusion The AWM-PNet and PRAM-GAN models have the capability to generate accurate pseudo-CT and pseudo-PET images, respectively. The pseudo-image-guided technique based on the 'CBCT-only' mode shows promising prospects for application in esophageal cancer radiotherapy.

Long Non-coding RNA COX10-AS1 Promotes Glioma Progression by Competitively Binding miR-1-3p to Regulate ORC6 Expression.

Glioma is one of the most common and difficult to cure malignant primary tumors of the central nervous system. Long non-coding RNA (lncRNA) has been reported to play important functions in biological processes of many tumors, including glioma. In our study, we aimed to reveal the role and molecular mechanisms of lncRNA COX10-AS1 in regulating the progression of glioma. First of all, we showed that lncRNA COX10-AS1 was significantly increased in glioma tissues and cell lines, and high-expressed COX10-AS1 was associated with a poor prognosis in glioma patients. Moreover, through performing the functional experiments, including CCK-8, colony formation and Transwell assays, we confirmed that COX10-AS1 ablation curbed cell proliferation, migration and invasion in glioblastoma (GBM) cells. In addition, we uncovered that there existed a regulatory relationship that COX10-AS1 upregulated OCR6 by sponging miR-1-3p in GBM cells, and the following rescue assays demonstrated that both miR-1-3p downregulation and origin recognition complex subunit 6 (ORC6) overexpression rescued cell viability, migration and invasion in the COX10-AS1-deficient GBM cells. Consistently, we also verified that COX10-AS1 promoted tumorigenesis of the GBM cells in vivo through modulating the miR-1-3p/ORC6 axis. On the whole, our findings indicated a novel ceRNA pattern in which COX10-AS1 elevated OCR6 expression via sponging miR-1-3p, therefore boosting tumorigenesis in glioma, and we firstly discussed the underlying mechanisms by which the COX10-AS1/miR-1-3p/ORC6 axis affected the progression of glioma.

Prostate cancer-derived small extracellular vesicle proteins: the hope in diagnosis, prognosis, and therapeutics.

Current diagnostic tools for prostate cancer (PCa) diagnosis and risk stratification are insufficient. The hidden onset and poor efficacy of traditional therapies against metastatic PCa make this disease a heavy burden in global men's health. Prostate cancer-derived extracellular vesicles (PCDEVs) have garnered attention in recent years due to their important role in communications in tumor microenvironment. Recent advancements have demonstrated PCDEVs proteins play an important role in PCa invasion, progression, metastasis, therapeutic resistance, and immune escape. In this review, we briefly discuss the applications of sEV proteins in PCa diagnosis and prognosis in liquid biopsy, focus on the roles of the PCa-derived small EVs (sEVs) proteins in tumor microenvironment associated with cancer progression, and explore the therapeutic potential of sEV proteins applied for future metastatic PCa therapy.

Albendazole induces an anti-tumor effect and potentiates PD-L1 blockade immunotherapy.

BACKGROUND: Previously, albendazole (ABZ) has been reported as an anti-parasitic drug rather than anti-tumor drug. Our study aim to investigate whether ABZ also has a potential anti-tumor effect by shaping the tumor immune microenvironment and interrogate whether ABZ could synergize with the PD-L1 blockade. METHODS: C57BL/6 mice (C57) were intravenously injected with B16F10-luciferase (B16-luc) cells to establish a lung metastatic melanoma model and subcutaneously inoculated with B16-luc cells to establish a subcutaneous tumor model. The tumor volume and tumor metastasis loci of the mice were measured by a vernier caliper and in vivo imaging. RNA sequencing was performed to analyze the different genes and pathways of immune cells in the tumors. Flow cytometry and immunofluorescence were used to analyze the different subsets of tumor-infiltrating immune cells. RESULTS: The results suggested that ABZ significantly inhibited lung melanoma metastasis with decreased fluorescence intensity and nodule score and mediated the regression of subcutaneous melanoma in mice with decreased tumor volume. Moreover, RNA sequencing results showed that ABZ regulated the gene expression levels and pathways of immune cells in the tumor microenvironment (TME). Meanwhile, flow cytometry and immunofluorescence showed that the number and percentage of CD8+ T cells, CD4+ T cells, and TH1 cells were enhanced in tumors after ABZ treatment. Furthermore, the combination of ABZ and anti-PD-L1 treatment significantly potentiated anti-tumor efficacy in both lung metastasis and subcutaneous melanoma models and mediated an increase in the percentage of CD8+ T cells, CD4+ T cells, and TH1 cells as compared to the control group. CONCLUSION: ABZ inhibits melanoma growth and metastasis. Moreover, ABZ synergized with PD-L1 blockade mediates tumor regression.

The gap before real clinical application of imaging-based machine-learning and radiomic models for chemoradiation outcome prediction in esophageal cancer: a systematic review and meta-analysis.

BACKGROUND: Due to tumoral heterogeneity and the lack of robust biomarkers, the prediction of chemoradiotherapy response and prognosis in patients with esophageal cancer (EC) is challenging. The goal of this study was to assess the study quality and clinical value of machine learning and radiomic-based quantitative imaging studies for predicting the outcomes of EC patients after chemoradiotherapy. MATERIALS AND METHODS: PubMed, Embase, and Cochrane were searched for eligible articles. The methodological quality and risk of bias were evaluated using the Radiomics Quality Score (RQS), Image Biomarkers Standardization Initiative (IBSI) Guideline, and Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement, as well as the modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. A meta-analysis of the evidence focusing on predicting chemoradiotherapy response and outcome in EC patients was implemented. RESULTS: Forty-six studies were eligible for qualitative synthesis. The mean RQS score was 9.07, with an adherence rate of 42.52%. The adherence rates of the TRIPOD and IBSI were 61.70 and 43.17%, respectively. Ultimately, 24 studies were included in the meta-analysis, of which 16 studies had a pooled sensitivity, specificity, and area under the curve (AUC) of 0.83 (0.76-0.89), 0.83 (0.79-0.86), and 0.84 (0.81-0.87) in neoadjuvant chemoradiotherapy datasets, as well as 0.84 (0.75-0.93), 0.89 (0.83-0.93), and 0.93 (0.90-0.95) in definitive chemoradiotherapy datasets, respectively. Moreover, radiomics could distinguish patients from the low-risk and high-risk groups with different disease-free survival (DFS) (pooled hazard ratio: 3.43, 95% CI 2.39-4.92) and overall survival (pooled hazard ratio: 2.49, 95% CI 1.91-3.25). The results of subgroup and regression analyses showed that some of the heterogeneity was explained by the combination with clinical factors, sample size, and usage of the deep learning (DL) signature. CONCLUSIONS: Noninvasive radiomics offers promising potential for optimizing treatment decision-making in EC patients. However, it is necessary to make scientific advancements in EC radiomics regarding reproducibility, clinical usefulness analysis, and open science categories. Improved model reporting of study objectives, blind assessment, and image processing steps are required to help promote real clinical applications of radiomics in EC research.

Plasma-derived exosomal immunoglobulins IGHV4-4 and IGLV1-40 as new non-small cell lung cancer biomarkers.

Exosomal proteins represent valuable research directions in the liquid biopsy of lung cancer (LC). Immunoglobulin subtypes, immunoglobulin molecules with different domains in variable regions, are products of B cell responses to different tumor antigens and are associated with tumor incidence and development. The plasma of patients with LC should theoretically contain a large number of B cell-derived exosomes that specifically recognize tumor antigens. This paper intended to assess the value of the proteomic screening of plasma exosomal immunoglobulin subtypes for diagnosing non-small cell LC (NSCLC). The plasma exosomes of NSCLC patients and healthy control participants (HCs) were isolated using ultracentrifugation. Label-free proteomics was employed to assess the differentially expressed proteins (DEPs), while the biological characteristics of the DEPs were analyzed using GO enrichment. The immunoglobulin content in the top two fold change (FC) values of the DEPs and the immunoglobulin with the lowest P-value were verified using an enzyme-linked immunosorbent assay (ELISA). The differentially expressed immunoglobulin subtypes verified via ELISA were selected to statistically analyze the receiver operating characteristic curve (ROC), after which the diagnostic values of the NSCLC immunoglobulin subtypes were determined via the ROC area under the curve (AUC). The plasma exosomes of the NSCLC patients contained 38 DEPs, of which 23 were immunoglobulin subtypes, accounting for 60.53%. The DEPs were mainly related to the binding between immune complexes and antigens. The ELISA results showed significant differences between the immunoglobulin heavy variable 4-4 (IGHV4-4) and immunoglobulin lambda variable 1-40 (IGLV1-40) in the LC patients and HCs. Compared with the HCs, the AUCs of IGHV4-4, IGLV1-40, and a combination of the two in diagnosing NSCLC were 0.83, 0.88, and 0.93, respectively, while the AUCs for non-metastatic cancer were 0.80, 0.85, and 0.89. Moreover, their diagnostic values for metastatic cancer compared to non-metastatic cancer displayed AUCs of 0.71, 0.74, and 0.83, respectively. When IGHV4-4 and IGLV1-40 were combined with serum CEA to diagnose LC, the AUC value increased, exhibiting values of 0.95, 0.89, and 0.91 for the NSCLC, non-metastatic, and metastatic groups, respectively. Plasma-derived exosomal immunoglobulins containing IGHV4-4 and IGLV 1-40 domains can provide new biomarkers for diagnosing NSCLC and metastatic patients.

Molecular genomic landscape of pediatric solid tumors in Chinese patients: implications for clinical significance.

PURPOSE: Pediatric solid tumors are significantly different from adult tumors. Studies have revealed genomic aberrations in pediatric solid tumors, but these analyses were based on Western populations. Currently, it is not known to what extent the existing genomic findings represent differences in ethnic backgrounds. EXPERIMENTAL: DESIGN: We retrospectively analyzed the basic clinical characteristics of the patients, including age, cancer type, and sex distribution, and further analyzed the somatic and germline mutations of cancer-related genes in a Chinese pediatric cohort. In addition, we investigated the clinical significance of genomic mutations on therapeutic, prognostic, diagnostic, and preventive actions. RESULTS: Our study enrolled 318 pediatric patients, including 234 patients with CNS tumors and 84 patients with non-CNS tumors. Somatic mutation analysis showed that there were significant differences in mutation types between CNS tumors and non-CNS tumors. P/LP germline variants were identified in 8.49% of patients. In total, 42.8% patients prompted diagnostic, 37.7% patients prompted prognostic, 58.2% patients prompted therapeutic, and 8.5% patients prompted tumor-predisposing and preventive, and we found that genomic findings might improve clinical management. CONCLUSIONS: Our study is the first large-scale study to analyze the landscape of genetic mutations in pediatric patients with solid tumors in China. Genomic findings in CNS and non-CNS solid pediatric tumors provide evidence for the clinical classification and individualized treatment of pediatric tumors, and they will facilitate improvement of clinical management. Data presented in this study should serve as a reference to guide the future design of clinical trials.

Comparison of Secular Trends in Peptic Ulcer Diseases Mortality in China, Brazil and India during 1990-2019: An Age-Period-Cohort Analysis.

BACKGROUND: Peptic ulcer disease (PUD) is a common disease worldwide, especially in developing countries. China, Brazil, and India are among the world's fastest-growing emerging economies. This study aimed to assess long-term trends in PUD mortality and explore the effects of age, period, and cohort in China, Brazil, and India. METHODS: We collected data from the 2019 Global Burden of Disease Study and used an age-period-cohort (APC) model to estimate the effects of age, period, and cohort. We also obtained net drift, local drift, longitudinal age curve, and period/cohort rate ratios using the APC model. RESULTS: Between 1990 and 2019, the age-standardized mortality rates (ASMRs) of PUD and PUD attributable to smoking showed a downward trend in all countries and both sexes. The local drift values for both sexes of all ages were below zero, and there were obvious sex differences in net drifts between China and India. India had a more pronounced upward trend in the age effects than other countries. The period and cohort effects had a similar declining trend in all countries and both sexes. CONCLUSIONS: China, Brazil, and India had an inspiring decrease in the ASMRs of PUD and PUD attributable to smoking and to period and cohort effects during 1990-2019. The decreasing rates of Helicobacter pylori infection and the implementation of tobacco-restricting policies may have contributed to this decrease.

Comparison of four nutritional screening tools in perioperative elderly patients: Taking orthopedic and neurosurgical patients as examples.

Background and aims: Malnutrition is widely present in elderly surgical patients and is highly correlated with prognosis after surgery. However, studies comparing the effectiveness of comprehensive nutritional screening tools in geriatric surgical patients have not yet been published. The nutritional risk among elderly orthopedic and neurosurgical patients and their associated clinical indicators and outcomes was assessed using four screening tools. The aim of this study was to explore suitable tools for screening the nutritional status and identify their potential to act as prognostic indicators. Methods: The Nutritional Risk Score 2002 (NRS2002), Mini Nutritional Assessment - Short Form (MNA-SF), Geriatric Nutritional Risk Index (GNRI), and Prognostic Nutritional Index (PNI) were all performed within two days of admission and before surgery. The relationships between nutritional risk classifications and conventional nutritional markers, complications and length of hospital stay (LOS) were evaluated. Results: In this study, a total of 167 orthopedic patients and 103 neurosurgical patients were evaluated. In neurosurgical patients, the rates of malnutrition or patients at risk of malnutrition according to the MNA-SF, GNRI, NRS2002 and PNI were 26.4, 24.6, 8.4, and 12.6%, respectively. According to the NRS2002 and PNI, the rates of old neurosurgical patients who were malnourished or at risk of malnutrition were 14.6 and 3.9%, respectively, which were lower than the results assessed by the MNA-SF (24.3%) and GNRI (15.5%). Multiple regression analysis revealed a significant relationship between the PNI (malnourished vs.well-nourished, OR = 5.39, 95% CI:1.11-26.18, P = 0.037), GNRI (at risk vs.no risk, OR = 3.96, 95% CI: 1.01-15.45, P = 0.048) and the complications in orthopedic patients. Only GNRI was significantly related to LOS > 7 days (at risk vs.no risk, OR = 4.01, 95% CI: 1.64-9.80, P = 0.002). For neurosurgical patients, an association between GNRI and LOS > 8 days was discovered (at risk vs.no risk, OR = 3.35, 95% CI: 1.03-10.86, P = 0.002). Conclusion: Among the four nutritional risk screening tools, the GNRI exhibited better predictive value for short-term outcomes in elderly perioperative orthopedic and neurosurgical patients, thereby suggesting that it might be a more suitable tool for nutritional risk screening. Additional studies are required to determine the applicability of GNRI in other surgical fields.

m6A Methyltransferase, WTAP, Promotes Cancer Progression in Laryngeal Squamous Cell Carcinoma by Regulating PLAU Stability.

OBJECTIVE: Laryngeal squamous cell carcinoma (LSCC) is a malignancy originating from laryngeal squamous cell lesions. Wilm's tumor 1-associated protein (WTAP)-mediated N6-methyladenosine (m6A) modification has been verified to stimulate the progression of numerous cancers, except for LSCC. This study was aimed at exploring the role of WTAP and its mechanism of action in LSCC. METHODS: The expression of WTAP and plasminogen activator urokinase (PLAU) mRNAs in LSCC tissues and cells was quantified using qRT-PCR. Western blotting was performed to estimate PLAU levels in LSCC cells. The relationship between WTAP and PLAU was ascertained using luciferase reporter and methylated-RNA immunoprecipitation (Me-RIP) assays. Functionally, the interaction of WTAP with PLAU in LSCC cells was investigated using CCK-8, EdU, and Transwell assays. RESULTS: The expression of WTAP and PLAU was increased in LSCC, and was positively correlated. WTAP regulated PLAU stability in an m6A-dependent manner. WTAP deficiency suppressed the migration, invasion, and proliferation of LSCC cells. Overexpression of PLAU rescued the phenotype induced by WTAP knockdown in vitro. CONCLUSIONS: These results indicate that WTAP mediates the m6A modification of PLAU to accelerate the growth, migration, and invasion of cells in LSCC. To our knowledge, this is the first report to clarify the functions of WTAP in LSCC and the underlying mechanisms in detail. Based on these findings, we suggest that WTAP may serve as a therapeutic target for LSCC.