Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis

BackgroundCancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression and are known to mediate endocrine and chemotherapy resistance through paracrine signaling. Additionally, they directly influence the expression and growth dependence of ER in Luminal breast cancer (LBC). This study aims to investigate stromal CAF-related factors and develop a CAF-related classifier to predict the prognosis and therapeutic outcomes in LBC.MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to obtain mRNA expression and clinical information from 694 and 101 LBC samples, respectively. CAF infiltrations were determined by estimating the proportion of immune and cancer cells (EPIC) method, while stromal scores were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify stromal CAF-related genes. A CAF risk signature was developed through univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. The Spearman test was used to evaluate the correlation between CAF risk score, CAF markers, and CAF infiltrations estimated through EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. The TIDE algorithm was further utilized to assess the response to immunotherapy. Additionally, Gene set enrichment analysis (GSEA) was applied to elucidate the molecular mechanisms underlying the findings.ResultsWe constructed a 5-gene prognostic model consisting of RIN2, THBS1, IL1R1, RAB31, and COL11A1 for CAF. Using the median CAF risk score as the cutoff, we classified LBC patients into high- and low-CAF-risk groups and found that those in the high-risk group had a significantly worse prognosis. Spearman correlation analyses demonstrated a strong positive correlation between the CAF risk score and stromal and CAF infiltrations, with the five model genes showing positive correlations with CAF markers. In addition, the TIDE analysis revealed that high-CAF-risk patients were less likely to respond to immunotherapy. Gene set enrichment analysis (GSEA) identified significant enrichment of ECM receptor interaction, regulation of actin cytoskeleton, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathway gene sets in the high-CAF-risk group patients.ConclusionThe five-gene prognostic CAF signature presented in this study was not only reliable for predicting prognosis in LBC patients, but it was also effective in estimating clinical immunotherapy response. These findings have significant clinical implications, as the signature may guide tailored anti-CAF therapy in combination with immunotherapy for LBC patients

Exploring risk transfer of human brucellosis in the context of livestock agriculture transition: A case study in Shaanxi, China

With the booming of worldwide agriculture intensification, brucellosis, one of the most neglected zoonotic diseases, has become an increasing challenge for global public health. Although the transmission patterns of human brucellosis (HB) have been studied in many regions, the dynamic transfer processes of risk and its driving factors remain poorly understood, especially in the context of agricultural intensification. This study attempted to explore the risk transfer of HB between the exact epidemic areas and the neighboring or distant low-risk areas to explain the impact of livestock agriculture intensification and foodborne infections on the transmission of HB in Shaanxi Province as a case study. We adopted multiple approaches, including test-based methods, model-based methods, and a geographical detector to detect the spatial-temporal dynamic changes of high-risk epidemic areas of HB at the county scale. We also quantitatively estimated how the related factors drove the risk transfer of the disease. Results confirmed the risk transfer pattern of HB with an expansion from north to south in Shaanxi Province and identified two primary transfer routes. In particular, in the traditional epidemic areas of the Shaanbei plateau, the farm agglomeration effect can significantly increase the risk of HB. Meanwhile, retail outlets for milk and dairy products were partially responsible for the foodborne infections of HB in the emerging epidemic areas of Xi'an. This study not only contributed helpful insights to support HB control and prevention in the rapid transition of livestock agriculture but also provided possible directions for further research on foodborne HB infections in urbanized areas

Lactylation, a Novel Metabolic Reprogramming Code: Current Status and Prospects

Lactate is an end product of glycolysis. As a critical energy source for mitochondrial respiration, lactate also acts as a precursor of gluconeogenesis and a signaling molecule. We briefly summarize emerging concepts regarding lactate metabolism, such as the lactate shuttle, lactate homeostasis, and lactate-microenvironment interaction. Accumulating evidence indicates that lactate-mediated reprogramming of immune cells and enhancement of cellular plasticity contribute to establishing disease-specific immunity status. However, the mechanisms by which changes in lactate states influence the establishment of diverse functional adaptive states are largely uncharacterized. Posttranslational histone modifications create a code that functions as a key sensor of metabolism and are responsible for transducing metabolic changes into stable gene expression patterns. In this review, we describe the recent advances in a novel lactate-induced histone modification, histone lysine lactylation. These observations support the idea that epigenetic reprogramming-linked lactate input is related to disease state outputs, such as cancer progression and drug resistance

Applications of machine learning in familial hypercholesterolemia

Familial hypercholesterolemia (FH) is a common hereditary cholesterol metabolic disease that usually leads to an increase in the level of low-density lipoprotein cholesterol in plasma and an increase in the risk of cardiovascular disease. The lack of disease screening and diagnosis often results in FH patients being unable to receive early intervention and treatment, which may mean early occurrence of cardiovascular disease. Thus, more requirements for FH identification and management have been proposed. Recently, machine learning (ML) has made great progress in the field of medicine, including many innovative applications in cardiovascular medicine. In this review, we discussed how ML can be used for FH screening, diagnosis and risk assessment based on different data sources, such as electronic health records, plasma lipid profiles and corneal radian images. In the future, research aimed at developing ML models with better performance and accuracy will continue to overcome the limitations of ML, provide better prediction, diagnosis and management tools for FH, and ultimately achieve the goal of early diagnosis and treatment of FH

Targeting Gpr52 lowers mutant HTT levels and rescues Huntington's disease-associated phenotypes.

See Huang and Gitler (doi:10.1093/brain/awy112) for a scientific commentary on this article.Lowering the levels of disease-causing proteins is an attractive treatment strategy for neurodegenerative disorders, among which Huntington's disease is an appealing disease for testing this strategy because of its monogenetic nature. Huntington's disease is mainly caused by cytotoxicity of the mutant HTT protein with an expanded polyglutamine repeat tract. Lowering the soluble mutant HTT may reduce its downstream toxicity and provide potential treatment for Huntington's disease. This is hard to achieve by small-molecule compound drugs because of a lack of effective targets. Here we demonstrate Gpr52, an orphan G protein-coupled receptor, as a potential Huntington's disease drug target. Knocking-out Gpr52 significantly reduces mutant HTT levels in the striatum and rescues Huntington's disease-associated behavioural phenotypes in a knock-in Huntington's disease mouse model expressing endogenous mutant Htt. Importantly, a novel Gpr52 antagonist E7 reduces mutant HTT levels and rescues Huntington's disease-associated phenotypes in cellular and mouse models. Our study provides an entry point for Huntington's disease drug discovery by targeting Gpr52

Clearance of Free Silica in Rat Lungs by Spraying with Chinese Herbal Kombucha

The effects of spraying with kombucha and Chinese herbal kombucha were compared with treatments with tetrandrine in a rat silicosis model. Silica dust (50 mg) was injected into the lungs of rats, which were then treated with one of the experimental treatments for a month. The rats were then killed and the effects of the treatments were evaluated by examining the extent and severity of the histopathological lesions in the animals’ lungs, measuring their organ coefficients and lung collagen contents, determining the dry and wet weights of their lungs, and measuring the free silica content of the dried lungs. In addition, lavage was performed on whole lungs taken from selected rats, and the numbers and types of cells in the lavage fluid were counted. The most effective treatment in terms of the ability to reduce lung collagen content and minimize the formation of pulmonary histopathological lesions was tetrandrine treatment, followed by Chinese herbal kombucha and non-Chinese herbal kombucha. However, the lavage fluid cell counts indicated that tetrandrine treatment had severe adverse effects on macrophage viability. This effect was much less pronounced for the kombucha and Chinese herbal kombucha treatments. Moreover, the free silica levels in the lungs of animals treated with Chinese herbal kombucha were significantly lower than those for any other silica-exposed group. These preliminary results indicate that spraying with Chinese herbal kombucha preparations can effectively promote the discharge of silica dust from lung tissues. Chinese herbal kombucha inhalation may thus be a useful new treatment for silicosis and other pneumoconiosis diseases