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Comprehensive analysis identifies AMIGO2 as a potential prognosis biomarker of pancreatic adenocarcinoma.
BACKGROUND: Pancreatic adenocarcinoma (PAAD) is a highly aggressive form of cancer characterized by a low survival rate. Adhesion molecule with Ig like domain family 2 (AMIGO2), a cell adhesion molecule, has been found to be expressed abnormally in various solid tumors, but its specific role in PAAD has not yet been investigated. This study aimed to investigate the potential prognostic value of AMIGO2 in pan-cancer, especially in PAAD. METHODS: RNA profiles and corresponding clinical data of PAAD patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were obtained. Kaplan-Meier survival analysis was conducted to assess the relationship between AMIGO2 expression and overall survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to evaluate the functional enrichment of AMIGO2 in PAAD. Subsequently, immune infiltration and single-cell RNA (scRNA) sequencing analyses were employed to investigate the composition of immune cells. The half maximal inhibitory concentration (IC50) value was utilized to estimate the drug sensitivity associated with AMIGO2. Finally, in vitro experiments were conducted to assess the biological function of AMIGO2 in PAAD. RESULTS: AMIGO2 exhibited abnormal expression patterns and demonstrated prognostic significance in various types of cancer. AMIGO2 was observed to be up-regulated in PAAD tissues. Its high expression was indicative of a poor prognosis. Additionally, elevated level of AMIGO2 was found to be associated with mutations in KRAS and TP53, as well as with dysregulation of key cellular processes such as "MAPK signaling" and "p53 signaling pathway". Furthermore, AMIGO2 expression exhibited correlations with the infiltration of macrophages and cancer-associated fibroblasts. PAAD patients with high AMIGO2 expression were more sensitive to BRD4 inhibitor BI-2536. The growth of PAAD cells was found to be inhibited upon knockdown of AMIGO2. CONCLUSIONS: AMIGO2 was identified as prognostic factor in PAAD, suggesting its potential as a biomarker and therapeutic target for PAAD patients.
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Targeted delivery of CCL3 reprograms macrophage antigen presentation and enhances the efficacy of immune checkpoint blockade therapy in hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related deaths worldwide, especially in advanced stages where limited treatment options result in poor prognosis. The immunosuppressive tumor immune microenvironment (TIME), characterized by low immune cell infiltration and exhaustion, limits immunotherapy efficacy. To address this, our study investigates the role of C-C motif chemokine ligand 3 (CCL3) in modulating the HCC TIME. METHODS: We analyzed CCL3 expression in human HCC samples from The Cancer Genome Atlas database, focusing on its correlation with inflammatory gene signatures and immune cell infiltration. High-dimensional single-cell RNA sequencing (scRNA-seq), flow cytometry, and multiplex immunofluorescence were used to investigate CCL3's effects on macrophage function and T cell activation. The biological impact of CCL3 on macrophages was assessed using co-culture systems, confocal imaging, metabolite detection, and inhibition assays. Preclinical HCC models and ex vivo tumor fragment assays further explored how CCL3 modulates immune responses and enhances immune checkpoint blockade efficacy. RESULTS: Our study shows that CCL3 is suppressed in the tumor microenvironment and positively correlates with immune infiltration and inflammatory responses. Targeted liver delivery of rAAV-Ccl3 reprograms the immune microenvironment in HCC, promoting immune cell recruitment and tertiary lymphoid structure formation, thus suppressing tumor growth via immune engagement. Through scRNA-seq, flow cytometry, and multiplex immunofluorescence, we found that CCL3 enhances macrophage antigen uptake and activates cytotoxic T cells. In vivo and in vitro experiments confirmed that CCL3 facilitates T cell infiltration and upregulates MHC II expression on macrophages, enhancing antigen presentation. The CCL3-CCR5 pathway also boosts macrophage metabolism, increasing lysosomal activity and antigen uptake, thereby strengthening adaptive immune responses and increasing sensitivity to immune checkpoint blockade therapies in preclinical models. CONCLUSIONS: This study highlights the pivotal role of CCL3 in reshaping the TIME and enhancing antitumor immunity in HCC. By promoting immune cell recruitment and enhancing antigen presentation, CCL3 demonstrates significant potential to improve the efficacy of immunotherapy, particularly in combination with immune checkpoint inhibitors. Targeting CCL3 may help to overcome the immunosuppressive TIME in HCC and improve patient outcomes.
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Exploring the role of mitophagy-related genes in breast cancer: subtype classification and prognosis prediction.
Background: Breast cancer (BC) is the most common cancer among women globally and poses the leading health threat to women worldwide, with persistently high incidence rates. Mitophagy is a selective autophagy process that specifically targets mitochondria within the cell, maintaining cellular energy balance and metabolic health by identifying and degrading damaged mitochondria. Although there is an understanding of the relationship between mitophagy and cancer, the specific mechanisms remain unclear due to the complexity and diversity of mitophagy, suggesting that it could be an effective and more targeted therapeutic approach for BC. Methods: In this study, we meticulously examined the BC expression and clinical pathology data from The Cancer Genome Atlas (TCGA) to assess the expression profiles, copy number variations (CNV), and to investigate the correlation, function, and prognostic impact of 34 mitophagy-related genes (MRGs). Differentially expressed genes (DEGs) were identified based on group classification. Lasso and Cox regression were used to determine prognostic genes for constructing a nomogram. Single-cell analysis mapped the distribution of these genes in BC cells. Additionally, the association between gene-derived risk scores and factors such as immune infiltration, tumor mutational burden (TMB), cancer stem cell (CSC) index, and drug responses was studied. In vitro experiments were conducted to confirm the analyses. Results: We included 34 MRGs and subsequently generated a risk score for 7 genes, including RPLP2, PCDHGA2, PRKAA2, CLIC6, FLT3, CHI3L1, and IYD. It was found that the low-risk group had better overall survival (OS) in BC, higher immune scores, but lower tumor mutational burden (TMB) and cancer stem cell (CSC) index, as well as lower IC50 values for commonly used drugs. To enhance clinical applicability, age and staging were incorporated into the risk score, and a more comprehensive nomogram was constructed to predict OS. This nomogram was validated and showed good predictive performance, with area under the curve (AUC) values for 1-year, 3-year, and 5-year OS of 0.895, 0.765, and 0.728, respectively. Conclusion: Our findings underscore the profound impact of prognostic genes on the immune response and prognostic outcomes in BC, indicating that they can provide new avenues for personalized BC treatment and potentially improve clinical outcomes.
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Single-cell transcriptomic atlas of mouse cochlear aging.
Progressive functional deterioration in the cochlea is associated with age-related hearing loss (ARHL). However, the cellular and molecular basis underlying cochlear aging remains largely unknown. Here, we established a dynamic single-cell transcriptomic landscape of mouse cochlear aging, in which we characterized aging-associated transcriptomic changes in 27 different cochlear cell types across five different time points. Overall, our analysis pinpoints loss of proteostasis and elevated apoptosis as the hallmark features of cochlear aging, highlights unexpected age-related transcriptional fluctuations in intermediate cells localized in the stria vascularis (SV) and demonstrates that upregulation of endoplasmic reticulum (ER) chaperon protein HSP90AA1 mitigates ER stress-induced damages associated with aging. Our work suggests that targeting unfolded protein response pathways may help alleviate aging-related SV atrophy and hence delay the progression of ARHL.
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Construction of Prediction Model for Atrial Fibrillation with Valvular Heart Disease Based on Machine Learning.
BACKGROUND: Valvular heart disease (VHD) is a major precipitating factor of atrial fibrillation (AF) that contributes to decreased cardiac function, heart failure, and stroke. Stroke induced by VHD combined with atrial fibrillation (AF-VHD) is a much more serious condition in comparison to VHD alone. The aim of this study was to explore the molecular mechanism governing VHD progression and to provide candidate treatment targets for AF-VHD. METHODS: Four public mRNA microarray datasets were downloaded and differentially expressed genes (DEGs) screening was performed. Weighted gene correlation network analysis was carried out to detect key modules and explore their relationships and disease status. Candidate hub signature genes were then screened within the key module using machine learning methods. The receiver operating characteristic curve and nomogram model analysis were used to determine the potential clinical significance of the hub genes. Subsequently, target gene protein levels in independent human atrial tissue samples were detected using western blotting. Specific expression analysis of the hub genes in the tissue and cell samples was performed using single-cell sequencing analysis in the Human Protein Atlas tool. RESULTS: A total of 819 common DEGs in combined datasets were screened. Fourteen modules were identified using the cut tree dynamic function. The cyan and purple modules were considered the most clinically significant for AF-VHD. Then, 25 hub genes in the cyan and purple modules were selected for further analysis. The pathways related to dilated cardiomyopathy, hypertrophic cardiomyopathy, and heart contraction were concentrated in the purple and cyan modules of the AF-VHD. Genes of importance (CSRP3, MCOLN3, SLC25A5, and FIBP) were then identified based on machine learning. Of these, CSRP3 had a potential clinical significance and was specifically expressed in the heart tissue. CONCLUSIONS: The identified genes may play critical roles in the pathophysiological process of AF-VHD, providing new insights into VHD development to AF and helping to determine potential biomarkers and therapeutic targets for treating AF-VHD.
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PSME2 offers value as a biomarker of M1 macrophage infiltration in pan-cancer and inhibits osteosarcoma malignant phenotypes.
A growing number of studies have revealed an association between proteasome activator complex subunit 2 (PSME2) and the progression of various forms of cancer. However, the effect of PSME2 on osteosarcoma progression is unknown. Pan-cancer analyses focused on the immunological activity and prognostic relevance of PSME2 have yet to be conducted. The Cancer Genome Atlas and Genome-Tissue Expression databases were leveraged to evaluate PSME2 expression and activity across 33 cancer types. Significant PSME2 dysregulation was noted in a wide range of cancer types and this gene was found to offer significant diagnostic and prognostic utility in most analyzed cancers. From a mechanistic perspective, PSME2 expression levels were correlated with DNA methylation, DNA repair, genomic instability, and TME scores in multiple cancer types. PSME2 was subsequently established as a pan-cancer biomarker of M1 macrophage infiltration based on a combination of bulk, single-cell, and spatial transcriptomic data and confirmatory fluorescent staining results. In osteosarcoma cells, overexpressing PSME2 significantly suppressed tumor proliferative, migratory, and invasive activity. Screening efforts also successfully identified the PSME2-activating drug irinotecan, which can synergistically promote the death of osteosarcoma cells when combined with the chemotherapeutic drug paclitaxel. As a biomarker of M1 macrophage infiltration, PSME2 expression levels may offer insight into tumor development and progression for a wide range of cancers including osteosarcoma, emphasizing its potential utility as a prognostic and therapeutic target worthy of further study.
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Single-cell transcriptome atlas revealed bronchoalveolar immune features related to disease severity in pediatric Mycoplasma pneumoniae pneumonia.
The mechanisms underlying protective immunity in mild Mycoplasma pneumoniae pneumonia (MPP) and the pathogenesis of severe MPP, characterized by dysregulated immune responses, remain unclear. Here, we performed single-cell RNA sequencing (scRNA-seq) to profile bronchoalveolar lavage fluid (BALF) samples from 13 healthy donors and 24 hospitalized pediatric patients with MPP, covering both mild and severe cases. Severe MPP patients exhibited high levels of exhausted T cells and M1-like macrophages, with the exhaustion of T cells attributed to persistent type I interferon signaling and inadequate assistance from CD4+ T cells. Significant cell-cell interactions between exhausted T cells and programmed death-ligand 1+ (PD-L1+) macrophages were detected in severe patients, potentially mediated through inhibitor molecules (e.g., PD1) and their receptors (e.g., PD-L1), as well as human leukocyte antigen class I molecules and their receptors (e.g., KLRC1/D2), resulting in the dysfunction of anti-MP immune responses. Mild MPP patients were featured by an increased abundance of neutrophils, coupled with enhanced activation, contributing to protective immunity. Together, our study provides a detailed characterization of the BALF immune landscape in MPP patients, revealing distinct immune characteristics between mild and severe cases, which offers a valuable resource for understanding MPP immunopathogenesis and formulating effective therapeutic strategies.
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Cardiac endothelial cells and cardiomyocytes alter their communication properties in diabetic mice.
OBJECTIVE: We aimed to explore the heterogeneities and communication properties of cardiac CMs and ECs in diabetes. METHODS: GSE213337 dataset was retrieved from NCBI Gene Expression Omnibus, containing the single-cell RNA sequencing data of hearts from the control and streptozotocin-induced diabetic mice. Cell cluster analysis was performed to identify the cell atlas. Data of CMs and ECs were extracted individually for re-cluster analysis, functional enrichment analysis and trajectory analysis. Cell communication analysis was conducted to explore the altered signals and significant ligand-receptor interactions. RESULTS: Eleven cell types were identified in the heart tissue. CMs were re-clustered into four subclusters, and cluster 4 was dominant in diabetic condition and enriched in cellular energy metabolism processes. ECs were re-clustered into six subclusters, and clusters 2, 4 and 5 were dominant in the diabetic condition and mainly enriched in cellular energy metabolism and lipid transport processes. The cellular communication network was altered in the diabetic heart. ECs dominated the overall signaling and notably increased the ANGPTL and SEMA4 signals in the diabetic heart. Four significant ligand-receptor pairs implicating the two signals contributed to the communication between ECs and other cell types, including Angptl1-(Itga1 + Itgb1), Angptl4-Cdh5, Angptl4-Sdc3, and Sema4a-(Nrp + Plxna2). The ligand Angptl4 engaged in ECs-CMs communication in a paracrine manner. CONCLUSION: Single-cell sequencing analysis revealed heterogeneities of ECs and CMs in diabetes, Angptl4-Cdh5 and Angptl4-Sdc3 were involved in the communication between ECs and CMs in diabetes.
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Predicting immunotherapy prognosis and targeted therapy sensitivity of colon cancer based on a CAF-related molecular signature.
The role of cancer-associated fibroblasts (CAFs) in modulating the tumor microenvironment (TME) is gaining attention, yet their impact on prognosis and therapeutic response in colon cancer remains unclear. Here, we identified genes associated with CAF infiltration via weighted gene co-expression network analysis (WGCNA) utilizing data from The Cancer Genome Atlas (TCGA) and GSE39582 cohorts. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct CAF molecular signatures (CAFscore). Patients were categorized into high and low CAFscore groups to analyze clinicopathological traits, somatic mutations, immune evasion, and treatment responses. In this study, a total of 244 genes were correlated with CAF infiltration, with 11 linked to overall survival. Notably, FSTL3, CRIP2, and SLC2A3 were selected for the CAFscore. A higher CAFscore was associated with poorer prognoses, increased malignancy, and therapeutic resistance, particularly among patients with high tumor mutation burden and microsatellite instability. Furthermore, elevated FSTL3 expression was associated with reduced CD8+ T cell infiltration, indicating a suppressive TME. Mechanistically, CAFs may promote immune evasion via NAMPT ligand-receptor interactions based on single-cell RNA sequencing data. Thus, the CAFscore is crucial for personalizing treatment strategies and identifying patients who require more aggressive management.
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Deciphering the interaction between the expression of LRP2 served as a mitochondrial metabolism-related gene and prognosis in colon cancer integrating multi-omics analysis.
BACKGROUND: Colon adenocarcinoma (COAD) is increasingly prevalent among patients under 50 years old, and the 5-year survival rate for patients with metastasis is less than 20%. Identifying significant biomarkers and therapeutic targets is crucial. We investigated the expression of LRP2 in COAD and its prognostic value utilizing single-cell sequencing and transcriptomics datasets, which was conducted preliminary validation at the patient samples and cellular levels as well. METHODS: Based on differential gene expression of tumor samples and normal tissues in The Cancer Genome Atlas (TCGA), we performed consensus clustering, univariate and multivariate Cox regression analysis applying 1,234 mitochondrial metabolism-related genes (MMRGs) to identify some essential genes associated with poor prognosis in COAD patients. We validated survival outcome and biological function of the target gene leveraging single-cell sequencing and transcriptomics datasets from Gene Expression Omnibus (GEO), and evaluated the value of the target gene in the clinical pathology stage of COAD patients. Simultaneously, the expression levels of critical gene were detected in the diverse tissues of COAD by immunohistochemistry (IHC) staining. Transcriptomics data was continuously implemented to compare the discrepancy between the expression levels of the target gene and somatic mutation burden, inspecting the key pathways of the target gene by gene set enrichment analysis (GSEA) and examining its drug sensitivity synthetically in the CellMiner databases. The proliferative capacity augmented in LRP2-overexpressed colon cancer cells was determined employing cell counting kit-8 (CCK-8) and flow cytometry assays. RESULTS: LRP2 served as a key mitochondrial metabolism-related gene was assessed clinical prognosis in COAD patients according to the TCGA database. High expression of LRP2 was prominently associated with poor prognosis in COAD patients (P < 0.05), which was validated by GEO databases, and the expression levels of LRP2 were positively related to clinical pathological stage simultaneously (P < 0.05). Some specific cell types were clustered and proliferation pathways were immensely enriched, which were correlated with LRP2 in two single-cell sequencing datasets. The mutation profiles displayed remarkable differences in two levels of LRP2, we also observed high expressions of LRP2 were immensely correlated with high tumor mutation burden (TMB) and unfavorable prognosis in these patients (P < 0.05). LRP2 was significantly enriched in multiple cancer proliferation-related pathways, and the noteworthy correlation between LRP2 and the sensitivity to various drugs was identified (P < 0.05). The expression levels of LRP2 were multifarious in different COAD patients based on IHC staining. LRP2-overpression could stimulate the proliferation capability of HCT116 and SW480 cell lines markedly (P < 0.05). CONCLUSION: The expression levels of LRP2 were intimately correlated with gene mutations, prognosis, pathological stage and the sensitivity to anticancer drugs in COAD. Augmented levels of LRP2 would manifest poor prognosis, which furnished novel insights for clinical diagnosis and treatment in COAD. LRP2 could extensively facilitate the proliferation ability of colon cell lines.