An integrative microenvironment approach for laryngeal carcinoma: the role of immune/methylation/autophagy signatures on disease clinical prognosis and single-cell genotypes

Exploring the prognostic analysis of autophagy and tumor microenvironment based on monocyte cells in lung cancer

A deep understanding of the biological mechanisms of lung cancer offers more precise treatment options for patients. In our study, we integrated data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) to investigate lung adenocarcinoma. Analyzing 538 lung cancer samples and 31 normal samples, we focused on 3076 autophagy-related genes. Using Seurat, dplyr, tidyverse, and ggplot2, we conducted single-cell data analysis, assessing the quality and performing Principal Component Analysis (PCA) and t-SNE analyses. Differential analysis of TCGA data using the "Limma" package, followed by immune infiltration analysis using the CIBERSORT algorithm, led us to identify seven key genes. These genes underwent further scrutiny through consensus clustering and gene set variation analysis (GSVA). We developed a prognostic model using Lasso Cox regression and multivariable Cox analysis, which was then validated with a nomogram, predicting survival rates for lung adenocarcinoma. The model's accuracy and universality were corroborated by ROC curves. Additionally, we explored the relationship between immune checkpoint genes and immune cell infiltration and identified two key genes, HLA-DQB1 and OLR1. This highlighted their potential as therapeutic targets. Our comprehensive approach sheds light on the molecular landscape of lung adenocarcinoma and offers insights into potential treatment strategies, emphasizing the importance of integrating single-cell and genomic data in cancer research.

Exploring the role of differentially expressed metabolic genes and their mechanisms in bone metastatic prostate cancer

Background

Approximately 10-20% of patients diagnosed with prostate cancer (PCa) evolve into castration-resistant prostate cancer (CRPC), while nearly 90% of patients with metastatic CRPC (mCRPC) exhibit osseous metastases (BM). These BM are intimately correlated with the stability of the tumour microenvironment.

Purpose

This study aspires to uncover the metabolism-related genes and the underlying mechanisms responsible for bone metastatic prostate cancer (BMPCa).

Methods

Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets of PCa and BM were analyzed through R Studio software to identify differentially expressed genes (DEGs). The DEGs underwent functional enrichment via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), with key factors screened by a random forest utilized to establish a prognostic model for PCa. The study explored the relationship between DEGs and the stability of the immune microenvironment. The action and specificity of CRISP3 in PCa was validated through western blot analysis, CCK-8 assay, scratch assay, and cellular assay.

Results

The screening of GEO and TCGA datasets resulted in the identification of 199 co-differential genes. Three DEGs, including DES, HBB, and SLPI, were selected by random forest classification model and cox regression model. Immuno-infiltration analysis disclosed that a higher infiltration of naïve B cells and resting CD4 memory T cells occurred in the high-expression group of DES, whereas infiltration of resting M1 macrophages and NK cells was greater in the low-expression group of DES. A significant infiltration of neutrophils was observed in the high-expression group of HBB, while greater infiltration of gamma delta T cells and M1 macrophages was noted in the low-expression group of HBB. Resting dendritic cells, CD8 T cells, and resting T regulatory cells (Tregs) infiltrated significantly in the high-expression group of SLPI, while only resting mast cells infiltrated significantly in the low-expression group of SLPI. CRISP3 was established as a critical gene in BMPCa linked to DES expression. Targeting CRISP3, d-glucopyranose may impact tumour prognosis. During the mechanistic experiments, it was established that CRISP3 can advance the proliferation and metastatic potential of PCa by advancing epithelial-to-mesenchymal transition (EMT).

Conclusion

By modulating lipid metabolism and maintaining immunological and microenvironmental balance, DES, HBB, and SLPI suppress prostate cancer cell growth. The presence of DES-associated CRISP3 is a harbinger of unfavorable outcomes in prostate cancer and may escalate tumor proliferation and metastatic capabilities by inducing epithelial-mesenchymal transition.

Metabolomic analysis of vascular cognitive impairment due to hepatocellular carcinoma

Introduction

Screening for metabolically relevant differentially expressed genes (DEGs) shared by hepatocellular carcinoma (HCC) and vascular cognitive impairment (VCI) to explore the possible mechanisms of HCC-induced VCI.

Methods

Based on metabolomic and gene expression data for HCC and VCI, 14 genes were identified as being associated with changes in HCC metabolites, and 71 genes were associated with changes in VCI metabolites. Multi-omics analysis was used to screen 360 DEGs associated with HCC metabolism and 63 DEGs associated with VCI metabolism.

Results

According to the Cancer Genome Atlas (TCGA) database, 882 HCC-associated DEGs were identified and 343 VCI-associated DEGs were identified. Eight genes were found at the intersection of these two gene sets: NNMT, PHGDH, NR1I2, CYP2J2, PON1, APOC2, CCL2, and SOCS3. The HCC metabolomics prognostic model was constructed and proved to have a good prognostic effect. The HCC metabolomics prognostic model was constructed and proved to have a good prognostic effect. Following principal component analyses (PCA), functional enrichment analyses, immune function analyses, and TMB analyses, these eight DEGs were identified as possibly affecting HCC-induced VCI and the immune microenvironment. As well as gene expression and gene set enrichment analyses (GSEA), a potential drug screen was conducted to investigate the possible mechanisms involved in HCC-induced VCI. The drug screening revealed the potential clinical efficacy of A-443654, A-770041, AP-24534, BI-2536, BMS- 509744, CGP-60474, and CGP-082996.

Conclusion

HCC-associated metabolic DEGs may influence the development of VCI in HCC patients.

Cuproptosis-associated CDKN2A is targeted by plicamycin to regulate the microenvironment in patients with head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), the most common malignancy of the head and neck, has an overall 5-year survival rate of <50%. Genes associated with cuproptosis, a newly identified copper-dependent form of cell death, are aberrantly expressed in various tumours. However, their role in HNSCC remains unknown. In this study, bioinformatic analysis revealed that the cuproptosis-related gene CDKN2A was correlated with the malignant behaviour of HNSCC. Kaplan-Meier (KM) curves showed that patients with high CDKN2A expression had a better prognosis. Multiomic analysis revealed that CDKN2A may be associated with cell cycle and immune cell infiltration in the tumour microenvironment and is important for maintaining systemic homeostasis in the body. Furthermore, molecular docking and molecular dynamics simulations suggested strong binding between plicamycin and CDKN2A. And plicamycin inhibits the progression of HNSCC in cellular assays. In conclusion, this study elucidated a potential mechanism of action of the cuproptosis-associated gene CDKN2A in HNSCC and revealed that plicamycin targets CDKN2A to improve the prognosis of patients.

ATP6AP1 is a potential prognostic biomarker and is associated with iron metabolism in breast cancer

Cancer occurrence and progression may be facilitated by aberrant expression of ATPase H+ transporting accessory protein 1 (ATP6AP1). However, the clinical relevance of ATP6AP1 in breast cancer remains unclear. In this study, we investigated the association between ATP6AP1 and breast cancer. Data collected from patients with breast cancer from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were used in this study. To determine the relationship between ATP6AP1 and breast cancer survival rates, Kaplan-Meier analysis was used. To determine the prognostic value of ATP6AP1, a receiver operating characteristic (ROC) curve was constructed. To identify the major pathways involving ATP6AP1, we performed functional enrichment analysis using gene set enrichment analysis (GSEA). We analyzed the association between ATP6AP1 expression and tumor immunity using the ESTIMATE algorithm and single-sample GSEA (ssGSEA). A nomogram based on a Cox regression analysis was constructed to predict the impact of ATP6AP1 on prognosis. ATP6AP1 expression was significantly upregulated in breast cancer tissues. Moreover, patients with elevated ATP6AP1 expression had shorter total survival rates than those with lower expression levels (p = 0.032). The area under the receiver operating characteristic curve for ATP6AP1 was 0.939. Gene set enrichment analysis revealed that reaction iron uptake and transport, proteasome degradation, glutathione metabolism, and pyruvate metabolism were enriched in the ATP6AP1 high expression phenotype. The relationship between immune infiltration cells and ATP6AP1 expression, including macrophages, B cells, dendritic cells, cytotoxic cells, NK cells, and T cells, was found to be negative, suggesting that ATP6AP1 overexpression results in immunosuppression. Based on the Cox regression analyses, the calibration plot of the nomogram demonstrated effective performance in predicting breast cancer patients. ATP6AP1 may facilitate breast cancer progression by inhibiting antitumor immunity and promoting iron metabolism and may be a biomarker for breast cancer prognosis.

Role of Ultrasound Imaging in the Prediction of TRIM67 in Brain Metastases From Breast Cancer

Objectives

Ultrasound (US) imaging is a relatively novel strategy to monitor the activity of the blood–brain barrier, which can facilitate the diagnosis and treatment of neurovascular-related metastatic tumors. The purpose of this study was to investigate the clinical significance of applying a combination of US imaging outcomes and the associated genes. This was performed to construct line drawings to facilitate the prediction of brain metastases arising from breast cancer.

Methods

The RNA transcript data from The Cancer Genome Atlas (TCGA) database was obtained for breast cancer, and the differentially expressed genes (DEGs) associated with tumor and brain tumor metastases were identified. Subsequently, key genes associated with survival prognosis were subsequently identified from the DEGs.

Results

Tripartite motif-containing protein 67 (TRIM67) was identified and the differential; in addition, the survival analyses of the TCGA database revealed that it was associated with brain tumor metastases and overall survival prognosis. Applying independent clinical cohort data, US-related features (microcalcification and lymph node metastasis) were associated with breast cancer tumor metastasis. Furthermore, ultrasonographic findings of microcalcifications showed correlations with TRIM67 expression. The study results revealed that six variables [stage, TRIM67, tumor size, regional lymph node staging (N), age, and HER2 status] were suitable predictors of tumor metastasis by applying support vector machine–recursive feature elimination. Among these, US-predicted tumor size correlated with tumor size classification, whereas US-predicted lymph node metastasis correlated with tumor N classification. The TRIM67 upregulation was accompanied by upregulation of the integrated breast cancer pathway; however, it leads to the downregulation of the miRNA targets in ECM and membrane receptors and the miRNAs involved in DNA damage response pathways.

Conclusions

The TRIM67 is a risk factor associated with brain metastases from breast cancer and it is considered a prognostic survival factor. The nomogram constructed from six variables—stage, TRIM67, tumor size, N, age, HER2 status—is an appropriate predictor to estimate the occurrence of breast cancer metastasis.

Single-Cell Transcriptome Analysis Reveals the Importance of IRF1/FSTL1 in Synovial Fibroblast Subsets for the Development of Rheumatoid Arthritis

Objectives

This study aimed to investigate the potential role of synovial fibroblasts (SFs) in the development of rheumatoid arthritis (RA) to identify potential molecular targets and provide a theoretical basis for the treatment of RA.

Methods

GSE109449, a fibroblast transcriptome dataset of synovial tissue from RA and osteoarthritis (OA), were obtained from the GEO database. After standard cell quality control, this single-cell transcriptome data was used to perform routine single-cell analysis processes. After completing dimensionality reduction, clustering, and cell subset identification of fibroblasts, the SCENIC analysis helped calculate the significant gene regulatory networks in fibroblasts and their subsets. From these computed gene regulatory networks, the regulon in which follistatin-like protein 1 (FSTL1) resides was extracted and used to analyze the transcriptional regulatory status of fibroblasts. Finally, the gene set enrichment analysis (GSEA) was used to calculate the respective enriched gene sets of IRF1 and FSTL1.

Results

Three SF subgroups were identified from the single-cell transcriptome analysis; SF subset 3 was more abundant in RA than in OA (p < 0.001). From the SCENIC analysis, we obtained 269 regulons and the corresponding gene regulatory networks in SF from the RA datasets. Next, we screened and obtained a regulon-containing FSTL1, where IRF1 was the major transcription factor. The top five regulons in SF subset 3 were TWIST1, MECOM, KLF6, MAFB, and RUNX1. Among the 3 SF subsets, IRF1 regulon was ranked the highest in SF subset 3. Differential analysis of pseudobulk RNA-seq showed that IRF1 was up-regulated in RA compared to OA. Between the three SF subgroups, IRF1 and FSTL1 expression was more up-regulated in SF subset 3 compared to the other two subgroups.

Conclusions

IRF1 was found to regulate the invasiveness of SFs by regulating FSTL1, which may influence the disease progression of RA.

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.

Eucommia ulmoides Oliver-Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke

Background

In this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions and IS via the ferroptosis pathway.

Methods

We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated.

Results

There were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS.

Conclusions

The active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.

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.

Bioinformatic Analysis and Cellular Assays Identify Substance P Influencing Th17/Treg Differentiation via the MyD88 Pathway as a Potential Contributor to the Progression of Asthma and Allergic Rhinitis

Objective

This study is aimed at investigating the role of substance P (SP) in the development of asthma.

Methods

The Gene Expression Omnibus (GEO) database was used to characterize SP expression in allergic rhinitis (AR) and asthma. Peripheral blood was collected from patients with asthma or AR. The expression of relevant cytokines and neuropeptides was measured. Enzyme-linked immunosorbent assay (ELISA) was also performed. The mast cell line LAD2 and the lung bronchial epithelial cell line BEAS-2B were treated with different concentrations of SP concentration. Then, the qRT-PCR method was used to determine the mRNA expression. Furthermore, p38 and p65 and their associated phosphorylated proteins (p-p38 and p-p65) were further validated by western blotting.

Result

Clinical and GSE75011 data analysis suggested that MyD88 expression was upregulated in AR and asthma. Through the gene set variation analysis (GSVA), MyD88-related pathways were noticed and further investigated. ELISA results suggested that the SP expression was significantly increased in AR and asthma and IL-10 expression was decreased, whereas the expression of IL-6, IL-17A, IL-23, and TGF-β expressions increased. The mast cell line LAD2 was treated with different SP concentrations, and ELISA results showed that the expression of IL-6, IL-17A, IL-23, and TGF-β in the cell supernatant gradually increased with increasing SP concentrations, whereas that of IL-10 decreased. The lung bronchial epithelial cell line BEAS-2B was treated with different SP concentrations, and the expression of myeloid differentiation factor 88 (MyD88) and its related proteins was elevated. The expression of p38 and p-p38 proteins was elevated after SP treatment, and their expression levels elevated as SP concentrations increased. Finally, MyD88 expression at the single-cell level was also demonstrated.

Conclusion

SP may affect the cytokine expression through the MyD88 pathway, thereby influencing Th17/Treg differentiation and eventually participating in the pathological process of asthma and AR. There are many pathological similarities between allergic rhinitis (AR) and bronchial asthma. In the present study, SP was found to possibly activate downstream inflammatory signaling pathways via MyD88, thereby affecting Th17/Treg differentiation and ultimately participating in the pathological process of asthma and AR.

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.

Serum Exosomal lncRNA AC007099.1 Regulates the Expression of Neuropeptide-Related FAP, as a Potential Biomarker for Hepatocarcinogenesis

Neuropeptide-associated fibroblast activation protein (FAP) may be an important risk factor for neurovascular metastasis in hepatocellular carcinoma. Analysis of The Cancer Genome Atlas (TCGA) database showed that FAP mRNA was highly expressed in most human tumor tissues. The HPA database then verified that FAP was highly expressed in tumor tissues following protein translation. Survival analysis then showed that the level of FAP expression significantly affected the overall survival (OS), progress free interval (PFI), and disease specific survival (DSS) of patients with hepatocellular carcinoma. A high expression of FAP in tumor tissue is associated with poor patient prognosis. According to the results of spearman correlation, AC009099 and FAP were negatively correlated with miR-7152 expression, while AC009099 and FAP expression were positively correlated. The lncRNA AC007099.1, which may serve as a potential target for the treatment of hepatocellular carcinoma, was associated with liver cancer. AC007099.1/miR-7152/FAP was found to be associated with immune infiltration in patients with hepatocellular carcinoma. Enrichment analysis suggests that the AC009099/miR-7152/FAP ceRNA regulatory network is associated with neuropeptide functional pathways. In conclusion, a neuropeptide-related AC009099/miR-7152/FAP ceRNA regulatory network was constructed in this study.

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.

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.

VEGF Family Gene Expression as Prognostic Biomarkers for Alzheimer's Disease and Primary Liver Cancer

BACKGROUND

To analyze the expression of vascular endothelial growth factor (VEGF) in hepatocellular carcinoma (HCC) and cognitive impairment, explore the relationship between the expression of VEGF family genes and prognosis of patients with HCC, and evaluate the predictive ability of VEGF in cognitive impairment using computerized methods.

METHODS

VEGF expression in liver cancer tissues and normal tissues was analyzed using bioinformatics methods. The Kaplan-Meier survival analysis method was also used to analyze the relationship between VEGF expression and the prognosis of patients with HCC. Furthermore, immune infiltration assessment and gene set enrichment analysis were performed. Meanwhile, the differential expression of VEGF family genes between patients with Alzheimer's disease (AD) and healthy controls was also checked.

RESULTS

Based on The Cancer Genome Atlas (TCGA) database, the VEGF family genes (VEFGA, VEGFB, VEGFC, and VEGFD) were highly expressed in cancer tissues and were significantly associated with poor prognosis in HCC. In HCC, the VEGF family genes showed significant heterogeneity in their functional and immune infiltration characteristics. Finally, VEGF family genes were identified as prognostic biomarkers in AD and risk prediction markers in HCC.

CONCLUSIONS

VEGF is highly expressed in patients with HCC and lowly expressed in patients with AD. VEGF has opposite opposing roles in the treatment of tumors and cognitive impairment.

Single-Cell Integration Analysis of Heterotopic Ossification and Fibrocartilage Developmental Lineage: Endoplasmic Reticulum Stress Effector Xbp1 Transcriptionally Regulates the Notch Signaling Pathway to Mediate Fibrocartilage Differentiation

INTRODUCTION

Regeneration of fibrochondrocytes is essential for the healing of the tendon-bone interface (TBI), which is similar to the formation of neurogenic heterotopic ossification (HO). Through single-cell integrative analysis, this study explored the homogeneity of HO cells and fibrochondrocytes.

METHODS

This study integrated six datasets, namely, GSE94683, GSE144306, GSE168153, GSE138515, GSE102929, and GSE110993. The differentiation trajectory and key transcription factors (TFs) for HO occurrence were systematically analyzed by integrating single-cell RNA (scRNA) sequencing, bulk RNA sequencing, and assay of transposase accessible chromatin seq. The differential expression and enrichment pathways of TFs in heterotopically ossified tissues were identified.

RESULTS

HO that mimicked pathological cells was classified into HO1 and HO2 cell subsets. Results of the pseudo-temporal sequence analysis suggested that HO2 is a differentiated precursor cell of HO1. The analysis of integrated scRNA data revealed that ectopically ossified cells have similar transcriptional characteristics to cells in the fibrocartilaginous zone of tendons. The modified SCENIC method was used to identify specific transcriptional regulators associated with ectopic ossification. Xbp1 was defined as a common key transcriptional regulator of ectopically ossified tissues and the fibrocartilaginous zone of tendons. Subsequently, the CellPhoneDB database was completed for the cellular ligand-receptor analysis. With further pathway screening, this study is the first to propose that Xbp1 may upregulate the Notch signaling pathway through Jag1 transcription. Twenty-four microRNAs were screened and were found to be potentially associated with upregulation of XBP1 expression after acute ischemic stroke.

CONCLUSION

A systematic analysis of the differentiation landscape and cellular homogeneity facilitated a molecular understanding of the phenotypic similarities between cells in the fibrocartilaginous region of tendon and HO cells. Furthermore, by identifying Xbp1 as a hub regulator and by conducting a ligand-receptor analysis, we propose a potential Xbp1/Jag1/Notch signaling pathway.

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

This study sought to perform integrative analysis of the immune/methylation/autophagy landscape on breast cancer prognosis and single-cell genotypes. Breast Cancer Recurrence Risk Score (BCRRS) and Breast Cancer Prognostic Risk Score (BCPRS) were determined based on 6 prognostic IMAAGs obtained from the TCGA-BRCA cohort. BCRRS and BCPRS, respectively, were used to construct a risk prediction model of overall survival and progression-free survival. Predictive capacity of the model was evaluated using clinical data. Analysis showed that BCRRS is associated with a high risk of stroke. In addition, PPI and drug-ceRNA networks based on differences in BCPRS were constructed. Single cells were genotyped through integrated scRNA-seq of the TNBC samples based on clustering results of BCPRS-related genes. The findings of this study show the potential regulatory effects of IMAAGs on breast cancer tumor microenvironment. High AUCs of 0.856 and 0.842 were obtained for the OS and PFS prognostic models, respectively. scRNA-seq analysis showed high expression levels of adipocytes and adipose tissue macrophages (ATMs) in high BCPRS clusters. Moreover, analysis of ligand-receptor interactions and potential regulatory mechanisms were performed. The LINC00276&MALAT1/miR-206/FZD4-Wnt7b pathway was also identified which may be useful in future research on targets against breast cancer metastasis and recurrence. Neural network-based deep learning models using BCPRS-related genes showed that these genes can be used to map the tumor microenvironment. In summary, analysis of IMAAGs, BCPRS, and BCRRS provides information on the breast cancer microenvironment at both the macro- and microlevels and provides a basis for development of personalized treatment therapy.