Roles of the Immune/Methylation/Autophagy Landscape on Single-Cell Genotypes and Stroke Risk in Breast Cancer Microenvironment

Exercise potentially prevents colorectal cancer liver metastases by suppressing tumor epithelial cell stemness via RPS4X downregulation

Background

Colorectal cancer (CRC) is the third most prevalent tumor globally. The liver is the most common site for CRC metastasis, and the involvement of the liver is a common cause of death in patients with late-stage CRC. Consequently, mitigating CRC liver metastasis (CRLM) is key to improving CRC prognosis and increasing survival. Exercise has been shown to be an effective method of improving the prognosis of many tumor types. However, the ability of exercise to inhibit CRLM is yet to be thoroughly investigated.

Methods

The GSE157600 and GSE97084 datasets were used for analysis. A pan-cancer dataset which was uniformly normalized was downloaded and analyzed from the UCSC database: TCGA, TARGET, GTEx (PANCAN, n = 19,131, G = 60,499). Several advanced bioinformatics analyses were conducted, including single-cell sequencing analysis, correlation algorithm, and prognostic screen. CRC tumor microarray (TMA) as well as cell/animal experiments are used to further validate the results of the analysis.

Results

The greatest variability was found in epithelial cells from the tumor group. RPS4X was generally upregulated in all types of CRC, while exercise downregulated RPS4X expression. A lowered expression of RPS4X may prolong tumor survival and reduce CRC metastasis. RPS4X and tumor stemness marker-CD44 were highly positively correlated and knockdown of RPS4X expression reduced tumor stemness both in vitro and in vivo.

Conclusion

RPS4X upregulation may enhance CRC stemness and increase the odds of metastasis. Exercise may reduce CRC metastasis through the regulation of RPS4X.

Identification of key lncRNAs in age-related macular degeneration through integrated bioinformatics and experimental validation

This study aimed to identify key long noncoding RNAs (lncRNAs) in age-related macular degeneration (AMD) patients and to identify relevant pathological mechanisms of AMD development. We identified 407 differentially expressed mRNAs and 429 differentially expressed lncRNAs in retinal pigment epithelium (RPE) and retina in the macular region of AMD patients versus controls (P < 0.05 and |log2FC| > 0.585) from GSE135092. A total of 14 key differentially expressed mRNAs were obtained through external data validation from GSE115828. A miRNA-mRNA and miRNA-lncRNA network containing 52 lncRNA nodes, 49 miRNA nodes, 14 mRNA nodes and 351 edges was constructed via integrated analysis of these components. Finally, the LINC00276-miR-619-5p-IFIT3 axis was identified via protein-protein network analysis. In the t-BH-induced ARPE-19 senescent cell model, LINC00276 and IFIT3 were downregulated. Overexpression of LINC00276 could accelerate cell migration in combination with IFIT3 upregulation. This compelling finding suggests that LINC00276 plays an influential role in the progression of AMD, potentially through modulating senescence processes, thereby setting a foundation for future investigative efforts to verify this relationship.

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Background

High relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. To optimize the surveillance regimen for distant recurrence after neoadjuvant chemotherapy (NAC), we conducted a comprehensive analysis using bioinformatics and machine learning approaches.

Materials and methods

Microarray data were retrieved from the GEO database, and differential expression analysis was performed with the R package 'Limma'. We used the Metascape tool for enrichment analyses, and 'WGCNA' was utilized to establish co-expression networks, selecting the soft threshold power with the 'pickSoftThreshold' algorithm. We integrated ten machine learning algorithms and 101 algorithm combinations to identify key genes associated with distant recurrence in BC. Unsupervised clustering was performed with the R package 'ConsensusCluster Plus'. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the Genetic Perturbation Similarity Analysis (GPSA) database. Single-cell RNA sequencing (scRNA-seq) analysis was conducted through the Tumour Immune Single-cell Hub (TISCH) database, and the XSum algorithm was used to screen candidate small molecule drugs based on the Connectivity Map (CMAP) database. Molecular docking processes were conducted using Schrodinger software. GMT files containing gene sets associated with metabolism and senescence were obtained from GSEA MutSigDB database. The GSVA score for each gene set across diverse samples was computed using the ssGSEA function implemented in the GSVA package.

Results

Our analysis, which combined Limma, WGCNA, and machine learning approaches, identified 16 RCB-relevant gene signatures influencing distant recurrence-free survival (DRFS) in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) with different distant recurrence risks. This molecular subtyping scheme was found to be closely associated with tumor metabolism and cellular senescence. Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60-6.29; log-rank test p < 0.0001). High GATA3 expression, high levels of resting mast cell infiltration, and a high proportion of estrogen receptor (ER)-positive patients contributed to better DRFS in cluster C1. We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95-0.86), with a C-index of 0.85 (95% CI: 0.81-0.90). Entinostat was identified as a potential small molecule compound to reverse high RCB after NAC. We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients.

Conclusion

This study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.

Oncoplastic breast-conserving surgery improves cosmetic outcomes without increasing recurrence risk compared to modified radical mastectomy in early breast cancer patients: development and validation of a recurrence risk prediction model

In the quest for effective treatment of early-stage breast cancer, this study aimed to compare the clinical efficacy of modified radical mastectomy (MRM) and oncoplastic breast-conserving surgery (OBCS). Breast cancer remains a major health concern globally, where early detection and effective treatment strategies are crucial for improving the outcomes of patients. MRM and OBCS are two primary treatment modalities for breast cancer, each with its distinct benefits and challenges. Through a retrospective analysis, we found that although the patients in the OBCS group experienced a longer operation time, they had significantly less intraoperative bleeding, postoperative drainage, and hospitalization time compared to the MRM group. Furthermore, patients in the OBCS group demonstrated higher subjective satisfaction and quality of life scores, along with better objective outcomes. In terms of postoperative complications and recurrence rates, no significant difference was identified between the two groups. However, our multivariate Cox regression analysis identified lymph node metastasis and molecular type as independent prognostic factors for disease-free survival (DFS). Subsequently, we constructed a risk model based on these variables, which was proven to be effective in predicting recurrence, with an area under the risk score curve for recurrence prediction being 0.852. The group with a lower risk score demonstrated a significantly higher DFS rate. Our study suggests that compared with MRM, OBCS can significantly reduce surgical incision, improve patient satisfaction, and does not increase the risk of complications or recurrence. Our risk model, developed using Cox regression, also demonstrated high clinical value in predicting breast cancer recurrence, thereby aiding in personalized patient management and treatment planning.

Predictors of cognitive impairment in patients undergoing ileostomy for colorectal cancer: a retrospective analysis

Background

Early detection of cognitive impairment in patients undergoing ileostomy for colorectal cancer may help improve patient outcomes and quality of life. Identifying risk factors and clinically accessible factors is crucial for prevention and treatment.

Objective

This retrospective study aimed to identify risk factors for post-operative cognitive impairment in patients undergoing ileostomy for colorectal cancer and to explore potential factors for its prevention and treatment.

Methods

A total of 108 cases were selected and included in the study. Patient data including general characteristics, disease stage, complications, and chemotherapy status were collected, and sleep quality and cognitive function were assessed using questionnaires and follow-up. Patients were randomly divided into training and validation groups. A random forest model was used to rank clinical features based on their contribution to predicting the prognosis of cancer-related cognitive impairment (CRCI). Nomograms were constructed using the support vector machine-recursive feature elimination (SVM-RFE) method, and the minimal root-mean-square error (RMSE) values were compared to select the best model. Regression analysis was performed to determine independent predictors.

Results

Significant differences were observed in age, body mass index (BMI), alcohol consumption, frequency of physical activity, comorbidity, and cancer-related anemia (CRA) between the CRCI and non-CRCI groups. Random forest analysis revealed that age, BMI, exercise intensity, PSQI scores, and history of hypertension were the most significant predictors of outcome. Univariate logistic regression analysis of 18 variables revealed that age, alcohol consumption, exercise intensity, BMI, and comorbidity were significantly associated with the outcome of CRCI (p < 0.05). Univariate and multivariate models with P-values less than 0.1 and 0.2, respectively, showed better predictive performance for CRCI. The results of univariate analysis were plotted on a nomogram to evaluate the risk of developing CRCI after colorectal cancer surgery. The nomogram was found to have good predictive performance. Finally, regression analysis revealed that age, exercise intensity, BMI, comorbidity, and CRA were independent predictors of CRCI.

Conclusions

This retrospective cohort study revealed that age, exercise intensity, BMI, comorbidity, CRA, and mobility are independent predictors of cognitive impairment in patients undergoing ileostomy for colorectal cancer. Identifying these factors and potential factors may have clinical implications in predicting and managing post-operative cognitive impairment in this patient population.

ncRNA-mediated ceRNA regulatory network: Transcriptomic insights into breast cancer progression and treatment strategies

With the rapid development of next-generation sequencing technology, several studies have shown that ncRNAs can act as competitive endogenous RNAs (ceRNAs) and are involved in various biological processes, such as proliferation, differentiation, apoptosis, and migration of breast cancer (BC) cells, and plays an important role in BC progression as a molecular target for its diagnosis, treatment, prognosis, and differentiation of subtypes and age groups of BC patients. Based on the description of ceRNA-related biological functions, this study screened and sorted the sequencing analysis and experimental verification conclusions of BC-related ceRNAs and found that the ncRNAs mediated ceRNA networks can promote the development of BC by promoting the expression of genes related to BC proliferation, drug resistance, and apoptosis, inducing the production of epithelial-mesenchymal transition (EMT) to promote metastasis and activating cancer-related signaling pathways.

High-fiber-diet-related metabolites improve neurodegenerative symptoms in patients with obesity with diabetes mellitus by modulating the hippocampal-hypothalamic endocrine axis

Objective

Through transcriptomic and metabolomic analyses, this study examined the role of high-fiber diet in obesity complicated by diabetes and neurodegenerative symptoms.

Method

The expression matrix of high-fiber-diet-related metabolites, blood methylation profile associated with pre-symptomatic dementia in elderly patients with type 2 diabetes mellitus (T2DM), and high-throughput single-cell sequencing data of hippocampal samples from patients with Alzheimer's disease (AD) were retrieved from the Gene Expression Omnibus (GEO) database and through a literature search. Data were analyzed using principal component analysis (PCA) after quality control and data filtering to identify different cell clusters and candidate markers. A protein-protein interaction network was mapped using the STRING database. To further investigate the interaction among high-fiber-diet-related metabolites, methylation-related DEGs related to T2DM, and single-cell marker genes related to AD, AutoDock was used for semi-flexible molecular docking.

Result

Based on GEO database data and previous studies, 24 marker genes associated with high-fiber diet, T2DM, and AD were identified. Top 10 core genes include SYNE1, ANK2, SPEG, PDZD2, KALRN, PTPRM, PTPRK, BIN1, DOCK9, and NPNT, and their functions are primarily related to autophagy. According to molecular docking analysis, acetamidobenzoic acid, the most substantially altered metabolic marker associated with a high-fiber diet, had the strongest binding affinity for SPEG.

Conclusion

By targeting the SPEG protein in the hippocampus, acetamidobenzoic acid, a metabolite associated with high-fiber diet, may improve diabetic and neurodegenerative diseases in obese people.

Prognostic microRNAs associated with phosphoserine aminotransferase 1 in gastric cancer as markers of bone metastasis

This study analyzed PSAT1-targeted miRNAs as a prognostic predictor for gastric cancer. The relationship between the clinical manifestations of gastric cancer in patients and phosphoserine aminotransferase 1 (PSAT1) was analyzed using correlation analysis. PSAT1 was highly expressed in gastric cancer, and its low expression was associated with a poor prognosis. By pan-cancer analysis, PSAT1 could affect the tumor immune microenvironment by immune infiltration analysis. Nine microRNAs targeting PSAT1 and associated with gastric cancer were screened by miRwalk and microRNA expression in TCGA tumor tissues. Six microRNAs were obtained by survival curve analysis, including hsa-miR-1-3p, hsa-miR-139-5p, hsa-miR-145-5p, hsa-miR-195-5p, hsa-miR-218-5p, and hsa-miR-497-5p. Based on the above six microRNAs, a model for bone metastasis prediction in gastric cancer prediction was constructed. An analysis of a decision curve was performed based on the microRNAs obtained to predict bone metastasis from gastric cancer. It had a positive area under the curve (AUC) value of 0.746, and the decision curve analysis (DCA) indicated that it was clinically significant. Dual-luciferase reporter genes indicated that hsa-miR-497-5p and PSAT1 were targeted, and qRT-PCR results confirmed that hsa-miR-497-5p could down-regulate PSAT1 expression. MicroRNAs targeting the regulation of PSAT1 expression can well predict the prognosis of gastric cancer.

hsa-miR-518-5p/hsa-miR-3135b Regulates the REL/SOD2 Pathway in Ischemic Cerebral Infarction

Objectives

Ischemic cerebral infarction (ICI) is a fatal neurovascular disorder. A bioinformatics approach based on single-cell and bulk RNA-seq analyses was applied to investigate the pathways and genes involved in ICI and study the expression profile of these genes.

Methods

First, the aberrantly regulated “small-molecule ribonucleic acids” [microRNA (miRNAs)] and messenger RNAs (mRNAs) were analyzed using transcriptome data from the ischemic brain infarction dataset of the Gene Expression Omnibus (GEO) database. In mouse cerebrovascular monocytes, the single-cell regulatory network inference and clustering (SCENIC) workflow was used to identify key transcription factors (TFs). Then, the two miRNA-TF-mRNA interaction networks were constructed. Moreover, the molecular complex detection (MCODE) extracted the core sub-networks and identified the important TFs within these sub-networks. Finally, whole blood samples were collected for validation of the expression of critical molecules in ICI.

Results

We identified four cell types and 266 regulons in mouse cerebrovascular monocytes using SCENIC analysis. Moreover, 112 differently expressed miRNAs and 3,780 differentially expressed mRNAs were identified. We discovered potential biomarkers in ICI by building a miRNA-TF-mRNA interaction network. The hsa-miR-518-5p/hsa-miR-3135b/REL/SOD2 was found to play a potential role in ICI progression. The expression of REL and superoxide dismutase 2 (SOD2) was significantly elevated in the ICI group in the clinical cohort (P &lt; 0.05). Furthermore, a REL expression was elevated in endothelial cells and fibroblasts at the single-cell level, indicating that REL is a cell-specific regulon. Functional enrichment analyses revealed that REL is primarily engaged in neurotransmitter activity and oxidative phosphorylation.

Conclusions

Our research uncovered novel biomarkers for ICI of neurovascular disease. The hsa-miR-518-5p/hsa-miR-3135b may regulate the REL/SOD2 pathway in ICI progression.

Bioinformatic Characterization of Whole Blood Neutrophils in Pelvic Inflammatory Disease: A Potential Prognostic Indicator for Transumbilical Single-Port Laparoscopic Pelvic Abscess Surgery

The purpose of this research is to determine the prognosis of patients treated with transumbilical single-port laparoscopic surgery for acute pelvic inflammatory illness. Postoperative data on 129 patients treated with laparoscopic surgery for acute pelvic inflammatory illness were obtained retrospectively. It was observed that the shorter the time required for postoperative leukocyte recovery to normal, the shorter the time required for postoperative pain and diet recovery, as well as hospital stay, in such individuals. CIBERSORT was used to examine patient data from GEO. The most significant difference between the normal and pelvic inflammatory groups was in neutrophil content. Association study found a substantial positive correlation between the quantity of neutrophils infiltrating the immune system and the abundance of monocyte M0 infiltrating the immune system. Neutrophil immune infiltration was strongly inversely linked with plasma cells, activated CD8+ Tm cells, and active CD4+ Tm cells. Four mRNAs linked with pelvic inflammatory illness were revealed to be strongly associated with neutrophil immune infiltration, notably CALML4, COQ10B, DCPS, and PPP2R1A. The ROC revealed that CALML4 (area under the curve (AUC): 0.769, 95% confidence interval (CI): 0.638-0.881), COQ10B (AUC: 0.742, 95% CI: 0.587-0.881), PPP2R1A (AUC: 0.733 95% CI: 0.593-0.857), and DCPS (AUC: 0.745, 95% CI: 0.571-0.900) were potential markers for predicting pelvic inflammatory disease. CALML4, COQ10B, PPP2R1A, and DCPS may be critical determinants determining the amount of preoperative neutrophil infiltration and the time required for leukocyte recovery after single-port laparoscopy in acute pelvic inflammatory illness.

Exploring the Mechanism of Yiqi Qingre Ziyin Method in Regulating Neuropeptide Expression for the Treatment of Atrophic Rhinitis

Atrophic rhinitis (AR) is a chronic disease that causes severe structural changes to the nasal mucosa leading to squamous epithelial metaplasia. However, treatment regarding AR remains a major challenge. We used network pharmacology and molecular docking methods to explore the potential mechanisms of the Yiqi Qingre Ziyin method to modulate neuropeptides in the treatment of AR. The active ingredients of the Yiqi Qingre Ziyin method and their targets of action were obtained from the Traditional Chinese Medicine Systematic Pharmacology Database Analysis Platform (TCMSP). Disease targets for AR were obtained from four databases: GeneCards, PharmGKB, DrugBank, and Online Mendelian Inheritance in Man (OMIM). A total of 59 active ingredients, 39 potential targets, and 76 relevant neuropeptides were obtained after deduplication. We constructed target interaction networks with the STRING database. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the 14 potential target proteins. We used Cytoscape software to construct the “drug-active ingredient-potential target” and “ingredient-target-pathway” networks of the Yiqi Qingre Ziyin method for treating AR. Molecular docking results suggest that dipeptidyl peptidase 4 (DPP4), opioid receptor gene d1 (OPRD1), and opioid receptor m1 (OPRM1) are key targets for the Yiqi Qingre Ziyin method. Therefore, this study proposed a potential mechanism for the treatment of AR by affecting the expression of neuropeptide-related genes (including DPP4, OPRD1, and OPRM1), which may potentially improve the immune microenvironment of the nasal mucosa.

Preoperative Serum Calcitonin Level and Ultrasonographic Characteristics Predict the Risk of Metastatic Medullary Thyroid Carcinoma: Functional Analysis of Calcitonin-Related Genes

Background. Early cervical lymph node (LN) metastasis is an important cause of poor survival in patients with medullary thyroid cancer (MTC). This study evaluated whether the preoperative serum calcitonin level in combination with ultrasonographic features of MTC can be used to assess the LN status as well as predict the risk of metastasis in patients with MTC. Methods. We retrospectively analyzed the clinical data of 95 patients with MTC, and a nomogram model was constructed and validated. Using integrated database analysis of The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), we mined pathways wherein CALCA is involved, identified calcitonin-related genes, and analyzed their functions. Results. Correlation analysis revealed a significant association between the infiltrating range, diameter, calcification, blood flow, the preoperative serum calcitonin level, and metastasis. The metastasis risk-prediction model showed great accuracy in determining the risk of metastasis in MTC (area under the curve of the receiver operating characteristic [ROC] curve: 0.979 [95% confidence interval 0.946–1.000]). Decision curve analysis (DCA) showed that the model has excellent clinical utilization potential. Significantly, CALCA, the mRNA for calcitonin, was highly expressed in thyroid cancer tissues and associated with the cytokine–cytokine receptor and neuroactive ligand-receptor interaction pathways as well as the cell-adhesion molecules. ROC curve indicated that the CNTFR, CD27, GDF6, and TSLP genes, which are related to the cytokine–cytokine receptor interaction pathway, could indicate the risk of metastasis in MTC. Conclusions. The preoperative serum calcitonin level, in combination with ultrasonographic features, can be used to predict the risk of metastasis in patients with MTC and constitute a noninvasive accurate method for preoperative diagnosis of MTC.

The Neuronal Transcription Factor Creb3l1 Potential Upregulates Ntrk2 in the Hypertensive Microenvironment to Promote Vascular Smooth Muscle Cell-Neuron Interaction and Prevent Neurons from Ferroptosis: A Bioinformatic Research of scRNA-seq Data

Background

There is still a lack of knowledge regarding the association between hypertension and ferroptosis. A single-cell approach was used to study the changes in neuropeptide expression as they might contribute to the mechanisms leading to ferroptosis in a hypertensive microenvironment.

Methods

We analyzed 11798 cells from the SHR group and 12589 cells from the WKY group of mouse arterial cells. CellPhoneDB was used for cell communication analysis, and the SCENIC method was used to identify key transcription factors in neurons. The correlation between Ntrk2 and ferroptosis-related genes was further analyzed and validated via quantitative polymerase chain reaction.

Results

The arterial cells were clustered into six cell types. Ligand-receptor analysis suggested that Ngf, Ntf3, Cxcr4, and Ntrk2 were key neuropeptide-related genes involved in the communication between vascular smooth muscle cells and neural cells. In the hypertensive microenvironment, the neuronal transcription factor Creb3l1 appears to play a key role in the upregulation of Ntrk2 to promote the interaction between neurons and vascular smooth muscle cells. An association between Ntrk2 and the ferroptosis death inhibitor Gpx4 was suggested. RT-qPCR experiments confirmed that Ntrk2 downregulation in neural cells was followed by downregulated expression of Gpx4.

Conclusions

Creb3l1, a key transcription factor in vascular neurons, may upregulate Ntrk2 to promote vascular smooth muscle cell-neuron interaction and thereby potentially prevent ferroptosis in neurons.

Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning

Objectives

Synovial fibroblasts (SFs) play an important role in the development and progression of rheumatoid arthritis (RA). However, the pathogenic mechanism of SFs remains unclear. The objective of this study was to investigate how neuropeptides and N6-methyladenosine (m6A) played an important role in the underlying pathogenic processes of SFs that contribute to the development of RA.

Methods

Single-cell RNA sequencing data were examined using single-cell analysis and machine learning. SF subgroups were identified based on the clustering and annotation results of the single-cell analysis. Moreover, cell–cell communication was used to analyse neuropeptide-related receptor and ligand pairs on the surface of SF cell membranes. Machine learning was used to explore the m6A factors acting on these neuropeptide genes.

Results

NPR3, GHR, BDKRB2, and CALCRL, four neuropeptide genes, were shown to be differently expressed among SF subgroups. Further investigation of receptor–ligand interactions found that NPR3 (in conjunction with NPPC, OSTN, NPPB, and NPPA) and GHR (in conjunction with GH1 and GH2) may have a role in SF interactions. As predicted by machine learning, IGFBP2 and METTL3 were identified as key factors regulating m6A of NPR3 and GHR. The expression levels and enrichment pathways of METTL3 and IGFBP2 were different among SF subgroups.

Conclusions

Single-cell analysis and machine learning efficiently identified neuropeptide genes and m6A factors that perform important regulatory functions in RA. Our strategy may provide a basis for future studies to identify pathogenic cell subpopulations and molecular mechanisms in RA and other diseases.

A Hyperglycemic Microenvironment Inhibits Tendon-to-Bone Healing through the let-7b-5p/CFTR Pathway

Background

Tendon-to-bone healing is a difficult process in treatment of rotator cuff tear (RCT). In addition, diabetes is an important risk factor for poor tendon-to-bone healing. Therefore, we investigated the specific mechanisms through which diabetes affects tendon-to-bone healing by regulating the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR).

Methods

Tendon-derived stem cells (TDSCs) were extracted from rats after which their proliferative capacities were evaluated by the MTT assay. The expression levels of CFTR and tendon-related markers were determined by qRT-PCR. Then, bioinformatics analyses and dual luciferase reporter gene assays were used to identify miRNAs with the ability to bind CFTR mRNA. Finally, CFTR was overexpressed in TDSCs to validate the specific mechanisms through which the high glucose microenvironment inhibits tendon-to-bone healing.

Results

The high glucose microenvironment downregulated mRNA expression levels of tendon-related markers and CFTR in TDSCs cultured with different glucose concentrations. Additionally, bioinformatics analyses revealed that let-7b-5p may be regulated by the high glucose microenvironment and can regulate CFTR levels. Moreover, a dual luciferase reporter gene assay was used to confirm that let-7b-5p targets and binds CFTR mRNA. Additional experiments also confirmed that overexpressed CFTR effectively reversed the negative effects of the hyperglycaemic microenvironment and upregulation of let-7b-5p on TDSC proliferation and differentiation. These findings imply that the hyperglycemic microenvironment inhibits CFTR transcription and, consequently, proliferation and differentiation of TDSCs in vitro by upregulating let-7b-5p.

Conclusions

A hyperglycemic microenvironment inhibits TDSC proliferation in vitro via the let-7b-5p/CFTR pathway, and this is a potential mechanism in diabetes-induced poor tendon-to-bone healing.

Transcription Factors Leading to High Expression of Neuropeptide L1CAM in Brain Metastases from Lung Adenocarcinoma and Clinical Prognostic Analysis

Background

There is a lack of understanding of the development of metastasis in lung adenocarcinoma (LUAD). This study is aimed at exploring the upstream regulatory transcription factors of L1 cell adhesion molecule (L1CAM) and to construct a prognostic model to predict the risk of brain metastasis in LUAD.

Methods

Differences in gene expression between LUAD and brain metastatic LUAD were analyzed using the Wilcoxon rank-sum test. The GRNdb (http://www.grndb.com) was used to reveal the upstream regulatory transcription factors of L1CAM in LUAD. Single-cell expression profile data (GSE131907) were obtained from the transcriptome data of 10 metastatic brain tissue samples. LUAD prognostic nomogram prediction models were constructed based on the identified significant transcription factors and L1CAM.

Results

Survival analysis suggested that high L1CAM expression was negatively significantly associated with overall survival, disease-specific survival, and prognosis in the progression-free interval (p < 0.05). The box plot indicates that high expression of L1CAM was associated with distant metastases in LUAD, while ROC curves suggested that high expression of L1CAM was associated with poor prognosis. FOSL2, HOXA9, IRF4, IKZF1, STAT1, FLI1, ETS1, E2F7, and ADARB1 are potential upstream transcriptional regulators of L1CAM. Single-cell data analysis revealed that the expression of L1CAM was found significantly and positively correlated with the expression of ETS1, FOSL2, and STAT1 in brain metastases. L1CAM, ETS1, FOSL2, and STAT1 were used to construct the LUAD prognostic nomogram prediction model, and the ROC curves suggest that the constructed nomogram possesses good predictive power.

Conclusion

By bioinformatics methods, ETS1, FOSL2, and STAT1 were identified as potential transcriptional regulators of L1CAM in this study. This will help to facilitate the early identification of patients at high risk of metastasis.

Mechanism and Role of the Neuropeptide LGI1 Receptor ADAM23 in Regulating Biomarkers of Ferroptosis and Progression of Esophageal Cancer

Background

According to recent studies, ferroptosis is closely related to the efficacy and prognosis of tumour treatment. However, the role of ferroptosis in esophageal squamous cell carcinoma (ESCC) has not been explored comprehensively.

Materials and Methods

The esophageal cancer (EC) transcriptome data was downloaded from The Cancer Genome Atlas (TCGA), then analyzed, to obtain the differentially expressed messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA) between groups with the low and high Ferroptosis Potential Index (FPI) and construct a ferroptosis-associated ceRNA network. In addition, the expression of ARHGEF26-AS1 and miR-372-3p in ESCC cell lines was assessed, and the appropriate cell lines were selected. The interaction between ARHGEF26-AS1, miR-372-3p, and ADAM23 was also determined through a dual-luciferase reporter assay. Moreover, the Western blot, Cell Counting Kit-8 (CCK-8), wound healing, cell viability, and cell death assays were conducted to establish the biological functions of the ARHGEF26-AS1/miR-372-3p/ADAM23 pathway in ESCCs.

Results

An FPI scoring model reflecting the activity of the ferroptosis pathway was constructed, and a ferroptosis-associated ceRNA network was established. The findings revealed that low expression of ADAM23 and ARHGEF26-AS1 as well as high expression of miR-372-3p was associated with poor prognosis and a lower FPI score in EC patients. Functionally, overexpression of ADAM23 and ARHGEF26-AS1 and the miR-372-3p inhibitor not only promoted ferroptosis in ESCC cells in vitro but also inhibited the proliferation and migration of cells. Mechanistically, ARHGEF26-AS1 upregulated the expression of ADAM23 by competitively binding to miR-372-3p.

Conclusions

The study showed that the lncRNA, ARHGEF26-AS1 acts as a miR-372-3p sponge that regulates the neuropeptide LGI1 receptor ADAM23 expression. This in turn not only inhibits the proliferation and migration of ESCC cells but also upregulates the ferroptosis pathway. A neuropeptide-related ferroptosis regulatory pathway was identified in this study.

Exploring the Potential Mechanisms of Melilotus officinalis (L.) Pall. in Chronic Muscle Repair Patterns Using Single Cell Receptor-Ligand Marker Analysis and Molecular Dynamics Simulations

Information regarding the function of Melilotus officinalis (L.) Pall. in skeletal muscles is still unknown. In this study, we explored the possible regulatory targets of M. (L.) Pall. that affects the repair patterns in chronic muscle injury. We analyzed the potential target genes and chemical composition of M. (L.) Pall. and constructed a "drug-component-disease target genes" network analysis. Five active ingredients and 87 corresponding targets were obtained. Muscle-tendon junction (MTJ) cells were used to perform receptor-ligand marker analysis using the CellphoneDB algorithm. Targets of M. (L.) Pall. were screened further for the cellular ligand-receptor protein action on MTJs. Enrichment analysis suggests that those protein-associated ligand receptors may be associated with a range of intercellular signaling pathways. Molecular docking validation was then performed. Five proteins (CCL2, VEGFA, MMP2, MET, and EGFR) may be regulated by the active ingredient luteolin and scoparone. Finally, molecular dynamics simulations revealed that luteolin can stably target binding to MMP2. M. (L.) Pall. influences skeletal muscle repair patterns by affecting the fibroblast interactions in the muscle-tendon junctions through the active ingredients luteolin and scoparone.

Exercise Modifies the Transcriptional Regulatory Features of Monocytes in Alzheimer's Patients: A Multi-Omics Integration Analysis Based on Single Cell Technology

Monocytes have been reported to be important mediators of the protective effect of exercise against the development of Alzheimer's disease (AD). This study aims explored the mechanism by which monocytes achieve this. Using single cell transcriptome analysis, results showed that CD14 + and CD16 + monocytes interacted with other cells in the circulating blood. TNF, CCR1, APP, and AREG, the key ligand-receptor-related genes, were found to be differentially expressed between exercise-treated and AD patients. The SCENIC analysis was performed to identify individual clusters of the key transcription factors (TFs). Nine clusters (M1-M9) were obtained from the co-expression network. Among the identified TFs, MAFB, HES4, and FOSL1 were found to be differentially expressed in AD. Moreover, the M4 cluster to which MAFB, HES4, and FOSL1 belonged was defined as the signature cluster for AD phenotype. Differential analysis by bulkRNA-seq revealed that the expression of TNF, CCR1, and APP were all upregulated after exercise (p < 0.05). And ATF3, MAFB, HES4, and KLF4 that were identified in M4 clusters may be the TFs that regulate TNF, CCR1, and APP in exercise prescription. After that, APP, CCR1, TNF, ATF3, KLF4, HES4, and MAFB formed a regulatory network in the ERADMT gene set, and all of them were mechanistically linked. The ERADMT gene set has been found to be a potential risk marker for the development of AD and can be used as an indicator of compliance to exercise therapy in AD patients. Using single-cell integration analysis, a network of exercise-regulating TFs in monocytes was constructed for AD disease. The constructed network reveals the mechanism by which exercise regulated monocytes to confer therapeutic benefits against AD and its complications. However, this study, as a bioinformatic research, requires further experimental validation.

Identification of KLF6/PSGs and NPY-Related USF2/CEACAM Transcriptional Regulatory Networks via Spinal Cord Bulk and Single-Cell RNA-Seq Analysis

Background

To further understand the development of the spinal cord, an exploration of the patterns and transcriptional features of spinal cord development in newborn mice at the cellular transcriptome level was carried out.

Methods

The mouse single-cell sequencing (scRNA-seq) dataset was downloaded from the GSE108788 dataset. Single-cell RNA-Seq (scRNA-Seq) was conducted on cervical and lumbar spinal V2a interneurons from 2 P0 neonates. Single-cell analysis using the Seurat package was completed, and marker mRNAs were identified for each cluster. Then, pseudotemporal analysis was used to analyze the transcription changes of marker mRNAs in different clusters over time. Finally, the functions of these marker mRNAs were assessed by enrichment analysis and protein-protein interaction (PPI) networks. A transcriptional regulatory network was then constructed using the TRRUST dataset.

Results

A total of 949 cells were screened. Single-cell analysis was conducted based on marker mRNAs of each cluster, which revealed the heterogeneity of neonatal mouse spinal cord neuronal cells. Functional analysis of pseudotemporal trajectory-related marker mRNAs suggested that pregnancy-specific glycoproteins (PSGs) and carcinoembryonic antigen cell adhesion molecules (CEACAMs) were the core mRNAs in cluster 3. GSVA analysis then demonstrated that the different clusters had differences in pathway activity. By constructing a transcriptional regulatory network, USF2 was identified to be a transcriptional regulator of CEACAM1 and CEACAM5, while KLF6 was identified to be a transcriptional regulator of PSG3 and PSG5. This conclusion was then validated using the Genotype-Tissue Expression (GTEx) spinal cord transcriptome dataset.

Conclusions

This study completed an integrated analysis of a single-cell dataset with the utilization of marker mRNAs. USF2/CEACAM1&5 and KLF6/PSG3&5 transcriptional regulatory networks were identified by spinal cord single-cell analysis.

Integrative Bioinformatics Analysis Reveals That Infarct-Mediated Overexpression of Potential miR-662/CREB1 Pathway-Induced Neuropeptide VIP Is Associated with the Risk of Atrial Fibrillation: A Correlation Analysis between Myocardial Electrophysiology and Neuroendocrine

Background

Neuropeptide levels are closely associated with the development and maintenance of atrial fibrillation (AF) after myocardial infarction (MI). This study was aimed at investigating the regulatory network that affects neuropeptide expression through transcription factor modulation.

Methods

We downloaded three datasets from the GEO database, and after performing differential and crosstabulation analyses, we screened out differentially expressed (DE) miRNAs and DEmRNAs coexpressed in AF and MI and performed DEmiRNA–DEmRNA pairing prediction; from which, we constructed a regulatory network. Subsequently, the hsa-miR-662-CREB1-VIP axis was obtained, and the role of CREB1 and VIP in the development of AF after MI was further revealed by single-cell analysis and prediction model construction.

Results

In this study, eight DEmRNAs and four miRNAs were screened. hsa-miR-662 was identified by database integration analysis to regulate the transcription factor CREB1, a potential transcriptional regulator in VIP. CREB1 and VIP are mainly enriched in pathways of energy metabolism, ion channels, and myocardial contraction. CREB1 and VIP were identified as biomarkers of the onset and prognosis of MI and AF.

Conclusions

In this study, the miR-662/CREB1/VIP regulatory pathway was constructed through integrated analysis of datasets, thus providing new ideas to study the mechanisms of AF development.