Identification of a TLR-Induced Four-lncRNA Signature as a Novel Prognostic Biomarker in Esophageal Carcinoma

Participation of TLRs in cancer immunopathogenesis and drug resistance via interacting with immunological and/or non-immunological signaling pathways as well as lncRNAs

Toll-like receptors (TLRs) have a convoluted role in cancer even though they are crucial to the immune system. By bridging the innate immune system and cancer, TLRs have a very complex impact on the formation of tumors and the effectiveness of anti-cancer treatments. TLR signaling links the innate and adaptive immune systems and initiates direct pathogen eradication. In cancer immunopathogenesis and treatment resistance, long non-coding RNAs (lncRNAs) modify TLR signaling linkages with immunological and non-immunological pathways. We identified lncRNAs that positively and negatively control TLR signaling, impacting immunological response and drug sensitivity. These results highlight the complex interactions between long non-coding RNAs and TLRs that influence the start of cancer and its response to treatment. Targeting specific lncRNAs is a practical way to control TLR signaling and perhaps enhance anti-tumor immunity while overcoming medication resistance. We provide a framework for developing novel immunotherapeutic regimens and customized medicine approaches for cancer treatment. The exact mechanisms by which lncRNAs regulate TLR signaling pathways should be defined by further research, and these findings should be validated in clinical situations. This finding makes future research of lncRNA-based drugs in combination with existing cancer treatments feasible.

Bioinformatics analysis and experimental verification of NLRX1 as a prognostic factor for esophageal squamous cell carcinoma

Nucleotide binding and oligomeric domain-like receptor X1 (NLRX1), a member of the NLR family, is associated with the physiological and pathological processes of inflammation, autophagy, immunity, metabolism and mitochondrial regulation, and has been demonstrated to have pro- or antitumor effects in various tumor types. However, the biological function of NLRX1 in esophageal squamous cell carcinoma (ESCC) has remained elusive. In the present study, by using bioinformatics methods, the differential expression of NLRX1 at the mRNA level was examined. Overall survival, clinical correlation, receiver operating characteristic curve, Cox regression, co-expression, enrichment, immune infiltration and drug sensitivity analyses were carried out. A nomogram and a calibration curve were constructed. Changes in protein expression levels were investigated by immunohistochemistry and western blotting. The impact of NLRX1 on i) cell proliferation was evaluated by Cell Counting Kit-8 assays; ii) migration was examined by wound-healing assays; iii) migration and invasion were evaluated by Transwell assays; and iv) apoptosis was assessed by Annexin V/PI staining and flow cytometry. The results revealed that, compared to normal adjacent tissue, NLRX1 was lowly expressed in ESCC, and patients with low NLRX1 expression had a shorter survival time. NLRX1 was an independent prognostic factor for ESCC and was associated with tumor grading. Patients in the low-NLRX1 group showed a decrease in the infiltration of activated natural killer cells, monocytes and M0 macrophages, and these immune-cell infiltration levels were positively correlated with NLRX1 expression. Knocking down NLRX1 promoted the proliferation of KYSE450 cells, while overexpression of NLRX1 inhibited the proliferation of ECA109 cells. NLRX1 negatively regulated the PI3K/AKT signaling pathway in ESCC. These findings indicate that, through several mechanisms, NLRX1 suppresses tumor growth in ESCC, which offers new insight for investigating the causes and progression of ESCC, as well as for identifying more efficient therapeutic approaches.

Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients

Background

Stroke is a disease with high morbidity, disability, and mortality. Immune factors play a crucial role in the occurrence of ischemic stroke (IS), but their exact mechanism is not clear. This study aims to identify possible immunological mechanisms by recognizing immune-related biomarkers and evaluating the infiltration pattern of immune cells.

Methods

We downloaded datasets of IS patients from GEO, applied R language to discover differentially expressed genes, and elucidated their biological functions using GO, KEGG analysis, and GSEA analysis. The hub genes were then obtained using two machine learning algorithms (least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE)) and the immune cell infiltration pattern was revealed by CIBERSORT. Gene-drug target networks and mRNA-miRNA-lncRNA regulatory networks were constructed using Cytoscape. Finally, we used RT-qPCR to validate the hub genes and applied logistic regression methods to build diagnostic models validated with ROC curves.

Results

We screened 188 differentially expressed genes whose functional analysis was enriched to multiple immune-related pathways. Six hub genes (ANTXR2, BAZ2B, C5AR1, PDK4, PPIH, and STK3) were identified using LASSO and SVM-RFE. ANTXR2, BAZ2B, C5AR1, PDK4, and STK3 were positively correlated with neutrophils and gamma delta T cells, and negatively correlated with T follicular helper cells and CD8, while PPIH showed the exact opposite trend. Immune infiltration indicated increased activity of monocytes, macrophages M0, neutrophils, and mast cells, and decreased infiltration of T follicular helper cells and CD8 in the IS group. The ceRNA network consisted of 306 miRNA-mRNA interacting pairs and 285 miRNA-lncRNA interacting pairs. RT-qPCR results indicated that the expression levels of BAZ2B, C5AR1, PDK4, and STK3 were significantly increased in patients with IS. Finally, we developed a diagnostic model based on these four genes. The AUC value of the model was verified to be 0.999 in the training set and 0.940 in the validation set.

Conclusion

Our research explored the immune-related gene expression modules and provided a specific basis for further study of immunomodulatory therapy of IS.

Identification of hub necroptosis-related lncRNAs for prognosis prediction of esophageal carcinoma

Necroptosis is a newly identified programmed cell death associated with the biological process of various cancers, including esophageal carcinoma (ESCA). Meanwhile, the dysregulation of long non-coding RNAs (lncRNAs) is greatly implicated in ESCA progression and necroptosis regulation. However, the lncRNAs involved in regulating necroptosis in ESCA are still unclear. In this study, we aim to explore the expression profile of necroptosis-related lncRNAs (NRLs), and evaluate their roles in ESCA prognosis and treatment. In the present study, 198 differentially expressed NRLs were identified between the ESCA and adjacent normal tissues through screening the data extracted from the Cancer Genome Atlas (TCGA) database. And, a prognostic panel consisting of 6 NRLs was constructed using the LASSO algorithm and multivariate Cox regression analysis. The ESCA patients with high risks had a markedly reduced survival time and higher mortality prevalence. Moreover, C-index of 6 NRLs-panel was superior to 48 published prognostic models based on lncRNAs or mRNAs for ESCA. There were significant differences between the high-risk and low-risk groups in tumor-related pathways, genetic mutations, and drug sensitivity responses. In vitro analysis revealed that inhibition of PVT1 impeded the proliferation, migration, and colony formation of ESCA cells, increased the expressions of p-RIP1 and p-MLKL and promoted necroptosis. By contrast, PVT1 overexpression resulted in a decrease in necroptotic cell death events, thus promoting tumor progression. Collectively, the established 6-NRLs panel was a promising biomarker for the prognostic prediction of ESCA. Moreover, our current findings provided potential targets for individualized therapy for ESCA patients.

Down-regulation of SLC16A-AS1 and LINC00900 lncRNAs in Iranian patients with breast cancer

Long non-coding RNAs (lncRNAs) influence pathetiology of breast cancer. Besides, VDR and ESR1 signaling pathways are two important pathways in this malignancy. In the present mixed bioinformatics and expression assay study, we have identified lncRNAs that are co-expressed with VDR and ESR1 in breast cancer tissues and analyzed their expression in 42 paired breast cancer and non-cancerous specimens. Expression of SLC16A-AS1 was significantly lower in breast cancer tissues compared with paired non-cancerous samples (expression ratio = 0.27, P value < 0.001). Similarly, LINC00900 was down-regulated in cancer tissues compared with non-cancerous ones (expression ratio = 0.26, P value = 0.01). There were no significant differences in the expressions of VDR and AATBC between these two sets of samples. Expression levels of VDR and AATBC were associated with histological grade (P values = 0.02 and 0.03, respectively). Moreover, expression of VDR was associated with tumor size (P value = 0.02). Finally, expression levels of SLC16A-AS1 were associated with first pregnancy age (P value = 0.006). In brief, the results of current study further support involvement of VDR and ESR1-associated lncRNAs in breast cancer.

A novel cuproptosis-related lncRNA signature predicts prognosis and therapeutic response in bladder cancer

Bladder cancer (BC) ranks the tenth in the incidence of global tumor epidemiology. LncRNAs and cuproptosis were discovered to regulate the cell death. Herein, we downloaded transcriptome profiling, mutational data, and clinical data on patients from The Cancer Genome Atlas (TCGA). High- and low-risk BC patients were categorized. Three CRLs (AL590428.1, AL138756.1 and GUSBP11) were taken into prognostic signature through least absolute shrinkage and selection operator (LASSO) Cox regression. Worse OS and PFS were shown in high-risk group (p < 0.05). ROC, independent prognostic analyses, nomogram and C-index were predicted via CRLs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated IncRNAs play a biological role in BC progression. Immune-related functions showed the high-risk group received more benefit from immunotherapy and had stronger immune responses, and the overall survival was better (p < 0.05). Finally, a more effective outcome (p < 0.05) was found from clinical immunotherapy via the TIDE algorithm and many potential anti-tumor drugs were identified. In our study, the cuproptosis-related signature provided a novel tool to predict the prognosis in BC patients accurately and provided a novel strategy for clinical immunotherapy and clinical applications.

Prediction of Potential Biomarkers in Early-Stage Nasopharyngeal Carcinoma Based on Platelet RNA Sequencing

Early diagnosis is essential for the treatment and prevention of nasopharyngeal cancer. However, there is a lack of effective biological indicators for nasopharyngeal carcinoma (NPC). Therefore, we explored the potential biomarkers in tumour-educated blood platelet (TEP) RNA in early NPC. Platelets were isolated from blood plasma and their RNA was extracted. High-throughput sequenced data from a total of 33 plasma samples were analysed using DESeq2 to identify the differentially expressed genes (DEGs). Subsequently, the DEGs were subjected to principal component analysis (PCA), gene ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis; and Cytoscape, TargetScan, and miRanda software were used for inferring the competing endogenous RNA network. We identified 19 long non-coding (lnc) RNAs (DElncRNAs) and 248 mRNAs (DEmRNAs) that were differentially expressed in the TEP RNA. In addition, SELP gene mRNA and lncRNAs AC092135.3, AC012358.2, AL021807.1, AP001972.5, and GPX1 were found to be down-regulated DEmRNA and DElncRNAs in the early stage of NPC. Bioinformatic analysis showed that these DEmRNAs and DElncRNAs may be involved in regulating the pathogenesis of NPC. Our research may provide new insights for exploring the biological mechanisms of NPC and early diagnosis using potential biomarkers.

A tumor immune microenvironment-related integrated signature can predict the pathological response and prognosis of esophageal squamous cell carcinoma following neoadjuvant chemoradiotherapy: A multicenter study in China

BACKGROUND

Currently, there are insufficient indicators for the reliable assessment of treatment response following neoadjuvant chemoradiotherapy (nCRT) in patients with esophageal squamous cell carcinoma (ESCC). Considering the essential role of protein-coding and non-coding RNAs in gene regulation and cellular processes, we systematically explored the molecular features and clinical significance of mRNA and lncRNA in 249 pretreatment biopsies from four hospitals in three districts with a high incidence of ESCC patients in China.

METHODS

During the discovery phrase, 13 differentially expressed genes were identified and validated between samples with a complete pathological response (pCR) and those with an incomplete pathological response (<pCR). Subsequently, we constructed a predictive mRNA and lncRNA signature (SERPINE1, LINC00592, and PRKAG2-AS1) using Fisher's linear discriminant analysis (FLDA) with stepwise variant-selection, followed by validation of its predictive ability in both internal and external cohorts.

RESULTS

Our signature showed great value in predicting the response to nCRT among ESCC samples and acted as an independent predictive indicator, in addition to demonstrating great potential in estimating patient prognosis. Interestingly, we found that patients with a high signature score had lower PD-L1 and IDO1 expression levels but higher CD8⁺ T cells infiltration, suggesting that PD-L1 and IDO1 are negatively correlated with a high signature score and further associated with pCR and a better prognosis.

CONCLUSION

The present study identified a promising three-gene-based predictive signature that has powerful clinical implications for the identification of pCR and a good prognosis among patients with ESCC. Further immune-related exploration may provide an opportunity for future therapeutic combination.

A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma

Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model.

Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR.

Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group.

Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.

Prognostic score model based on six m6A-related autophagy genes for predicting survival in esophageal squamous cell carcinoma

BACKGROUND

Prognostic signatures based on autophagy genes have been proposed for esophageal squamous cell carcinoma (ESCC). Autophagy genes are closely associated with m6A genes. Our purpose is to identify m6A-related autophagy genes in ESCC and develop a survival prediction model.

METHODS

Differential expression analyses for m6A genes and autophagy genes were performed based on TCGA and HADd databases followed by constructing a co-expression network. Uni-variable Cox regression analysis was performed for m6A-related autophagy genes. Using the optimal combination of feature genes by LASSO Cox regression model, a prognostic score (PS) model was developed and subsequently validated in an independent dataset.

RESULTS

The differential expression of 13 m6A genes and 107 autophagy genes was observed between ESCC and normal samples. The co-expression network contained 13 m6A genes and 96 autophagy genes. Of the 12 m6A-related autophagy genes that were significantly related to survival, DAPK2, DIRAS3, EIF2AK3, ITPR1, MAP1LC3C, and TP53 were used to construct a PS model, which split the training set into two risk groups with significant different survival ratios (p = 0.015, 1-year, 3-year, and 5-year AUC = 0.873, 0.840, and 0.829). Consistent results of GSE53625 dataset confirmed predictive ability of the model (p = 0.024, 1-year, 3-year, and 5-year AUC = 0.793, 0.751, and 0.744). The six-gene PS score was an independent prognostic factor from clinical factors (HR, 2.362; 95% CI, 1.390-7.064; p-value = 0.012).

CONCLUSION

Our study recommends 6 m6A-related autophagy genes as promising prognostic biomarkers and develops a PS model to predict survival in ESCC.

The Emerging Role of Long Non-Coding RNAs in Esophageal Cancer: Functions in Tumorigenesis and Clinical Implications

Esophageal cancer (EC) is one of the most common malignancies of digestive tracts with poor five-year survival rate. Hence, it is very significant to further investigate the occurrence and development mechanism of esophageal cancer, find more effective biomarkers and promote early diagnosis and effective treatment. Long non-coding RNAs (lncRNAs) are generally defined as non-protein-coding RNAs with more than 200 nucleotides in length. Existing researches have shown that lncRNAs could act as sponges, guides, scaffolds, and signal molecules to influence the oncogene or tumor suppressor expressions at transcriptional, post-transcriptional, and protein levels in crucial cellular processes. Currently, the dysregulated lncRNAs are reported to involve in the pathogenesis and progression of EC. Importantly, targeting EC-related lncRNAs through genome editing, RNA interference and molecule drugs may be one of the most potential therapeutic methods for the future EC treatment. In this review, we summarized the biological functions and molecular mechanisms of lncRNAs, including oncogenic lncRNAs and tumor suppressor lncRNAs in EC. In addition, we generalized the excellent potential lncRNA candidates for diagnosis, prognosis and therapy in EC. Finally, we discussed the current challenges and opportunities of lncRNAs for EC.

Long Non-Coding NONRATG001910.2 Promotes the Proliferation of Rat Mesangial Cell Line HBZY-1 Through the miR-339-3p/CTNNB1 Axis

Chronic glomerulonephritis (CGN) is one of the leading causes of end-stage renal disease (ESRD). A growing body of literature emphasizes the important role of long non-coding RNAs (lncRNAs) in the development and progression of the disease. However, the function of NONRATG001910.2 in the development of CGN was not well understood. This research aimed to investigate the effect of NONRATG001910.2 on CGN and revealed its potential molecular mechanisms. In this work, the expression of NONRATG001910.2 was detected by quantitative real-time polymerase chain reaction (qRT-RCR) in cell lines. We found that NONRATG001910.2 was significantly up-regulated in lipopolysaccharide (LPS) induced cells. High NONRATG001910.2 levels were associated with the development of CGN. In addition, NONRATG001910.2 knockdown inhibited cell proliferation and cell cycle. At the same time, we found that up-regulation of microRNA-339-3p (miR-339-3p) abrogated the biological roles of NONRATG001910.2 up-regulation. Moreover, the knockdown of CTNNB1 can upregulate miR-339-3p expression, thereby inhibiting cell proliferation. In conclusion, these results demonstrated that NONRATG001910.2 in LPS-stimulated rat mesangial cell line HBZY-1 (HBZY-1) by targeting miR-339-3p, which subsequently promotes the expression of CTNNB1, and suggested that NONRATG001910.2 may be a potential biomarker.

A four immune-related long noncoding RNAs signature as predictors for cervical cancer

The progression, metastasis, and prognosis of cervical cancer (CC) is influenced by the tumor immune microenvironment. Studies proved that long non-coding RNAs (lncRNAs) to engage in cervical cancer development, especially immune-related lncRNAs, have emerged crucial in the tumor immune process. This study was set out to identify an immune-related lncRNA signature. In total, 13,838 lncRNA expression profiles and 328 immune genes were acquired from the clnical data of 306 CC tissues and 3 non-CC tissues. From the 433 identified immune-related lncRNAs, 4 candidate immune-related lncRNAs (SOX21-AS1, AC005332.4, NCK1-DT, LINC01871) were considered independent indicators of cervical cancer prognosis through the univariate and multivariate Cox regression analysis, and they were used to construct a prognostic and survival lncRNA signature model followed by the bootstrap method for further verification. Kaplan-Meier curves illustrated that cervical cancer patients could be divided into high-risk and low-risk groups with significant differences (P = 2.052e - 05), and the discrepancy of immune profiles between these two risk groups was illustrated by principal components analysis. Taken together, the novel survival predictive model created by the four immune-related lncRNAs showed promising clinical prediction value in cervical cancer.

A Novel Ferroptosis-Related Prognostic Signature Reveals Macrophage Infiltration and EMT Status in Bladder Cancer

Bladder cancer (BC) belongs to one of the most common and highly heterogeneous malignancies. Ferroptosis is a newly discovered regulated cell death (RCD), characterized by accumulation of toxic lipid peroxides, and plays a crucial role in tumor progression. Here, we conducted a comprehensive analysis on the transcriptomics data of ferroptosis-related genes in BC based on The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets. In our study, a 6-gene signature was identified based on the potential prognostic ferroptotic regulatory genes. Furthermore, our signature revealed a good independent prognostic ability in BC. Patients with low-risk score exhibited higher FGFR3 mutation rates while high risk score had a positive association with higher RB1 mutation rates. Meanwhile, higher proportions of macrophages were observed in high BC risk group simultaneously with four methods. Unexpectedly, the risk score showed a significant positive correlation with epithelial-mesenchymal transition (EMT) status. Functional assays indicated that CRYAB and SQLE knockdown was associated with attenuated invasion capacity. Our study revealed a ferroptosis-related risk model for predicting prognostic and BC progression. Our results indicate that targeting ferroptosis may be a therapeutic strategy for BC.

Epigenetic Mechanisms of LncRNAs Binding to Protein in Carcinogenesis

Epigenetic dysregulation is an important feature for cancer initiation and progression. Long non-coding RNAs (lncRNAs) are transcripts that stably present as RNA forms with no translated protein and have lengths larger than 200 nucleotides. LncRNA can epigenetically regulate either oncogenes or tumor suppressor genes. Nowadays, the combined research of lncRNA plus protein analysis is gaining more attention. LncRNA controls gene expression directly by binding to transcription factors of target genes and indirectly by complexing with other proteins to bind to target proteins and cause protein degradation, reduced protein stability, or interference with the binding of other proteins. Various studies have indicated that lncRNA contributes to cancer development by modulating genes epigenetically and studies have been done to determine which proteins are combined with lncRNA and contribute to cancer development. In this review, we look in depth at the epigenetic regulatory function of lncRNAs that are capable of complexing with other proteins in cancer development.