A novel long non-coding RNA linc-93.2 participates in bisphenol induced oxidative stress and macrophage polarization in red common carp (Cyprinus carpio).

Previous studies show that bisphenol A (BPA) and its analogs induce oxidative stress and promote inflammatory response. However, the key molecules in regulating this process remain unclear. Here, we report significant inductive effects of BPA and bisphenol AF (BPAF) on a newly found long non-coding RNA linc-93.2 accompanied by oxidative stress and activation of pro-inflammatory pathways in treated fish and fish primary macrophages. Silencing linc-93.2 in fish primary macrophages in vitro or fish in vivo significantly promotes the expression of anti-oxidative stress-related genes and anti-inflammatory cytokines. This inhibition of pro-inflammatory cytokine expression, showing cell status disruption towards to M2 polarization. Followed by exposure to BPA or BPAF, silencing linc-93.2 in vitro or in vivo significantly attenuates the increased production of reactive oxygen species and malondialdehyde level aroused by bisphenol treatment, possibly owing to the enhancement of total antioxidant capacity observed in cells and tissue after linc-93.2 knockdown. RNA-sequencing further revealed regulation of nuclear factor-kappa b (NF-κB) in linc-93.2's downstream network, combining with our previous observation on the upstream regulation of linc-93.2 via NF-κB, which together suggest a critical role of linc-93.2 in promoting NF-κB positive feedback loop that may be an important molecular event initiating the immunotoxicity of bisphenols.

Development of m6A/m5C/m1A regulated lncRNA signature for prognostic prediction, personalized immune intervention and drug selection in LUAD.

Research indicates that there are links between m6A, m5C and m1A modifications and the development of different types of tumours. However, it is not yet clear if these modifications are involved in the prognosis of LUAD. The TCGA-LUAD dataset was used as for signature training, while the validation cohort was created by amalgamating publicly accessible GEO datasets including GSE29013, GSE30219, GSE31210, GSE37745 and GSE50081. The study focused on 33 genes that are regulated by m6A, m5C or m1A (mRG), which were used to form mRGs clusters and clusters of mRG differentially expressed genes clusters (mRG-DEG clusters). Our subsequent LASSO regression analysis trained the signature of m6A/m5C/m1A-related lncRNA (mRLncSig) using lncRNAs that exhibited differential expression among mRG-DEG clusters and had prognostic value. The model's accuracy underwent validation via Kaplan-Meier analysis, Cox regression, ROC analysis, tAUC evaluation, PCA examination and nomogram predictor validation. In evaluating the immunotherapeutic potential of the signature, we employed multiple bioinformatics algorithms and concepts through various analyses. These included seven newly developed immunoinformatic algorithms, as well as evaluations of TMB, TIDE and immune checkpoints. Additionally, we identified and validated promising agents that target the high-risk mRLncSig in LUAD. To validate the real-world expression pattern of mRLncSig, real-time PCR was carried out on human LUAD tissues. The signature's ability to perform in pan-cancer settings was also evaluated. The study created a 10-lncRNA signature, mRLncSig, which was validated to have prognostic power in the validation cohort. Real-time PCR was applied to verify the actual manifestation of each gene in the signature in the real world. Our immunotherapy analysis revealed an association between mRLncSig and immune status. mRLncSig was found to be closely linked to several checkpoints, such as IL10, IL2, CD40LG, SELP, BTLA and CD28, which could be appropriate immunotherapy targets for LUAD. Among the high-risk patients, our study identified 12 candidate drugs and verified gemcitabine as the most significant one that could target our signature and be effective in treating LUAD. Additionally, we discovered that some of the lncRNAs in mRLncSig could play a crucial role in certain cancer types, and thus, may require further attention in future studies. According to the findings of this study, the use of mRLncSig has the potential to aid in forecasting the prognosis of LUAD and could serve as a potential target for immunotherapy. Moreover, our signature may assist in identifying targets and therapeutic agents more effectively.

LncRNAs involvement in pathogenesis of immune-related disease via regulation of T regulatory cells, an updated review.

The pathophysiology of several illnesses, including cancer and autoimmune diseasesdepends on human regulatory T cells (Tregs), and abnormalities in these cells may function as triggers for these conditions. Cancer and autoimmune, and gynecological diseases are associated with the differentiation of the proinflammatory T cell subset TH17 and its balance with the production of Treg. Recently, long non-coding RNAs (lncRNAs) have become important regulatory molecules in a wide range of illnesses. During epigenetic regulation, they can control the expression of important genes at several levels by affecting transcription, post-transcriptional actions, translation, and protein modification. They might connect with different molecules, such as proteins, DNA and RNA, and their structural composition is intricate. Because lncRNAs regulatebiological processes, including cell division, death, and growth, they are linked to severaldiseases. A notable instance of this is the lncRNA NEAT1, which has been the subject of several investigations to ascertain its function in immune cell development. In the context of immune cell development, several additional lncRNAs have been connected to Treg cell differentiation. In this work, we summarize current findings about the diverse functions of lncRNAs in Treg cell differentiation and control of the Th17/Treg homeostasis in autoimmune disorders, cancers, as well as several gynecological diseases where Tregs are key players.

Clinical Value and Mechanism of Long Non-Coding RNA UCA1 in Acute Respiratory Distress Syndrome Induced by Cardiopulmonary Bypass.

AIM: Long non-coding RNA (lncRNA) can be used as a biological marker for the diagnosis and treatment of various diseases. The study aimed to detect changes in the expression of lncRNA for urothelial carcinoma associated 1 (UCA1) in patients with cardiopulmonary bypass (CPB)-induced acute respiratory distress syndrome (ARDS). Clinical values and cell function in ARDS were explored. METHOD: In total, 195 patients without CPB-induced ARDS were included in the control group, and 85 patients with ARDS were included in the ARDS group. Serum UCA1 levels were measured by quantitative real-time polymerase chain reaction. A549 was used for the cell experiments by establishing oxygen-glucose deprivation/reperfusion (OGD/R) cell models, and the cell viability and apoptosis were tested. The concentration of inflammatory factors was tested by an enzyme-linked immunosorbent assay. A luciferase reporting assay was applied for target gene analysis. RESULTS: Quantitative real-time polymerase chain reaction revealed a gradual increase in serum UCA1 in both control and ARDS cases, and patients with ARDS had higher levels of UCA1 than those in the control group. Serum UCA1 was positively correlated with serum tumour necrosis factor-α and interleukin-6 concentration in patients with ARDS. UCA1 had the ability to distinguish patients with ARDS from those without it. UCA1 inhibition protected against lung injury and inhibited cell inflammation in vitro. MicroRNA (miR-182-5p) was downregulated in OGD/R-induced cell models and sponged by UCA1. CONCLUSIONS: Elevated expression of UCA1 may be associated with the occurrence of ARDS after CPB surgery. The regulatory role of UCA1 in ARDS might be related to inflammation and downregulated miR-182-5p in alveolar epithelial cells.

tRNA-like Transcripts from the NEAT1-MALAT1 Genomic Region Critically Influence Human Innate Immunity and Macrophage Functions.

The evolutionary conserved NEAT1-MALAT1 gene cluster generates large noncoding transcripts remaining nuclear, while tRNA-like transcripts (mascRNA, menRNA) enzymatically generated from these precursors translocate to the cytosol. Whereas functions have been assigned to the nuclear transcripts, data on biological functions of the small cytosolic transcripts are sparse. We previously found NEAT1-/- and MALAT1-/- mice to display massive atherosclerosis and vascular inflammation. Here, employing selective targeted disruption of menRNA or mascRNA, we investigate the tRNA-like molecules as critical components of innate immunity. CRISPR-generated human ΔmascRNA and ΔmenRNA monocytes/macrophages display defective innate immune sensing, loss of cytokine control, imbalance of growth/angiogenic factor expression impacting upon angiogenesis, and altered cell-cell interaction systems. Antiviral response, foam cell formation/oxLDL uptake, and M1/M2 polarization are defective in ΔmascRNA/ΔmenRNA macrophages, defining first biological functions of menRNA and describing new functions of mascRNA. menRNA and mascRNA represent novel components of innate immunity arising from the noncoding genome. They appear as prototypes of a new class of noncoding RNAs distinct from others (miRNAs, siRNAs) by biosynthetic pathway and intracellular kinetics. Their NEAT1-MALAT1 region of origin appears as archetype of a functionally highly integrated RNA processing system.

Long noncoding RNA uc.230/CUG-binding protein 1 axis sustains intestinal epithelial homeostasis and response to tissue injury.

Intestinal epithelial integrity is commonly disrupted in patients with critical disorders, but the exact underlying mechanisms are unclear. Long noncoding RNAs transcribed from ultraconserved regions (T-UCRs) control different cell functions and are involved in pathologies. Here, we investigated the role of T-UCRs in intestinal epithelial homeostasis and identified T-UCR uc.230 as a major regulator of epithelial renewal, apoptosis, and barrier function. Compared with controls, intestinal mucosal tissues from patients with ulcerative colitis and from mice with colitis or fasted for 48 hours had increased levels of uc.230. Silencing uc.230 inhibited the growth of intestinal epithelial cells (IECs) and organoids and caused epithelial barrier dysfunction. Silencing uc.230 also increased IEC vulnerability to apoptosis, whereas increasing uc.230 levels protected IECs against cell death. In mice with colitis, reduced uc.230 levels enhanced mucosal inflammatory injury and delayed recovery. Mechanistic studies revealed that uc.230 increased CUG-binding protein 1 (CUGBP1) by acting as a natural decoy RNA for miR-503, which interacts with Cugbp1 mRNA and represses its translation. These findings indicate that uc.230 sustains intestinal mucosal homeostasis by promoting epithelial renewal and barrier function and that it protects IECs against apoptosis by serving as a natural sponge for miR-503, thereby preserving CUGBP1 expression.

Downregulation of LEMD1-AS1 and Its Influences on the Diagnosis, Prognosis, and Immune Infiltrates of Epithelial Ovarian Cancer.

Previous studies have confirmed long noncoding RNA LEMD1-AS1 (LEMD1-AS1) as a functional factor in several tumors. The present work is aimed at exploring the prognostic and diagnostic values of LEMD1-AS1 in patients with epithelial ovarian cancer (EOC). We examined the expressions of LEMD1-AS1 in pan-cancer from TCGA microarray datasets and GTEx Project. The expressions of LEMD1-AS1 were detected by qRT-PCR in EOC specimens and normal ovarian specimens from 30 EOC patients. The χ 2 test was applied to compare the clinicopathological characteristics of different groups. ROC curves were established to determine the diagnostic values of LEMD1-AS1 in screening EOC tissues. The association of LEMD1-AS1 expression with clinical outcome was determined by the Kaplan-Meier methods and COX assays. A decreased expression of LEMD1-AS1 was observed in EOC tissues compared to matched normal specimens (p < 0.01). Low LEMD1-AS1 expression could be used to distinguish EOC from adjacent normal specimens. A clinical study revealed that patients with low LEMD1-AS1 expression have a shorter overall survival (p = 0.035) and progress-free interval (p = 0.041) than those with high LEMD1-AS1 expression. The Spearman correlation test revealed that LEMD1-AS1 expressions were negatively associated with the expressions of neutrophil and myeloid dendritic cell. Overall, our finding suggested that LEMD1-AS1 may have potential roles as a potential biomarker and/or a therapeutic target in EOC.

An Integrative Analysis Revealing ZFHX4-AS1 as a Novel Prognostic Biomarker Correlated with Immune Infiltrates in Ovarian Cancer.

Ovarian cancer (OC) is the main cause of deaths worldwide in female reproductive system malignancies. Growing studies have indicated that eRNAs could regulate cellular activities in various tumors. Yet the potential roles of eRNAs in OC progression have not been elucidated. Thus, comprehensive assays were needed to screen the critical eRNAs and to explore their possible function in OC. We used Kaplan-Meier methods to identify survival-associated eRNAs in OC based on TCGA datasets. The levels of ZFHX4-AS1 were examined using TCGA datasets. Further exploration was carried out based on the following assays: clinical and survival assays, GO terms, and KEGG assays. TIMER was applied to delve into the relationships between ZFHX4-AS1 and tumor immune infiltration. In this research, we observed 71 survival-related eRNAs in OC patients. ZFHX4-AS1 was highly expressed in OC specimens and predicted a poor prognosis of OC patients. In addition, high ZFHX4-AS1 expression was positively related to the advanced stages of OC specimens. Multivariate assays revealed that ZFHX4-AS1 was an independent prognostic factor for overall survival of OC patients. KEGG analysis indicated that ZFHX4-AS1 may play a regulatory effect on TGF-beta signaling, PI3K-Akt signaling, and proteoglycans in cancer. The pan-cancer validation indicated that ZFHX4-AS1 was related to survival in eight tumors, namely, UCEC, STAD, SARC, OV, ACC, KICH, KIRC, and BLCA. The expression of ZFHX4-AS1 was correlated with the levels of B cells, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cells. Simultaneously, ZFHX4-AS1 may be a prognostic biomarker and a distinctly immunotherapy-related eRNA in OC.

Involvement of blood lncRNA UCA1 in sepsis development and prognosis, and its correlation with multiple inflammatory cytokines.

BACKGROUND: Sepsis is a highly life-threatening disease. Long non-coding RNA urothelial carcinoma associated 1 (lncRNA UCA1) participates in the processes of inflammation and organ injury in several diseases, whereas its role in sepsis patients is still unclear. The aim was to explore the clinical value of lncRNA UCA1 in sepsis patients. METHODS: One hundred seventy-four sepsis patients and 100 age and gender-matched controls were enrolled. LncRNA UCA1 in peripheral blood mononuclear cell samples was examined, and the level of inflammatory cytokines in serum samples was assessed. RESULTS: LncRNA UCA1 was highly expressed in sepsis patients compared with controls. LncRNA UCA1 was positively correlated with tumor necrosis factor-α, interleukin (IL)-6, IL-17, intercellular adhesion molecule 1, and vascular cell adhesion molecule 1 in sepsis patients, while it was not correlated with these inflammatory cytokines in controls. lncRNA UCA1 upregulation was related to raised APACHE II score and SOFA score in sepsis patients. Moreover, lncRNA UCA1 was increased in sepsis deaths compared with sepsis survivors and was independently correlated with increased 28-day sepsis mortality risk. Further receiver operating characteristic curves presented that lncRNA UCA1 had a good value to predict 28-motality risk, while its combination with other independent factors (including age, history of chronic kidney disease, G+ bacterial infection, Fungus infection, C-reactive protein, and APACHE II score) exerted a great predictive value for 28-day mortality risk. CONCLUSION: LncRNA UCA1 is upregulated and correlates with multiple pro-inflammatory cytokines, terrible disease severity, and poor prognosis in sepsis patients.

The correlation of lncRNA SNHG16 with inflammatory cytokines, adhesion molecules, disease severity, and prognosis in acute ischemic stroke patients.

BACKGROUND: Long non-coding RNA small nucleolar RNA host gene 16 (lncRNA SNHG16) is involved in the pathogenesis of acute ischemic stroke (AIS) through the regulation of brain endothelial cell viability, inflammation, atherosclerotic plaque formation, and neural apoptosis. This study aimed to evaluate the prognostic value of lncRNA SNHG16 in AIS patients. METHODS: Newly diagnosed AIS patients (N = 120) were serially recruited. Their lncRNA SNHG16 expressions in peripheral blood mononuclear cells (PBMCs) were detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR); serum inflammatory cytokines and adhesion molecules were determined using enzyme-linked immunosorbent assay (ELISA). The accumulating recurrence-free survival (RFS) and overall survival (OS) were analyzed. Moreover, controls (N = 60) were recruited and their lncRNA SNHG16 expressions in PBMCs were detected. RESULTS: LncRNA SNHG16 was declined in AIS patients compared to controls (p < 0.001). Moreover, lncRNA SNHG16 was not related to any comorbidities in AIS patients (all p > 0.05). Interestingly, lncRNA SNHG16 was negatively related to tumor necrosis factor alpha (TNF-α) (p < 0.001), interleukin 6 (IL-6) (p = 0.013), and intracellular cell adhesion molecule-1 (ICAM-1) (p = 0.024), while positively correlated with interleukin 10 (IL-10) (p = 0.022) in AIS patients. Besides, lncRNA SNHG16 was inversely associated with the National Institutes of Health Stroke Scale (NIHSS) score in AIS patients (p = 0.003). During the follow-up period, in 14 (11.7%) patients occurred recurrence and 5 (4.2%) patients died. Unexpectedly, lncRNA SNHG16 was not associated with accumulating RFS (p = 0.103) or OS (p = 0.150) in AIS patients. CONCLUSION: LncRNA SNHG16 relates to lower inflammatory cytokines, adhesion molecules, and milder disease severity, but fails to predict prognosis in AIS patients.

LncRNA GAS5 relates to Th17 cells and serves as a potential biomarker for sepsis inflammation, organ dysfunctions and mortality risk.

BACKGROUND: Long noncoding RNA GAS5 (lnc-GAS5) is able to regulate macrophage M1 polarization and Th17 cell differentiation, also engaged in sepsis-induced inflammation and organ injury. This study aimed to further evaluate its linkage with Th1 cells and Th17 cells, as well as its clinical value in sepsis management. METHODS: About 101 sepsis patients were enrolled followed by peripheral blood mononuclear cell (PBMC) and serum samples collection. PBMC lnc-GAS5 was detected by RT-qPCR; Th1 cells and Th17 cells in PBMC CD4+ T cells were detected by flow cytometry; serum IFN-γ and IL-17A were detected by ELISA. Besides, PBMC lnc-GAS5 was also detected in 50 health controls (HCs). RESULTS: Lnc-GAS5 was reduced in sepsis patients than in HCs (p < 0.001), which also well-distinguished sepsis patients from HCs with AUC 0.860. Lnc-GAS5 did not relate to Th1 cells (p = 0.059) or IFN-γ (p = 0.192); while negatively linked with Th17 cells (p = 0.002) and IL-17A (p = 0.019) in sepsis patients. Interestingly, lnc-GAS5 negatively correlated with SOFA score (p = 0.001), SOFA-Respiratory system score (p = 0.001), SOFA-Coagulation score (p = 0.015), and SOFA-Renal system score (p = 0.026), but not SOFA-Liver score (p = 0.080), SOFA-Cardiovascular system score (p = 0.207) or SOFA-Nervous system score (p = 0.182) in sepsis patients. Furthermore, lnc-GAS5 was negatively related to CRP (p = 0.002) and APACHE II score (p = 0.004) in sepsis patients. Finally, lnc-GAS5 was decreased in dead sepsis patients compared to survivors (p = 0.007), which also distinguished sepsis deaths from survivors with AUC 0.713. CONCLUSION: Lnc-GAS5 relates to Th17 cells and serves as a potential biomarker for sepsis severity and mortality risk.

MALAT-1/p53/miR-155/miR-146a ceRNA circuit tuned by methoxylated quercitin glycoside alters immunogenic and oncogenic profiles of breast cancer.

Triple-Negative Breast Cancer (TNBC) is one of the most aggressive and hot BC subtypes. Our research group has recently shed the light on the utility of natural compounds as effective immunotherapeutic agents. The aim of this study is to investigate the role of a methoxylated quercetin glycoside (MQG) isolated from Cleome droserifolia in harnessing TNBC progression and tuning the tumor microenvironment and natural killer cells cytotoxicity. Results showed that MQG showed the highest potency (IC50 = 12 µM) in repressing cellular proliferation, colony-forming ability, migration, and invasion capacities. Mechanistically, MQG was found to modulate a circuit of competing endogenous RNAs where it was found to reduce the oncogenic MALAT-1 lncRNA and induce TP53 and its downstream miRNAs; miR-155 and miR-146a. Accordingly, this leads to alteration in several downstream signaling pathways such as nitric oxide synthesizing machinery, natural killer cells' cytotoxicity through inducing the expression of its activating ligands such as MICA/B, ULBP2, CD155, and ICAM-1 and trimming of the immune-suppressive cytokines such as TNF-α and IL-10. In conclusion, this study shows that MQG act as a compelling anti-cancer agent repressing TNBC hallmarks, activating immune cell recognition, and alleviating the immune-suppressive tumor microenvironment experienced by TNBC patients.

Constructing a Novel Signature Based on Immune-Related lncRNA to Improve Prognosis Prediction of Cervical Squamous Cell Carcinoma Patients.

We downloaded gene expression data, clinical data, and somatic mutation data of cervical squamous cell carcinoma (CSCC) patients from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Predictive lncRNAs were screened using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and risk scores were calculated for each patient according to the expression levels of lncRNAs and regression coefficients to establish a risk model that could be a novel signature. We assessed the correlation between immune infiltration status, chemotherapeutics sensitivity, immune checkpoint proteins (ICP), and the signature. Therefore, we selected 11 immune-related lncRNAs (WWC2,AS2, STXBP5.AS1, ERICH6.AS1, USP30.AS1, LINC02073, RBAKDN, IL21R.AS1, LINC02078, DLEU1, LINC00426, BOLA3.AS1) to construct the risk model. Patients who were in the high-risk group had a shorter survival time than those in the low-risk group (p < 0.001). Risk scores in the signature were negatively correlated with macrophage M1, macrophage M2, and T cell CD8 + ; what's more, T cell CD8 + was higher in the low-risk group. The expression levels of ICP such as PD-L1, PD-1, CTLA-4, TIGIT, LAG-3, and TIM-3 were substantially higher in the low-risk group. For chemotherapeutic agents, high-risk scores were associated with higher half-inhibitory concentrations (IC50) of cisplatin. These findings suggested that the risk model can be a novel signature for predicting CSCC patients' prognosis, and it also can be used to formulate clinical treatment plans for CSCC patients.

A prognostic model based on immune-related long noncoding RNAs for patients with epithelial ovarian cancer.

BACKGROUND: Long noncoding RNAs (lncRNAs) are important regulators of gene expression and can affect a variety of physiological processes. Recent studies have shown that immune-related lncRNAs play an important role in the tumour immune microenvironment and may have potential application value in the treatment and prognosis prediction of tumour patients. Epithelial ovarian cancer (EOC) is characterized by a high incidence and poor prognosis. However, there are few studies on immune-related lncRNAs in EOC. In this study, we focused on immune-related lncRNAs associated with survival in EOC. METHODS: We downloaded mRNA data for EOC patients from The Cancer Genome Atlas (TCGA) database and mRNA data for normal ovarian tissue from the Genotype-Tissue Expression (GTEx) database and identified differentially expressed genes through differential expression analysis. Immune-related lncRNAs were obtained through intersection and coexpression analysis of differential genes and immune-related genes from the Immunology Database and Analysis Portal (ImmPort). Samples in the TCGA EOC cohort were randomly divided into a training set, validation set and combination set. In the training set, Cox regression analysis and LASSO regression were performed to construct an immune-related lncRNA signature. Kaplan-Meier survival analysis, time-dependent ROC curve analysis, Cox regression analysis and principal component analysis were performed for verification in the training set, validation set and combination set. Further studies of pathways and immune cell infiltration were conducted through Gene Set Enrichment Analysis (GSEA) and the Timer data portal. RESULTS: An immune-related lncRNA signature was identified in EOC, which was composed of six immune-related lncRNAs (KRT7-AS, USP30-AS1, AC011445.1, AP005205.2, DNM3OS and AC027348.1). The signature was used to divide patients into high-risk and low-risk groups. The overall survival of the high-risk group was lower than that of the low-risk group and was verified to be robust in both the validation set and the combination set. The signature was confirmed to be an independent prognostic biomarker. Principal component analysis showed the different distribution patterns of high-risk and low-risk groups. This signature may be related to immune cell infiltration (mainly macrophages) and differential expression of immune checkpoint-related molecules (PD-1, PDL1, etc.). CONCLUSIONS: We identified and established a prognostic signature of immune-related lncRNAs in EOC, which will be of great value in predicting the prognosis of clinical patients and may provide a new perspective for immunological research and individualized treatment in EOC.

Exosomes Secreted by Mesenchymal Stem Cells Induce Immune Tolerance to Mouse Kidney Transplantation via Transporting LncRNA DANCR.

Mesenchymal stem cells induce kidney transplant tolerance by increasing regulatory T (Treg) cells. Bone marrow mesenchymal stem cell exosomes (BMMSC-Ex) promote Treg cell differentiation. Long non-coding RNA differentiation antagonizing non-protein coding RNA (DANCR) is expressed in BMMSCs and can be encapsulated in exosomes. We aimed to explore the role of DANCR in BMMSC-Ex in immune tolerance after kidney transplantation and related mechanism. The isogenic/allograft kidney transplantation mouse model was established, and levels of serum creatinine (SCr) were determined. Hematoxylin-eosin staining was conducted to detect the inflammation, and immunohistochemistry was performed to detect the infiltration of CD4+ T cells. Levels of IFN-γ, IL-17, and IL-2 were examined by ELISA. Flow cytometry was conducted to determine Treg cells. In the allograft group, the inflammatory response was severe, CD4+ T cell infiltration, SCr levels, and plasma rejection-related factors were up-regulated, while injection of BMMSC-Ex reversed the results. BMMSC-Ex increased Treg cells in kidney transplantation mice. Interference with DANCR reversed the promoting effect of BMMSC-Ex on Treg cell differentiation. DANCR bound to SIRT1, promoted ubiquitination and accelerated its degradation. The injection of BMMSC-Ex (after interference with DANCR) promoted SIRT1 levels, inflammatory response, CD4+ T cell infiltration, SCr levels, and plasma rejection related factors' expression, while Treg cells were decreased. LncRNA DANCR in BMMSC-Ex promoted Treg cell differentiation and induced immune tolerance of kidney transplantation by down-regulating SIRT1 expression in CD4+ T cells.

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.

Identifying immune subtypes of uterine corpus endometrial carcinoma and a four-paired-lncRNA signature with immune-related lncRNAs.

Uterine corpus endometrial carcinoma (UCEC) is the third most frequent gynecological malignancies in the female reproductive system. Long non-coding RNAs (lncRNAs) are closely involved in tumor progression. This study aimed to develop an immune subtyping system and a prognostic model based on lncRNAs for UCEC. Paired lncRNAs and non-negative matrix factorization were applied to identify immune subtypes. Enrichment analysis was conducted to assess functional pathways, immune-related genes, and cells. Univariate and multivariate Cox regression analysis were performed to analyze the relation between lncRNAs and overall survival (OS). A prognostic model was constructed and optimized by least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). Two immune subtypes (C1 and C2) and four paired-prognostic lncRNAs closely associated with overall survival were identified. Some immune features, sensitivity of chemotherapy and immunotherapy, and the relation with immune escape showed variations between two subtypes. A nomogram established based on prognostic model and clinical features was effective in OS prediction. The immune subtyping system based on lncRNAs and the four-paired-lncRNA signature was predictive of UCEC prognosis and can facilitate personalized therapies such as immunotherapy or RNA-based therapy for UCEC patients.

TransLnc: a comprehensive resource for translatable lncRNAs extends immunopeptidome.

LncRNAs are not only well-known as non-coding elements, but also serve as templates for peptide translation, playing important roles in fundamental cellular processes and diseases. Here, we describe a database, TransLnc (http://bio-bigdata.hrbmu.edu.cn/TransLnc/), which aims to provide comprehensive experimentally supported and predicted lncRNA peptides in multiple species. TransLnc currently documents approximate 583 840 peptides encoded by 33 094 lncRNAs. Six types of direct and indirect evidences supporting the coding potential of lncRNAs were integrated, and 65.28% peptides entries were with at least one type of evidence. Considering the strong tissue-specific expression of lncRNAs, TransLnc allows users to access lncRNA peptides in any of the 34 tissues involved in. In addition, both the unique characteristic and homology relationship were also predicted and provided. Importantly, TransLnc provides computationally predicted tumour neoantigens from peptides encoded by lncRNAs, which would provide novel insights into cancer immunotherapy. There were 220 791 and 237 915 candidate neoantigens binding by major histocompatibility complex (MHC) class I or II molecules, respectively. Several flexible tools were developed to aid retrieve and analyse, particularly lncRNAs tissue expression patterns, clinical relevance across cancer types. TransLnc will serve as a valuable resource for investigating the translation capacity of lncRNAs and greatly extends the cancer immunopeptidome.

A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma.

BACKGROUND: The abundant immune-related long non-coding RNA (IRLNRs) in immune cells and immune microenvironment have the potential to forecast prognosis and evaluate the effect of immunotherapy. IRLNRs analysis will provide a new perspective for LUAC research. METHODS: We calculated the immune score of each sample according to the expression levels of immune-related genes (IRGs) and screened the survival-related IRLNRs (sIRLNRs) by Cox regression analysis. The expression levels of AC068338.3 and AL691432.2 in tissues and cell lines were confirmed by RT-qPCR. RESULTS: 36 IRLNRs were selected by Pearson correlation analysis. Ten sIRLNRs were significantly correlated with the clinical outcomes of LUAC patients. Five sIRLNRs were identified by multivariate COX regression analysis to establish the immune-related risk score model (IRRS). The overall survival (OS) in the high-risk group was shorter than that in the low-risk group. IRRS could be an independent prognostic factor with significant survival correlation The distributions of immune gene concentrations were different between high-risk group and low-risk group. Furthermore, we further verified that the expression levels of AC068338.3 and AL691432.2 in different LUAC cell lines and tumor tissues were lower than that in Human bronchial epithelial cell (HBE) and adjacent tissues respectively. The lower expression levels of AC068338.3 and AL691432.2 were detected with the more advance T-stages. CONCLUSIONS: Our results highlighted some sIRLNRs with significant clinical correlations and demonstrated their monitored and prognostic values for LUAC patients. The results of this study may provide a new perspective for immunological research and immunotherapy strategies.

Identification of Immune-Related lncRNA Prognostic Signature and Molecular Subtypes for Glioblastoma.

Background: Glioblastoma multiforme (GBM) is extensively genetically and transcriptionally heterogeneous, which poses challenges for classification and management. Long noncoding RNAs (lncRNAs) play a critical role in the development and progression of GBM, especially in tumor-associated immune processes. Therefore, it is necessary to develop an immune-related lncRNAs (irlncRNAs) signature. Methods: Univariate and multivariate Cox regression analyses were utilized to construct a prognostic model. GBM-specific CeRNA and PPI network was constructed to predict lncRNAs targets and evaluate the interactions of immune mRNAs translated proteins. GO and KEGG pathway analyses were used to show the biological functions and pathways of CeRNA network-related immunity genes. Consensus Cluster Plus analysis was used for GBM gene clustering. Then, we evaluated GBM subtype-specific prognostic values, clinical characteristics, genes and pathways, immune infiltration access single cell RNA-seq data, and chemotherapeutics efficacy. The hub genes were finally validated. Results: A total of 17 prognostically related irlncRNAs were screened to build a prognostic model signature based on six key irlncRNAs. Based on GBM-specific CeRNAs and enrichment analysis, PLAU was predicted as a target of lncRNA-H19 and mainly enriched in the malignant related pathways. GBM subtype-A displayed the most favorable prognosis, high proportion of genes (IDH1, ATRX, and EGFR) mutation, chemoradiotherapy, and low risk and was characterized by low expression of four high-risk lncRNAs (H19, HOTAIRM1, AGAP2-AS1, and AC002456.1) and one mRNA KRT8. GSs with poor survival were mainly infiltrated by mesenchymal stem cells (MSCs) and astrocyte, and were more sensitive to gefitinib and roscovitine. Among GSs, three hub genes KRT8, NGFR, and TCEA3, were screened and validated to potentially play feasible oncogenic roles in GBM. Conclusion: Construction of lncRNAs risk model and identification of GBM subtypes based on 17 irlncRNAs, which suggesting that irlncRNAs had the promising potential for clinical immunotherapy of GBM.