BioFactors最新文献

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection and a comprehensive understanding of tumor-immune interactions are crucial for improving patient outcomes. This study aimed to develop a novel biomarker panel utilizing peripheral blood transcriptomics and machine learning algorithms for early lung cancer diagnosis, while simultaneously providing insights into tumor-immune crosstalk mechanisms. Leveraging a training cohort (GSE135304), we employed multiple machine learning algorithms to formulate a Lung Cancer Diagnostic Score (LCDS) based on peripheral blood transcriptomic features. The LCDS model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) in multiple validation cohorts (GSE42834, GSE157086, and an in-house dataset). Peripheral blood samples were obtained from 20 lung cancer patients and 10 healthy control subjects, representing an in-house cohort recruited at the Sixth People's Hospital of Chengdu. We employed advanced bioinformatics techniques to explore tumor-immune interactions through comprehensive immune infiltration and pathway enrichment analyses. Initial screening identified 844 differentially expressed genes, which were subsequently refined to 87 genes using the Boruta feature selection algorithm. The random forest (RF) algorithm demonstrated the highest accuracy in constructing the LCDS model, yielding a mean AUC of 0.938. Lower LCDS values were significantly associated with elevated immune scores and increased CD4+ and CD8+ T-cell infiltration, indicative of enhanced antitumor-immune responses. Higher LCDS scores correlated with activation of hypoxia, peroxisome proliferator-activated receptor (PPAR), and Toll-like receptor (TLR) signaling pathways, as well as reduced DNA damage repair pathway scores. Our study presents a novel, machine learning-derived peripheral blood transcriptomic biomarker panel with potential applications in early lung cancer diagnosis. The LCDS model not only demonstrates high accuracy in distinguishing lung cancer patients from healthy individuals but also offers valuable insights into tumor-immune interactions and underlying cancer biology. This approach may facilitate early lung cancer detection and contribute to a deeper understanding of the molecular and cellular mechanisms underlying tumor-immune crosstalk. Furthermore, our findings on the relationship between LCDS and immune infiltration patterns may have implications for future research on therapeutic strategies targeting the immune system in lung cancer.

Mitochondrial dysfunction may precipitate intestinal dysfunction, while inflammatory bowel disease manifests as a chronic inflammatory ailment affecting the gastrointestinal tract. This condition disrupts the barrier function of the intestinal epithelium and alters metabolic products. Increasing mitochondrial adenosine triphosphate (ATP) synthesis in intestinal epithelial cells presents a promising avenue for colitis treatments. Nevertheless, the impact of cedrol on ATP and the intestinal barrier remains unexplored. Hence, this study is dedicated to examining the cedrol's protective effect on an inflammatory cocktail (IC)-induced intestinal epithelial barrier dysfunction in Caco-2 cells. The finding reveals that cedrol enhances ATP content and the transepithelial electrical resistance value in the intestinal epithelial barrier. Moreover, cedrol mitigates the IC-induced decrease in the messenger ribonucleic acid (mRNA) expression of tight junction proteins (ZO-1, Occludin, and Claudin-1), thereby ameliorating intestinal epithelial barrier dysfunction. Furthermore, nuclear magnetic resonance (NMR)-based metabolomic analysis indicated that IC-exposed Caco-2 cells are restored by cedrol treatments. Notably, cedrol elevates metabolites such as amino acids, thereby enhancing the intestinal barrier. In conclusion, cedrol alleviates IC-induced intestinal epithelial barrier dysfunction by promoting ATP-dependent proliferation of Caco-2 cells and bolstering amino acid levels to sustain tight junction messenger ribonucleic acid expression.

To explore the potential mechanisms which O-linked-N-acetylglucosaminylation (O-GlcNAcylation) regulates osteogenesis, a publicly RNA-seq dataset was re-analyzed with literature-mining and showed the primary targets of O-GlcNAcylation in osteoblasts are mitochondria/cytoskeleton. Although the O-GlcNAcylation-regulated mitochondria/cytoskeleton has been extensively studied, its specific role during osteogenesis remains unclear. To address this, we knocked out Ogt (Ogt-KO) in MC3T3-E1 osteoblastic cells. Then, significantly reduced osteoblast differentiation, motility, proliferation, mitochondria-endoplasmic reticulum (Mito-ER) coupling, volume of ER, nuclear tubulins, and oxygen metabolism were observed in Ogt-KO cells. Through artificial intelligence (AI)-predicted cellular structures, the time-lapse live cells imaging with reactive-oxygen-species/hypoxia staining showed that lower cell proliferation and altered oxygen metabolism in the Ogt-KO cells were correlated with the Mito-ER coupling. Bioinformatics analysis, combined with correlated mRNA and protein expression, suggested that Ezh2 and its downstream targets (Opa1, Gsk3a, Wnt3a, Hif1a, and Hspa9) may be involved in O-GlcNAcylation-regulated Mito-ER coupling, ultimately impacting osteoblast differentiation. In conclusion, our findings indicate that O-GlcNAcylation-regulated osteoblast differentiation is linked to morphological changes in mitochondria, cytoskeleton, and ER, with Ezh2 potentially playing a crucial role.

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to the treatment of lung squamous cell carcinoma (LUSC). However, there is a lack of optimal predictive models that can accurately forecast patient prognosis and guide the selection of targeted therapies. The extensive multi-omic data obtained from multi-level molecular biology provides a unique perspective for understanding the underlying biological characteristics of cancer, offering potential prognostic indicators and drug sensitivity biomarkers for LUSC patients. We integrated diverse datasets encompassing gene expression, DNA methylation, genomic mutations, and clinical data from LUSC patients to achieve consensus clustering using a suite of 10 multi-omics integration algorithms. Subsequently, we employed 10 commonly used machine learning algorithms, combining them into 101 unique configurations to design an optimal performing model. We then explored the characteristics of high- and low-risk LUSC patient groups in terms of the tumor microenvironment and response to immunotherapy, ultimately validating the functional roles of the model genes through in vitro experiments. Through the application of 10 clustering algorithms, we identified two prognostically relevant subtypes, with CS1 exhibiting a more favorable prognosis. We then constructed a subtype-specific machine learning model, LUSC multi-omics signature (LMS) based on seven key hub genes. Compared to previously published LUSC biomarkers, our LMS score demonstrated superior predictive performance. Patients with lower LMS scores had higher overall survival rates and better responses to immunotherapy. Notably, the high LMS group was more inclined toward "cold" tumors, characterized by immune suppression and exclusion, but drugs like dasatinib may represent promising therapeutic options for these patients. Notably, we also validated the model gene SERPINB13 through cell experiments, confirming its role as a potential oncogene influencing the progression of LUSC and as a promising therapeutic target. Our research provides new insights into refining the molecular classification of LUSC and further optimizing immunotherapy strategies.

Paclitaxel (PTX)-induced peripheral neuropathy (PIPN) is a disabling side effect of PTX, which adversely affects the life quality of cancer patients. Flavonoids such as hesperidin methyl chalcone (HMC) and taxifolin (TAX) can alleviate neuropathic pain via their anti-inflammatory, antioxidant, neuroprotective, and antinociceptive properties. The current study aimed to assess the efficacy of HMC and TAX in preventing PIPN individually or in combination. Pretreatment with HMC and TAX mitigated PTX-induced mechanical allodynia and hyperalgesia, cold allodynia, and thermal hyperalgesia as well as restore the normal histological architecture. Remarkably, neuropathic pain was relieved by suppression of nerve growth factor (NGF), p38 mitogen-activated protein kinase (p38 MAPK), and transient receptor potential vanilloid type-1 (TRPV1), which ultimately lead to reduced calcitonin gene-related peptide (CGRP). Furthermore, both HMC or TAX enhanced nuclear factor erythroid 2-related factor 2 (Nrf2), leading to elevated glutathione (GSH) and total antioxidant capacity (TAC) along with lowered malondialdehyde (MDA), which in turn, downregulated nuclear factor kappa B P65 (NF-κB P65) and its phosphorylated form and eventually reduced tumor necrosis factor alpha (TNF-α) and interleukin-1 beta (IL-1β) then lowered the apoptotic indices. Promisingly, the combination of both agents was superior to each drug alone through targeting more diverse signaling pathways and achieving synergistic and comprehensive therapeutic effects. In conclusion, pretreatment with HMC and TAX separately or in combination alleviated PIPN via modulating NGF/p38 MAPK/NF-κB P65/TRPV1/CGRP pathway.

Indoor air pollution is a recognized emerging threat, claiming millions of lives annually. People are constantly exposed to ambient and indoor air pollution. The latest research shows that people in developed countries spend up to 90% of their time indoors and almost 70% at home. Although impaired IAQ represents a significant health risk, it affects people differently, and specific populations are more vulnerable: children, the elderly, and people with respiratory illnesses are more sensitive to these environmental risks. Despite rather extensive research on IAQ, most of the current understanding about the subject, which includes pollution sources, indoor-outdoor relationships, and ventilation/filtration, is still quite limited, mainly because air quality monitoring in the EU is primarily focused on ambient air quality and regulatory requirements are lacking for indoor environments. Therefore, the EDIAQI project aims to improve guidelines and awareness for advancing the IAQ in Europe and beyond by allowing user-friendly access to information about indoor air pollution exposures, sources, and related risk factors. The solution proposed with EDIAQI consists of conducting a characterization of sources and routes of exposure and dispersion of chemical, biological, and emerging indoor air pollution in multiple cities in the EU. The project will deploy cost-effective/user-friendly monitoring solutions to create new knowledge on sources, exposure routes, and indoor multipollutant body burdens. The EDIAQI project brings together 18 organizations from 11 different European countries that provide interdisciplinary skills and expertise in various fields, including environmental science and technology, medicine, and toxicology, as well as policy design and public engagement.

The thyroid hormone (TH) status is routinely assessed by thyrotropin (TSH) and thyroxine (T4). Both biomarkers are mainly regulated by TH receptor beta, whereas many peripheral organs employ the alpha receptor. Serum cluster of differentiation 5-like molecule (CD5L) is a liver-derived protein under control of both TH receptor isoforms. However, clinical data on its relation to TH status are sparse. An additional biomarker of TH status is needed in particular during pregnancy, where the routine biomarkers become dynamically disturbed. This study aimed to determine possible covariates regulating serum CD5L and to test its potential suitability as additional TH biomarker during pregnancy. A sandwich ELISA for serum CD5L was established using newly raised antibodies. Circadian effects and the impact of liver disease on serum CD5L concentrations were assessed. Serum samples from pregnant women with well-characterized TH and trace element status were analyzed, and CD5L concentrations were correlated with other indicators of TH status including TSH, fT4, fT3, copper, and selenium concentrations. The new quantitative assay for CD5L showed high accuracy. Serum CD5L was stable in dilution and refreezing experiments and did not show strong circadian variance or dependency on liver disease. In serum of pregnant women, CD5L correlated positively to fT3, but not to fT4 or TSH. Significant positive correlations of CD5L were observed with serum levels of the TH-responsive trace elements selenium and copper. The data support the potential suitability of serum CD5L as an additional marker of TH status, with potential value for pregnancy and thyroid disease.

Pancreatic ductal adenocarcinoma (PDAC) is one of malignancies with worst outcomes among digestive system tumors. Identification of novel biomarkers is of great significance for treatment researches and prognosis prediction of pancreatic cancer patients. Due to OSBPL10 known involvement in oncogenic activity in other tumors, we elucidated the mechanism underlying its contribution to pancreatic cancer progression. We employed data from the Gene Expression Omnibus database to detect the expression of OSBPL10 in normal and pancreatic cancer tissues. A series of assays were conducted to assess the impact of OSBPL10 on the proliferation and metastatic capacities of pancreatic cancer cells and the influence of OSBPL10 on macrophages were evaluated by Flow cytometry. In addition, Co-immunoprecipitation, mass spectrometry, and western blot assays were utilized to investigate the potential mechanisms of OSBPL10 activity. From our study, OSBPL10 is revealed to be upregulated in pancreatic cancer, with poor prognosis. The overexpression promotes malignant behaviors of pancreatic cancer cells and has an impact on tumor immune microenvironment by stimulating the transformation M1 macrophages into M2 macrophages. Mechanistically, hypoxia induces the expression of OSBPL10 through interaction between hypoxia-inducible factor 1-α and the promoter region of OSBPL10. Additionally, OSBPL10 directly bound to CNBP, mediating CNBP expression and ultimately regulating the proliferation and metastasis capacity of pancreatic cancer cells, as well as influencing macrophage polarization. The research emphasized the oncogenic role of OSBPL10 in pancreatic cancer, uncovering key mechanisms involving hypoxia, HIF-1α, and CNBP. The finding suggests that OSBPL10 is a novel biomarker in pancreatic cancer, making it a potential therapeutic target for intervention in this malignancy.