Phenomics (Cham, Switzerland)最新文献

Increasing evidence indicates that Calumenin (CALU), which is localized in the endoplasmic reticulum, is significantly associated with tumor progression. However, the effect of CALU on patients with clear cell renal cell carcinoma (ccRCC) is unknown. By integrating multi-omics data and molecular biology experiments, we found that CALU expression was significantly increased in tumors compared with normal tissues, and the pathological grade and prognosis of patients were correlated with CALU expression. Next, knockdown or ectopic expression of CALU could affect the proliferative and invasive abilities of ccRCC cells. Moreover, immune landscape characterization revealed that CALU expression was positively associated with neutrophils and macrophages, whereas it was negatively associated with natural killer T cells and CD8⁺ T cells. Single-cell sequencing showed that the localization and binding targets of CALU mainly involved monocytes/macrophages and CD4⁺ and CD8⁺ T-cells. Sensitivity analysis of common chemotherapeutic drugs showed that high expression of CALU could sensitize chemotherapeutic drugs such as 5Z-7-Oxozeaenol, AMG-706 and Cytarabine, but could lead to drug resistance to chemotherapeutic drugs such as Embelin, Salubrinal and Tipifarnib. We demonstrated a significant correlation between high CALU expression and poor patient survival. Further, we demonstrated a correlation between CALU expression, tumor microenvironment, and the sensitivity of patients to common chemo- and immuno-therapy drugs. Thus, our results indicate that CALU could be a biomarker and designing personalized treatment approaches for ccRCC patients.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00169-7.

Little is known about the links of disturbed lipid metabolism with hyperuricemia (HUA). We aimed to investigate the associations of lipidomic profiles with uric acid (UA)/HUA and their modifying factors in middle-aged and elderly Chinese. A total of 350 lipids were quantified in 2247 community-based Chinese aged 50-70 years by high-coverage targeted lipidomics. HUA was defined by plasma UA > 420 μmol/L in men or > 360 μmol/L in women. The prevalence of HUA in this population was 10.4%. After multivariable adjustment including BMI and lifestyle, 123 lipids were significantly associated with UA, predominantly glycerolipids (GLs) and glycerophospholipids (GPs). Specifically, diacylglycerol [DAG (16:0/22:5), DAG (16:0/22:6), DAG (18:1/20:5), DAG (18:1/22:6)], phosphatidylcholine [PC (16:0/20:5)), and triacylglycerol (TAG (53:0)] were the most significant lipid signatures positively associated with HUA risk, while lysophosphatidylcholine (LPC (20:2)) was inversely associated with HUA risk (p < 0.05). Network analysis also showed a positive association between TAGs/PCs/DAGs contained module and HUA risk (p < 0.01). Notably, HUA-related lipids were associated with de novo lipogenesis fatty acids, especially 16:1n-7 (Spearman correlation coefficients = 0.32-0.41, p < 0.001). Reduced rank regression showed that increased aquatic products intake was correlated to elevated HUA risk and HUA-associated lipids; while high dairy consumption was correlated with low level of HUA-associated lipids (|factor loadings| ≥ 0.2). Moreover, mediation analyses suggested that the lipid-HUA associations were partially mediated by retinol-binding protein 4 (RBP4, mediation proportion 5-14%), an adipokine linked with dyslipidemia and insulin resistance. In conclusion, disturbed specific metabolisms of GLs and GPs were associated with high prevalent HUA, partially mediated by RBP4 and/or influenced by certain dietary factors.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00157-x.

Cancer immunotherapy has made great progress in effectively attacking or eliminating cancer. However, the challenges posed by the low reactivity of some solid tumors still remain. Macrophages, as a key component of the tumor microenvironment (TME), play an important role in determining the progression of solid tumors due to their plasticity and heterogeneity. Targeting and reprogramming macrophages in TME to desired phenotypes offers an innovative and promising approach for cancer immunotherapy. Meanwhile, the rapid development of in vivo molecular imaging techniques provides us with powerful tools to study macrophages. In this review, we summarize the current progress in macrophage reprogramming from conceptual roadmaps to therapeutic approaches, including monoclonal antibody drugs, small molecule drugs, gene therapy, and chimeric antigen receptor-engineered macrophages (CAR-M). More importantly, we highlight the significance of molecular imaging in observing and understanding the process of macrophage reprogramming during cancer immunotherapy. Finally, we introduce the therapeutic applications of imaging and reprogramming macrophages in three solid tumors. In the future, the integration of molecular imaging into the development of novel macrophage reprogramming strategies holds great promise for precise clinical cancer immunotherapy.

Pyroptosis is a newly recognized type of programmed cell death mediated by the gasdermin family and caspase. It is characterized by the formation of inflammasomes and the following inflammatory responses. Recent studies have elucidated the value of pyroptosis induction in cancer treatment. The inflammatory cytokines produced during pyroptosis can trigger immune responses to suppress malignancy. Physical approaches for cancer treatment, including radiotherapy, light-based techniques (photodynamic and photothermal therapy), ultrasound-based techniques (sonodynamic therapy and focused ultrasound), and electricity-based techniques (irreversible electroporation and radiofrequency ablation), are effective in clinical application. Recent studies have reported that pyroptosis is involved in the treatment process of physical approaches. Manipulating pyroptosis using physical approaches can be utilized in combating cancer, according to recent studies. Pyroptosis-triggered immunotherapy can be combined with the original anti-tumor methods to achieve a synergistic therapy and improve the therapeutic effect. Studies have also revealed that enhancing pyroptosis may increase the sensitivity of cancer cells to some physical approaches. Herein, we present a comprehensive review of the literature focusing on the associations between pyroptosis and various physical approaches for cancer and its underlying mechanisms. We also discussed the role of pyroptosis-triggered immunotherapy in the treatment process of physical manipulation.

Many laboratories have demonstrated that the ketogenic diet (KD) can lead to weight loss and reduced fasting glucose levels, while also increasing total serum cholesterol levels. However, it's worth noting that the specific outcomes induced by KD can vary across different research settings. Certain studies have indicated that environmental factors, such as housing conditions and the acidity of drinking water, can influence physiological parameters and gut microbes in mice. Thus, our current study aimed to investigate whether differences in housing conditions and pH levels of drinking water contribute to variations in KD-induced phenotypes and gut microbes. Our findings revealed that mice housed in conventional (CV) conditions experienced more significant weight loss, lower fasting blood glucose levels, and a greater elevation of blood cholesterol levels compared to those in the specific pathogen-free (SPF) condition. Additionally, similar differences were observed when comparing mice fed with non-acidified water versus acidified water. Furthermore, we analyzed cecum content samples using 16S rRNA sequencing to assess gut microbial composition and found that the tested environmental variables also had an impact on the gut microbial composition of KD-fed mice, which was correlated with their phenotypic alterations. In summary, both housing conditions and the pH of drinking water were identified as crucial environmental factors that influenced KD-induced changes in metabolic phenotypes and gut microbes. Our study emphasizes the importance of considering these factors in animal studies related to KD and gut microbes, as well as in other types of animal research.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00161-1.

Phenome has become a consensus as the next innovation source of biomedicine. As the global network dedicated to large-scale research efforts on human phenome and promoting the Human Phenome Project, the Board of International Human Phenome Consortium (IHPC) plays an essential role to guide the strategy and implementation of international human phenome project and to ensure coordination across the IHPC members. The 4th International Human Phenome Consortium Board Meeting was held virtually on December 13, 2022. During the meeting, the keynote speeches highlighted the latest advancements in phenomics. The construction and discoveries of the first human phenome Atlas had shown promising potential in limb development, disease prevention, and early diagnosis. Combining genome-phenome sequencing, analysis, and wellness coaching enhanced individual wellness. Phenomics trajectories from healthy to diseased states and recovery provided insight into the metabolic risk spaces associated with COVID-19. Board members from Ghana, Malaysia, India, and Russia presented their own plans and research progress. The IHPC Board deliberated on the "Framework Guidelines for Human Phenome-related Measurements" and "Proposal of the PhenoBank Initiative". The meeting also featured a presentation of the annual report of the IHPC Journal Phenomics. Laboratory coordination, interoperable databases, and standardized platforms were productively discussed, which would enable concerted research efforts of the Human Phenome Project.

It is widely recognized that tumor immune microenvironment (TIME) plays a crucial role in tumor progression, metastasis, and therapeutic response. Despite several noninvasive strategies have emerged for cancer diagnosis and prognosis, there are still lack of effective radiomic-based model to evaluate TIME status, let alone predict clinical outcome and immune checkpoint inhibitor (ICIs) response for hepatocellular carcinoma (HCC). In this study, we developed a radiomic model to evaluate TIME status within the tumor and predict prognosis and immunotherapy response. A total of 301 patients who underwent magnetic resonance imaging (MRI) examinations were enrolled in our study. The intra-tumoral expression of 17 immune-related molecules were evaluated using co-detection by indexing (CODEX) technology, and we construct Immunoscore (IS) with the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression method to evaluate TIME. Of 6115 features extracted from MRI, five core features were filtered out, and the Radiomic Immunoscore (RIS) showed high accuracy in predicting TIME status in testing cohort (area under the curve = 0.753). More importantly, RIS model showed the capability of predicting therapeutic response to anti-programmed cell death 1 (PD-1) immunotherapy in an independent cohort with advanced HCC patients (area under the curve = 0.731). In comparison with previously radiomic-based models, our integrated RIS model exhibits not only higher accuracy in predicting prognosis but also the potential guiding significance to HCC immunotherapy.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00136-8.

Nuclear medicine and molecular imaging plays a significant role in the detection and management of cardiovascular disease (CVD). With recent advancements in computer power and the availability of digital archives, artificial intelligence (AI) is rapidly gaining traction in the field of medical imaging, including nuclear medicine and molecular imaging. However, the complex and time-consuming workflow and interpretation involved in nuclear medicine and molecular imaging, limit their extensive utilization in clinical practice. To address this challenge, AI has emerged as a fundamental tool for enhancing the role of nuclear medicine and molecular imaging. It has shown promising applications in various crucial aspects of nuclear cardiology, such as optimizing imaging protocols, facilitating data processing, aiding in CVD diagnosis, risk classification and prognosis. In this review paper, we will introduce the key concepts of AI and provide an overview of its current progress in the field of nuclear cardiology. In addition, we will discuss future perspectives for AI in this domain.