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Brain metastases challenge cancer treatments with poor prognoses, despite ongoing advancements. Immunotherapy effectively alleviates advanced cancer, exhibiting immense potential to revolutionize brain metastasis management. To identify research priorities that optimize immunotherapies for brain metastases, 2164 related publications were analyzed. Scientometric visualization via R software, VOSviewer, and CiteSpace showed the interrelationships among literature, institutions, authors, and topic areas of focus. The publication rate and citations have grown exponentially over the past decade, with the US, China, and Germany as the major contributors. The University of Texas MD Anderson Cancer Center ranked highest in publications, while Memorial Sloan Kettering Cancer Center was most cited. Clusters of keywords revealed six hotspots: 'Immunology', 'Check Point Inhibitors', 'Lung Cancer', 'Immunotherapy', 'Melanoma', 'Breast Cancer', and 'Microenvironment'. Melanoma, the most studied primary tumor with brain metastases offers promising immunotherapy advancements with generalizability and adaptability to other cancers. Our results outline the holistic overview of immunotherapy research for brain metastases, which pinpoints the forefront in the field, and directs researchers toward critical inquiries for enhanced mechanistic insight and improved clinical outcomes. Moreover, governmental and funding agencies will benefit from assigning financial resources to entities and regions with the greatest potential for combating brain metastases through immunotherapy. [ABSTRACT FROM AUTHOR]

JS-K is a nitric oxide (NO)-releasing prodrug of the O2-arylated diazeniumdiolate group that shows pronounced cytotoxicity and antitumor properties in numerous cancer models, including in vitro as well as in vivo. Reactive oxygen species (ROS) induce carcinogenesis by altering the redox status, causing increment in vulnerability to oxidative stress.

Distant metastasis remains the primary cause of morbidity in patients with breast cancer. Hence, the development of more efficacious strategies and the exploration of potential targets for patients with metastatic breast cancer are urgently needed. The data of six patients with breast cancer brain metastases (BCBrM) from two centres were collected, and a comprehensive landscape of the entire tumour ecosystem was generated through the utilisation of single‐cell RNA sequencing. We utilised the Monocle2 and CellChat algorithms to investigate the interrelationships among each subcluster. In addition, multiple signatures were collected to evaluate key components of the subclusters through multi‐omics methodologies. Finally, we elucidated common expression programs of malignant cells, and experiments were conducted in vitro and in vivo to determine the functions of interleukin enhancer‐binding factor 2 (ILF2), which is a key gene in the metastasis module, in BCBrM progression. We found that subclusters in each major cell type exhibited diverse characteristics. Besides, our study indicated that ILF2 was specifically associated with BCBrM, and experimental validations further demonstrated that ILF2 deficiency hindered BCBrM progression. Our study offers novel perspectives on the heterogeneity of BCBrM and suggests that ILF2 could serve as a promising biomarker or therapeutic target for BCBrM. [ABSTRACT FROM AUTHOR]

The etiology of epilepsy is ascribed to the synchronized aberrant neuronal activity within the brain. Circular RNAs (circRNAs), a class of non‐coding RNAs characterized by their circular structures and covalent linkage, exert a substantial influence on this phenomenon. CircRNAs possess stereotyped replication, transience, repetitiveness, and paroxysm. Additionally, MicroRNA (miRNA) plays a crucial role in the regulation of diverse pathological processes, including epilepsy. CircRNA is of particular significance due to its ability to function as a competing endogenous RNA, thereby sequestering or inhibiting miRNA activity through binding to target mRNA. Our review primarily concentrates on elucidating the pathological and functional roles, as well as the underlying mechanisms, of circRNA–miRNA–mRNA networks in epilepsy. Additionally, it explores the potential utility of these networks for early detection and therapeutic intervention. [ABSTRACT FROM AUTHOR]

Background: Bone metastasis is a common event in lung cancer progression. Early diagnosis of lung malignant tumor with bone metastasis is crucial for selecting effective treatment strategies. However, 14.3% of patients are still difficult to diagnose after SPECT/CT examination. Purpose: Machine learning analysis of [99mTc]‐methylene diphosphate (99mTc‐MDP) SPECT/CT scans to distinguish bone metastases from benign bone lesions in patients with lung cancer. Methods: One hundred forty‐one patients (69 with bone metastases and 72 with benign bone lesions) were randomly assigned to the training group or testing group in a 7:3 ratio. Lesions were manually delineated using ITK‐SNAP, and 944 radiomics features were extracted from SPECT and CT images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the radiomics features in the training set, and the single/bimodal radiomics models were established based on support vector machine (SVM). To further optimize the model, the best bimodal radiomics features were combined with clinical features to establish an integrated Radiomics‐clinical model. The diagnostic performance of models was evaluated using receiver operating characteristic (ROC) curve and confusion matrix, and performance differences between models were evaluated using the Delong test. Results: The optimal radiomics model comprised of structural modality (CT) and metabolic modality (SPECT), with an area under curve (AUC) of 0.919 and 0.907 for the training and testing set, respectively. The integrated model, which combined SPECT, CT, and two clinical features, exhibited satisfactory differentiation in the training and testing set, with AUC of 0.939 and 0.925, respectively. Conclusions: The machine learning can effectively differentiate between bone metastases and benign bone lesions. The Radiomics‐clinical integrated model demonstrated the best performance. [ABSTRACT FROM AUTHOR]

Gut microbiota is essential for maintaining local and systemic immune homeostasis in the presence of bacterial challenges. It has been demonstrated that microbiota play contrasting roles in cancer development as well as anticancer immunity. Cancer immunotherapy, a novel anticancer therapy that relies on the stimulation of host immunity, has suffered from a low responding rate and incidence of severe immune‐related adverse events (irAEs). Previous studies have demonstrated that the diversity and composition of gut microbiota were associated with the heterogeneity of therapeutic effects. Therefore, alteration in microbiota taxa can lead to improved clinical outcomes in immunotherapy. In this review, we determine whether microbiota composition or microbiota‐derived metabolites are linked to responses to immunotherapy and irAEs. Moreover, we discuss various approaches to improve immunotherapy efficacy or reduce toxicities by modulating microbiota composition. Highlights: Gut microbiota has been acknowledged as key regulators in host‐mediated anticancer immune response especially during immunotherapy, and antibiotics‐induced dysbiosis often leads to resistance to immunotherapy and poor clinical outcomes.Although the mechanisms underlying gut microbiota‐mediated potentiating efficacy while ameliorating side effects of immunotherapy differs across bacteria genus and immunotherapy types, it's generally via enhancing anticancer immunity and remodulating the tumor microenvironment.We reviewed the commensal bacteria profiles associated with responders to immunotherapy in various cancer types, characterized by a high diversity with abundance of specific species, which may help predict patients; sensitivity to immunotherapy before treatment.Since the causal relationship between individual gut microbiota and response to immunotherapy, we propose gut microbiota act as the future therapeutic target and adjuvant in personalized anticancer regimen, and reviewed the current dilemma and potential strategies to manipulate gut microbiota towards "beneficial bacteria." [ABSTRACT FROM AUTHOR]

Background: To establish a radiomics-clinical model based on 99mTc-MDP SPECT/CT for distinguishing between bone metastasis and benign bone disease in tumor patients. Methods: We retrospectively analyzed 256 patients (122 with bone metastasis and 134 with benign bone disease) and randomized them in the ratio of 6:2:2 into training, test and validation sets. All patients underwent 99mTc-labeled methylene diphosphonate (99mTc-MDP) SPECT/CT. We manually outlined the volumes of interest (VOIs) of lesions using ITK-SNAP from SPECT and CT images. In the training set, radiomics features were extracted using PyRadiomics and selected using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Then, we established three radiomics models (CT, SPECT and SPECT-CT models) using support vector machine (SVM). In addition, a radiomics-clinical model was constructed using multivariable logistic regression analysis. The four models' performance was assessed using the area under the receiver operating characteristic curve (AUC). Using DeLong test to make comparisons between the ROC (receiver operating characteristic) curves of different models. The clinical utility of the models was evaluated using decision curve analysis (DCA). Results: The radiomics-clinical displayed excellent performance, and its AUC was 0.941 and 0.879 in the training and test sets. The DCA of radiomics-clinical model showed the highest clinical utility. Conclusions: The radiomics-clinical nomogram for identifying bone metastasis and benign bone disease in tumor patients was suitable to assist in clinical decision. [ABSTRACT FROM AUTHOR]

Distant metastasis remains the major cause of morbidity for breast cancer. Individuals with liver or brain metastasis have an extremely poor prognosis and low response rates to anti‐PD‐1/L1 immune checkpoint therapy compared to those with metastasis at other sites. Therefore, it is urgent to investigate the underlying mechanism of anti‐PD‐1/L1 resistance and develop more effective immunotherapy strategies for these patients. Using single‐cell RNA sequencing, a high‐resolution map of the entire tumor ecosystem based on 44 473 cells from breast cancer liver and brain metastases is depicted. Identified by canonical markers and confirmed by multiplex immunofluorescent staining, the metastatic ecosystem features remarkable reprogramming of immunosuppressive cells such as FOXP3+ regulatory T cells, LAMP3+ tolerogenic dendritic cells, CCL18+ M2‐like macrophages, RGS5+ cancer‐associated fibroblasts, and LGALS1+ microglial cells. In addition, PD‐1 and PD‐L1/2 are barely expressed in CD8+ T cells and cancer/immune/stromal cells, respectively. Interactions of the immune checkpoint molecules LAG3‐LGALS3 and TIGIT‐NECTIN2 between CD8+ T cells and cancer/immune/stromal cells are found to play dominant roles in the immune escape. In summary, this study dissects the intratumoral heterogeneity and immunosuppressive microenvironment in liver and brain metastases of breast cancer for the first time, providing insights into the most appropriate immunotherapy strategies for these patients. [ABSTRACT FROM AUTHOR]

In order to improve the utilization value of tobacco leaves by making full use of tobacco, aqueous extracts of tobacco were prepared from leaf residues after subcritical extraction, and the Maillard reaction products prepared under different conditions were quantitatively analyzed by GC-MS. The effects of amino acid species, glucose/amino acid molar ratios and reaction time on the chemical composition of the reaction products and the sensory quality of cigarettes were systematically studied. The correlations between 18 components in the Maillard reaction products and the sensory indexes of prepared cigarettes were investigated. The results showed that: 1) The Maillard reaction products of glutamic acid and aspartic acid were similar to those of the aqueous extract itself. 5-Hydroxymethylfurfural was dominant in the products, followed by hydroxyacetone and 2-acetylpyrrole. The products of Maillard reaction involving proline were dominated by hydroxyacetone, furfuryl alcohol and 5-hydroxymethylfurfural. 2) On the basis of cigarette smoke sensory effects, the optimal conditions for the Maillard reaction for the tobacco aqueous extract were at the molar ratio of reduced sugar (glucose) and glutamic acid 1:0.5, reacting for 2 h at 110 °. 3) Among the 18 components, the relationship between 2-methyltetrahydrofuran-3-one and smoke concentration was close; furfural, 5-methyl-2-furfural, 2-furanyl hydroxymethyl ketone and 5-hydroxymethylfurfural were closely correlated to smoke volatility; and hydroxyacetone and 3-methylcyclopentane-1,2-dione were closely correlated to baked aroma. [ABSTRACT FROM AUTHOR]