LINC01094/miR-577 axis regulates the progression of ovarian cancer

A lactate-related tSNE signature defines prognostic subtypes of bladder cancer and reveals LINC01094-mediated VIM stabilization in metastasis and drug resistance

Background

Bladder cancer (BLCA) is prone to metastasis and often shows poor responses to chemotherapy and immunotherapy. Investigating the underlying mechanisms of metastasis and drug resistance may therefore offer new therapeutic strategies for BLCA.

Methods

Publicly available datasets were analyzed using consensus clustering and t-distributed stochastic neighbor embedding (tSNE) to characterize a lactate-related gene signature in BLCA. Gene set variation analysis (GSVA) was employed to assess signaling pathway activity, while immune cell infiltration in the tumor microenvironment (TME) was evaluated using single-sample gene set enrichment analysis (ssGSEA), the Estimation of Stromal and Immune cells in Malignant Tumors using Expression data (ESTIMATE), and CIBERSORT. RNA pull-down and RNA-binding protein immunoprecipitation (RIP) assays were then performed to confirm molecular interactions.

Results

Two distinct BLCA subtypes were identified based on lactate-related gene expression, and a lactate-based tSNE score was constructed. This score demonstrated prognostic value and was integrated into a nomogram confirmed by a calibration curve. Functionally, higher tSNE scores correlated with immune- and inflammation-related pathways, as well as with immunotherapy efficacy in BLCA. Among candidate regulators identified, LINC01094 emerged as a key factor in BLCA metastasis and drug resistance. LINC01094 was predominantly localized in the cytoplasm and was upregulated in tumor tissues compared with adjacent normal tissues, acting as an unfavorable prognostic factor. In vitro, LINC01094 promoted metastasis and chemotherapy resistance, potentially by stabilizing VIM protein levels and inhibiting its ubiquitination.

Conclusions

This comprehensive analysis of lactate-related genes reveals how this gene signature may shape the tumor microenvironment and affect BLCA patient prognosis. Additionally, our data suggest that targeting LINC01094 with antisense oligonucleotides (ASOs) could reduce BLCA cell metastasis and enhance their sensitivity to chemotherapy.

Exploring miR-577 and miR-494-3p as Emerging Biomarkers in Sepsis-Associated Acute Kidney Injury: Diagnostic and Prognostic Perspectives

Sepsis-associated acute kidney injury (AKI) poses a severe threat to patients' lives and health, making early predictions, intervention, and treatment crucial. This study aims to preliminarily explore the clinical role of miR-577 and miR-494-3p in sepsis-associated AKI. The study included 70 sepsis patients with AKI, 65 sepsis patients without AKI, and a healthy control group (HC, n = 67) to set baseline miRNA levels. Urinary miR-577 and miR-494-3p levels were measured using qRT-PCR. ROC curves evaluated their diagnostic value for sepsis-associated AKI. Logistic regression analyzed AKI risk factors, while Pearson correlation explored miRNA-clinical indicator links. Cox regression models and KM curves assessed the prognostic value of miRNAs in sepsis-associated AKI patients. Sepsis-associated AKI patients showed heightened inflammatory markers, renal indicators, and APACHE II scores compared to those without AKI. However, their urinary miR-577 and miR-494-3p levels were notably lower, distinguishing them with high diagnostic value. These miRNAs inversely correlated with inflammatory markers, renal indicators, and severity scores. Logistic regression showed lactate, PCT, BUN, Scr, Cys-C, NGAL, KIM-1, and APACHE II, as risk factors, while miR-577 and miR-494-3p were protective. In deceased sepsis-associated AKI patients, these miRNAs were lower, with higher inflammatory markers, renal indicators, and severity scores. miR-577 and miR-494-3p independently predicted mortality, with lower expressions linked to higher death rates. miR-577 and miR-494-3p are closely related to sepsis-associated AKI and can serve as potential biomarkers for diagnosis and prognostic assessment.

Latest Update on lncRNA in Epithelial Ovarian Cancer-A Scoping Review

Long noncoding RNAs (lncRNAs) are RNA molecules exceeding 200 nucleotides that do not encode proteins yet play critical roles in regulating gene expression at multiple levels, such as chromatin modification and transcription. These molecules are significantly engaged in cancer progression, development, metastasis, and chemoresistance. However, the function of lncRNAs in epithelial ovarian cancer (EOC) has not yet been thoroughly studied. EOC remains challenging due to its complex molecular pathogenesis, characterized by genetic and epigenetic alterations. Emerging evidence suggests that lncRNAs, such as XIST, H19, NEAT1, and MALAT1, are involved in EOC by modulating gene expression and signaling pathways, influencing processes like cell proliferation, invasion, migration, and chemoresistance. Despite extensive research, the precise mechanism of acting of lncRNAs in EOC pathogenesis and treatment resistance still needs to be fully understood, highlighting the need for further studies. This review aims to provide an updated overview of the current understanding of lncRNAs in EOC, emphasizing their potential as biomarkers and therapeutic targets. We point out the gaps in the knowledge regarding lncRNAs' influence on epithelial ovarian cancer (EOC), deliberating on new possible research areas.

LINC01094 promotes gastric cancer through dual targeting of CDKN1A by directly binding RBMS2 and HDAC1

BACKGROUND

Accumulating studies have focused on long noncoding RNAs (lncRNAs) because of their regulatory effects on multiple cancers. However, the biological functions and molecular mechanisms of lncRNAs in gastric cancer (GC) remain to be elucidated in depth.

METHODS

Long intergenic nonprotein coding RNA 1094 (LINC01094), a differentially expressed lncRNA between GC tissues and adjacent normal tissues, was identified. Moreover, gain- and loss-of-function experiments in vitro and in vivo were carried out. To understand the mechanisms underlying the regulatory effects of LINC01094, we performed RNA pull-down assays, RNA immunoprecipitation assays, chromatin immunoprecipitation assays, luciferase reporter assays, etc. RESULTS: LINC01094 was markedly upregulated in GC tissues and cell lines, and LINC01094 upregulation was positively correlated with GC malignant behaviours in vitro and in vivo. Mechanistically, LINC01094 downregulated the expression of CDKN1A by interacting with RNA binding motif single stranded interacting protein 2 (RBMS2) and histone deacetylase 1 (HDAC1). Additionally, LINC01094 was confirmed to sponge miR-128-3p and participate in the LINC01094-miR-128-3p-RUNX family transcription factor 1 (RUNX1) feedback loop. Finally, Ro 5-3335, a validated RUNX1 inhibitor, was explored for anticancer drug development in GC.

CONCLUSIONS

The LINC01094-miR-128-3p-RUNX1 feedback loop downregulates CDKN1A and promotes GC cooperatively with RBMS2 and HDAC1. Furthermore, Ro 5-3335 may hold promising therapeutic potential in the treatment of GC. Hence, our study found an oncogenic lncRNA, LINC01094, which could be a promising target for cancer treatment and diagnosis.

The LINC01094/miR-545-3p/SLC7A11 Signaling Axis Promotes the Development of Gastric Cancer by Regulating Cell Growth and Ferroptosis

This study aimed to investigate the role and mechanism of action of LINC01094 in the development of gastric cancer (GC). The expression levels of LINC01094 in GC patients and healthy individuals were analyzed online using the Cancer Genome Atlas database. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analyses were performed to determine the expression of LINC01094/miR-545-3p/SLC7A11 in GC tissues and cells. Functional experiments (MTT assay, colony formation assay, and flow cytometry) were conducted to assess the effect of LINC01094 and miR-545-3p on cell proliferation, viability, apoptosis, cell cycle, and reactive oxygen species. Correlations between LINC01094 and miR-545-3p, as well as SLC7A11, were analyzed and validated using the dual-luciferase reporter assay and RNA immunoprecipitation. The levels of Fe2+, malondialdehyde, and glutathione in the cells were measured biochemically, and the protein expression levels of Bcl-2, cleaved caspase3, Cyclin D1, and p21 were detected by Western blotting. LINC01094 was significantly upregulated in the GC tissues and cells with a targeting relationship with miR-545-3p; the expression levels of LINC01094 and miR-545-3p were negatively correlated. Knockdown of LINC01094 notably inhibited the proliferation and viability of GC cells and promoted cell ferroptosis, which, however, was abrogated by the silencing of miR-545-3p. These findings indicate that miR-545-3p could target and positively correlate with SLC7A11 expression. Additionally, LINC01094 could promote GC cell progression and affect cellular ferroptosis by regulating the miR-545-3p/SLC7A11 signaling axis.

Identification of lncRNA dual targeting PD-L1 and PD-L2 as a novel prognostic predictor for gastric cancer

Background

Although breakthroughs have been achieved in gastric cancer (GC) therapy with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1), the acquisition of high response rate remains a huge challenge for clinicians. It is imperative to identify novel biomarkers for predicting response to immunotherapy and explore alternative therapeutic strategy for GC.

Methods

The transcriptomic profiles and clinical information of GC patients from The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) database was used to screen differentially expressed lncRNAs between the tumor specimens and the paracancerous tissues. The TargetScan, miRDB and miRcode database were then utilized to construct competing endogenous RNA (ceRNA) networks and identify pivotal lncRNAs. An independent dataset from GEO (GSE70880) and 23 pairs of GC specimens of our cohort were subsequently performed for external validity. The relationship between clinical variables and gene expression were evaluated by Kruskal-wallis test and Wilcoxon signed-rank. The prognostic value of the candidate genes was assessed using Kaplan-Meier analysis and Cox regression models. CIBERSORT and Gene set enrichment analysis (GSEA) were used to determine immune cell infiltration. Gastric adenocarcinoma AGS cells and human embryonic kidney 293T (HEK293T) cells with knockdown of LINC01094 were generated by siRNA transfection, followed by detecting the alteration of the target miRNA and PD-L1/PD-L2 by RT-qPCR. Besides, the interaction between lncRNA and the miRNA-PD-L1/PD-L2 axis were verified by dual luciferase reporter assay.

Results

Twenty-two intersecting lncRNAs were identified to be PD-L1/PD-L2-related lncRNAs and LINC01094-miR-17-5p-PD-L1/PD-L2 was constructed as a potential ceRNA network. LINC01094 was increased in tumor specimens than adjacent normal samples and was positively associated with advanced tumor stages and EBV and MSI status. Furthermore, LINC01094 expression was an independent risk factor for poor overall survival (OS) in GC patients. CD8+ T cell exhaustion-related genes were enriched in high-LINC01094 tissues and high-PD-L2 group. A strong positive association of LINC01094 expression was established with M2 macrophages, IL-10+ TAM, as well as PD-L1 and PD-L2 levels, therefore a LINC01094-miR-17-5p-IL-10 network was proposed in macrophages. Using the exoRBase database, LINC01094 was assumed in blood exosomes of GC patients The results of knockdown experiments and luciferase reporter assays revealed that LINC01094 interacted with miR-17-5p and served as a miRNA sponge to regulate the expression of PD-L1 and PD-L2.

Conclusion

LINC01094 dually regulates the expression of PD-L1 and PD-L2 and shapes the immunosuppressive tumor microenvironment via sponging miR-17-5p. LINC01094 may serve as a potential prognostic predictor and therapeutic target in GC.

LINC01094: A key long non-coding RNA in the regulation of cancer progression and therapeutic targets

LINC01094 is a long non-coding RNA that plays a crucial role in cancer progression by modulating key signaling pathways, such as PI3K/AKT, Wnt/β-catenin and TGF-β Signaling Pathway Feedback Loop. In this review we summarize the recent research on the functional mechanisms of LINC01094 in various cancers, including its impact on tumor growth, metastasis, and resistance to therapy. We also discuss the therapeutic potential of targeting LINC01094 and highlight the current strategies and challenges in this area. Perspectives on future development of LINC01094-based therapies are also provided.

Prognostic significance of non-coding RNAs related to the tumorigenic epithelial-mesenchymal transition (EMT) process among ovarian cancer patients: A systematic review and meta-analysis

Introduction

Ovarian cancer is the seventh most prevalent cancer among women. It has high mortality and morbidity and imposes a great burden on healthcare systems worldwide. Unraveling the mechanisms behind the Epithelial-Mesenchymal Transition and finding a panel for predicting the prognosis of the disease may help find the appropriate treatment approaches for the management of the disease. The overarching aim of this systematic review was to define a panel of different types of EMT-associated non-coding RNAs (ncRNAs) with significant prognostic value in all types of ovarian cancers.

Methods

We searched PubMed, Web of Science, Scopus, and Embase till Jun 2024 to retrieve relevant papers. Two independent reviewers screened papers, and discrepancies were resolved by consensus. Publications related to the dysregulation of different types of ncRNAs, including microRNAs, lncRNAs, and circRNAs, only in patients with ovarian cancer were included. The participation of ncRNAs in epithelial-mesenchymal transformation should be assessed via methods evaluating different EMT-related proteins. To assess the quality and risk of bias for the included case-control and cohort studies, refined Newcastle-Ottawa Scale (NOS) and Quadas-2 were recruited. A bivariate meta-analysis was performed to analyze extracted data.

Results

A total of 37 studies with overall 42 non-coding RNAs (15 microRNA, 24 long non-coding RNAs, and 3 circular RNAs) were entered into the analysis. Overall diagnostic odds ratio for ncRNAs in lymph node metastasis, distant metastasis, TNM stage, and clinical stage were 4.19, 3.80, 6.52, and 3.97, respectively. Also, a hazard ratio of 1.39 (P = 0.32) for overall survival was observed. Bioinformatic analyses on the Pan-cancer database demonstrated a significant correlation between low expression of miRNA and high expression of lncRNAs with poor prognosis of ovarian cancer.

Conclusion

Based on the results, the defined panel of ncRNAs can properly predict prognostic factors related to EMT in ovarian cancer without involving potentially invasive methods.

TGF-β1-Induced LINC01094 promotes epithelial-mesenchymal transition in hepatocellular carcinoma through the miR-122-5p/TGFBR2-SAMD2-SMAD3 Axis

Hepatocellular carcinoma (HCC) is a common malignancy with a poor prognosis. It has been proven that long non-coding RNAs (lncRNAs) play an essential role in regulating HCC progression. However, the involvement of LINC01094 in regulating epithelial-mesenchymal transition (EMT) in HCC remains unclear. LINC01094 expression in HCC patients was retrieved from the Cancer Genome Atlas database. Overexpressing and downregulating LINC01094 were conducted to investigate its biological functions using Hep3B, SNU-387, and HuH-7 cells. Western blotting and morphological observation were performed to study the EMT in HCC cells. Transwell assay was adopted to determine the migration and invasion of HCC cells. The underlying mechanism of competitive endogenous RNAs (ceRNAs) was investigated using bioinformatics analysis, quantitative reverse-transcription polymerase chain reaction, and rescue experiments. Elevated LINC01094 expression was observed in HCC and associated with a poor prognosis. Knockdown of LINC01094 expression in SNU-387 and HuH-7 cells could inhibit migration, invasion, and EMT markers. Overexpression of LINC01094 indicated that LINC01094 promoted EMT via the TGF-β/SMAD signaling pathway. The bioinformatics analysis revealed that miR-122-5p was a target of LINC01094. The miRWalk database analysis showed that TGFBR2, SMAD2, and SMAD3 were downstream targets of miR-122-5p. Mechanically, LINC01094 acted as a ceRNA that facilitated HCC metastasis by sponging miR-122-5p to regulate the expression of TGFBR2, SMAD2, and SMAD3. Further, TGF-β1 could enhance the expression of LINC01094, forming a positive feedback loop. TGF-β1-induced LINC01094 expression promotes HCC cell migration and invasion by targeting the miR-122-5p/TGFBR2-SMAD2-SMAD3 axis. LINC01094 may be a potential prognostic biomarker and therapeutic target for HCC metastasis.

MicroRNAs, long non-coding RNAs, and circular RNAs and gynecological cancers: focus on metastasis

Gynecologic cancer is a significant cause of death in women worldwide, with cervical cancer, ovarian cancer, and endometrial cancer being among the most well-known types. The initiation and progression of gynecologic cancers involve a variety of biological functions, including angiogenesis and metastasis-given that death mostly occurs from metastatic tumors that have invaded the surrounding tissues. Therefore, understanding the molecular pathways underlying gynecologic cancer metastasis is critical for enhancing patient survival and outcomes. Recent research has revealed the contribution of numerous non-coding RNAs (ncRNAs) to metastasis and invasion of gynecologic cancer by affecting specific cellular pathways. This review focuses on three types of gynecologic cancer (ovarian, endometrial, and cervical) and three kinds of ncRNAs (long non-coding RNAs, microRNAs, and circular RNAs). We summarize the detailed role of non-coding RNAs in the different pathways and molecular interactions involved in the invasion and metastasis of these cancers.

Identification of a pyroptosis-related long non-coding RNA Signature for prognosis and its related ceRNA regulatory network of ovarian cancer

Aim: To identify the pyroptosis-related long non-coding RNAs (lncRNAs) in ovarian cancer and construct a prognostic signature based on them. Methods: Expression data from TCGA was used to explore differentially expressed pyroptosis-related lncRNAs in ovarian cancer. A risk signature was established by LASSO and cox regression analysis and then validated. Databases such as ESTIMATE, CIBERSORT, TIMER, XCELL were used to identify the relation between this signature and the immune microenvironment of ovarian cancer. Gene Set Enrichment Analysis was introduced to identify the pathways and functions that the signature may participate in. Based on miRcode and starBase databases, microRNAs related to the lncRNAs in our signature and the positively co-expressed pyroptosis- related genes were screened and a competing endogenous RNA (ceRNA) network was then constructed. Quantitative reverse transcription PCR was conducted to validate the expression levels of two lncRNAs in this ceRNA network. Results: A 13 pyroptosis-related lncRNA prognostic signature (MYCNOS, AL161772.1, USP30-AS1, ZNF32-AS2, AC068733.3, AC012236.1, AC015802.5, KIAA1671-AS1, AC013403.2, MIR223HG, KRT7-AS, PTPRD-AS1 and LINC01094) was constructed. Patients in high-risk group had a significantly worse prognosis than that of low-risk (P<0.0001). Immune infiltration analysis found that patients identified as high-risk had a higher infiltration of macrophages and tumor-associated fibroblasts. Further pathway analysis revealed that the signature may be involved in epithelial mesenchymal transition, extracellular matrix receptor interaction, and focal adhesion. Finally, a competitive endogenous inhibition relationship was discovered between LINC01094, KRT7-AS, MYCNOS, ZNF32-AS2, AC012236.1 and pyroptosis- related genes such as IRF1, NOD1, GSDMC, NLRP1, PLCG1, GSDME and GZMB, in which LINC01094 and KRT7-AS were found to be overexpressed in three ovarian cancer cell lines. Conclusion: We constructed a pyroptosis-related lncRNA signature and correlate it to the immune microenvironment. A ceRNA regulatory network related to pyroptosis was also constructed, which provides novel insights useful for the study of pyroptosis in ovarian cancer.

The role of pyroptosis-related lncRNA risk signature in ovarian cancer prognosis and immune system

Ovarian cancer is a leading cause of death in females with gynecologic cancers. Pyroptosis is a relatively new discovered programmed cell death that is believed to be associated with inflammation. However, studies on pyroptosis-related lncRNAs in ovarian cancer are limited. In this study, we identified 29 pyroptosis-related genes and screened out 72 pyroptosis-related lncRNAs. Furthermore, the 72 lncRNAs were eliminated to 2 survival-related lncRNAs using Cox regression and Lasso regression to build an ovarian cancer prognostic prediction signature and were further validated on the test set. We adopted a riskscore from the two-gene signature, and the survival in low-risk group was higher than the high-risk group. Functional enrichment analysis indicated that the differentially expressed genes (DEGs) between two risk groups were associated with tumor immunity. This study implies that pyroptosis-related genes are closely related to tumor immunity and could be potential therapeutic factors for ovarian cancer treatment.

The Role of EMT-Related lncRNAs in Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers worldwide; late diagnosis and drug resistance are two major factors often responsible for high morbidity and treatment failure. Epithelial-to-mesenchymal transition (EMT) is a dynamic process that has been closely linked with cancer. Long non-coding RNAs (lncRNAs) have been also associated with several cancer-related mechanisms, including EMT. We conducted a literature search in the PubMed database in order to sum up and discuss the role of lncRNAs in regulating OC-related EMT and their underlying mechanisms. Seventy (70) original research articles were identified, as of 23 April 2023. Our review concluded that the dysregulation of lncRNAs is highly associated with EMT-mediated OC progression. A comprehensive understanding of lncRNAs' mechanisms in OC will help in identifying novel and sensitive biomarkers and therapeutic targets for this malignancy.

A new ferroptosis-related signature model including messenger RNAs and long non-coding RNAs predicts the prognosis of gastric cancer patients

BACKGROUND AND OBJECTIVES

Gastric cancer (GC) is among the most malignant tumor types, which causes heavy healthy and economic burden to the people and societies all around the world. Establishment of an effective set of prognostic marker will benefit a lot to the treatment of GC patients clinically. Ferroptosis is a newly identified regulated cell death modality, with tight relevance with GC development. However, its application in the prognosis of GC has not been studied in detail. Deregulated messenger RNA (mRNA) and long non-coding RNA (lncRNA) expression profile in tumor can serve as novel prognostic marker for predicting the survival and cancer relapse in patients.

METHODS

We downloaded ferroptosis-related gene expression microarray data, clinicopathologic information and a list of 259 ferroptosis-related genes from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Ferroptosis database, respectively. Then, correlation analysis, univariate and multivariate Cox regression analysis were used to construct a novel prognostic model for GC. Then, we validated the model in the GEO datasets. Finally, we evaluated the differences in immune microenvironment between high- and low-risk groups.

RESULTS

We utilized the ferroptosis-related mRNA and lncRNA profile to successfully construct a prognostic model (incorporating 2 mRNAs and 15 lncRNAs) in GC. Our model, integrating diverse clinical traits and critical factors of GC, showed desirable efficacy in the prognosis of GC patients. This model also manifested effectively in validation by using external patients' data.

CONCLUSIONS

Our study developed a novel ferroptosis-related signature to predict the prognosis of gastric cancer patients. The ferroptosis-related signature had a favorable predictive ability. This model may greatly boost the treatment of GC patients in clinical practice.

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer

Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model's reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS' correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker.

Taxol‑resistant breast cancer cell‑derived exosome‑delivered miR‑187‑5p regulates the growth of breast cancer cells via ABCD2 and Wnt/β‑catenin signaling

Acquired resistance to Taxol (TAX) contributes to clinical treatment failure and significantly reduces the survival rate of patients. The present study aimed to explore the effects of exosomal microRNA (miR)-187-5p on TAX resistance in breast cancer cells and its underlying mechanisms. Exosomes were isolated from MCF-7 and TAX-resistant MCF-7/TAX cells, and the miR-187-5p and miR-106a-3p levels of the cells and exosomes were determined using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Next, MCF-7 cells were treated with TAX for 48 h and either treated with exosomes or transfected with miR-187-5p mimics. Cell viability, apoptosis, migration, invasion and colony formation were determined using Cell Counting Kit-8, flow cytometry, Transwell and colony formation assays, and the expression levels of associated genes and proteins were detected by RT-qPCR and western blotting, respectively. Finally, a dual-luciferase reporter gene assay was performed to confirm the target of miR-187-5p. The results showed that miR-187-5p expression levels increased significantly in TAX-resistant MCF-7 cells and exosomes compared with normal MCF-7 cells and exosomes (P<0.05). However, miR-106a-3p was not detected in the cells or exosomes. Therefore, miR-187-5p was selected for subsequent experiments. A series of cell assays showed that TAX inhibited the viability, migration, invasion and colony formation of MCF-7 cells and promoted their apoptosis; however, these changes were reversed by resistant cell exosomes and miR-187-5p mimics. Additionally, TAX significantly upregulated ABCD2 and downregulated β-catenin, c-Myc and cyclin D1, whereas resistant exosomes and miR-187-5p mimics reversed the TAX-induced changes in expression. Finally, ABCD2 was confirmed to directly bind with miR-187-5p. It may be concluded that TAX-resistant cell-derived exosomes delivering miR-187-5p may affect the growth of TAX-induced breast cancer cells by targeting ABCD2 and c-Myc/Wnt/β-catenin signaling.

An angiogenesis-related three-long non-coding ribonucleic acid signature predicts the immune landscape and prognosis in hepatocellular carcinoma

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.

LncRNA LINC01094 Promotes Cells Proliferation and Metastasis through the PTEN/AKT Pathway by Targeting AZGP1 in Gastric Cancer

Long noncoding RNAs (lncRNAs) were recently reported to play an essential role in multiple cancer types. Herein, through next-generation sequencing, we screened metastasis-driving molecules by using tissues from early-stage gastric cancer (GC) patients with lymph node metastasis, and we identified a lncRNA LINC01094, which was associated with the metastasis of GC. According to the clinical data from the TCGA, GSE15459, and GSE62254 cohorts, the high expression of LINC01094 was associated with an unfavorable prognosis. Moreover, 106 clinical GC and paired normal samples were collected, and the qRT-PCR results showed that the high expression of LINC01094 was associated with high T and N stages and a poor prognosis. We found that LINC01094 promotes the proliferation and metastasis of GC in vitro and in vivo. AZGP1 was found as the protein-binding partner of LINC01094 by using RNA pulldown and RNA-binding protein immunoprecipitation (RIP) assays. LINC01094 antagonizes the function of AZGP1, downregulates the expression of PTEN, and further upregulates the AKT pathway. Collectively, our results suggested that LINC01094 might predict the prognosis of GC patients and become the therapy target for GC.

An immune infiltration-related long non-coding RNAs signature predicts prognosis for hepatocellular carcinoma

Background: With a high incidence and dismal survival rate, hepatocellular carcinoma (HCC) tops the list of the world's most frequent malignant tumors. Immunotherapy is a new approach to cancer treatment, and its effect on prolonging overall survival (OS) varies from patient to patient. For a more effective prognosis and treatment of HCC, we are committed to identifying immune infiltration-related long non-coding RNAs (IIRLs) with prognostic value in hepatocellular carcinoma. Methods: In our study, we calculated immune scores of 369 hepatocellular carcinoma samples from the Cancer Genome Atlas (TCGA) database by using an estimation algorithm, and obtained long non-coding RNAs (lncRNAs) associated with immune infiltration by using Weighted Gene Co-expression Network analysis (WGCNA). For training cohort, univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis were used to determine prognostic IIRLs, we established a prognostic IIRLs signature. By testing cohort and entire cohort, we confirmed that the signature is practical. The prognosis of people with different clinicopathological stages and risk scores were predicted by the nomogram we constructed. In addition, Immune cell infiltration analysis and prediction of therapeutic drugs were performed. Results: 93 IIRLs were obtained by WGCNA. Furthermore, the prognostic value of these IIRLs were evaluated by using univariate Cox, Lasso and multivariate Cox analysis. Four IIRLs were used to create a signature with a prognosis. Time-related receiver operating characteristic (ROC) curve revealed that this model had an acceptable prognostic value for HCC patients. By using univariate and multivariate Cox regression analysis, this risk score has been shown to be an independent prognostic factor for HCC. The nomogram we made showed good predictions. Except for that, the treatment with immune checkpoint inhibitors (ICI) was likely to be more effective for low-risk patients. Conclusion: Based on four IIRLs, a prognostic signature was created in this research showed good accuracy in predicting OS. This study also provided valuable references for Immunotherapy of hepatocellular carcinoma.

Screening and validation of platelet activation-related lncRNAs as potential biomarkers for prognosis and immunotherapy in gastric cancer patients

Background: Platelets (PLT) have a significant effect in promoting cancer progression and hematogenous metastasis. However, the effect of platelet activation-related lncRNAs (PLT-related lncRNAs) in gastric cancer (GC) is still poorly understood. In this study, we screened and validated PLT-related lncRNAs as potential biomarkers for prognosis and immunotherapy in GC patients.

Methods: We obtained relevant datasets from the Cancer Genome Atlas (TCGA) and Gene Ontology (GO) Resource Database. Pearson correlation analysis was used to identify PLT-related lncRNAs. By using the univariate, least absolute shrinkage and selection operator (LASSO) Cox regression analyses, we constructed the PLT-related lncRNAs model. Kaplan-Meier survival analysis, univariate, multivariate Cox regression analysis, and nomogram were used to verify the model. The Gene Set Enrichment Analysis (GSEA), drug screening, tumor immune microenvironment analysis, epithelial-mesenchymal transition (EMT), and DNA methylation regulators correlation analysis were performed in the high- and low-risk groups. Patients were regrouped based on the risk model, and candidate compounds and immunotherapeutic responses aimed at GC subgroups were also identified. The expression of seven PLT-related lncRNAs was validated in clinical medical samples using quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

Results: In this study, a risk prediction model was established using seven PLT-related lncRNAs -(AL355574.1, LINC01697, AC002401.4, AC129507.1, AL513123.1, LINC01094, and AL356417.2), whose expression were validated in GC patients. Kaplan-Meier survival analysis, the receiver operating characteristic (ROC) curve analysis, univariate, multivariate Cox regression analysis verified the accuracy of the model. We screened multiple targeted drugs for the high-risk patients. Patients in the high-risk group had a poorer prognosis since low infiltration of immune killer cells, activation of immunosuppressive pathways, and poor response to immunotherapy. In addition, we revealed a close relationship between risk scores and EMT and DNA methylation regulators. The nomogram based on risk score suggested a good ability to predict prognosis and high clinical benefits.

Conclusion: Our findings provide new insights into how PLT-related lncRNAs biomarkers affect prognosis and immunotherapy. Also, these lncRNAs may become potential biomarkers and therapeutic targets for GC patients.

LINC01094/SPI1/CCL7 Axis Promotes Macrophage Accumulation in Lung Adenocarcinoma and Tumor Cell Dissemination

Objective

Infiltration of tumor-associated macrophages is closely linked to the malignant development of human cancers. This research studies the function of C-C motif chemokine ligand 7 (CCL7) in the macrophage accumulation in lung adenocarcinoma (LUAD) and the underpinning mechanism.

Methods

The expression profile of CCL7 in LUAD and its correlations with patient's prognosis and macrophage infiltration were predicted via bioinformatics systems. Artificial up- or downregulation of CCL7 was induced in LUAD cells to explore its function in the mobility, EMT of cancer cells, and migration of M2 macrophages. Cancer cells were implanted in NOD/SCID mice to induce xenograft tumors. The CCL7-related transcription factors or factors were predicted by bioinformatic tools, and the molecular interactions were confirmed by immunoprecipitation or luciferase assays.

Results

CCL7 was highly expressed in LUAD and linked to increased TAM infiltration. Knockdown of CCL7 suppressed the chemotaxis and M2 skewing of macrophages, and it blocked the EMT and mobility of LUAD cells. CCL7 downregulation also suppressed macrophage infiltration in xenograft tumors in mice. Spi-1 proto-oncogene (SPI1) was confirmed as an upstream factor activating CCL7 transcription, and LINC01094 was found to bind to SPI1 to promote its nuclear translocation. Upregulation of SPI1 restored the chemotactic migration and M2 polarization of macrophages in LUAD cells.

Conclusion

This paper reveals that LINC01094 binds to SPI1 to promote its nuclear translocation, which further activates CCL7 transcription by binding to its promoter, leading to M2 macrophage accumulation and dissemination of tumor cells.

Identification of cuproptosis-associated IncRNAs signature and establishment of a novel nomogram for prognosis of stomach adenocarcinoma

Purpose: Stomach adenocarcinoma (STAD) is one of the common cancers globally. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in STAD is unknown.

Methods: STAD patient data from TCGA were used to identify prognostic lncRNAs by Cox regression and LASSO. A nomogram was constructed to predict patient survival. The biological profiles were evaluated through GO and KEGG.

Results: We identified 298 cuproptosis-related lncRNAs and 13 survival-related lncRNAs. Patients could be categorized into either high risk group or low risk group with 9-lncRNA risk model with significantly different survival time (p < 0.001). ROC curve and nomogram confirmed the 9-lncRNA risk mode had good prediction capability. Patients in the lower risk score had high gene mutation burden. We also found that patients in the two groups might respond differently to immune checkpoint inhibitors and some anti-tumor compounds.

Conclusion: The nomogram with 9-lncRNA may help guide treatment of STAD. Future clinical studies are necessary to verify the nomogram.

Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer

Hypoxia and angiogenesis are the leading causes of tumor progression, and their strong correlation has been discovered in many cancers. However, their collective function's prognostic and biological roles were not reported in gastric cancer. Hence, we aimed to investigate the effects of hypoxia and angiogenesis on gastric cancer via sequencing data. This study used weighted gene coexpression network analysis and random forest regression to build a hypoxia-angiogenesis-related model (HARM) via the TCGA-STAD lncRNA data. It estimated the HARM's correlation with clinical features and its accuracy for survival prediction. Sequential functional analyses were conducted to investigate its biological role, and we next sought the immune landscape status and immunological function variation by ESTIMATE score calculation and GSVA, respectively. Seven different algorithms were conducted to assess the immunocyte infiltration, and TIDE score and immune checkpoint levels were compared between the high- and low-HARM groups. As a result, we found that HARM predicted patient survival with high accuracy and was correlated with higher stages of gastric cancer. Various cancer-associated pathways and macrophage-related regulations were upregulated in the high-HRAM group. The high-HARM group harbored higher immune levels, and M2 macrophages and cancer-associated fibroblasts were particularly highly unfiltered. Furthermore, globally upregulated immune checkpoints and higher TIDE scores were observed in the high-HARM group. Finally, we filtered eight drugs with lower IC50 in the high-HARM group as potential drugs for the HARM-targeted therapy. We believe this study opens up novel perspectives into the interaction between hypoxia-angiogenesis and immunosuppression and will provide novel insights for gastric cancer immunotherapy.

Long non-coding RNA TRIM52-AS1 sponges microRNA-577 to facilitate diffuse large B cell lymphoma progression via increasing TRIM52 expression

Diffuse large B cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL) globally, featuring heterogeneous clinical phenotypes and altered molecular manifestations. The long non-coding ribose nucleic acids (lncRNAs) play crucial roles in the diagnosis, treatment, and prognosis of DLBCL, requiring the exploration of complex functions and mechanisms. In this study, the expression of lncRNA TRIM52-AS1 in DLBCL tissues from the Cancer Genome Atlas (TCGA) database was initially analyzed and correlated to the data from collected clinical samples. Then, the significance of TRIM52-AS1 on the diagnosis and prognosis of DLBCL patients was predicted with the receiver-operating characteristic (ROC) curve and Kaplan-Meier (KM) analysis. Further, cell counting kit (CCK)-8, EdU staining, and flow cytometry analyses were performed to assess the effect of TRIM52-AS1 on DLBCL cell proliferation, apoptosis, and cell cycle. Then, the mechanism of TRIM52-AS1 sponging miR-577 to increase TRIM52 expression was explored using a starBase prediction approach, dual-luciferase reporter, RNA immunoprecipitation assay (RIPA), quantitative reverse transcription-polymerase chain reaction (RT-qPCR), and Western blot analyses. The experimental results confirmed the overexpression of TRIM52-AS1 in the DLBCL cell lines. Further, the high expression of TRIM52-AS1 predicted the poor Ann Arbor stage and were correlated with the presence of B symptoms, high international prognostic index, and poor disease prognosis. TRIM52-AS1 knockdown inhibited the DLBCL cell proliferation, and induced apoptosis and G0/G1 cycle arrest. Interestingly, the overexpression of TRIM52-AS1 increased the mRNA stability of TRIM52 through binding IGFBP3 protein and upregulated the TRIM52 protein expression by sponging miR-577. Together, the overexpressed TRIM52-AS1 could promote the DLBCL progression through IGFBP3/miR-218-5p/TRIM52 axis, highlighting the clinical significance of TRIM52-AS1 in the DLBCL diagnosis.

Identification of Immune-Related lncRNA Regulatory Network in Pulpitis

Background. Long noncoding RNAs (lncRNAs) are emerging as critical regulators of various biological processes, including immune regulation. Methods. Due to the critical significance of immunological responses in the development and progression of pulpitis, we used an integrated algorithm to identify immune-related lncRNAs and then examined the lncRNA-immunity regulation network in pulpitis. Before identifying immune-related lncRNAs, the data from GEO datasets were precleaned. ConsensusClusterPlus was used to differentiate immune-related pulpitis subgroups. Enrichment analysis using GO and MSigDB databases was employed to determine the differences in molecular function, cellular component, and biological process between the two pulpitis subtypes. Results. An integrated algorithm was designed to filtrate immune-related lncRNAs accurately. 790 immune-related lncRNAs were found in 17 immunological categories, with 38 of them perturbated in pulpitis. The Cytoscape software was used to visualize the relationship between representative immune regulatory pathways and immune-related lncRNAs. Two immune-related pulpitis subtypes were discovered using differentially expressed immune-related lncRNAs. Subtype 2 has a stronger association with immune-related pathways than subtype 1 does. Conclusions. Our study identified many immune-related lncRNAs and investigated potential lncRNA regulation networks; meanwhile, the molecular subtypes of pulpitis were identified, all of which will be relevant for further research into inflammatory and immunological processes in pulpitis.

Construction of a Prognostic Signature of 10 Autophagy-Related lncRNAs in Gastric Cancer

Background

Autophagy plays a double-edged sword role in cancers. LncRNAs could regulate cancer initiation and development at various levels. However, the role of autophagy-related lncRNAs (ARlncs) in gastric cancer (GC) remains indistinct.

Methods

GC gene expression profile and clinical data were acquired from the Cancer Genome Atlas (TCGA). The prognostic signature composed of ARlncs was established via cox regression analysis. Kaplan–Meier (K-M) survival curve was adopted to show overall survival (OS). Independence and reliability of risk signature were visualized by cox regression analysis and ROC curve. A nomogram was constructed and the reliability was analyzed by ROC curve. Immune infiltrating cells and check points were also analyzed.

Results

A prognostic signature was constructed which stratified GC patients into high- and low-risk groups according to risk score calculated via the 10 ARlncs including LINC01094, AC068790.7, AC090772.1, AC005165.1, PVT1, LINC00106, AC026368.1, AC090912.3, AC013652.1, UICLM. Patients in high-risk group showed a poor prognosis (p<0.001). Cox regression analysis showed signature was an independent prognostic factor (p<0.001). Areas under curves (AUC) of ROC for risk signature for predicting OS outweighed age, gender, grade, T, M and N, which suggested the reliability of the signature. A nomogram was constructed with risk signature, T, M, N and age and its AUC of ROC for 1-, 3-, and 5-year was 0.700, 0.730, 0.757 respectively, which showed good reliability. Macrophage M2, T cell CD8+ and T cell CD4+ memory resting had greatest difference between the two risk groups according to CIBERSORE-ABS algorithm (p<0.001). CD274 (PD-L1), PDCD1 (PD-1) and PDCD1LG2 (PD-L2) were expressed higher in the high-risk group (p<0.05), which implied that immunotherapy may be a good choice for these patients.

Conclusion

The risk signature based on 10 ARlncs can serve as an efficacious prognostic predictor and guide the immunotherapies and precise treatment for GC patients.

A Necroptosis-Related lncRNA-Based Signature to Predict Prognosis and Probe Molecular Characteristics of Stomach Adenocarcinoma

Background: As a caspase-independent type of cell death, necroptosis plays a significant role in the initiation, and progression of gastric cancer (GC). Numerous studies have confirmed that long non-coding RNAs (lncRNAs) are closely related to the prognosis of patients with GC. However, the relationship between necroptosis and lncRNAs in GC remains unclear.

Methods: The molecular profiling data (RNA-sequencing and somatic mutation data) and clinical information of patients with stomach adenocarcinoma (STAD) were retrieved from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted to identify the necroptosis-related lncRNAs (NRLs). Subsequently, univariate Cox regression and LASSO-Cox regression were conducted to establish a 12-NRLs signature in the training set and validate it in the testing set. Finally, the prognostic power of the 12-NRLs signature was appraised via survival analysis, nomogram, Cox regression, clinicopathological characteristics correlation analysis, and the receiver operating characteristic (ROC) curve. Furthermore, correlations between the signature risk score (RS) and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anticancer drug sensitivity were analyzed.

Results: In the present study, a 12-NRLs signature comprising REPIN1-AS1, UBL7-AS1, LINC00460, LINC02773, CHROMR, LINC01094, FLNB-AS1, ITFG1-AS1, LASTR, PINK1-AS, LINC01638, and PVT1 was developed to improve the prognosis prediction of STAD patients. Unsupervised methods, including principal component analysis and t-distributed stochastic neighbor embedding, confirmed the capability of the present signature to separate samples with RS. Kaplan-Meier and ROC curves revealed that the signature had an acceptable predictive potency in the TCGA training and testing sets. Cox regression and stratified survival analysis indicated that the 12-NRLs signature were risk factors independent of various clinical parameters. Additionally, immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and half-inhibitory concentration differed significantly among different risk subtypes, which implied that the signature could assess the clinical efficacy of chemotherapy and immunotherapy.

Conclusion: This 12-NRLs risk signature may help assess the prognosis and molecular features of patients with STAD and improve treatment modalities, thus can be further applied clinically.

Upregulated long intergenic non-protein coding RNA 1094 (LINC01094) is linked to poor prognosis and alteration of cell function in colorectal cancer

Colorectal cancer (CRC) showed high cancer-related mortality in recent years partly due to the absence of an effective prognostic predictor. This research intended to evaluate the prognostic value and potential role of long intergenic non-protein coding RNA 1094 (LINC01094) in CRC. In this work, we evaluated the LINC01094 level in 122 CRC patients’ tissues and in human CRC cell lines. We explored the ability of LINC01094 in overall survival and progression-free survival estimate. The effect of LINC01094 dysregulation on the CRC cells was investigated. LINC01094 is highly expressed in CRC tissues and cells than normal ones. This high expression was correlated with absent vascular invasion, positive lymph node metastasis, and advanced TNM stage. With the result of Kaplan-Meier analysis and multivariate Cox’s proportional hazard analysis, LINC01094 was an effective biomarker for CRC overall survival. Downregulation of LINC01094 impeded the malignant biological behavior (proliferation, invasion, and migration) of CRC cells, while overexpression of LINC01094 boosted that maybe by sponging miR-1266-5p. LINC01094 might function as an oncogene in CRC and allowed the discovery of a new biomarker for prognosis and therapy of CRC.

Ferroptosis‑related long non‑coding RNAs and the roles of LASTR in stomach adenocarcinoma

Ferroptosis is a form of programmed cell death that participates in diverse physiological processes. Increasing evidence suggests that long noncoding RNAs (lncRNAs) regulate ferroptosis in tumors, including stomach adenocarcinoma (STAD). In the present study, RNA-sequencing data from The Cancer Genome Atlas database and ferroptosis-related markers from the FerrDb data resource were analyzed to select differentially expressed lncRNAs. Univariate and multivariate Cox regression analyses were performed on these differentially expressed lncRNAs to screen 12 lncRNAs linked with overall survival (OS) and 13 associated with progression-free survival (PFS). Subsequently, two signatures for predicting OS and PFS were established based on these lncRNAs. Kaplan-Meier analyses indicated that the high-risk group of patients with STAD had relatively poor prognosis. The areas under the receiver operating characteristic curves of the two signatures indicated their excellent efficacy in predicting STAD prognosis. In addition, the effect of the lncRNA LASTR on proliferation and migration in gastric cancer was confirmed and the relationship between LASTR and ferroptosis was initially explored through experiments. These results provide potential novel targets for tumor treatment and promote personalized medicine.

Bioinformatics Analysis of the Mechanisms of Diabetic Nephropathy via Novel Biomarkers and Competing Endogenous RNA Network

Diabetic nephropathy (DN) is one of the common chronic complications of diabetes with unclear molecular mechanisms, which is associated with end-stage renal disease (ESRD) and chronic kidney disease (CKD). Our study intended to construct a competing endogenous RNA (ceRNA) network via bioinformatics analysis to determine the potential molecular mechanisms of DN pathogenesis. The microarray datasets (GSE30122 and GSE30529) were downloaded from the Gene Expression Omnibus database to find differentially expressed genes (DEGs). GSE51674 and GSE155188 datasets were used to identified the differentially expressed microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), respectively. The DEGs between normal and DN renal tissues were performed using the Linear Models for Microarray (limma) package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to reveal the mechanisms of DEGs in the progression of DN. The protein-protein interactions (PPI) of DEGs were carried out by STRING database. The lncRNA-miRNA-messenger RNA (mRNA) ceRNA network was constructed and visualized via Cytoscape on the basis of the interaction generated through the miRDB and TargetScan databases. A total of 94 significantly upregulated and 14 downregulated mRNAs, 31 upregulated and 121 downregulated miRNAs, and nine upregulated and 81 downregulated lncRNAs were identified. GO and KEGG pathways enriched in several functions and expression pathways, such as inflammatory response, immune response, identical protein binding, nuclear factor kappa b (NF-κB) signaling pathway, and PI3K-Akt signaling pathway. Based on the analysis of the ceRNA network, five differentially expressed lncRNAs (DElncRNAs) (SNHG6, KCNMB2-AS1, LINC00520, DANCR, and PCAT6), five DEmiRNAs (miR-130b-5p, miR-326, miR-374a-3p, miR-577, and miR-944), and five DEmRNAs (PTPRC, CD53, IRF8, IL10RA, and LAPTM5) were demonstrated to be related to the pathogenesis of DN. The hub genes were validated by using receiver operating characteristic curve (ROC) and real-time PCR (RT-PCR). Our research identified hub genes related to the potential mechanism of DN and provided new lncRNA-miRNA-mRNA ceRNA network that contributed to diagnostic and potential therapeutic targets for DN.

Identification of miR-199-5p and miR-199-3p Target Genes: Paxillin Facilities Cancer Cell Aggressiveness in Head and Neck Squamous Cell Carcinoma

Our previous study revealed that the miR-199 family (miR-199a-5p/-3p and miR-199b-5p/-3p) acts as tumor-suppressive miRNAs in head and neck squamous cell carcinoma (HNSCC). Furthermore, recent studies have indicated that the passenger strands of miRNAs are involved in cancer pathogenesis. The aim of this study was to identify cancer-promoting genes commonly regulated by miR-199-5p and miR-199-3p in HNSCC cells. Our in silico analysis and luciferase reporter assay identified paxillin (PXN) as a direct target of both miR-199-5p and miR-199-3p in HNSCC cells. Analysis of the cancer genome atlas (TCGA) database showed that expression of PXN significantly predicted a worse prognosis (5-year overall survival rate; p = 0.0283). PXN expression was identified as an independent factor predicting patient survival according to multivariate Cox regression analyses (p = 0.0452). Overexpression of PXN was detected in HNSCC clinical specimens by immunostaining. Functional assays in HNSCC cells showed that knockdown of PXN expression attenuated cancer cell migration and invasion, suggesting that aberrant expression of PXN contributed to HNSCC cell aggressiveness. Our miRNA-based approach will provide new insights into the molecular pathogenesis of HNSCC.

Inflammation-Related Long Non-Coding RNA Signature Predicts the Prognosis of Gastric Carcinoma

Background: Gastric carcinoma (GC) is a molecularly and phenotypically highly heterogeneous disease, making the prognostic prediction challenging. On the other hand, Inflammation as part of the active cross-talk between the tumor and the host in the tumor or its microenvironment could affect prognosis.

Method: We established a prognostic multi lncRNAs signature that could better predict the prognosis of GC patients based on inflammation-related differentially expressed lncRNAs in GC.

Results: We identified 10 differently expressed lncRNAs related to inflammation associated with GC prognosis. Kaplan-Meier survival analysis demonstrated that high-risk inflammation-related lncRNAs signature was related to poor prognosis of GC. Moreover, the inflammation-related lncRNAs signature had an AUC of 0.788, proving their utility in predicting GC prognosis. Indeed, our risk signature is more precise in predicting the prognosis of GC patients than traditional clinicopathological manifestations. Immune and tumor-related pathways for individuals in the low and high-risk groups were further revealed by GSEA. Moreover, TCGA based analysis revealed significant differences in HLA, MHC class-I, cytolytic activity, parainflammation, co-stimulation of APC, type II INF response, and type I INF response between the two risk groups. Immune checkpoints revealed CD86, TNFSF18, CD200, and LAIR1 were differently expressed between lowand high-risk groups.

Conclusion: A novel inflammation-related lncRNAs (AC015660.1, LINC01094, AL512506.1, AC124067.2, AC016737.1, AL136115.1, AP000695.1, AC104695.3, LINC00449, AC090772.1) signature may provide insight into the new therapies and prognosis prediction for GC patients.

Identification of an Immune-Related LncRNA Signature in Gastric Cancer to Predict Survival and Response to Immune Checkpoint Inhibitors

Immune microenvironment in gastric cancer is closely associated with patient’s prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of immune responses. In this study, we aimed to construct a prognostic model based on immune-related lncRNAs (IRLs) to predict the overall survival and response to immune checkpoint inhibitors (ICIs) of gastric cancer (GC) patients. The IRL signature was constructed through a bioinformatics method, and its predictive capability was validated. A stratification analysis indicates that the IRL signature can distinguish different risk patients. A nomogram based on the IRL and other clinical variables efficiently predicted the overall survival of GC patients. The landscape of tumor microenvironment and mutation status partially explain this signature’s predictive capability. We found the level of cancer-associated fibroblasts, endothelial cells, M2 macrophages, and stroma cells was high in the high-risk group, while the number of CD8⁺ T cells and T follicular helper cells was high in the low-risk group. Immunophenoscore (IPS) is validated for ICI response, and the IRL signature low-risk group received higher IPS, representing a more immunogenic phenotype that was more inclined to respond to ICIs. In addition, we found RNF144A-AS1 was highly expressed in GC patients and promoted the proliferation, migration, and invasive capacity of GC cells. We concluded that the IRL signature represents a novel useful model for evaluating GC survival outcomes and could be implemented to optimize the selection of patients to receive ICI treatment.

LINC01094 promotes the invasion of ovarian cancer cells and regulates the Wnt/β-catenin signaling pathway by targeting miR-532-3p

Long non-coding RNAs (lncRNAs) participate in the development of ovarian cancer (OC). The present study aimed to explore the roles of long intergenic non-protein coding RNA 1094 (LINC01094) in OC. LINC01094 and microRNA (miR)-532-3p expression in OC tissues and cells were measured using reverse transcription-quantitative PCR. Cell migration and invasion were detected using wound healing assays and Transwell assays, respectively. The binding of LINC01094 or β-catenin to miR-126-5p was detected using a Dual-luciferase reporter assay, and protein expression was confirmed using western blot analysis. The expression level of LINC01094 in patients with OC was higher in OC tissues compared with in adjacent tissues, and LINC01094 was upregulated in OC cell lines. In addition, LINC01094 overexpression promoted the viability, migration, invasion and cell cycle progression of OC cells, and inhibited OC cell apoptosis. Moreover, LINC01094 negatively regulated miR-532-3p in OC cells and tissues. miR-532-3p overexpression decreased the viability, migration, invasion and cell cycle progression of OC cells alongside downregulation of Wnt/β-catenin signaling pathway protein expression, as well as increasing OC cell apoptosis. Inhibition of LINC01094 with small interfering (si)-LINC01094 and overexpression of LINC01094 respectively reversed the effect of miR-532-3p inhibitor and mimics on OC cells. miR-532-3p could directly target β-catenin, and miR-532-3p inhibitor increased β-catenin expression, while si-LINC01094 attenuated this effect. In addition, LINC01094 overexpression promoted tumor growth in vivo by regulating miR-532-3p. Taken together, LINC01094 promoted the growth, migration, invasion and Wnt/β-catenin signaling pathway expression of OC cells by modulating miR-532-3p.

Long intergenic non-protein coding RNA 1094 (LINC01094) promotes the progression of breast cancer (BC) by regulating the microRNA-340-5p (miR-340-5p)/E2F transcription factor 3 (E2F3) axis

The present study was targeted at investigating the effects of long intergenic non-protein coding RNA 1094 on breast cancer (BC) cell proliferation, apoptosis, and cell cycle and its related mechanism. In this study, Western blot and quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the expressions of LINC01094, microRNA (miRNA, miR)-340-5p, and E2F transcription factor 3 (E2F3) in BC tissues and cells. With transfection, LINC01094 and miR-340-5p expressions were selectively up-regulated or down-regulated in BC cell lines, and then cell proliferation, cell cycle, and apoptosis were examined by cell counting kit-8 (CCK-8), 5-bromo-2ʹ-deoxyuridine (BrdU), and flow cytometry assays. Bioinformatics was utilized to predict the targeted relationships between miR-340-5p and LINC01094, as well as miR-340-5p and E2F3 mRNA 3ʹ-untranslated region (3ʹUTR), and RNA immunoprecipitation (RIP) assay and dual-luciferase reporter gene assay were employed to validate them. It was revealed that, LINC01094 expression was enhanced in BC cells and tissues, and LINC01094 overexpression promoted BC cell proliferation, accelerated cell cycle progression, and inhibited apoptosis while knocking down LINC01094 worked oppositely. LINC01094 directly targeted miR-340-5p and negatively regulated its expression in BC cells. Besides, E2F3 was substantiated to be the target gene of miR-340-5p, and E2F3 expression could be indirectly and positively modulated by LINC01094. All in all, LINC01094 promotes BC cell proliferation and cell cycle progression and inhibits apoptosis via modulating miR-340-5p/E2F3 molecular axis.

FBXW7 inhibits invasion, migration and angiogenesis in ovarian cancer cells by suppressing VEGF expression through inactivation of β-catenin signaling

F-box and WD repeat domain containing 7 (FBXW7) is a tumor suppressor gene frequently inactivated in several human malignancies. The present study aimed to investigate the role of FBXW7 in the invasion, migration and angiogenesis of ovarian cancer (OC) cells, and to identify its potential molecular mechanisms. First, the expression levels of FBXW7 and vascular endothelial growth factor (VEGF) were detected in several human OC cell lines using western blotting. Subsequently, FBXW7 was overexpressed to determine VEGF expression in SKOV3 cells. Transwell, wound healing and tube formation assays were performed following transfection with FBXW7 and VEGF overexpression plasmids to assess invasion, migration and angiogenesis in SKOV3 cells, respectively. Western blot analysis was performed to detect the expression levels of epithelial-to-mesenchymal transition and angiogenesis-associated proteins. In addition, the expression levels of β-catenin and c-Myc were assessed, and lithium chloride (LiCl), an agonist of β-catenin signaling, was used to elucidate the molecular mechanisms by which FBXW7 mediates its antitumor activity in OC. The results demonstrated that FBXW7 expression was markedly downregulated, whilst VEGF expression was markedly upregulated in OC cell lines compared with that in normal ovarian cells. Overexpression of FBXW7 significantly decreased VEGF expression in SKOV3 cells. Notably, overexpression of VEGF reversed the inhibitory effects of FBXW7 overexpression on the invasion, migration and angiogenesis of OC cells, accompanied by upregulated expression levels of N-cadherin, slug, CD31, VEGF receptor 1 (VEGFR1) and VEGFR2, and downregulated expression levels of E-cadherin. Furthermore, overexpression of FBXW7 markedly suppressed β-catenin and c-Myc expression, whereas the decreased expression levels of VEGF, VEGFR1 and VEGFR2 following overexpression of FBXW7 were increased after treatment of SKOV3 cells with LiCl. Overall, the results of the present study suggested that FBXW7 inhibited invasion, migration and angiogenesis of OC cells by suppressing VEGF expression through inactivation of β-catenin signaling. Thus, FBXW7 may be used as a novel therapeutic target for the treatment of OC.