RBM47 is a novel immunotherapeutic target and prognostic biomarker in gliomas.

The role of RBM47, an RNA-binding protein, in shaping the immune landscape of gliomas and tumor immune responses is yet to be fully studied. Therefore, a comprehensive investigation into the immunomodulatory roles of RBM47 in gliomas was conducted, leveraging gene expression data from multi-omic datasets. The prognosis of patients with gliomas considering RBM47 was elucidated using bioinformatics methods and clinical data, with results validated using immunohistochemistry and immunofluorescence analyses.

Multiomics Approach Identifies Key Proteins and Regulatory Pathways in Colorectal Cancer.

The prevalence rate of colorectal cancer (CRC) has dramatically increased in recent decades. However, robust CRC biomarkers with therapeutic value for early diagnosis are still lacking. To comprehensively reveal the molecular characteristics of CRC development, we employed a multiomics strategy to investigate eight different types of CRC samples.

Microenvironmental G protein-coupled estrogen receptor-mediated glutamine metabolic coupling between cancer-associated fibroblasts and triple-negative breast cancer cells governs tumour progression.

Background: Triple-negative breast cancer (TNBC) is a particularly aggressive type of breast cancer, known for its lack of effective treatments and unfavorable prognosis. The G protein-coupled estrogen receptor (GPER), a novel estrogen receptor, is linked to increased malignancy in various cancers. However, its involvement in the metabolic regulation of cancer-associated fibroblasts (CAFs), a key component in the tumour microenvironment, remains largely unexplored.

The impacts of noise and air pollution on breast cancer risk in European and East Asian populations: Insights from genetic evidence.

Objectives: Previous studies have reported associations of noise and air pollution with breast cancer (BC) risk, but the causality remains unclear. This study aimed to explore the effects of noise and air pollution on BC from a genetic perspective.

Study Design: Genetic association study.

Robust nCuO modulated by defect engineering enhanced photoelectrochemical biosensor for the detection of miRNA-21.

Traditional p-type CuO (pCuO), valued for its tunable band gap and p-type conductivity, has been widely used in photoelectrochemical biosensors. However, its weak conductivity leads to unsatisfied photoelectrochemical signals and limits its use in in situ vulcanization reactions. We synthesized n-type CuO (nCuO) with abundant oxygen vacancies through a simple chemical reduction for the first time, which was applied as efficient photoactive material.

Development of a neoadjuvant chemotherapy efficacy prediction model for nasopharyngeal carcinoma integrating magnetic resonance radiomics and pathomics: a multi-center retrospective study.

Objective: This study aimed to develop and validate a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NACT) in nasopharyngeal carcinoma (NPC) by integrating radiomics and pathomics features using a particle swarm optimization-supported support vector machine (PSO-SVM).

Methods: A retrospective multi-center study was conducted, which included 389 NPC patients who received NACT from three institutions. Radiomics features were extracted from magnetic resonance imaging scans, while pathomics features were derived from histopathological images.

MLN4924 Suppresses head and neck squamous cell carcinoma progression by inactivating the mTOR signaling pathway via the NEDD8/CUL4/TSC2 axis.

Head and neck squamous cell carcinoma (HNSCC) is an aggressive cancer with a five-year survival rate below 50 %. Standard treatments for HNSCC include surgery, radiotherapy, chemotherapy, and targeted therapies, but they still have significant limitations. Neddylation, a post-translational modification involving the attachment of NEDD8 (neural precursor cells expressed developmentally down-regulated 8) to proteins, is frequently dysregulated in HNSCC, thereby promoting tumor growth.

Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases.

The objective of this study was to explore the potential of machine-learning techniques in the automatic identification and classification of brain metastases from a radiomic perspective, aiming to improve the accuracy of tumor volume assessment for radiotherapy. By using various machine-learning algorithms, including random forest, support vector machine, gradient boosting machine, XGBoost, decision tree, artificial neural network, k-nearest neighbors, LightGBM, and CatBoost algorithms, a stacking ensemble model was developed to classify gross tumor volume (GTV), brainstem, and normal brain tissue based on radiomic features. Multiple evaluation metrics, including the specificity, sensitivity, negative predictive value, positive predictive value, accuracy, Matthews correlation coefficient, and the Youden index, were used to assess the model's performance.

Bulk- and single cell-RNA sequencing reveal KIF20A as a key driver of hepatocellular carcinoma progression and immune evasion.

Introduction: Kinesin family member 20A (KIF20A) is essential for cell proliferation and is implicated in promoting tumor progression, but its role in hepatocellular carcinoma (HCC) remains poorly studied.

Methods: Through the analysis of bulk RNA-sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq) data, the expression of KIF20A and its relationship with diagnosis, prognosis, and the immune microenvironment were examined. The association between KIF20A and the malignant progression and metastasis of HCC was confirmed through and experiments.

Early and noninvasive prediction of response to neoadjuvant therapy for breast cancer via longitudinal ultrasound and MR deep learning: A multicentre study.

Rationale And Objectives: The early prediction of response to neoadjuvant chemotherapy (NAC) will aid in the development of personalized treatments for patients with breast cancer. This study investigated the value of longitudinal multimodal deep learning (DL) based on breast MR and ultrasound (US) in predicting pathological complete response (pCR) after NAC.

Materials And Methods: We retrospectively reviewed the pre-NAC and post-2nd-NAC MR and/or US images of 448 patients enrolled from three centers and extracted DL features from the largest section of the breast tumour using ResNet50.

Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.

This study aimed to develop an automated classification framework for distinguishing between cervical cancer tumor and normal uterine tissue, leveraging CT images for radiomics feature extraction. We retrospectively analyzed CT images from 117 cervical cancer patients. To distinguish between cancerous and healthy tissue, we segmented gross tumor volume and normal uterine tissue as distinct regions of interest (ROIs) using manual segmentation techniques.

Improvement of plan quality in whole-breast radiation following BCS using feasibility DVH by less-experienced planners.

Variability in plan quality of radiotherapy is commonly attributed to the planner's skill rather than technological parameters. While experienced planners can set reasonable parameters before optimization, less experienced planners face challenges. This study aimed to assess the quality of volumetric-modulated arc therapy (VMAT) in patients with left-sided breast cancer following breast-conserving surgery.

Integrating anoikis and ErbB signaling insights with machine learning and single-cell analysis for predicting prognosis and immune-targeted therapy outcomes in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but their relevance in HCC remains insufficiently explored.

Methods: This study evaluates the prognostic significance of anoikis and ErbB signaling pathways in HCC by utilizing data from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), three additional independent validation cohorts, and an in-house cohort.

Deciphering colorectal cancer radioresistance and immune microrenvironment: unraveling the role of EIF5A through single-cell RNA sequencing and machine learning.

Background: Radiotherapy (RT) is a critical component of treatment for locally advanced rectal cancer (LARC), though patient response varies significantly. The variability in treatment outcomes is partly due to the resistance conferred by cancer stem cells (CSCs) and tumor immune microenvironment (TiME). This study investigates the role of EIF5A in radiotherapy response and its impact on the CSCs and TiME.

PILRB potentiates the PI3K/AKT signaling pathway and reprograms cholesterol metabolism to drive gastric tumorigenesis and metastasis.

Paired immunoglobin-like type 2 receptor beta (PILRB) mainly plays a crucial role in regulating innate immunity, but whether PILRB is involved in cancer is poorly understood. Here, we report that PILRB potentiates the PI3K/AKT pathway to drive gastric tumorigenesis by binding and stabilizing IRS4, which could hyperactivate the PI3K/AKT pathway. Firstly, the levels of PILRB are upregulated in human gastric cancer (GC) specimens and associated with poor prognosis in patients with GC.

Primary intestinal diffuse large B-cell lymphoma: novel insights and clinical perception.

Background: Extranodal Non-Hodgkin lymphoma (NHL) is more prevalent in the gastrointestinal (GI) tract than in other sites. This study aimed to explore the clinical features and prognostic factors of primary intestinal diffuse large B-cell lymphoma (PI-DLBCL), in order to provide new references for basic research and clinical diagnosis and treatment of the rare extranodal malignant lymphoma.

Methods: The clinical data of 88 patients with PI-DLBCL admitted to Fujian Medical University Union Hospital from June 2011 to June 2022 were retrospectively studied, the clinical and pathological features, diagnosis and treatment process and prognosis of PI-DLBCL were analyzed, and univariate and multivariate analysis of prognostic factors was carried out.

Expression and clinical significance of KDM5A, KDM5B, and FOXO1 in endometrial cancer.

There is growing evidence that the KDM5 family of histone demethylases plays a causal role in human cancer. However, few studies have been reported on the KDM5 family in endometrial carcinoma (EC). Moreover, it was found that there was some correlation between the KDM5 family and FOXO1 in EC.

Immune-targeted therapy with transarterial chemo(embolization) for unresectable HCC: a systematic review and meta-analysis.

Background: Transarterial chemo(embolization) is preferred for treating unresectable hepatocellular carcinoma (uHCC); however, because of emerging immune-targeted therapies, its efficacy is at stake. This systematic review pioneers to evaluate the clinical efficacy and safety of transarterial chemo(embolization) combined with immune-targeted therapy for uHCC patients.

Methods: PubMed, Embase, and Cochrane Library were searched for studies comparing immune-targeted therapy with or without transarterial chemo(embolization) until 31 May 2024.

Overexpression of ESYT3 improves radioimmune responses through activating cGAS-STING pathway in lung adenocarcinoma.

Background: Radiotherapy can modulate systemic antitumor immunity, while immune status in the tumor microenvironment also influences the efficacy of radiotherapy, but relevant molecular mechanisms are poorly understood in lung adenocarcinoma (LUAD).

Methods: In this study, we innovatively proposed a radiotherapy response classification for LUAD, and discovered ESYT3 served as a tumor suppressor and radioimmune response sensitizer. ESYT3 expression was measured both in radioresistant and radiosensitive LUAD tissues and cells.

Improved automatic segmentation of brain metastasis gross tumor volume in computed tomography images for radiotherapy: a position attention module for U-Net architecture.

Background: Brain metastases present significant challenges in radiotherapy due to the need for precise tumor delineation. Traditional methods often lack the efficiency and accuracy required for optimal treatment planning. This paper proposes an improved U-Net model that uses a position attention module (PAM) for automated segmentation of gross tumor volumes (GTVs) in computed tomography (CT) simulation images of patients with brain metastases to improve the efficiency and accuracy of radiotherapy planning and segmentation.

Advances in immune regulation of the G protein-coupled estrogen receptor.

Estrogen and related receptors have been shown to have a significant impact on human development, reproduction, metabolism and immune regulation and to play a critical role in tumor development and treatment. Traditionally, the nuclear estrogen receptors (nERs) ERα and ERβ have been thought to be involved in mediating the estrogenic effects. However, our group and others have previously demonstrated that the G protein-coupled estrogen receptor (GPER) is the third independent ER, and estrogen signaling mediated by GPER is known to play an important role in normal physiology and a variety of abnormal diseases.

Quantify the Effect of Air Gap Errors on Skin Dose for Breast Cancer Radiotherapy.

Determining the impact of air gap errors on the skin dose in postoperative breast cancer radiotherapy under dynamic intensity-modulated radiation therapy (IMRT) techniques. This was a retrospective study that involved 55 patients who underwent postoperative radiotherapy following modified radical mastectomy. All plans employed tangential IMRT, with a prescription dose of 50 Gy, and bolus added solely to the chest wall.

Dosimetric Effect of Target Position Accuracy on Single-Isocenter Multiple Liver Metastases SBRT.

To evaluate the dosimetric effects of intrafraction baseline shifts combined with rotational errors on Four-dimensional computed tomography-guided stereotactic body radiotherapy for multiple liver metastases (MLMs). A total of 10 patients with MLM (2 or 3 lesions) were selected for this retrospective study. Baseline shift errors of 0.