Pleural effusion (PE) caused by lung cancer is prevalent, and it is difficult to differentiate it from PE caused by tuberculosis. Exosome-based liquid biopsy offers a non-invasive technique to ...diagnose benign and malignant PE. Exosomal miRNAs are potential diagnostic markers and play an essential role in signal transduction and biological processes in tumor development. We hypothesized that exosomal miRNA expression profiles in PE would contribute to identifying its diagnostic markers and elucidating the molecular basis of PE formation in lung cancer.
The exosomes from PE caused by lung adenocarcinoma (LUAD) and pulmonary tuberculosis were isolated and verified by transmission electron microscopy. The exosomal miRNA profiles were identified using deep sequencing and validated with quantitative real-time PCR (qRT-PCR). We performed bioinformatic analysis for differentially expressed miRNAs to explore how exosomal miRNAs regulate pleural effusion.
We identified 99 upregulated and 91 downregulated miRNAs in malignant pleural effusion (MPE) compared to tuberculous pleural effusion (TPE). Seven differentially expressed miRNAs (DEmiRNAs) were validated by qRT-PCR, out of which 5 (71.4%) were confirmed through sequencing. Gene Ontology (GO) analysis revealed that most exosomal miRNAs target genes were involved in regulating cellular processes and nitrogen compound metabolism. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the exosomal miRNAs target genes were mainly involved in Fc gamma R-mediated phagocytosis, Rap1 signaling pathway, and breast cancer. The hub genes, including ITGAM, FOXO1, MAPK14, YWHAB, GRIN1, and PRF1, were screened through plug-in cytoHubba. The PFR1 was identified as a critical gene in MPE formation using single-cell sequencing analysis. Additionally, we hypothesized that tumor cells affected natural killer cells and promoted the generation of PE in LUAD
the exosomal hsa-miR-3120-5p-PRF1 axis.
We identified exosomal miRNA profiles in LUAD-MPE and TPE, which may help in the differential diagnosis of MPE and TPE. Bioinformatic analysis revealed that these miRNAs might affect PE generation through tumor immune response in LUAD. Our results provided a new theoretical basis for understanding the function of exosomal miRNAs in LUAD-MPE.
The tumour microenvironment is a key determinant of the efficacy of immunotherapy. Angiogenesis is closely linked to tumour immunity. We aimed to screen long non-coding ribonucleic acids (lncRNAs) ...associated with angiogenesis to predict the prognosis of individuals with hepatocellular carcinoma (HCC) and characterise the tumour immune microenvironment (TIME). Patient data, including transcriptome and clinicopathological parameters, were retrieved from The Cancer Genome Atlas database. Moreover, co-expression algorithm was utilized to obtain angiogenesis-related lncRNAs. Additionally, survival-related lncRNAs were identified using Cox regression and the least absolute shrinkage and selection operator algorithm, which aided in constructing an angiogenesis-related lncRNA signature (ARLs). The ARLs was validated using Kaplan-Meier method, time-dependent receiver operating characteristic analyses, and Cox regression. Additionally, an independent external HCC dataset was used for further validation. Then, gene set enrichment analysis, immune landscape, and drug sensitivity analyses were implemented to explore the role of the ARLs. Finally, cluster analysis divided the entire HCC dataset into two clusters to distinguish different subtypes of TIME. This study provides insight into the involvement of angiogenesis-associated lncRNAs in predicting the TIME characteristics and prognosis for individuals with HCC. Furthermore, the developed ARLs and clusters can predict the prognosis and TIME characteristics in HCC, thereby aiding in selecting the appropriate therapeutic strategies involving immune checkpoint inhibitors and targeted drugs.
Background:
Necroptosis is a form of programmed cell death, and studies have shown that long non-coding RNA molecules (lncRNAs) can regulate the process of necroptosis in various cancers. We sought ...to screen lncRNAs associated with necroptosis to predict prognosis and tumor immune infiltration status in patients with hepatocellular carcinoma (HCC).
Methods:
Transcriptomic data from HCC tumor samples and normal tissues were extracted from The Cancer Genome Atlas database. Necroptosis-associated lncRNAs were obtained by co-expression analysis. Necroptosis-associated lncRNAs were then screened by Cox regression and least absolute shrinkage and selection operator methods to construct a risk model for HCC. The models were also validated and evaluated by Kaplan-Meier analysis, univariate and multivariate Cox regression, and time-dependent receiver operating characteristic (ROC) curves. In addition, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment, gene set enrichment, principal component, immune correlation, and drug sensitivity analyses were applied to assess model risk groups. To further differentiate the immune microenvironment of different HCC subtypes, the entire dataset was divided into three clusters, based on necroptosis-associated lncRNAs, and a series of analyses performed.
Results:
We constructed a model comprising four necroptosis-associated lncRNAs: POLH-AS1, DUXAP8, AC131009.1, and TMCC1-AS1. Overall survival (OS) duration was significantly longer in patients classified as low-risk than those who were high-risk, according to our model. Univariate and multivariate Cox regression analyses further confirmed risk score stability. The analyzed models had area under the ROC curve values of 0.786, 0.713, and 0.639 for prediction of 1-, 3-, and 5-year OS, respectively, and risk score was significantly associated with immune cell infiltration and ESTIMATE score. In addition, differences between high and low-risk groups in predicted half-maximal inhibitory concentration values for some targeted and chemical drugs, providing a potential basis for selection of treatment approach. Finally, cluster analysis facilitated more refined differentiation of the immune microenvironment in patients with HCC and may allow prediction of the effectiveness of immune checkpoint inhibitors.
Conclusions:
This study contributes to understanding of the function of necroptosis-related lncRNAs in predicting the prognosis and immune infiltration status of HCC. The risk model constructed and cluster analysis provide a basis for predicting the prognosis of patients with HCC and to inform the selection of immunotherapeutic strategies.
PANoptosis is a type of programmed cell death (PCD) characterised by apoptosis, necroptosis and pyroptosis. Long non-coding ribonucleic acids (lncRNAs) are participating in the malignant behaviour of ...tumours regulated by PCD. Nevertheless, the function of PANoptosis-associated lncRNAs in lung adenocarcinoma remains to be investigated. In this work, a PANoptosis-related lncRNA signature (PRLSig) was developed based on the least absolute shrinkage and selection operator algorithm. The stability and fitness of PRLSig were confirmed by systematic evaluation of Kaplan–Meier, Cox analysis algorithm, receiver operating characteristic analysis, stratification analysis. In addition, ESTIMATE, single sample gene set enrichment analysis, immune checkpoints and the cancer immunome database confirmed the predictive value of the PRLSig in immune microenvironment and helped to identify populations for which immunotherapy is advantageous. The present research provides novel insights to facilitate risk stratification and optimise personalised treatment for LUAD.
BACKGROUNDThe Perilipin (PLIN) family of genes were previously shown to be involved in the formation and degradation of Lipid Droplets (LDs). In addition, they may play important roles in the ...development and progression of breast cancer. However, the prognostic value of PLIN family members in breast cancer patients remains unclear. METHODSMutations and copy number alterations of PLIN family genes in breast cancer were examined using the cBioportal for Cancer Genomics. In addition, the expression patterns of PLIN family genes were explored using the UCSC Xena online tool. Finally, the Kaplan-Meier Plotter was used to investigate the prognostic value of PLIN family genes in breast cancer. RESULTSThe findings revealed a low frequency of genetic alterations and amplification was the most frequent change in the PLIN family genes. Additionally, there was an increase in the expression of Perilipin 3 (PLIN3) in breast cancer tissues compared to normal breast tissues. However, expression of the other genes in the PLIN family was significantly lower in breast cancer tissues compared to normal breast tissues. Moreover, there was an increase in the expression levels of Perilipin 1 (PLIN1), PLIN3, Perilipin 4 (PLIN4) and Perilipin 5 (PLIN5) in the luminal A and luminal B subgroups. On the other hand, the expression of Perilipin 2 (PLIN2) was elevated in the human epidermal growth factor receptor 2 (HER2) positive and basal-like subgroups. Furthermore, Kaplan-Meier Plotter analysis demonstrated that high expression of PLIN1 might predict a longer Overall Survival (OS) in patients with breast cancer while overexpression of PLIN2 indicated poor OS of breast cancer patients. CONCLUSIONThe findings from this study indicated that genes in the PLIN family were aberrantly expressed in breast cancer and may serve as novel therapeutic targets as well as prognostic biomarkers for the disease.
BACKGROUNDCancer-associated fibroblasts (CAFs) regulate the malignant biological behaviour of hepatocellular carcinoma (HCC) as a significant component of the tumour immune microenvironment (TIME). ...This study aimed to develop a CAFs-based scoring system to predict the prognosis and TIME of patients with HCC.METHODSData for the TCGA-LIHC and GSE14520 cohorts were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Single-cell RNA-sequencing data for HCC samples were retrieved from the GSE166635 cohort. The Least Absolute Shrinkage and Selection Operator algorithm was employed to develop a CAFs-related scoring system (CAFRss). The predictive value of the CAFRss was determined using Kaplan-Meier, Cox regression and Receiver Operating Characteristic curves. Additionally, the TIMER platform, single sample Gene Set Enrichment Analysis and the Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data algorithms were performed to determine the TIME landscape. Finally, the pRRophic algorithm was utilised for drug sensitivity analysis.RESULTSThe evaluation of the CAFRss system demonstrated its superior ability to predict the clinical outcome of patients with HCC. Additionally, CAFRss effectively distinguished HCC populations with distinct TIME landscapes. Furthermore, CAFRss-based risk stratification identified individuals with immune 'hot tumours' and predicted the survival of patients treated with ICBs.CONCLUSIONSThe developed CAFRss can serve as a predictive tool for determining the clinical outcome of HCC and differentiating populations with diverse TIME characteristics.
Pannexin 1 (PANX1) channel is a critical ATP-releasing pathway that modulates tumor immunity, progression, and prognosis. However, the roles of PANX1 in different cancers remain unclear. We analyzed ...the expression of PANX1 in human pan-cancer in the Oncomine and GEPIA2.0 databases. The prognostic value of PANX1 expression was determined using Kaplan-Meier plotter and OncoLnc tools. The correlation between PANX1 and tumor-infiltrating immune cells was investigated using the TIMER 2.0. In addition, the relationship between PANX1 and immunomodulators was explored using TISIDB. Finally, gene set enrichment analysis (GSEA) was performed utilizing LinkedOmics. The results indicated that PANX1 was overexpressed in most cancers compared to normal tissues. The high expression of PANX1 was associated with poor prognosis in multiple tumors, especially in pancreatic adenocarcinoma (PAAD). In addition, PANX1 was correlated with a variety of immunomodulators, such as CD274, IL10, CD276, IL2RA, TAP1, and TAP2. PANX1 expression level was significantly related to infiltration of multiple immune cells in many cancers, including cancer associated fibroblast, macrophage, and neutrophil cells. Further analysis revealed that PANX1 was significantly associated with T cells CD8+ (rho = 0.524, P = 1.94e-13) and Myeloid dendritic cell (rho = 0.564, P = 9.45e-16). GSEA results showed that PANX1 was closely associated with leukocyte cell-cell adhesion, endoplasmic reticulum lumen, ECM-receptor interaction, and Focal adhesion pathways in PAAD. PANX1 expression was higher in pan-cancer samples than in normal tissues. The high expression of PANX1 was associated with poor outcome and immune infiltration in multiple cancers, especially in PAAD.
Colorectal cancer (CRC) is the most common malignant gastrointestinal tumor worldwide. Serum exosomal microRNAs (miRNAs) play a critical role in tumor progression and metastasis. However, the ...underlying molecular mechanisms are poorly understood.The miRNAs expression profile (GSE39833) was downloaded from Gene Expression Omnibus (GEO) database. GEO2R was applied to screen the differentially expressed miRNAs (DEmiRNAs) between healthy and CRC serum exosome samples. The target genes of DEmiRNAs were predicted by starBase v3.0 online tool. The gene ontology (GO) and Kyoto Encyclopedia of Genomes pathway (KEGG) enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. The protein-protein interaction (PPI) network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) visualized using Cytoscape software. Molecular Complex Detection (MCODE) and cytohubba plug-in were used to screen hub genes and gene modules.In total, 102 DEmiRNAs were identified including 67 upregulated and 35 downregulated DEmiRNAs, and 1437 target genes were predicted. GO analysis showed target genes of upregulated DEmiRNAs were significantly enriched in transcription regulation, protein binding, and ubiquitin protein ligase activity. While the target genes of downregulated DEmiRNAs were mainly involved in transcription from RNA polymerase II promoter, SMAD binding, and DNA binding. The KEGG pathway enrichment analyses showed target genes of upregulated DEmiRNAs were significantly enriched in proteoglycans in cancer, microRNAs in cancer, and phosphatidylinositol-3 kinases/Akt (PI3K-Akt) signaling pathway, while target genes of downregulated DEmiRNAs were mainly enriched in transforming growth factor-beta (TGF-beta) signaling pathway and proteoglycans in cancer. The genes of the top 3 modules were mainly enriched in ubiquitin mediated proteolysis, spliceosome, and mRNA surveillance pathway. According to the cytohubba plugin, 37 hub genes were selected, and 4 hub genes including phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), SRC, cell division cycle 42 (CDC42), E1A binding protein p300 (EP300) were identified by combining 8 ranked methods of cytohubba.The study provides a comprehensive analysis of exosomal DEmiRNAs and target genes regulatory network in CRC, which can better understand the roles of exosomal miRNAs in the development of CRC. However, these findings require further experimental validation in future studies.
•Interval analysis method is utilized for transient heat conduction.•Convex models are utilized for transient heat conduction.•In convex models, we propose a novel convex model to quantify uncertain ...parameters.•The novel convex model can partly reduce the space of temperature field response.
Thermal protection systems (TPS) play a key role in the development of hypersonic aircrafts and the performance of TPS is directly in connection with its temperature field, thus a number of analytical and experimental studies have been conducted to study heat transfer analysis. Due to the existence of uncertain parameters in the temperature field, it is imperative to adopt the approaches involving uncertainty analysis to obtain reliable results. The non-probabilistic set-theoretic models, compared with the probabilistic approach, only require a small amount of experimental samples to process the study of uncertainties. Interval analysis method (IAM), classical convex model (CCM) and novel convex model (NCM) are applied to quantify uncertain parameters in TPS and then combined with finite elemental differential equation of transient thermal analysis to study the effects of uncertain parameters on temperature field response by means of Taylor series expansion. Moreover, the thermal responsive bounds in both CCM and NCM are yielded by the Lagrange multiplier method. A ceramic TPS is performed to illustrate the application of the present method and the results show that NCM can reduce the space of temperature field responses. Besides, the non-probabilistic set-theoretic methods can serve for the design of TPS.
Cathepsin X (Cat X) has been identified as a member of cathepsin family. Studies have shown that Cat X is involved in tumorigenesis and tumor development of various cancers. The aim of this study is ...to investigate the relationship between the clinicopathological prognosis and the levels of Cat X and cystatin C in the serum of patients with lung cancer.
Blood samples were collected from 84 patients with lung cancer and 36 healthy control subjects. Cat X and cystatin C were determined by quantitative ELISA.
Cat X and cystatin C levels were significantly higher in the patients with lung cancer than that in the healthy control subjects (P<0.01). Cat X level was correlated with the pathological types of lung cancer (P=0.076). Cystatin C was positively correlated with TNM stage (P=0.01). Furthermore, cystatin C/Cat X was correlated with lymph node metastasis (P=0.058). The patients with high Cat X levels experienced significantly shorter overall survival rates compared with those with low Cat X. Univariate analysis
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