Systemic immunity-inflammation index is associated with body fat distribution among U.S. adults: evidence from national health and nutrition examination survey 2011-2018.

OBJECTIVE: The systemic immunity-inflammation index (SII) is a newly developed biomarker that provides an integrated measure of inflammation in the body. We aim to evaluate the relationship between SII and body fat distribution. METHODS: Adults from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were included. The SII was computed using lymphocyte (LC), neutrophil (NC), and platelet (PC) counts as its components. Body fat distribution was assessed by (total, android, gynoid) percentage fat, total abdominal fat area, subcutaneous adipose tissue area, visceral adipose tissue area, and the ratio of visceral to subcutaneous adipose tissue area (V/S ratio). Multivariable weighted linear regression and subgroup analysis were use to examine the relationships between fat distribution and SII. Restricted cubic splines (RCS) and threshold effect analysis were used to examine analyze nonlinear associations. RESULTS: After exclusions, a total of 11,192 adults with a weighted mean age of 38.46 ± 0.26 years were studied. In multivariable weighted linear regression, each level increase in log2SII was associated with increased of 0.23 SDs total percentage fat (95% CI = 0.03, 0.43) and 0.26 SDs android percentage fat (95% CI = 0.06, 0.47). Besides, the subgroup analysis showed that the positive association between SII and android percentage fat was mainly among obese individuals (BMI > 30 kg/m2) and non-obese individuals without DM or hypertension. Meanwhile, the relationship between SII and the V/S ratio was found to be significant in the female subgroup, the obese subgroup, individuals with non-alcoholic fatty liver disease (NAFLD), and those without diabetes mellitus. Finally, SII exhibited an inverted U-shaped relationship with total percentage fat, android percent fat and total abdominal fat. Accordingly, threshold effect analysis indicated a positive association between lower SII levels and total percentage fat, android percentage fat and total abdominal fat area. CONCLUSIONS: In the nationwide study, it was observed that the SII exhibited a significant correlation with higher levels of body fat, specifically android fat. This association was particularly noticeable within specific subgroups of the population.

Clinical features and molecular landscape of cuproptosis signature-related molecular subtype in gastric cancer.

Recent studies have highlighted the biological significance of cuproptosis in disease occurrence and development. However, it remains unclear whether cuproptosis signaling also has potential impacts on tumor initiation and prognosis of gastric cancer (GC). In this study, 16 cuproptosis-related genes (CRGs) transcriptional profiles were harnessed to perform the regularized latent variable model-based clustering in GC. A cuproptosis signature risk scoring (CSRS) scheme, based on a weighted sum of principle components of the CRGs, was used to evaluate the prognosis and risk of individual tumors of GC. Four distinct cuproptosis signature-based clusters, characterized by differential expression patterns of CRGs, were identified among 1136 GC samples across three independent databases. The four clusters were also associated with different clinical outcomes and tumor immune contexture. Based on the CSRS, GC patients can be divided into CSRS-High and CSRS-Low subtypes. We found that DBT, MTF1, and ATP7A were significantly elevated in the CSRS-High subtype, while SLC31A1, GCSH, LIAS, DLAT, FDX1, DLD, and PDHA1 were increased in the CSRS-Low subtype. Patients with CSRS-Low score were characterized by prolonged survival time. Further analysis indicated that CSRS-Low score also correlated with greater tumor mutation burden (TMB) and higher mutation rates of significantly mutated genes (SMG) in GC. In addition, the CSRS-High subtype harbored more significantly amplified focal regions related to tumorigenesis (3q27.1, 12p12.1, 11q13.3, etc.) than the CSRS-Low tumors. Drug sensitivity analyses revealed the potential compounds for the treatment of gastric cancer with CSRS-High score, which were experimentally validated using GC cells. This study highlights that cuproptosis signature-based subtyping is significantly associated with different clinical features and molecular landscape of GC. Quantitative evaluation of the CSRS of individual tumors will strengthen our understanding of the occurrence and development of cuproptosis and the treatment progress of GC.

Efficacy and regulatory strategies of gut microbiota in immunotherapy: a narrative review.

Background and Objective: With advances in gut microbiome research, it has been recognized that the gut microbiome has an important and far-reaching impact on many human diseases, including cancer. Therefore, more and more researchers are focusing on the treatment of gut flora in tumors. In this article, we present a review of the mechanisms of gut microbes in tumor immunotherapy and related studies to provide reference for further research and insights into the clinical application of gut microbes. Methods: Between April 25, 2023, and November 25, 2023, we searched for articles published only in English between 1984 and 2023 using the databases PubMed, American Medical Association and Elsevier ScienceDirect using the keywords "gut microbiology" and "tumor" or "immunotherapy". Key Content and Findings: The gastrointestinal tract contains the largest number of microorganisms in the human body. Microorganisms are involved in regulating many physiological activities of the body. Studies have shown that gut microbes and their derivatives are involved in the occurrence and development of a variety of inflammations and tumors, and changes in their abundance and proportion affect the degree of cancer progression and sensitivity to immunotherapy. Gut microbiota-based drug research is ongoing, and some anti-tumor studies have entered the clinical trial stage. Conclusions: The abundance and proportion of intestinal microorganisms influence the susceptibility of tumors to tumor immunotherapy. This article reviewed the effects and mechanisms of gut microbes on tumor immunotherapy to further explore the medical value of gut microbes in tumor immunotherapy.

Research progress of exosomes in the angiogenesis of digestive system tumour.

Malignant tumours of the digestive system cover a wide range of diseases that affect the health of people to a large extent. Angiogenesis is indispensable in the development, and metastasis of tumours, mainly in two ways: occupation or formation. Vessels can provide nutrients, oxygen, and growth factors for tumours to encourage growth and metastasis, so cancer progression depends on simultaneous angiogenesis. Recently, exosomes have been proven to participate in the angiogenesis of tumours. They influence angiogenesis by binding to tyrosine kinase receptors (VEGFR)-1, VEGFR-2, and VEGFR-3 with different affinities, regulating Yap-VEGF pathway, Akt pathway or other signaling pathway. Additionally, exosomes are potential therapeutic vectors that can deliver many types of cargoes to different cells. In this review, we summarize the roles of exosomes in the angiogenesis of digestive system tumours and highlight the clinical application prospects, directly used as targers or delivery vehicles, in antiangiogenic therapy.

Pan-cancer analysis of the tumorigenic role of Fanconi anemia complementation group D2 (FANCD2) in human tumors.

Monoubiquitination of FANCD2 is a central step in the activation of the Fanconi anemia (FA) pathway after DNA damage. Defects in the FA pathway centered around FANCD2 not only lead to genomic instability but also induce tumorigenesis. At present, few studies have investigated FANCD2 in tumors, and no pan-cancer research on FANCD2 has been conducted. We conducted a comprehensive analysis of the role of FANCD2 in cancer using public databases and other published studies. Moreover, we evaluated the role of FANCD2 in the proliferation, migration and invasion of lung adenocarcinoma cells through in vitro and in vivo experiments, and explored the role of FANCD2 in cisplatin chemoresistance. We investigated the regulatory effect of FANCD2 on the cell cycle of lung adenocarcinoma cells by flow cytometry, and verified this effect by western blotting. FANCD2 expression is elevated in most TCGA tumors and shows a strong positive correlation with poor prognosis in tumor patients. In addition, FANCD2 expression shows strong correlations with immune infiltration, immune checkpoints, the tumor mutation burden (TMB), and microsatellite instability (MSI), which are immune-related features, suggesting that it may be a potential target of tumor immunotherapy. We further found that FANCD2 significantly promotes the proliferation, invasion, and migration abilities of lung adenocarcinoma cells and that its ability to promote cancer cell proliferation may be achieved by modulating the cell cycle. The findings indicate that FANCD2 is a potential biomarker and therapeutic target in cancer treatment by analyzing the oncogenic role of FANCD2 in different tumors.

Machine learning-based identification of a novel prognosis-related long noncoding RNA signature for gastric cancer.

Gastric cancer (GC) is one of the most common malignancies with a poor prognosis. Immunotherapy has attracted much attention as a treatment for a wide range of cancers, including GC. However, not all patients respond to immunotherapy. New models are urgently needed to accurately predict the prognosis and the efficacy of immunotherapy in patients with GC. Long noncoding RNAs (lncRNAs) play crucial roles in the occurrence and progression of cancers. Recent studies have identified a variety of prognosis-related lncRNA signatures in multiple cancers. However, these studies have some limitations. In the present study, we developed an integrative analysis to screen risk prediction models using various feature selection methods, such as univariate and multivariate Cox regression, least absolute shrinkage and selection operator (LASSO), stepwise selection techniques, subset selection, and a combination of the aforementioned methods. We constructed a 9-lncRNA signature for predicting the prognosis of GC patients in The Cancer Genome Atlas (TCGA) cohort using a machine learning algorithm. After obtaining a risk model from the training cohort, we further validated the model for predicting the prognosis in the test cohort, the entire dataset and two external GEO datasets. Then we explored the roles of the risk model in predicting immune cell infiltration, immunotherapeutic responses and genomic mutations. The results revealed that this risk model held promise for predicting the prognostic outcomes and immunotherapeutic responses of GC patients. Our findings provide ideas for integrating multiple screening methods for risk modeling through machine learning algorithms.

Proposal of X-ray absorption spectroscopy and magnetic circular dichroism using broadband free-electron lasers.

X-ray free-electron lasers (XFELs) have been widely used for applications such as X-ray crystallography and magnetic spin probes because of their unprecedented performance. Recently, time-resolved X-ray magnetic circular dichroism (XMCD) with ultrafast XFEL pulses have made it possible to achieve an instantaneous view of atomic de-excitation. However, owing to the narrow bandwidth and coherence of XFELs, X-ray absorption spectroscopy (XAS) and XMCD are time- and effort-consuming for both machine scientists and users of XFELs. In this work, an efficient scheme using a broadband XFEL pulse and single-shot X-ray spectrometer is proposed, in which the XAS and XMCD measurements can be accomplished with the same machine conditions. An evolutionary multi-objective optimization algorithm is used to maximize the XFEL bandwidth offered by the Shanghai Soft X-ray FEL user facility without additional hardware. A numerical example using MnO is demonstrated, showing that, by using approximately 1000 consecutive XFEL shots with a central photon energy of 650 eV and full bandwidth of 4.4%, precise spectral measurements for XAS and XMCD can be achieved. Additional considerations related to single-shot XAS and XMCD are discussed.