NPR3, transcriptionally regulated by POU2F1, inhibits osteosarcoma cell growth through blocking the PI3K/AKT pathway

Identification of a novel immune-related gene signature by single-cell and bulk sequencing for the prediction of the immune landscape and prognosis of breast cancer

BACKGROUND

As a common cause of cancer-related deaths in women, BRCA (breast cancer) shows complexity and requires precise biomarkers and treatment methods. This study delves into the molecular makeup of BRCA, focusing on immune profiles, molecular subtypes, gene expression and single-cell analysis.

METHODS

XCell was used to assess immune infiltration based on TCGA (the Cancer Genome Atlas) data and the clustering analysis was made. Differentially expressed genes were examined in distinct clusters, and the WGCNA (weighted correlation network analysis) was made to establish co-expression networks. The prognostic models were developed by Cox and LASSO-Cox regression. The clustering analysis, GSEA (Gene set enrichment analysis), GSVA (gene set variation analysis) and communication analysis of the single-cell dataset GSE161529 were performed to investigate the functional relevance. Real-time polymerase chain reaction (RT-PCR) was employed for evaluating gene expression.

RESULTS

The results revealed significant differences in immune cell infiltration between two clusters (C1 and C2). C2 had poorer survival outcomes, which was associated with higher expression of immune checkpoints PD1 and PD-L1. The gene modules identified via WGCNA were correlated with the immune-based subtypes. Then, a prognostic model comprising seven genes (ACSL1, ABCB5, XG, ADH4, OPN4, NPR3, NLGN1) was used to divide patients into high- and low-risk subgroups. The high-risk group had worse prognosis and higher scores of TIDE (Tumor Immune Dysfunction and Exclusion). The single-cell analysis depicted the immune landscape. Macrophages and endothelial cells exhibited higher AUCell scores. In cellular communication analysis, notably significant ligand-receptor interactions of HLA-DRA-> CD4 and TNFSF13B-> HLA-DPB1 were observed. The proportion of endothelial cells was correlated with risk scores. Finally, RT-PCR results illustrated the expression of seven genes in BRCA specimens.

CONCLUSION

The integrative analysis provides new insights into molecular complexities of BRCA. Immune profiles and gene signatures hold potential for improving stratification of BRCA patients and guiding the development of personalized immunotherapy strategies.

Development and verification of a manganese metabolism- and immune-related genes signature for prediction of prognosis and immune landscape in gastric cancer

Background

Gastric cancer (GC) poses a global health challenge due to its widespread prevalence and unfavorable prognosis. Although immunotherapy has shown promise in clinical settings, its efficacy remains limited to a minority of GC patients. Manganese, recognized for its role in the body's anti-tumor immune response, has the potential to enhance the effectiveness of tumor treatment when combined with immune checkpoint inhibitors.

Methods

Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases was utilized to obtain transcriptome information and clinical data for GC. Unsupervised clustering was employed to stratify samples into distinct subtypes. Manganese metabolism- and immune-related genes (MIRGs) were identified in GC by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis. We conducted gene set variation analysis, and assessed the immune landscape, drug sensitivity, immunotherapy efficacy, and somatic mutations. The underlying role of NPR3 in GC was further analyzed in the single-cell RNA sequencing data and cellular experiments.

Results

GC patients were classified into four subtypes characterized by significantly different prognoses and tumor microenvironments. Thirteen genes were identified and established as MIRGs, demonstrating exceptional predictive effectiveness in GC patients. Distinct enrichment patterns of molecular functions and pathways were observed among various risk subgroups. Immune infiltration analysis revealed a significantly greater abundance of macrophages and monocytes in the high-risk group. Drug sensitivity analysis identified effective drugs for patients, while patients in the low-risk group could potentially benefit from immunotherapy. NPR3 expression was significantly downregulated in GC tissues. Single-cell RNA sequencing analysis indicated that the expression of NPR3 was distributed in endothelial cells. Cellular experiments demonstrated that NPR3 facilitated the proliferation of GC cells.

Conclusion

This is the first study to utilize manganese metabolism- and immune-related genes to identify the prognostic MIRGs for GC. The MIRGs not only reliably predicted the clinical outcome of GC patients but also hold the potential to guide future immunotherapy interventions for these patients.

Exercise-induced Musclin determines the fate of fibro-adipogenic progenitors to control muscle homeostasis

The effects of exercise on fibro-adipogenic progenitors (FAPs) are unclear, and the direct molecular link is still unknown. In this study, we reveal that exercise reduces the frequency of FAPs and attenuates collagen deposition and adipose formation in injured or disused muscles through Musclin. Mechanistically, Musclin inhibits FAP proliferation and promotes apoptosis in FAPs by upregulating FILIP1L. Chromatin immunoprecipitation (ChIP)-qPCR confirms that FoxO3a is the transcription factor of FILIP1L. In addition, the Musclin/FILIP1L pathway facilitates the phagocytosis of apoptotic FAPs by macrophages through downregulating the expression of CD47. Genetic ablation of FILIP1L in FAPs abolishes the effects of exercise or Musclin on FAPs and the benefits on the reduction of fibrosis and fatty infiltration. Overall, exercise forms a microenvironment of myokines in muscle and prevents the abnormal accumulation of FAPs in a Musclin/FILIP1L-dependent manner. The administration of exogenous Musclin exerts a therapeutic effect, demonstrating a potential therapeutic approach for muscle atrophy or acute muscle injury.

LncRNA NONRATT014888.2 contributes to cancer-induced bone pain through downregulation of natriuretic peptide receptor 3 in rats

Long noncoding RNA (lncRNA) is implicated in both cancer development and pain process. However, the role of lncRNA in the development of cancer-induced bone pain (CIBP) is unclear. LncRNA NONRATT014888.2 is highly expressed in tibia related dorsal root ganglions (DRGs) in CIBP rats which function is unknown. CIBP was induced by injection of Walker 256 mammary gland tumor cells into the tibia canal of female SD rats. Paw withdrawal threshold (PWT) and paw withdrawal latency (PWL) of rats were measured. Down-regulation of NONRATT014888.2 by siRNA in CIBP rats markedly attenuated hind-paw mechanical pain hypersensitivity. LncRNA-predicted target mRNAs analysis and mRNA sequencing results cued Socs3, Npr3 were related with NONRATT014888.2. Intrathecal injection of NONRATT014888.2-siR206 upregulated Npr3 both in mRNA and protein level. Npr3 was co-expressed in NONRATT014888.2-positive DRGs neurons and mainly located in cytoplasm, but not in Glial fibrillary acidic protein (GFAP)-positive cells. Intrathecal injection of ADV-Npr3 upregulated Npr3 expression and enhanced the PWT of CIBP rats. Our results suggest that upregulated lncRNA NONRATT014888.2 contributed to hyperalgesia in CIBP rats, and the mechanism may through downregulation of Npr3.

Discovery of another mechanism for the inhibition of particulate guanylyl cyclases by the natriuretic peptide clearance receptor

The cardiac natriuretic peptides (NPs) control pivotal physiological actions such as fluid and electrolyte balance, cardiovascular homeostasis, and adipose tissue metabolism by activating their receptor enzymes [natriuretic peptide receptor-A (NPRA) and natriuretic peptide receptor-B (NPRB)]. These receptors are homodimers that generate intracellular cyclic guanosine monophosphate (cGMP). The natriuretic peptide receptor-C (NPRC), nicknamed the clearance receptor, lacks a guanylyl cyclase domain; instead, it can bind the NPs to internalize and degrade them. The conventional paradigm is that by competing for and internalizing NPs, NPRC blunts the ability of NPs to signal through NPRA and NPRB. Here we show another previously unknown mechanism by which NPRC can interfere with the cGMP signaling function of the NP receptors. By forming a heterodimer with monomeric NPRA or NPRB, NPRC can prevent the formation of a functional guanylyl cyclase domain and thereby suppress cGMP production in a cell-autonomous manner.

A novel immune score model predicting the prognosis and immunotherapy response of breast cancer

Breast cancer (BC) is one of the most common malignancies. However, the existing pathological grading system cannot accurately and effectively predict the survival rate and immune checkpoint treatment response of BC patients. In this study, based on The Cancer Genome Atlas (TCGA) database, a total of 7 immune-related genes (IRGs) were screened out to construct a prognostic model. Subsequently, the clinical prognosis, pathological characteristics, cancer-immunity cycle, tumour immune dysfunction and exclusion (TIDE) score, and immune checkpoint inhibitor (ICI) response were compared between the high- and low-risk groups. In addition, we determined the potential regulatory effect of NPR3 on BC cell proliferation, migration, and apoptosis. The model consisting of 7 IRGs was an independent prognostic factor. Patients with lower risk scores exhibited longer survival times. Moreover, the expression of NPR3 was increased but the expression of PD-1, PD-L1, and CTLA-4 was decreased in the high-risk group compared to the low-risk group. In addition, compared with si-NC, si-NPR3 suppressed proliferation and migration but promoted apoptosis in both MDA-MB-231 and MCF-7 cells. This study presents a model for predicting survival outcomes and provides a strategy to guide effective personalized immunotherapy in BC patients.

Cellular Transcriptomics of Carboplatin Resistance in a Metastatic Canine Osteosarcoma Cell Line

Osteosarcoma prognosis has remained unchanged for the past three decades. In both humans and canines, treatment is limited to excision, radiation, and chemotherapy. Chemoresistance is the primary cause of treatment failure, and the trajectory of tumor evolution while under selective pressure from treatment is thought to be the major contributing factor in both species. We sought to understand the nature of platinum-based chemotherapy resistance by investigating cells that were subjected to repeated treatment and recovery cycles with increased carboplatin concentrations. Three HMPOS-derived cell lines, two resistant and one naïve, underwent single-cell RNA sequencing to examine transcriptomic perturbation and identify pathways leading to resistance and phenotypic changes. We identified the mechanisms of acquired chemoresistance and inferred the induced cellular trajectory that evolved with repeated exposure. The gene expression patterns indicated that acquired chemoresistance was strongly associated with a process similar to epithelial–mesenchymal transition (EMT), a phenomenon associated with the acquisition of migratory and invasive properties associated with metastatic disease. We conclude that the observed trajectory of tumor adaptability is directly correlated with chemoresistance and the phase of the EMT-like phenotype is directly affected by the level of chemoresistance. We infer that the EMT-like phenotype is a critical component of tumor evolution under treatment pressure and is vital to understanding the mechanisms of chemoresistance and to improving osteosarcoma prognosis.

Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea

Background: The molecular mechanisms underlying obstructive sleep apnea (OSA) and its comorbidities may involve mitochondrial dysfunction. However, very little is known about the relationships between mitochondrial dysfunction-related genes and OSA. Methods: Mitochondrial dysfunction-related differentially expressed genes (DEGs) between OSA and control adipose tissue samples were identified using data from the Gene Expression Omnibus database and information on mitochondrial dysfunction-related genes from the GeneCards database. A mitochondrial dysfunction-related signature of diagnostic model was established using least absolute shrinkage and selection operator Cox regression and then verified. Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. A protein-protein interaction network of the DEGs between the mitochondrial dysfunction-related clusters was constructed using STRING database and the hub genes were identified. Functional analyses, including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA), were conducted to explore the mechanisms involved in mitochondrial dysfunction in OSA. Immune cell infiltration analyses were conducted using CIBERSORT and single-sample GSEA (ssGSEA). Results: we established mitochondrial dysfunction related four-gene signature of diagnostic model consisted of NPR3, PDIA3, SLPI, ERAP2, and which could easily distinguish between OSA patients and controls. In addition, based on mitochondrial dysfunction-related gene expression, we identified two clusters among all the samples and three clusters among the OSA samples. A total of 10 hub genes were selected from the PPI network of DEGs between the two mitochondrial dysfunction-related clusters. There were correlations between the 10 hub genes and the 4 diagnostic genes. Enrichment analyses suggested that autophagy, inflammation pathways, and immune pathways are crucial in mitochondrial dysfunction in OSA. Plasma cells and M0 and M1 macrophages were significantly different between the OSA and control samples, while several immune cell types, especially T cells (γ/δ T cells, natural killer T cells, regulatory T cells, and type 17 T helper cells), were significantly different among mitochondrial dysfunction-related clusters of OSA samples. Conclusion: A novel mitochondrial dysfunction-related four-gen signature of diagnostic model was built. The genes are potential biomarkers for OSA and may play important roles in the development of OSA complications.

Next Generation Sequencing for Potential Regulated Genes and Micro-RNAs of Early Growth Response-1 in the Esophageal Squamous Cell Carcinoma

Esophageal cancer has a poor prognosis due to its aggressiveness and low survival rate. In Ease Asia, esophageal squamous cell carcinoma (ESCC) outnumbers esophageal adenocarcinoma (EAC). The ESCC patients still have high mortality despite modern surgical resection and neoadjuvant treatment. Determining patient and outcome prognostic factors is critical in ESCC treatment. In esophageal cancer, early growth response-1 (Egr-1) is a tumor suppressor gene, but the mechanism and associated genes are unknown. The study utilizes RNA interference method, the platform of Next Generation Sequencing (NGS) and bioinformatics analysis to investigate the influences after the Egr-1 gene slicing on the ESCC cells. The heat maps of differentially expressed mRNA and microRNAs were analyzed using the algorithm, Burrows-Wheller Aligner. The study showed that the expression of 51 mRNA and 26 microRNAs have significant changes in ESCC cells after Egr-1 knockdown. The KEGG enrichment analysis linked Egr-1-regulated genes and microRNAs. Egr-1 interactions with these genes and microRNAs may be important in tumor progression. In conclusions, this study provided the transcriptome patterns and relating pathway analysis for Egr-1 knockdown in ESCC cells. The mRNA and microRNAs altered by Egr-1 gene silencing might provide key information in the treatment of ESCC.

Development of a Novel Immune-Related Gene Prognostic Index for Breast Cancer

Objective

To construct an immune-related gene prognostic index (IRGPI) for breast cancer (BC) and investigate its prognostic specificity and the molecular and immune characteristics.

Methods

BC hub genes were identified from The Cancer Genome Atlas and immune-related databases using weighted gene co-expression network analysis (WGCNA). IRGPI was constructed using univariate, LASSO, and multivariate regression analyses, and was validated with GSE58812 and GSE97342 in the Gene Expression Omnibus database (GEO). At the same time, we evaluated the predictive ability of IRGPI for different BC subtypes. Subsequently, the molecular and immune characteristics, clinical relevance, and benefits of immune checkpoint inhibitor treatment were analyzed for different IRGPI subgroups.

Results

IRGPI consisted of six genes: SOCS3, TCF7L2, TSLP NPR3, ANO6, and HMGB3. The IRGPI 1-, 5-, and 10-years area under curve (AUC) values were 0.635, 0.752, and 0.753, respectively, indicating that IRGPI has good potential in predicting the long-term survival of BC patients, consistent with the results in the GEO cohort. IRGPI showed good predictive power in four different breast cancer subtypes: ER positive, PR positive, HER2 positive and triple-negative (P<0.01). Compared with the low-IRGPI group, the high-IRGPI group had a worse prognosis and a lower degree of immune infiltrating cells (p < 0.05). IRGPI showed specificity in distinguishing age, TNM stage, ER, and HER2 statuses, and our study found that the high-IRGPI group had low tumor immune dysfunction and exclusion (TIDE), microsatellite instability (MSI), and T cell dysfunction scores (p < 0.05). In addition, compared with the TIDE and TIS models, showed that the AUCs of IRGPI were better during the 5-year follow-up.

Conclusion

IRGPI can be used as an independent prognostic indicator of breast cancer, providing a method for monitoring the long-term treatment of BC.

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).

Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.

Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4⁺ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.

Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.