Identification of cancer risk lncRNAs and cancer risk pathways regulated by cancer risk lncRNAs based on genome sequencing data in human cancers

Cuproptosis-related lncRNAs predict the prognosis and immune response in hepatocellular carcinoma

Cuproptosis has been recently used to indicate unique biological processes triggered by Cu action as a new term. This study aimed to explore the relationship between cuproptosis-related lncRNA and hepatocellular carcinoma (HCC) with regard to immunity and prognosis. RNA sequencing and the clinical data were downloaded from the TCGA database. The cuproptosis-related genes were sorted out through literature study. The cuproptosis-related IncRNA signature was identified by Cox regression analysis and the least absolute shrinkage and selection operator analysis. The K-M survival analysis, receiver operating characteristic analysis, and C-index analysis were adopted to evaluate the prognostic prediction performance of the signature. The functional enrichment, immune infiltration and tumor mutation analysis were further analyzed. Subsequently, we predicted the differences in chemosensitivity from tumor gene expression levels for some chemotherapy drugs. The prognostic signature consisting of 5 overall survival-related CUPlncRNAs. It showed an extraordinary ability to predict the prognoses of patients with HCC. The signature can predict the abundance of immune cell infiltration, immune functions, expression of immune checkpoint inhibitors, m6A genes, which was supported by the GO biological process and KEGG analysis. And it may also have a guiding effect in the sensitivity of different chemotherapeutic drugs and tumor mutation burden. We constructed a new cuproptosis-related lncRNA signature for HCC patients. The model can be used for prognostic prediction and immune evaluation, providing a reference for immunotherapies and targeted therapies.

Computational prediction of disease related lncRNAs using machine learning

Long non-coding RNAs (lncRNAs), which were once considered as transcriptional noise, are now in the limelight of current research. LncRNAs play a major role in regulating various biological processes such as imprinting, cell differentiation, and splicing. The mutations of lncRNAs are involved in various complex diseases. Identifying lncRNA-disease associations has gained a lot of attention as predicting it efficiently will lead towards better disease treatment. In this study, we have developed a machine learning model that predicts disease-related lncRNAs by combining sequence and structure-based features. The features were trained on SVM and Random Forest classifiers. We have compared our method with the state-of-the-art and obtained the highest F1 score of 76% on SVM classifier. Moreover, this study has overcome two serious limitations of the reported method which are lack of redundancy checking and implementation of oversampling for balancing the positive and negative class. Our method has achieved improved performance among machine learning models reported for lncRNA-disease associations. Combining multiple features together specifically lncRNAs sequence mutation has a significant contribution to the disease related lncRNA prediction.

Methylome Profiling of PD-L1-Expressing Glioblastomas Shows Enrichment of Post-Transcriptional and RNA-Associated Gene Regulation

Glioblastomas are the most frequent primary brain tumors in adults. They show highly malignant behavior and devastating outcomes. Since there are still no targeted therapies available, median survival remains in the range of 12 to 15 months for glioblastoma patients. Programmed Cell Death Ligand 1 (PD-L1) is a promising novel candidate in precision medicine. Here, we performed integrated epigenome-wide methylation profiling of 866,895 methylation-specific sites in 20 glioblastoma samples comparing PD-L1 high- (i.e., TPS (tumor proportion score) > 30%) and PD-L1 low-expressing glioblastomas (i.e., TPS < 10%). We found 12,597 significantly differentially methylated CpGs (DMCG) (Δβ ≥ 0.1 and p-value < 0.05) in PD-L1 high- compared with PD-L1 low-expressing glioblastomas. These DMCGs were annotated to 2546 tiling regions, 139 promoters, 107 genes, and 107 CpG islands. PD-L1 high-expressing glioblastomas showed hypomethylation in 68% of all DMCGs. Interestingly, the list of the top 100 significantly differentially methylated genes showed the enrichment of regulatory RNAs with 19 DMCGs in miRNA, snoRNAs, lincRNAs, and asRNAs. Gene Ontology analysis showed the enrichment of post-transcriptional and RNA-associated pathways in the hypermethylated gene regions. In summary, dissecting the methylomes depending on PD-L1 status revealed significant alterations in RNA regulation and novel molecular targets in glioblastomas.

Identification and Validation of Three Autophagy-Related Long Noncoding RNAs as Prognostic Signature in Cholangiocarcinoma

Cholangiocarcinoma (CCA) is featured by common occurrence and poor prognosis. Autophagy is a biological process that has been extensively involved in the progression of tumors. Long noncoding RNAs (lncRNAs) have been discovered to be critical in diagnosing and predicting various tumors. It may be valuable to elaborate autophagy-related lncRNAs (ARlncRNAs) in CCA, and indeed, there are still few studies concerning the role of ARlncRNAs in CCA. Here, a prognostic ARlncRNA signature was constructed to predict the survival outcome of CCA patients. Through identification, three differentially expressed ARlncRNAs (DEARlncRNAs), including CHRM3.AS2, MIR205HG, and LINC00661, were screened and were considered predictive signatures. Furthermore, the overall survival (OS) of patients with high-risk scores was significantly lower than that of patients with low scores. Interestingly, the risk score was an independent factor for the OS of patients with CCA. Moreover, receiver operating characteristic (ROC) curve analysis showed that the screened and constructed prognosis signature for 1 year (AUC = 0.884), 3 years (AUC =0.759), and 5 years (AUC = 0.788) presented a high score of accuracy in predicting OS of CCA patients. Gene set enrichment analysis (GSEA) revealed that the three DEARlncRNAs were significantly enriched in CCA-related signaling pathways, including “pathways of basal cell carcinoma”, “glycerolipid metabolism”, etc. Quantitative real-time PCR (qRT-PCR) showed that expressions of CHRM3.AS2, MIR205HG, and LINC00661 were higher in CCA tissues than those in normal tissues, similar to the trends detected in the CCA dataset. Furthermore, Pearson’s analysis reported an intimate correlation of the risk score with immune cell infiltration, indicating a predictive value of the signature for the efficacy of immunotherapy. In addition, the screened lncRNAs were found to have the ability to modulate the expression of mRNAs by interacting with miRNAs based on the established lncRNA-miRNA-mRNA network. In conclusion, our study develops a novel nomogram with good reliability and accuracy to predict the OS of CCA patients, providing a significant guiding value for developing tailored therapy for CCA patients.

Long non-coding RNAs regulate the hallmarks of cancer in HPV-induced malignancies

High-risk human papillomavirus (HPV) is the most frequent sexually transmitted agent worldwide and is responsible for approximately 5% of human cancers. Identifying novel biomarkers and therapeutic targets for these malignancies requires a deeper understanding of the mechanisms involved in the progression of HPV-induced cancers. Long non-coding RNAs (lncRNAs) are crucial in the regulation of biological processes. Importantly, these molecules are key players in the progression of multiple malignancies and are able to regulate the development of the different hallmarks of cancer. This review highlights the action of lncRNAs in the regulation of cellular processes leading to the typical hallmarks of cancer. The regulation of lncRNAs by HPV oncogenes, their targets and also their mechanisms of action are also discussed, in the context of HPV-induced malignancies. Overall, accumulating data indicates that lncRNAs may have a significant potential to become useful tools for clinical practice as disease biomarkers or therapy targets.

LncRNA LINC00668 promotes cell proliferation, migration, invasion ability and EMT process in hepatocellular carcinoma by targeting miR-532-5p/YY1 axis

Liver cancer is now one of the most lethal and commonest cancers in the world, among which over 90% is hepatocellular carcinoma (HCC). Recent studies have confirmed long non-coding RNAs (lncRNAs) are implicated in carcinogenesis. It has been reported lncRNA LINC00668 serves as an oncogene in several cancers. However, the mechanism where LINC00668 regulates HCC is still unclear. qRT-PCR analysis was adopted to detect the expression of relative RNAs. Cytoplasmic and nuclear RNA fraction analysis was conducted to verify the underlying molecular mechanism. Cell colony formation was carried out to test cell colony formation ability and transwell assays were performed to testify cell migratory and invaded abilities. Relevant protein expression level was measured by Western blot assay. LINC00668 was significantly up-regulated in HCC tissues and cell lines. LINC00668 knockdown inhibited cell proliferative, migratory and invasion abilities and slowed down the epithelial–mesenchymal transition (EMT) process. Mechanistically, LINC00668 positively modulates the expression of YY1 by competitively binding to miR-532-5p. It was revealed that LINC00668 up-regulation accelerated cell proliferation and motility in HCC and suggested LINC00668 could be a potential therapeutic target for HCC.

A Novel Autophagy-Related IncRNAs Signature for Prognostic Prediction and Clinical Value in Patients With Pancreatic Cancer

Autophagy is an important bioprocess throughout the occurrence and development of cancer. However, the role of autophagy-related lncRNAs in pancreatic cancer (PC) remains obscure. In the study, we identified the autophagy-related lncRNAs (ARlncRNAs) and divided the PC patients from The Cancer Genome Atlas into training and validation set. Firstly, we constructed a signature in the training set by the least absolute shrinkage and selection operator penalized cox regression analysis and the multivariate cox regression analysis. Then, we validated the independent prognostic role of the risk signature in both training and validation set with survival analysis, receiver operating characteristic analysis, and Cox regression. The nomogram was established to demonstrate the predictive power of the signature. Moreover, high risk scores were significantly correlated to worse outcomes and severe clinical characteristics. The Pearson’s analysis between risk scores with immune cells infiltration, tumor mutation burden, and the expression level of chemotherapy target molecules indicated that the signature could predict efficacy of immunotherapy and targeted therapy. Next, we constructed an lncRNA–miRNA–mRNA regulatory network and identified several potential small molecule drugs in the Connectivity Map (CMap). What’s more, quantitative real-time PCR (qRT-PCR) analysis showed that serum LINC01559 could serve as a diagnostic biomarker. In vitro analysis showed inhibition of LINC01559 suppressed PC cell proliferation, migration, and invasion. Additionally, silencing LINC01559 suppressed gemcitabine-induced autophagy and promoted the sensitivity of PC cells to gemcitabine. In conclusion, we identified a novel ARlncRNAs signature with valuable clinical utility for reliable prognostic prediction and personalized treatment of PC patients. And inhibition of LINC01559 might be a novel strategy to overcome chemoresistance.

Crosstalk Between MYC and lncRNAs in Hematological Malignancies

The human genome project revealed the existence of many thousands of long non-coding RNAs (lncRNAs). These transcripts that are over 200 nucleotides long were soon recognized for their importance in regulating gene expression. However, their poor conservation among species and their still controversial annotation has limited their study to some extent. Moreover, a generally lower expression of lncRNAs as compared to protein coding genes and their enigmatic biochemical mechanisms have impeded progress in the understanding of their biological roles. It is, however, known that lncRNAs engage in various kinds of interactions and can form complexes with other RNAs, with genomic DNA or proteins rendering their functional regulatory network quite complex. It has emerged from recent studies that lncRNAs exert important roles in gene expression that affect many cellular processes underlying development, cellular differentiation, but also the pathogenesis of blood cancers like leukemia and lymphoma. A number of lncRNAs have been found to be regulated by several well-known transcription factors including Myelocytomatosis viral oncogene homolog (MYC). The c-MYC gene is known to be one of the most frequently deregulated oncogenes and a driver for many human cancers. The c-MYC gene is very frequently activated by chromosomal translocations in hematopoietic cancers most prominently in B- or T-cell lymphoma or leukemia and much is already known about its role as a DNA binding transcriptional regulator. Although the understanding of MYC's regulatory role controlling lncRNA expression and how MYC itself is controlled by lncRNA in blood cancers is still at the beginning, an intriguing picture emerges indicating that c-MYC may execute part of its oncogenic function through lncRNAs. Several studies have identified lncRNAs regulating c-MYC expression and c-MYC regulated lncRNAs in different blood cancers and have unveiled new mechanisms how these RNA molecules act. In this review, we give an overview of lncRNAs that have been recognized as critical in the context of activated c-MYC in leukemia and lymphoma, describe their mechanism of action and their effect on transcriptional reprogramming in cancer cells. Finally, we discuss possible ways how an interference with their molecular function could be exploited for new cancer therapies.

Role of long non-coding RNA NEAT1 in the prognosis of prostate cancer patients

Prostate cancer is the second leading cause of cancer-related deaths among male population worldwide, its incidence and lethality steadily increase. Nuclear enriched abundant transcript 1 (NEAT1) is a long non-coding RNA (ncRNA), located on chromatin 11. It has been found to function as an oncogene in different kinds of cancer. However, until now, the clinical significance of NEAT1 has not been investigated in prostate cancer.Paired tissue specimens of prostate cancer and matched normal prostate tissues were obtained from 130 patients with prostate cancer between 2014 and 2019 at The Fourth Affiliated Hospital Zhejiang University, School of Medicine. Group means were compared using the Student t test. Chi-Squared test was used for analyzing the correlation of the expression of NEAT1 with clinicopathologic features of prostate cancer patients. Survival data was analyzed using the Kaplan-Meier estimate and log-rank P was calculated. Cox regression model was used for univariate and multivariate analysis for factors related to overall survival.The expression of NEAT1 was increased significantly in prostate cancer tissues, compared with adjacent normal prostate tissues (P < .001). NEAT1 expression was significantly associated with TNM stage (P = .005), lymph nodes metastasis (P = .005), distant metastasis(P = .003), and Gleason score (P = .001). Overall survival rate was significantly lower for prostate cancer patients with a high expression level of NEAT1 than those with a low NEAT1a expression level (P = .048). In multivariate analysis, the results showed that the expression of NEAT1 was an independent prognostic factor for overall patient survival (HR: 2.111, CI: 1.735-10.295, P = .039).In the present study, NEAT1 is identified as an important lncRNA that may predict the prognosis of patients with prostate cancer.

M2-like tumor-associated macrophages-secreted EGF promotes epithelial ovarian cancer metastasis via activating EGFR-ERK signaling and suppressing lncRNA LIMT expression

Background: Ovarian cancer (OC) is the gynecologic malignant tumor with high mortality. Accumulating evidence indicates that M2-like tumor-associated macrophages (TAMs) can secret EGF to participate in ovarian cancer growth, migration, and metastasis. An EGF-downregulated lncRNA, LIMT (lncRNA inhibiting metastasis), was identified as a critical regulator of mammary cell migration and invasion. Nevertheless, whether EGF secreted from M2-like TAMs regulates LIMT expression in ovarian cancer progression remains largely unknown. Methods: The human OC cell lines OV90 and OVCA429 were recruited in this study. The differentiation of the human monocyte cell line THP-1 into M2-like TAMs was confirmed using flow cytometry within the application of phorbol 12-myristate 13-acetate (PMA). ELISA was performed to detect EGF concentration in co-culture system of M2-like TAMs and OC cell lines. Moreover, CCK-8, flow cytometry and immunofluorescence staining of Ki67 were performed to assess the capacity of cell proliferation. Besides, cell migration and invasion were determined by wound healing and transwell assays. Furthermore, the expression levels of epithelial-mesenchymal transition (EMT) markers and EGFR/ERK signals were analyzed by qRT-PCR and western blot. Female athymic nude mice (8-12 weeks of age; n = 8 for each group) were recruited for in vivo study. Results: In the present study, THP-1 cells exhibited the phenotype markers of M2-like TAMs with low proportion of CD14+ marker and high proportion of CD68+, CD204+, CD206+ markers within the application of PMA. After co-culturing with M2-like TAMs, EGF concentration in the supernatants was significantly increased in a time-dependent manner. Besides, OC cells presented better cell viability, higher cell proliferation, and stronger migration and invasion. The expression of EMT-related markers N-cadherin, Vimentin and EGFR/ERK signals were markedly up-regulated, while E-cadherin was significantly decreased. However, these effects induced by co-culture system were reversed by the application of AG1478 (an EGFR inhibitor) or LIMT overexpression. Furthermore, the endogenous expression of LIMT was decreased in OC cell lines compared with the control group. Also, the in vivo experiments verified that the inhibition of EGFR signaling by AG1478 or overexpression of LIMT effectively repressed the tumor growth. Conclusion: Taken together, we demonstrated that EGF secreted by M2-like TAMs might suppress LIMT expression via activating EGFR-ERK signaling pathway to promote the progression of OC.

Long noncoding RNAs in cancer cells

Long noncoding RNA (lncRNA) has recently been investigated as key modulators that regulate many biological processes in human cancers via diverse mechanisms. LncRNAs can interact with macromolecules such as DNA, RNA, or protein to exert cellular effects and to act as either tumor promoters or tumor suppressors in various malignancies. Moreover, the aberrant expression of lncRNAs may be detected in multiple cancer phenotypes by employing the rapidly developing modern gene chip technology and bioinformatics analysis. Herein, we highlight the mechanisms of action of lncRNAs, their functional cellular roles and their involvement in cancer progression. Finally, we provide an overview of recent progress in the lncRNA field and future potential for lncRNAs as cancer diagnostic markers and therapeutics.

A novel lncRNA-focus expression signature for survival prediction in endometrial carcinoma

Background

Endometrial cancer (UCEC) is a complex malignant tumor characterized by both genetic level and clinical trial. Patients with UCEC exhibit the similar clinical features, however, they have distinct outcomes due to molecular heterogeneity. The aim of this study was to access the prognostic value of long non-coding RNAs (lncRNAs) in UCEC patients and to identify potential lncRNA signature for predicting patients’ survival and improving patient-tailored treatment.

Methods

We performed a comprehensive genome-wide analysis of lncRNA expression profiles and clinical data in a large cohort of 301 UCEC patients. UCEC patients were randomly divided into the discovery cohort (n = 150) and validation cohort (n = 151). A novel lncRNA-focus expression signature was identified in the discovery cohort, and independently accessed in the validation cohort. Additionally, the lncRNA signature was evaluated by multivariable Cox regression and stratification analysis as well as functional enrichment analysis.

Results

We detected a novel lncRNA-focus expression signature (LFES) consisting of 11 lncRNAs that were associated with survival based on risk scoring strategy in UCEC. The risk score based on the LFES was able to separate patients of discovery cohort into high-risk and low-risk groups with significantly different overall survival and progression-free survival, and has been successfully confirmed in the validation cohort. Furthermore, the LFES is an independent prognostic predictor of survival and demonstrates superior prognostic performance compared with the clinical covariates for predicting 5-year survival (AUC = 0.887). Functional analysis has linked the expression of prognostic lncRNAs to well-known tumor suppressor or ontogenetic pathways in endometrial carcinogenesis.

Conclusions

Our study revealed a novel 11-lncRNA signature to predict survival of UCEC patient. This lncRNA signature may be a valuable and alternative marker for risk evaluation to aid patient-tailored treatment and improve the outcome of patients with UCEC.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3983-0) contains supplementary material, which is available to authorized users.

Long non‑coding RNA HOTTIP promotes hepatocellular carcinoma tumorigenesis and development: A comprehensive investigation based on bioinformatics, qRT‑PCR and meta‑analysis of 393 cases

HOTTIP functions as an independent biomarker in multiple cancers. However, the role of HOTTIP in hepatocellular carcinoma (HCC) remains unclear. In this study, we sought to investigate the HOTTIP expression in HCC and normal liver. We combined quantitative reverse transcription-polymerase chain reactions (qRT-PCR), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), Multi Experiment Matrix (MEM) and Oncomine database to assess the clinical role and the potential molecular mechanism of HOTTIP in HCC. Furthermore, a meta-analysis was performed to evaluate the relationship between HOTTIP and HCC tumorigenesis and development. Additionally, bioinformatics analysis, which contained Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and network analysis, were applied to investigate the underlying functions, pathways and networks of the potential genes. HOTTIP was obviously upregulated in HCC. A statistically significant higher expression of HOTTIP was found in TNM (III +IV), age (≥60), sex (male), race (white) and cirrhosis (no) compared to the control groups (P<0.05). Furthermore, the meta-analysis of 393 cases from multiple centers indicated that HOTTIP had high diagnostic value in HCC. Additionally, according to GO and KEGG analyses, we found that the most strongly enriched functional terms were gland development, transcription factor activity and extrinsic to membrane. Also, the HOTTIP co-expressed genes were significantly related to PPAR signaling pathway. We speculate that HOTTIP might play a vital part in HCC via regulating various pathways, especially PPAR signaling pathway. However, the detailed mechanism should be confirmed by functional experiments.

Serum long noncoding RNA urothelial carcinoma-associated 1: A novel biomarker for diagnosis and prognosis of hepatocellular carcinoma

Objective

Long noncoding RNAs (lncRNAs) offer great potential as cancer biomarkers. This study was performed to assess the applicability of serum lncRNA urothelial carcinoma-associated 1 (UCA1) as a diagnostic and/or prognostic biomarker for hepatocellular carcinoma (HCC).

Methods

We examined UCA1 expression in serum samples from 105 patients with HCC, 105 patients with benign liver disease (BLD), and 105 healthy volunteers using reverse-transcription polymerase chain reaction and analyzed the relationship between serum UCA1 and clinicopathological parameters of HCC as well as survival.

Results

Expression of serum UCA1 was significantly higher in patients with HCC and allowed for discrimination of HCC from BLD and healthy controls. High expression of serum UCA1 was significantly associated with a high tumor grade, large tumor size, positive vascular invasion, and advanced TNM stage. Multivariate analysis revealed that a high serum UCA1 level was an independent unfavorable prognostic factor for HCC.

Conclusions

Our results confirm the upregulation of serum UCA1 expression in HCC and indicate its clinical value as a noninvasive biomarker for HCC screening and prognostic prediction.

Diagnostic potential of serum exosomal colorectal neoplasia differentially expressed long non-coding RNA (CRNDE-p) and microRNA-217 expression in colorectal carcinoma

In this study, we investigated the diagnostic potential of serum exosomal colorectal neoplasia differentially expressed (CRNDE-p) long coding RNA and microRNA-217 in colorectal carcinoma (CRC). We detected high CRNDE-p and low miR-217 levels in exosomes released by multiple CRC cell lines into culture media as well as in sera from CRC xenograft mice and CRC patients. Conversely, we observed lower CRNDE-p and higher miR-217 levels in serum exosomes from post-chemotherapy than from pre-chemotherapy patient samples. The area under curve (AUC) value for the serum exosomal CRNDE-p and miR-217 combination was higher than CRNDE-p or miR-217 alone. Moreover, high CRNDE-p and low miR-217 serum exosomal levels correlated with advanced clinical stages (III/IV), tumor classification (T3/T4), and lymph node or distant metastasis. Thus combined evaluation of serum exosomal CRNDE-p and miR-217 levels show diagnostic and prognostic potential for CRC patients.