Construction of a metastasis-associated ceRNA network reveals a prognostic signature in lung cancer

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

Non-coding RNAs: a promising target for early metastasis intervention

ABSTRACT

Metastases account for the overwhelming majority of cancer-associated deaths. The dissemination of cancer cells from the primary tumor to distant organs involves a complex process known as the invasion-metastasis cascade. The underlying biological mechanisms of metastasis, however, remain largely elusive. Recently, the discovery and characterization of non-coding RNAs (ncRNAs) have revealed the diversity of their regulatory roles, especially as key contributors throughout the metastatic cascade. Here, we review recent progress in how three major types of ncRNAs (microRNAs, long non-coding RNAs, and circular RNAs) are involved in the multistep procedure of metastasis. We further examine interactions among the three ncRNAs as well as current progress in their regulatory mechanisms. We also propose the prevention of metastasis in the early stages of cancer progression and discuss current translational studies using ncRNAs as targets for metastasis diagnosis and treatments. These studies provide insights into developing more effective strategies to target metastatic relapse.

Integrated analysis of competitive endogenous RNA networks in elder patients with non-small cell lung cancer

BACKGROUND

Lung cancer is one of the most prevalent cancers and the leading cause of cancer-related deaths worldwide; non-small cell lung cancer (NSCLC) comprises approximately 80% of all lung cancer cases. This study aimed to construct a competing endogenous RNA (ceRNA) network and identify prognostic signatures in elderly patients with NSCLC.

METHODS

We extracted data from elderly patients with NSCLC from The Cancer Genome Atlas and identified differentially expressed (DE) messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to investigate the functions of DEmRNAs. The interactions between RNAs were predicted using starBase, TargetScan, miRTarBase, and miRanda. Cytoscape version 3.0 was used to construct and visualize the lncRNA-miRNA-mRNA ceRNA network. The association between the expression levels of DERNAs in the constructed ceRNA network and overall survival was determined using the survival package in R software. Furthermore, another Gene Expression Omnibus cohort was studied to externally validate the ceRNA network.

RESULTS

In total, 2865 DEmRNAs, 62 DEmiRNAs, and 131 DElncRNAs were identified. Dysregulated mRNAs are enriched in cancer-related processes and pathways. A ceRNA network was constructed using 38 miRNAs, 61 lncRNAs, and 164 mRNAs. Of these, 3 lncRNAs, 3 miRNAs, and 16 mRNAs were closely related to overall survival. The MIR99AHG-hsa-miR-31-5p-PRKCE axis has been identified as a potential ceRNA network involved in the development of NSCLC in elderly individuals. External validation of the MIR99AHG-hsa-miR-31-5p-PRKCE axis in the GSE19804 cohort showed that PRKCE was downregulated and that MIR99AHG was upregulated in the tumor tissues of elderly patients with NSCLC compared with normal lung tissues.

CONCLUSIONS

This study provides novel insights into the lncRNA-miRNA-mRNA ceRNA network and reveals potential biomarkers for the diagnosis and prognosis of elderly patients with NSCLC.

The interplay of long noncoding RNAs and hepatitis B virus

Hepatitis B Virus (HBV) infections remain a major global health burden with an estimated 296 million people living with a chronic infection and 884,000 HBV-related deaths annually. Notably, patients with a chronic hepatitis B (CHB) infection are at a 30-fold greater risk of developing hepatocellular carcinoma (HCC), the most common type of primary liver cancer, which is the 3rd deadliest cancer worldwide. Several groups have assessed HBV-related aberrant expression of host-cell long noncoding RNAs (lncRNAs) and how altered expression of specific lncRNAs affects HBV replication and progression to associated disease states. Given the challenges in establishing effective HBV models and analyzing transcriptomic data, this review focuses on lncRNA expression data primarily collected from clinical patient samples and primary human hepatocytes, with the subsequent mechanism of action analysis in cell lines or other model systems. Ultimately, understanding HBV-induced lncRNA-expression dysregulation could lead to new treatments and biomarkers for HBV infection and its associated diseases.

A novel risk model construction and immune landscape analysis of gastric cancer based on cuproptosis-related long noncoding RNAs

Recent studies have identified cuproptosis, a new mechanism of regulating cell death. Accumulating evidence suggests that copper homeostasis is associated with tumorigenesis and tumor progression, however, the clinical significance of cuproptosis in gastric cancer (GC) is unclear. In this study, we obtained 26 prognostic cuproptosis-related lncRNAs (CRLs) based on 19 cuproptosis-related genes (CRGs) via Pearson correlation analysis, differential expression analysis, and univariate Cox analysis. A risk model based on 10 CRLs was established with the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazards model to predict the prognosis and immune landscape of GC patients from The Cancer Genome Atlas (TCGA). The risk model has excellent accuracy and efficiency in predicting prognosis of GC patients (Area Under Curve (AUC) = 0.742, 0.803, 0.806 at 1,3,5 years, respectively, P < 0.05). In addition, we found that the risk score was negatively correlated with the infiltration of natural killer (NK) cells and helper T cells, while positively correlated with the infiltration of monocytes, macrophages, mast cells, and neutrophils. Moreover, we evaluated the difference in drug sensitivity of patients with different risk patterns. Furthermore, low-risk patients showed higher tumor mutation burden (TMB) and better immunotherapy response than high-risk patients. In the end, we confirmed the oncogenic role of AL121748.1 which exhibited the highest Hazard Ratio (HR) value among 10 CRLs in GC via cellular functional experiments. In conclusion, our risk model shows a significant role in tumor immunity and could be applied to predict the prognosis of GC patients.

Genome-wide association study of SNP- and gene-based approaches to identify susceptibility candidates for lupus nephritis in the Han Chinese population

Background

Lupus nephritis (LN) is one of the most common and serious complications of systemic lupus erythaematosus (SLE). Genetic factors play important roles in the pathogenesis of LN and could be used to predict who might develop LN. The purpose of this study was to screen for susceptible candidates of LN across the whole genome in the Han Chinese population.

Methods

592 LN patients and 453 SLE patients without renal damage were genotyped at 492,970 single nucleotide polymorphisms (SNPs) in the genome-wide association study (GWAS). Fifty-six SNPs were selected for replication in an independent cohort of 188 LN and 171 SLE without LN patients. Further quantitative real-time (qRT) PCR was carried out in 6 LN patients and 6 healthy controls. Gene-based analysis was conducted using the versatile gene-based test for GWAS. Subsequently, enrichment and pathway analyses were performed in the DAVID database.

Results

The GWAS analysis and the following replication research identified 9 SNPs showing suggestive correlation with LN (P&lt;10-4). The most significant SNP was rs12606116 (18p11.32), at P=8.72×10−6. The qRT-PCR results verified the mRNA levels of LINC00470 and ADCYAP1, the closest genes to rs12606116, were significantly lower in LN patients. From the gene-based analysis, 690 genes had suggestive evidence of association (P&lt;0.05), including LINC00470. The enrichment analysis identified the involvement of transforming growth factor beta (TGF-β) signalings in the development of LN. Lower plasma level of TGF-β1 (P&lt;0.05) in LN patients and lower expression of transforming growth factor beta receptor 2 in lupus mice kidney (P&lt;0.05) futher indicate the involvement of TGF-β in LN.

Conclusions

Our analyses identified several promising susceptibility candidates involved in LN, and further verification of these candidates was necessary.

Integrated analysis of lncRNA-associated ceRNA network in p16-positive and p16-negative head and neck squamous cell carcinoma

Determination of human papillomavirus (HPV) status has become clinically relevant for head and neck squamous cell carcinoma (HNSCC) patients. p16 immunohistochemistry is one of the recommended methods for classifying HPV status. However, long noncoding RNAs (lncRNAs) and related competing endogenous RNA (ceRNA) networks linked to different p16-status HNSCC are still absent. In the present study, The Cancer Genome Atlas database provided RNA profiles as well as clinical information from 26 p16-positive HNSCC samples, 71 p16-negative HNSCC samples, and 44 adjacent normal control samples. Differentially expressed RNAs (DERNAs) between HNSCC samples and normal samples were identified by limma package in R. Functional enrichment analysis of differentially expressed mRNAs was performed using Clusterprofiler package in R. Survival analysis of DERNAs was carried out by survival package in R. The ceRNA network was constructed using GDCRNATools package in R. A total of 102 lncRNAs, 196 microRNAs (miRNAs), and 2282 mRNAs were identified as p16-positive-specific DERNAs. There were 90 lncRNAs, 153 miRNAs, and 2038 mRNAs were identified as p16-negative-specific DERNAs. Functional enrichment analysis revealed that the differentially expressed mRNAs in the p16-positive and the p16-negative group were mainly enriched in the "DNA replication" and "extracellular matrix -receptor interaction" pathway, respectively. Among the top 25 DERNAs, there were 1 key lncRNA, 1 key miRNA, and 1 key messenger RNA in the p16-positive group and 2 key lncRNAs, 1 key miRNA, and 2 key mRNAs in the p16-negative group were significantly related to the overall survival. Then the ceRNA network in the p16-positive and p16-negative group was constructed. There were 5 lncRNAs, 16 miRNAs, and 66 mRNAs included in the p16-positive group ceRNA network and 1 lncRNA, 4 miRNAs, and 28 mRNAs included in the p16-negative group ceRNA network. Among the RNAs in the ceRNA network, 5 mRNAs were significantly related to the overall survival. Taken together, we revealed the differential RNA expression profiling and the differential ceRNA network in the p16-positive and p16-negative group of HNSCC. Our findings provided a novel insight into this HPV-related cancer and potential biomarkers and therapeutic targets for HNSCC based on p16 status.

Systematic Analysis of Long Non-Coding RNA Genes in Nonalcoholic Fatty Liver Disease

The largest solid organ in humans, the liver, performs a variety of functions to sustain life. When damaged, cells in the liver can regenerate themselves to maintain normal liver physiology. However, some damage is beyond repair, which necessitates liver transplantation. Increasing rates of obesity, Western diets (i.e., rich in processed carbohydrates and saturated fats), and cardiometabolic diseases are interlinked to liver diseases, including non-alcoholic fatty liver disease (NAFLD), which is a collective term to describe the excess accumulation of fat in the liver of people who drink little to no alcohol. Alarmingly, the prevalence of NAFLD extends to 25% of the world population, which calls for the urgent need to understand the disease mechanism of NAFLD. Here, we performed secondary analyses of published RNA sequencing (RNA-seq) data of NAFLD patients compared to healthy and obese individuals to identify long non-coding RNAs (lncRNAs) that may underly the disease mechanism of NAFLD. Similar to protein-coding genes, many lncRNAs are dysregulated in NAFLD patients compared to healthy and obese individuals, suggesting that understanding the functions of dysregulated lncRNAs may shed light on the pathology of NAFLD. To demonstrate the functional importance of lncRNAs in the liver, loss-of-function experiments were performed for one NAFLD-related lncRNA, LINC01639, which showed that it is involved in the regulation of genes related to apoptosis, TNF/TGF, cytokine signaling, and growth factors as well as genes upregulated in NAFLD. Since there is no lncRNA database focused on the liver, especially NAFLD, we built a web database, LiverDB, to further facilitate functional and mechanistic studies of hepatic lncRNAs.

A novel prognostic signature of metastasis-associated genes and personalized therapeutic strategy for lung adenocarcinoma patients

Lung adenocarcinoma (LUAD) is a highly invasive and metastatic malignant tumor with high morbidity and mortality. This study aimed to construct a prognostic signature for LUAD patients based on metastasis-associated genes (MAGs). RNA expression profiles were downloaded from the Cancer Genome Atlas (TCGA) database. RRA method was applied to identify differentially expressed MAGs. A total of 192 significantly robust MAGs were determined among seven GEO datasets. MAGs were initially selected through the Lasso Cox regression analysis and 6 MAGs were included to construct a prognostic signature model. Transcriptome profile, patient prognosis, correlation between the risk score and clinicopathological features, immune cell infiltration characteristics, immunotherapy sensitivity and chemotherapy sensitivity differed between low- and high-risk groups after grouping according to median risk score. The reliability and applicability of the signature were further validated in the GSE31210, GSE50081 and GSE68465 cohort. CMap predicted 62 small molecule drugs on the base of the prognostic MAGs. Targeted drug staurosporine had hydrogen bonding with Gln-172 of SLC2A1, which is one of MAGs. Staurosporine could inhibit cell migration in A549 and H1299. We further verified mRNA and protein expression of 6 MAGs in A549 and H1299. The signature can serve as a promising prognostic tool and may provide a novel personalized therapeutic strategy for LUAD patients.

CASC1 Expression in Bladder Cancer Is Regulated by Exosomal miRNA-150: A Comprehensive Pan-Cancer and Bioinformatics Study

This study explored the role of cancer susceptibility 1 (CASC1) in tumorigenesis and development as well as the key pathways affecting bladder cancer progression. CASC1 was examined in various normal tissues in humans using the HPA database to quantify its expression level and subcellular localization. CASC1 is abundantly expressed in tumor tissues, primarily in cytoplasmic vesicles and stroma. TIMER2 was used to analyze the correlation between CASC1 expression levels and the types of infiltrates associated with immune cells and immunosuppressive cells. MDSC, Treg, M2, and CAF were significantly correlated with CASC1 expression in various tumors. Comparing patients with and without CASC1 mutation, those with CASC1 mutation had worse overall survival, progression-free survival, and disease-free survival. The correlation between has-miR-150 and CASC1 (for the case of bladder cancer) was then analyzed, and the related ceRNA network was mapped. A negative relationship between CASC1 expression and has-miR-150 expression was found in cases of bladder cancer. And the presence of miR-150-targeted CASC1 may be associated with bladder cancer progression. CASC1 is expressed at elevated levels in various tumor tissues, and it is associated with tumorigenesis and development. Exosomes containing miR-150-targeted CASC1 may affect the progression of bladder cancer.

Pan-Cancer Methylated Dysregulation of Long Non-coding RNAs Reveals Epigenetic Biomarkers

Different cancer types not only have common characteristics but also have their own characteristics respectively. The mechanism of these specific and common characteristics is still unclear. Pan-cancer analysis can help understand the similarities and differences among cancer types by systematically describing different patterns in cancers and identifying cancer-specific and cancer-common molecular biomarkers. While long non-coding RNAs (lncRNAs) are key cancer modulators, there is still a lack of pan-cancer analysis for lncRNA methylation dysregulation. In this study, we integrated lncRNA methylation, lncRNA expression and mRNA expression data to illuminate specific and common lncRNA methylation patterns in 23 cancer types. Then, we screened aberrantly methylated lncRNAs that negatively regulated lncRNA expression and mapped them to the ceRNA relationship for further validation. 29 lncRNAs were identified as diagnostic biomarkers for their corresponding cancer types, with lncRNA AC027601 was identified as a new KIRC-associated biomarker, and lncRNA ACTA2-AS1 was regarded as a carcinogenic factor of KIRP. Two lncRNAs HOXA-AS2 and AC007228 were identified as pan-cancer biomarkers. In general, the cancer-specific and cancer-common lncRNA biomarkers identified in this study may aid in cancer diagnosis and treatment.

miR-17-5p/HOXA7 Is a Potential Driver for Brain Metastasis of Lung Adenocarcinoma Related to Ferroptosis Revealed by Bioinformatic Analysis

Objectives

Present study aims to identify the essential mRNAs responsible for the development of brain neurovascular-related metastases (BNM) among lung adenocarcinoma (LUAD) patients. Further, we attempted to predict brain metastases more accurately and prevent their development in LUAD patients.

Methods

Transcriptome data analysis was used to identify differentially expressed mRNAs (DEMs) associated with brain metastasis, and thereby the ferroptosis index (FPI) is calculated using a computational model. Meanwhile, the DEmRNAs linked with FPI, and brain metastasis were derived by the intersection of these two groups of DEMs. We also constructed a ceRNA network containing these DEmRNAs, identifying the HCP5 /hsa-miR-17-5p/HOXA7 axis for analysis. Further, a clinical cohort was employed to validate the regulatory roles of molecules involved in the ceRNA regulatory axis.

Results

Here we report the development of a ceRNA network based on BNM-associated DEMs and FPI-associated DEmRNAs which includes three core miRNAs (hsa-miR-338-3p, hsa-miR-429, and hsa-miR-17-5p), three mRNAs (HOXA7, TBX5, and TCF21), and five lncRNAs (HCP5, LINC00460, TP53TG1). Using gene set enrichment analysis (GSEA) and survival analysis, the potential axis of HCP5 /hsa-miR-17-5p/HOXA7 was further investigated. It is found that HOXA7 and ferroptosis index are positively correlated while inhibiting tumor brain metastasis. It may be that HCP5 binds competitively with miR-17-5p and upregulates HOXA7 to increase iron death limiting brain cancer metastases.

Conclusions

The expression of both HOXA7 and HCP5 is positively correlated with FPI, indicating a possible link between ferroptosis and BNM. According to the results of our study, the ferroptosis-related ceRNA HCP5 /hsa-miR-17-5p/HOXA7 axis may contribute to the development of BNM in LUAD patients.

SNAP25 is a potential prognostic biomarker for prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most lethal cancers in male individuals. The synaptosome associated protein 25 (SNAP25) gene is a key mediator of multiple biological functions in tumors. However, its significant impact on the prognosis in PCa remains to be elucidated.

METHODS

We performed a comprehensive analysis of the Cancer Genome Atlas dataset (TCGA) to identify the differentially expressed genes between PCa and normal prostate tissue. We subjected the differentially expressed genes to gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes functional analysis, and constructed a protein-protein interaction network. We then screened for pivotal genes to identify the hub genes of prognostic significance by performing Cox regression analysis. We identified SNAP25 as one such gene and analyzed the relationship between its expression in PCa to poor prognosis using GEPIA interactive web server.

RESULTS

TCGA database demonstrated that SNAP25 was significantly downregulated in PCa. The progressive decrease in SNAP25 expression with the increase in the clinical staging and grading of PCa demonstrates that reduced SNAP25 expression considerably exacerbates the clinical presentation. Our findings confirm that SNAP25 expression strongly correlates with overall survival, which was determined using the Gleason score. We also validated the role of SNAP25 expression in the prognosis of patients with PCa. We used Gene Set Enrichment and Gene Ontology analyses to evaluate the function of SNAP25 and further explored the association between SNAP25 expression and tumor-infiltrating immune cells using the Tumor Immune Assessment Resource database. We found for the first time that SNAP25 is involved in the activation, differentiation, and migration of immune cells in PCa. Its expression was positively correlated with immune cell infiltration, including B cells, CD8⁺ T cells, CD4⁺ T cells, neutrophils, dendritic cells, macrophages, and natural killer cells. SNAP25 expression also positively correlated with chemokines/chemokine receptors, suggesting that SNAP25 may regulate the migration of immune cells. In addition, our experimental results verified the low expression of SNAP25 in PCa cells.

CONCLUSION

Our findings indicate a relationship between SNAP25 expression and PCa, demonstrating that SNAP25 is a potential prognostic biomarker due to its vital role in immune infiltration.

Comprehensive analysis of PTEN-related ceRNA network revealing the key pathways WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 as potential biomarker in tumorigenesis and prognosis of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most common malignancies, and there is still a lack of effective biomarkers for early detection and prognostic prediction. In here, we compared the characteristics of RNA sequencing data sets of KIRC samples based on the tumor suppressor gene phosphatase and tensin homolog (PTEN). The 1016 long noncoding RNAs, 48 microRNAs (miRNAs), and 2104 messenger RNAs associated with PTEN were identified and these genes were differentially expressed between tumor and paracancerous tissues. The most relevant pathway was found to be WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 according to the rules of competing endogenous RNA (ceRNA) regulation. WDFY3-AS2 and TIMP3 expression were positively correlated and reduced in KIRC samples, while miR-21-5p, miR-221-3p, and miR-222-3p were relatively highly expressed. The relatively low expression of WDFY3-AS2 and TIMP3 in KIRC were associated with poor prognosis in KIRC patients, while higher expression of miR-21-5p, miR-221-3p, and miR-222-3p predicted reduced survival (p < 0.05). Univariate and multivariate Cox regression analysis showed that lower expression of WDFY3-AS2 and TIMP3 was significantly related to tumor grade, tumor size, lymph node metastasis, distant metastasis, and TNM stage. The expression of TIMP3 in KIRC tissues was also verified by immunohistochemistry, and the results were consistent with our analytical data. In summary, this study constructed a new model with clinical predictive value and identified the WDFY3-AS2/TIMP3 pathway that was closely associated with the prognosis of KIRC, which could serve as a promising biomarker for the diagnosis and treatment of KIRC.

A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC

LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer.

HBV HBx-Downregulated lncRNA LINC01010 Attenuates Cell Proliferation by Interacting with Vimentin

Hepatitis B virus (HBV) infection is closely related to hepatocellular carcinoma (HCC) development. To investigate the mechanism of HBV causing HCC, we previously analyzed the transcription of the HBV-transgenic cell line HepG2-4D14 and parental HepG2 cells and identified a subset of long noncoding RNAs (lncRNAs) differentially expressed between them. In this study, we focus on lncRNA LINC01010, as it is significantly downregulated in HepG2-4D14 cells and in liver tissues of HCC patients, and positively correlated with survival. We found that HBV-encoded HBx can reduce the transcription of LINC01010. Functional analysis showed that the overexpression of LINC01010 inhibits proliferation, migration and invasion of HepG2 cells while the knockdown of LINC01010 promotes these processes. By taking the approach of RNA immunoprecipitation (RIP) and mass spectrometry, we identified that LINC01010 can interact with vimentin. Further studies demonstrated that LINC01010 negatively affects the vimentin network extension and causes more rapid subunit exchange and lower stability of vimentin filaments. In addition, LINC01010 can reduce the amount of insoluble vimentin within cells, which suggests that LINC01010 interfers with vimentin polymerization. These data indicate that LINC01010 can inhibit the assembly of vimentin filament. Thus, we revealed that HBV HBx-downregulated LINC01010, which suppresses cell proliferation and migration by negatively regulating the formation of vimentin filament. Taken together, LINC01010 is a potential tumor suppressor that may restrain HBV-related HCC development.

The COX10-AS1/miR-641/E2F6 Feedback Loop Is Involved in the Progression of Glioma

Glioma is the most common primary tumour of the central nervous system and is considered one of the greatest challenges for neurosurgery. Mounting evidence has shown that lncRNAs participate in various biological processes of tumours, including glioma. This study aimed to reveal the role and relevant mechanism of COX10-AS1 in glioma. The expression of COX10-AS1, miR-641 and E2F6 was measured by qRT-PCR and/or western blot. Clone formation assays, EdU assays, Transwell assays and tumour xenograft experiments were performed to evaluate the effects of COX10-AS1, miR-641 and E2F6 on glioma proliferation, migration and invasion. Luciferase reporter assays, RNA pull-down assays and ChIP assays were conducted to analyse the relationship among COX10-AS1, miR-641 and E2F6. We demonstrated that COX10-AS1 was upregulated in glioma tissues and cell lines, which was related to the grade of glioma and patient survival. Next, through functional assays, we found that COX10-AS1 influenced the proliferation, migration and invasion of glioma cell lines. Then, with the help of bioinformatics analysis, we confirmed that COX10-AS1 regulated glioma progress by acting as a sponge of miR-641 to regulate E2F6. Moreover, further study indicated that E2F6 could promote COX10-AS1 expression by binding to its promoter region. Taken together, the data indicated that COX10-AS1 acts as an oncogene in combination with COX10-AS1/miR-641/E2F6 in glioma, which may be beneficial to the diagnosis and treatment of glioma.

Hypoxia-related lncRNAs to build prognostic classifier and reveal the immune characteristics of EGFR wild type and low expression of PD-L1 squamous and adenocarcinoma NSCLC

Background

Recently, the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have achieved remarkable survival benefits in non‐small cell lung cancer (NSCLC) treatment. However, epidermal growth factor receptor (EGFR) wild type and low expression of programmed death‐ligand 1 (PD‐L1) NSCLC remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a hypoxia‐related lncRNAs (hypolncRNAs) classifier that could successfully identify the high‐risk patients and reveal its underlying molecular immunology characteristics.

Methods

By identifying the bottom 25% PD‐L1 expression level as low expression of PD‐L1 and removing EGFR mutant samples, a total of 222 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) samples and 93 adjacent non‐tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). A 0 or 1 matrix was constructed by cyclically pairing hypoxia‐related long non‐coding RNAs (hypolncRNAs) and divided into the train set and test set. The univariate Cox regression analysis determined the prognostic hypolncRNAs pairs. Then, the prognostic classifier contained nine hypolncRNAs pairs which were generated by Lasso regression and multivariate Cox analysis. It successfully stratified EGFR wild type and low expression of PD‐L1 squamous and adenocarcinoma NSCLC (double‐negative LUAD and LUSC) patients into the high‐ and low‐risk groups, whose accuracy was proved by the time‐dependent receiver operating characteristic (ROC) curve. Furthermore, diverse acknowledged immunology methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT‐ABS, CIBERSORT, and the single‐sample gene set enrichment analysis (ssGSEA) revealed its underlying antitumor immunosuppressive status in the high‐risk patients.

Conclusions

It is noteworthy that hypolncRNAs are associated with the survival of double‐negative LUAD and LUSC patients, for which the possible mechanism is inhibiting the antitumor immune process.

LINC01287 facilitates proliferation, migration, invasion and EMT of colon cancer cells via miR-4500/MAP3K13 pathway

Background

Accumulated studies indicate that aberrant expression of long noncoding RNAs (lncRNAs) is associated with tumorigenesis and progression of colon cancer. In the present study, long intergenic non-protein coding RNA 1287 (LINC01287) was identified to up-regulate in colon cancer by transcriptome RNA-sequencing, but the exact function remained unclear.

Methods

Transcriptome RNA-sequencing was conducted to identify dysregulated lncRNAs. Expression of LINC01287 was evaluated by real-time quantitative PCR. The downstream targets of LINC01287 and miR-4500 were verified by luciferase reporter assay, pull down assay and western blot. The potential functions of LINC01287 were evaluated by cell viability assay, colony formation assay, soft agar assay, flow cytometry, transwell migration and invasion assay, and tumor xenograft growth in colon cancer cells.

Results

Our results indicated that LINC01287 was up-regulated in colon cancer patients. High LINC01287 expression was associated with advanced TNM stage, lymph node metastasis, distant metastasis and shorter overall survival. Knockdown of LINC01287 inhibited cell growth, colony formation in plates and soft agar, transwell cell migration and invasion, and epithelial-mesenchymal transition (EMT) of colon cancer cells, while LINC01287 overexpression had contrary effects. In addition, LINC01287 mediated MAP3K13 expression by sponging miR-4500, thus promoted NF-κB p65 phosphorylation. Restored MAP3K13 expression or miR-4500 knockdown partially abrogated the effects of silencing LINC01287 in colon cancer cells.

Conclusion

Our findings demonstrated that the LINC01287/miR-4500/MAP3K13 axis promoted progression of colon cancer. Therefore, LINC01287 might be a potential therapeutic target and prognostic marker for colon cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08528-7.

Comprehensive analysis of lncRNA biomarkers in kidney renal clear cell carcinoma by lncRNA-mediated ceRNA network

Introduction

Kidney renal clear cell carcinoma (KIRC) has a high incidence globally, and its pathogenesis remains unclear. Long non-coding RNA (lncRNA), as a molecular sponge, participates in the regulation of competitive endogenous RNA (ceRNA). We aimed to construct a ceRNA network and screened out possible lncRNAs to predict KIRC prognosis.

Material and methods

All KIRC data were downloaded from the TCGA database and screened to find the possible target lncRNA; a ceRNA network was designed. Next, GO functional enrichment and KEGG pathway of differentially expressed mRNA related to lncRNA were performed. We used Kaplan-Meier curve analysis to predict the survival of these RNAs. We used Cox regression analysis to construct a model to predict KIRC prognosis.

Results

In the KIRC datasets, 1457 lncRNA, 54 miRNA and 2307 mRNA were screened out. The constructed ceRNA network contained 81 lncRNAs, nine miRNAs, and 17 mRNAs differentially expressed in KIRC. Survival analysis of all differentially expressed RNAs showed that 21 lncRNAs, four miRNAs, and two mRNAs were related to the overall survival rate. Cox regression analysis was performed again, and we found that eight lncRNAs were related to prognosis and used to construct predictive models. Three lnRNAs from independent samples were meaningful.

Conclusion

The construction of ceRNA network was involved in the process and transfer of KIRC, and three lncRNAs may be potential targets for predicting KIRC prognosis.

Two predicted models based on ceRNAs and immune cells in lung adenocarcinoma

Background

It is well accepted that both competitive endogenous RNAs (ceRNAs) and immune microenvironment exert crucial roles in the tumor prognosis. The present study aimed to find prognostic ceRNAs and immune cells in lung adenocarcinoma (LUAD).

Materials and Methods

More specifically, we explored the associations of crucial ceRNAs with the immune microenvironment. The Cancer Genome Atlas (TCGA) database was employed to obtain expression profiles of ceRNAs and clinical data. CIBERSORT was utilized to quantify the proportion of 22 immune cells in LUAD.

Results

We constructed two cox regression models based on crucial ceRNAs and immune cells to predict prognosis in LUAD. Subsequently, seven ceRNAs and seven immune cells were involved in prognostic models. We validated both predicted models via an independent cohort GSE72094. Interestingly, both predicted models proved that the longer patients were smoking, the higher risk scores would be obtained. We further investigated the relationships between seven genes and immune/stromal scores via the ESTIMATE algorithm. The results indicated that CDC14A and H1F0 expression were significantly related to stromal scores/immune scores in LUAD. Moreover, based on the result of the ceRNA model, single-sample gene set enrichment analysis (ssGSEA) suggested that differences in immune status were evident between high- and low-risk groups.

Identification of Five Immune-Related lncRNAs Predicting Survival and Tumor Microenvironment Characteristics in Breast Cancer

A common cancer in females, breast cancer (BRCA) mortality has been recently reduced; however, the prognosis of BRCA patients remains poor. This study attempted to develop prognostic immune-related long noncoding RNAs (lncRNAs) for BRCA and identify the effects of these lncRNAs on the tumor microenvironment (TME). Gene expression data from The Cancer Genome Atlas (TCGA) database were collected in order to select differentially expressed lncRNAs. Immune-related lncRNAs were downloaded from the ImmLnc database, where 316 immune-related lncRNAs were identified, 12 of which were found to be significantly related to the prognosis of BRCA patients. Multivariate cox regression analysis was then applied to construct prognostic immune-related lncRNAs as the risk model, including C6orf99, LINC00987, SIAH2-AS1, LINC01010, and ELOVL2-AS1. High-risk and low-risk groups were distinguished according to the median of immune-related risk scores. Accordingly, the overall survival (OS) in the high-risk group was observed to be shorter than that in the low-risk group. qRT-PCR analysis demonstrated that lncRNA expression levels in BRCA cell lines were in basic agreement with predictions except for LINC00987. By validating numerous clinical samples, lncRNA C6orf99 was shown to be highly expressed in the advanced stage, while LINC01010 and SIAH2-AS1 decreased in the advanced T-stage and M-stage. Moreover, the expression of LINC0098 was found to be significantly decreased among the groups (>50 years old). Gene set enrichment analysis (GSEA) was applied to analyze the cancer hallmarks and immunological characteristics of the high-risk and low-risk groups. Importantly, the TIMER database demonstrated that this immune-related lncRNA risk model for breast cancer is related to the infiltration of immune cells. In conclusion, the results indicated that five immune-related lncRNAs could be used as a prognostic model and may even accelerate immunotherapy for BRCA patients.