Identification of a six-lncRNA signature associated with recurrence of ovarian cancer

Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological cancers worldwide, mainly because of its initially asymptomatic nature and consequently late diagnosis. Long non-coding RNAs (lncRNA) are non-coding transcripts of more than 200 nucleotides, whose deregulation is involved in pathologies such as EOC, and are therefore envisaged as future biomarkers. We present a meta-analysis of available gene expression profiling (microarray and RNA sequencing) studies from EOC patients to identify lncRNA genes with diagnostic and prognostic value. In this meta-analysis, we include 46 independent cohorts, along with available expression profiling data from EOC cell lines. Differential expression analyses were conducted to identify those lncRNAs that are deregulated in (i) EOC versus healthy ovary tissue, (ii) unfavorable versus more favorable prognosis, (iii) metastatic versus primary tumors, (iv) chemoresistant versus chemosensitive EOC, and (v) correlation to specific histological subtypes of EOC. From the results of this meta-analysis, we established a panel of lncRNAs that are highly correlated with EOC. The panel includes several lncRNAs that are already known and even functionally characterized in EOC, but also lncRNAs that have not been previously correlated with this cancer, and which are discussed in relation to their putative role in EOC and their potential use as clinically relevant tools.

The enhancer RNA ADCY10P1 is associated with the progression of ovarian cancer

BACKGROUND

Emerging evidence identifies enhancer RNAs (eRNAs) as a class of regulatory ncRNAs that can contribute to the transcription of target genes. In this study, we used an integrated data analysis method to identify the important role of eRNAs in ovarian cancer (OC).

METHODS

Gene expression profiles and clinical information from The Cancer Genome Atlas (TCGA) database were used for this study. Based on expression analysis using GEPIA2 gene and Kaplan-Meier survival was performed to ensure the significance of the selected enhancer RNA ADCY10P1 in OC. Next, we explored the correlation and clinical significance between ADCY10P1 and target gene NFYA. Furthermore, we evaluated the effects of overexpression of ADCY10P1 on the proliferation, migration, invasion and epithelial-mesenchymal transformation (EMT) of OC cell lines. We also investigated the biological function enrichment score of ADCY10P1 and verified it with OC cell lines. Finally, external validation was conducted, and the prognostic value of the ADCY10P1 in different tumors was demonstrated.

RESULTS

We selected the eRNA ADCY10P1 associated with OC prognosis, with NFYA as its predicted target gene. Low ADCY10P1 expression was found to be associated with poor overall survival, high histological grade, and advanced stage of OC. Additionally, overexpression of ADCY10P1 inhibited the proliferation, migration, invasion and EMT phenotype of OC cell lines. Furthermore, ADCY10P1 was observed to inhibit glycolysis and fatty acid metabolism, thereby affecting OC progression. Meanwhile, OC tissue samples were externally validated. In addition, the pan-cancer analysis revealed that ADCY10P1 had prognostic value in other cancers.

CONCLUSIONS

This study showed that ADCY10P1 plays a key role in OC progression and may facilitate prognosis prediction.

N6-methyladenosine-related lncRNAs is a potential marker for predicting prognosis and immunotherapy in ovarian cancer

Background

With a lack of specific symptoms, ovarian cancer (OV) is often diagnosed at an advanced stage. This coupled with inadequate prognostic indicators and treatments with limited therapeutic effect make OV the deadliest type of gynecological tumor. Recent research indicates that N6-methyladenosine (m6A) and long-chain non-coding RNA (lncRNA) play important roles in the prognosis of OV and the efficacy of immunotherapy.

Results

Using the Cancer Genome Atlas (TCGA) OV-related data set and the expression profiles of 21 m6A-related genes, we identified two m6A subtypes, and the differentially expressed genes between the two. Based on the differentially expressed lncRNAs in the two m6A subtypes and the lncRNAs co-expressed with the 21 m6A-related genes, single-factor cox and LASSO regression were used to further isolate the 13 major lncRNAs. Finally, multi-factor cox regression was used to construct a m6A-related lncRNA risk score model for OV, with good performance in patient prognosis. Using risk score, OV tumor samples are divided into with high- and low-score groups. We explored the differences in clinical characteristics, tumor mutational burden, and tumor immune cell infiltration between the two groups, and evaluated the risk score’s ability to predict the benefit of immunotherapy.

Conclusion

Our m6A-based lncRNA risk model could be used to predict the prognosis and immunotherapy response of future OV patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00222-3.

Degradation of amyloid peptide aggregates by targeted singlet oxygen delivery from a benzothiazole functionalized naphthalene endoperoxide

Aggregate structures formed by amyloid-β (Aβ) are correlated with the progression of pathogenesis in Alzheimer's disease. Previous works have shown that photodynamic photosensitizers were effective in oxidatively degrading amyloid-β aggregates and thus decreasing their cytotoxicity under various conditions. In this work, we designed and synthesized a benzothiazole-naphthalene conjugate, with high level of structural analogy to Thioflavin T which is known to have high affinities for the amyloid peptide aggregates. The endoperoxide form (BZTN-O2) of this compound, which releases singlet oxygen with a half-life of 77 minutes at 37 °C, successfully inhibited and/or reversed amyloid aggregation. The endoperoxide is capable of singlet oxygen release without any need for light, and its charge-neutral form could allow blood-brain barrier (BBB) permeability. The therapeutic potential of such endoperoxide compounds with amyloid binding affinity is exciting.

(In)Distinctive Role of Long Non-Coding RNAs in Common and Rare Ovarian Cancers

Rare ovarian cancers (ROCs) are OCs with an annual incidence of fewer than 6 cases per 100,000 women. They affect women of all ages, but due to their low incidence and the potential clinical inexperience in management, there can be a delay in diagnosis, leading to a poor prognosis. The underlying causes for these tumors are varied, but generally, the tumors arise due to alterations in gene/protein expression in cellular processes that regulate normal proliferation and its checkpoints. Dysregulation of the cellular processes that lead to cancer includes gene mutations, epimutations, non-coding RNA (ncRNA) regulation, posttranscriptional and posttranslational modifications. Long non-coding RNA (lncRNA) are defined as transcribed RNA molecules, more than 200 nucleotides in length which are not translated into proteins. They regulate gene expression through several mechanisms and therefore add another level of complexity to the regulatory mechanisms affecting tumor development. Since few studies have been performed on ROCs, in this review we summarize the mechanisms of action of lncRNA in OC, with an emphasis on ROCs.

LncRNA MATN1-AS1 for Prediction of Prognosis in Osteosarcoma Patients and Its Cellular Function

Long non-coding RNAs show essential roles in various cancer processes. This study aimed at the expression features, prognosis significance, and biological effect of lnc MATN1-AS1 in osteosarcoma (OS). Five kinds of cell lines and 117 pairs of tissues were analyzed by qRT-PCR for quantification of lnc MATN1-AS1 and miR-1299 level. Clinical data were analyzed using Chi-Square Tests to show the association with lnc MATN1-AS1 level. Kaplan-Meier analysis and Cox regression were used to judge the prognostic value. Cell counting kit-8 and Transwell assay were conducted, respectively, to analyze the effect of lnc MATN1-AS1 on cell proliferation and metastasis. The target miRNA was predicted. lnc MATN1-AS1 level was significantly elevated in OS cells and tissues and related to Enneking staging, lung metastasis, and histologic type. Patients with high lnc MATN1-AS1 level showed a shorter overall survival and recurrence-free survival. Lnc MATN1-AS1 knockdown inhibited OS cell proliferation, migration, and invasion by sponging miR-1299. Lnc MATN1-AS1 has oncogenic features and prognostic significance in OS and is a novel therapeutic strategy for OS.

Ovarian cancer: epigenetics, drug resistance, and progression

Ovarian cancer (OC) is one of the most common malignant tumors in women. OC is associated with the activation of oncogenes, the inactivation of tumor suppressor genes, and the activation of abnormal cell signaling pathways. Moreover, epigenetic processes have been found to play an important role in OC tumorigenesis. Epigenetic processes do not change DNA sequences but regulate gene expression through DNA methylation, histone modification, and non-coding RNA. This review comprehensively considers the importance of epigenetics in OC, with a focus on microRNA and long non-coding RNA. These types of RNA are promising molecular markers and therapeutic targets that may support precision medicine in OC. DNA methylation inhibitors and histone deacetylase inhibitors may be useful for such targeting, with a possible novel approach combining these two therapies. Currently, the clinical application of such epigenetic approaches is limited by multiple obstacles, including the heterogeneity of OC, insufficient sample sizes in reported studies, and non-optimized methods for detecting potential tumor markers. Nonetheless, the application of epigenetic approaches to OC patient diagnosis, treatment, and prognosis is a promising area for future clinical investigation.

A Potential Immune-Related Long Non-coding RNA Prognostic Signature for Ovarian Cancer

Ovarian cancer (OC), the most lethal gynecologic malignancy, ranks fifth in cancer deaths among women, largely because of late diagnosis. Recent studies suggest that the expression levels of immune-related long non-coding RNAs (lncRNAs) play a significant role in the prognosis of OC; however, the potential of immune-related lncRNAs as prognostic factors in OC remains unexplored. In this study, we aimed to identify a potential immune-related lncRNA prognostic signature for OC patients. We used RNA sequencing and clinical data from The Cancer Genome Atlas and the Gene Expression Omnibus database to identify immune-related lncRNAs that could serve as useful biomarkers for OC diagnosis and prognosis. Univariate Cox regression analysis was used to identify the immune-related lncRNAs with prognostic value. Functional annotation of the data was performed through the GenCLiP310 website. Seven differentially expressed lncRNAs (AC007406.4, AC008750.1, AL022341.2, AL133351.1, FAM74A7, LINC02229, and HOXB-AS2) were found to be independent prognostic factors for OC patients. The Kaplan-Meier curve indicated that patients in the high-risk group had a poorer survival outcome than those in the low-risk group. The receiver operating characteristic curve revealed that the predictive potential of the immune-related lncRNA signature for OC was robust. The prognostic signature of the seven lncRNAs was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the signature of the seven lncRNAs was an independent prognostic factor for OC patients. Finally, we constructed a nomogram model and a competing endogenous RNA network related to the lncRNA prognostic signature. In conclusion, our study reveals novel immune-related lncRNAs that may serve as independent prognostic factors in OC.

Long non-coding RNA-H19 promotes ovarian cancer cell proliferation and migration via the microRNA-140/Wnt1 axis

To explore the effect and underlying molecular mechanism of long non-coding RNA (lncRNA)-H19 on ovarian cancer (OC) cells, a total of 41 cases of OC and adjacent normal tissues were collected. H19 and microRNA (miR)-140 expressions in OC tissues and cells were detected using quantitative real-time polymerase chain reaction (qRT-RCR). The correlation between H19 expression and prognosis of OC patient was analyzed. siRNA (si)-H19 and si-negative control (NC) were transfected into OC cells. Cell proliferation was checked by cell counting kit-8 assay and colony formation assay, and cell migration and invasion were analyzed via Transwell assay. The targeted binding relationship between H19 and miR-140 was predicted and verified, miR-140 downstream gene was predicted and Wnt1 was screened out. The impact of in-miR-140 on the si-H19-induced decreased OC cell proliferation and migration was evaluated. H19 expression was upregulated in OC tissues and cells, and its overexpression was associated with a poor prognosis of OC. si-H19 remarkably reduced OC cell proliferation and migration. H19 upregulated Wnt1 expression through targeting miR-140 in OC cells. Altogether, miR-140 was notably downregulated in OC, and in-miR-140 partially inhibited the si-H19-induced decrease of OC cell proliferation and migration. H19 competitively bound to miR-140 to upregulate Wnt1, thereby promoting OC cell proliferation and migration.

Long Noncoding RNAs as Innovative Urinary Diagnostic Biomarkers

The characterization of circulating tumor cells (CTCs) is now widely studied as a promising source of cancer-derived biomarkers because of their role in tumor formation and progression. However, CTCs analysis presents some limitations and no standardized method for CTCs isolation from urine has been defined so far. In fact, besides blood, urine represents an ideal source of noninvasive biomarkers, especially for the early detection of genitourinary tumors. Besides CTCs, long noncoding RNAs (lncRNAs) have also been proposed as potential noninvasive biomarkers, and the evaluation of the diagnostic accuracy of urinary lncRNAs has dramatically increased over the last years, with many studies being published. Therefore, this review provides an update on the clinical utility of urinary lncRNAs as novel biomarkers for the diagnosis of bladder and prostate cancers.

LncRNA HOTAIRM1, miR-433-5p and PIK3CD function as a ceRNA network to exacerbate the development of PCOS

Background

Currently, several non-coding RNAs (ncRNAs) were distinguished in polycystic ovarian syndrome (PCOS). This present study aims to explore the potential function of lncRNA HOTAIRM1/miR-433-5p/PIK3CD in ovarian granulosa cells.

Methods

We analyzed the expression profiles of HOTAIRM1, miR-433-5p and PIK3CD in PCOS samples by enquiring GEO database. GSEA was applied to enrich the pathways related to PCOS. The target association between HOTAIRM1 and miR-433-5p or the binding association between miR-433-5p and PIK3CD were assessed by online prediction tools and a dual luciferase reporter assay. qPCR and western blotting assays were used to detect PIK3CD expression after HOTAIRM1 and miR-433-5p treatment. The proliferation and apoptosis of ovarian granulosa cells were estimated by cell counting kit-8 and flow cytometry assays, respectively.

Results

The expression profiles of HOTAIRM1 and PIK3CD were increased, whereas miR-433-5p was decreased in PCOS tissues. PIK3CD expression was positively regulated by HOTAIRM1 and negatively modulated by miR-433-5p. Overexpression of HOTAIRM1 reduced the proliferative ability and increased the apoptotic ability of granulosa cells, whereas upregulation of miR-433-5p or downregulation of PIK3CD reversed the effects of HOTAIRM1 on granulosa cells. Moreover, overexpression of miR-433-5 displayed a results with increasing proliferative ability and decreasing apoptotic ability, but upregulation of PIK3CD eliminated the function of miR-433-5p on granulosa cells.

Conclusions

Our findings illustrated that HOTAIRM1 could sponge miR-433-5p to promote PIK3CD expression, thereby regulating the growth and apoptosis of granulose cells in PCOS.

Long non-coding RNAs in recurrent ovarian cancer: Theranostic perspectives

Nearly 70% of ovarian cancer (OC) patients experience recurrence within the first 2 years after initial treatment. Emerging evidence indicates that long non-coding RNAs (lncRNAs) play a pivotal role in the pathogenesis of OC progression, resistance to therapy and recurrent OC (ROC). Transcriptome profiling studies have reported differential expression patterns of lncRNAs in OC which are related to increased cell invasion, metastasis and drug resistance. In this review, we highlighted the roles of lncRNAs in OC progression and outlined the potential molecular mechanisms by which lncRNAs impact on ROC. Recent advances using lncRNAs as potential biomarkers for screening, detection, prediction, response to therapy and as therapeutic targets are discussed.

LINC00452 promotes ovarian carcinogenesis through increasing ROCK1 by sponging miR-501-3p and suppressing ubiquitin-mediated degradation

Ovarian cancer refers to all sorts of cancerous growth that starts from the ovary. Dysregulation of long non-coding RNAs (lncRNAs) is associated with ovarian cancer development and progression. Cellular expression and localization of LINC00452 in ovarian cancer cells were detected by qPCR and FISH. The roles of LINC00452 in ovarian carcinogenesis were characterized by MTT, transwell and colony-formation assays in vitro as well as xenograft mouse model. The underlying mechanism was explored by microarray, RIP, Co-IP and luciferase reporter assays. This study identified a novel lncRNA LINC00452 being elevated in both ovarian cancer cells and tumor tissues in patients. Such aberrant expression of LINC00452 was negatively correlated with relapse-free survival of ovarian cancer patients. Overexpression of LINC00452 potentiated CaOV3 cell viability, migration and invasion in vitro as well as xenograft tumor growth in vivo. Evidence from the current study suggests that the carcinogenicity of LINC00452 is partially due to competitive sponging of miR-501-3p followed with release of repression on the ROCK1, a key effector in Rho signaling pathway. Irrespective of its miRNA sponge function, LINC00452 is capable of preventing ROCK1 protein from ubiquitin/proteasome-mediated degradation via their mutual physical interaction. Our study makes LINC00452 a potential therapeutic target for ovarian cancer.

Advancing Pan-cancer Gene Expression Survial Analysis by Inclusion of Non-coding RNA

Non-coding RNAs occupy a significant fraction of the human genome. Their biological significance is backed up by a plethora of emerging evidence. One of the most robust approaches to demonstrate non-coding RNA's biological relevance is through their prognostic value. Using the rich gene expression data from The Cancer Genome Altas (TCGA), we designed Advanced Expression Survival Analysis (AESA), a web tool which provides several novel survival analysis approaches not offered by previous tools. In addition to the common single-gene approach, AESA computes the gene expression composite score of a set of genes for survival analysis and utilizes permutation test or cross-validation to assess the significance of log-rank statistic and the degree of over-fitting. AESA offers survival feature selection with post-selection inference and utilizes expanded TCGA clinical data including overall, disease-specific, disease-free, and progression-free survival information. Users can analyse either protein-coding or non-coding regions of the transcriptome. We demonstrated the effectiveness of AESA using several empirical examples. Our analyses showed that non-coding RNAs perform as well as messenger RNAs in predicting survival of cancer patients. These results reinforce the potential prognostic value of non-coding RNAs. AESA is developed as a module in the freely accessible analysis suite MutEx. Abbreviation: ACC: Adrenocortical Carcinoma (n = 92); BLCA: Bladder Urothelial Carcinoma (n = 412); BRCA: Breast Invasive Carcinoma (n = 1098); CESC: Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (n = 307); CHOL: Cholangiocarcinoma (n = 51); COAD: Colon Adenocarcinoma (n = 461); DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (n = 58); ESCA: Oesophageal Carcinoma (n = 185); GBM: Glioblastoma Multiforme (n = 617); HNSC: Head and Neck Squamous Cell Carcinoma (n = 528); KICH: Kidney Chromophobe (n = 113); KIRC: Kidney Renal Clear Cell Carcinoma (n = 537); KIRP: Kidney Renal Papillary Cell Carcinoma (n = 291); LAML: Acute Myeloid Leukaemia (n = 200); LGG: Brain Lower Grade Glioma (n = 516); LIHC: Liver Hepatocellular Carcinoma (n = 377); LUAD: Lung Adenocarcinoma (n = 585); LUSC: Lung Squamous Cell Carcinoma (n = 504); MESO: Mesothelioma (n = 87); OV: Ovarian Serous Cystadenocarcinoma (n = 608) PAAD: Pancreatic Adenocarcinoma (n = 185); PCPG: Pheochromocytoma and Paraganglioma (n = 179); PRAD: Prostate Adenocarcinoma (n = 500); READ: Rectum Adenocarcinoma (n = 172); SARC: Sarcoma (n = 261); SKCM: Skin Cutaneous Melanoma (n = 470); STAD: Stomach Adenocarcinoma (n = 443); TGCT: Testicular Germ Cell Tumours (n = 150); THCA: Thyroid Carcinoma (n = 507) THYM: Thymoma (n = 124); UCEC: Uterine Corpus Endometrial Carcinoma (n = 560); UCS: Uterine Carcinosarcoma (n = 57); UVM: Uveal Melanoma (n = 80).

The Interplay between Long Noncoding RNAs and Proteins of the Epigenetic Machinery in Ovarian Cancer

Comprehensive large-scale sequencing and bioinformatics analyses have uncovered a myriad of cancer-associated long noncoding RNAs (lncRNAs). Aberrant expression of lncRNAs is associated with epigenetic reprogramming during tumor development and progression, mainly due to their ability to interact with DNA, RNA, or proteins to regulate gene expression. LncRNAs participate in the control of gene expression patterns during development and cell differentiation and can be cell and cancer type specific. In this review, we described the potential of lncRNAs for clinical applications in ovarian cancer (OC). OC is a complex and heterogeneous disease characterized by relapse, chemoresistance, and high mortality rates. Despite advances in diagnosis and treatment, no significant improvements in long-term survival were observed in OC patients. A set of lncRNAs was associated with survival and response to therapy in this malignancy. We manually curated databases and used bioinformatics tools to identify lncRNAs implicated in the epigenetic regulation, along with examples of direct interactions between the lncRNAs and proteins of the epigenetic machinery in OC. The resources and mechanisms presented herein can improve the understanding of OC biology and provide the basis for further investigations regarding the selection of novel biomarkers and therapeutic targets.

Study and Characterization of Long Non-coding RUNX1-IT1 among Large Artery Atherosclerosis Stroke Patients Based on the ceRNA Hypothesis

Recent studies have shed light on the involvement of long non-coding RNAs (lncRNAs) in the initiation and development of stroke. However, the regulatory function of many lncRNAs in large artery atherosclerosis (LAA) has not been fully elucidated. Based on the competing endogenous RNA (ceRNA) hypothesis recently proposed by Pandolfi, the present study was conducted using experimental techniques and bioinformatics to investigate the expression and regulatory function of a lncRNA involved in the development of LAA. The lncRNAs differentially expressed in stroke were obtained using meta-analysis, and one lncRNA was selected for experimental studies on patients with LAA (n = 100) and healthy controls (n = 100) using quantitative real-time polymerase chain reaction (qRT-PCR). The patients were also evaluated through meta-analysis to identify the function of the selected lncRNA, miRNAs, and mRNAs with altered expression in stroke. Finally, the experimental results and meta-analysis findings were integrated, and different functional groups were assigned. The results indicated that the level of lncRNA-RUNX1-IT1 was significantly lower in the patients with LAA compared to the healthy control subjects (p > 0.05). Logistic regression analyses revealed that the expression of lncRNA-RUNX1-IT1 was inversely correlated with LAA (P = 009, OR = 0.871, 95% CI: 0.786-0.965). In addition, a network of differentially expressed genes (DE genes) was created for miRNAs and mRNAs based on their association with lncRNA-RUNX1-IT1. Functional analysis showed that the DE genes in the network are involved in the apoptosis and alternative splicing of RNAs. The findings of the present study suggest that the downregulation of lncRNA-RUNX1-IT1 is associated with LAA development by interrupting the regulatory network of cells. The results of network analysis demonstrated that the lncRNA-RUNX1-IT1 could influence the expression of mRNAs and miRNAs involved in the apoptosis and alternative splicing of RNAs.

A prognostic index based on a fourteen long non-coding RNA signature to predict the recurrence-free survival for muscle-invasive bladder cancer patients

Background

Bladder cancer (BC) is regarded as one of the most fatal cancer around the world. Nevertheless, there still lack of sufficient markers to predict the prognosis of BC patients. Herein, we aim to establish a prognosis predicting signature based on long-noncoding RNA (lncRNA) for the invasive BC patients.

Methods

The lncRNA expression profile was downloaded from The Cancer Genome Atlas (TCGA) database, along with the correlated clinicopathological information. The univariate Cox regression test was employed to screen out the recurrence-free survival (RFS)-related lncRNAs. Then, the LASSO method was conducted to construct the signature based on these RFS-related lncRNA candidates. Genes correlated with these fourteen lncRNAs were extracted from the mRNA expression profile, with the Pearson correlation coefficient > 0.60 or < − 0.40. Subsequently, the Proteomap pathway enrichment analyses were conducted to classify the function of these correlated genes. Furthermore, the multivariate analyses were executed to reveal the independent role of the proposed signature with the clinicopathological features.

Results

We established an lncRNA-based RFS predicting signature by the LASSO Cox regression test, and proved its usage and stability on both the training and validation cohorts by the Kaplan-Meier and receiver operating characteristic (ROC) curves. Notably, the multivariate Cox regression analysis found that our classifier was an independent indicator for muscle-invasive BC patients rather than sex, age and tumor grade, with higher predictive value than the existing ones. Besides, we did the pathway analyses for these genes that highly correlated with the proposed fourteen lncRNAs, as well as the differentially expressed genes (DEGs) derived from the high-risk vs. low-risk groups, and the recurrence vs. non-recurrence groups, respectively. Notably, these results were consistent, and these genes were mostly enriched in the transcription factors, G protein-coupled receptors, MAPK signaling pathways, which were proved significantly associated with tumor progression and drug resistance.

Conclusions

Our results suggested that the fourteen-lncRNA-based RFS predicting signature is an independent indicator for BC patients. Further prospective studies with more samples are needed to verify our findings.

Beyond MicroRNAs: Emerging Role of Other Non-Coding RNAs in HPV-Driven Cancers

Persistent infection with high-risk Human Papilloma Virus (HPV) leads to the development of several tumors, including cervical, oropharyngeal, and anogenital squamous cell carcinoma. In the last years, the use of high-throughput sequencing technologies has revealed a number of non-coding RNA (ncRNAs), distinct from micro RNAs (miRNAs), that are deregulated in HPV-driven cancers, thus suggesting that HPV infection may affect their expression. However, since the knowledge of ncRNAs is still limited, a better understanding of ncRNAs biology, biogenesis, and function may be challenging for improving the diagnosis of HPV infection or progression, and for monitoring the response to therapy of patients affected by HPV-driven tumors. In addition, to establish a ncRNAs expression profile may be instrumental for developing more effective therapeutic strategies for the treatment of HPV-associated lesions and cancers. Therefore, this review will address novel classes of ncRNAs that have recently started to draw increasing attention in HPV-driven tumors, with a particular focus on ncRNAs that have been identified as a direct target of HPV oncoproteins.

Long Noncoding RNA HOTAIRM1 Maintains Tumorigenicity of Glioblastoma Stem-Like Cells Through Regulation of HOX Gene Expression

Noncoding RNAs regulate transcription of gene expression and play an important role in the pathogenesis of glioblastomas. These tumors are heterogeneous with some glioma stem cells (GSCs) that are highly tumorigenic subpopulations of cells contributing to recurrence and treatment resistance. In this study, GSCs were established by neurosphere cultures of primary glioblastoma cells and validated by the expression of GSC marker CD133. The expression of the long noncoding RNA HOTAIRM1 was detected using real-time quantitative reverse transcription PCR (qRT-PCR). The role of HOTAIRM1 in the proliferation, apoptosis, stemness, and tumorigenicity of GSCs was investigated by soft agar colony formation, flow cytometry, TUNEL analysis, sphere formation, and in vivo xenograft models through silencing of HOTAIRM1. The expression of HOTAIRM1 and the neighboring HOX genes were analyzed by qRT-PCR in different grades of gliomas and nontumor tissues. We found that HOTAIRM1 is significantly elevated in GSCs. The silencing of HOTAIRM1 significantly impairs the proliferation, apoptosis, self-renewal, tumorigenesis of GSCs. In addition, HOTAIRM1 is significantly upregulated in gliomas and associated with tumor grade and patient survival. HOTAIRM1 neighboring genes, HOXA1, HOXA2, and HOXA3, are also significantly upregulated in gliomas and correlate with the expression of HOTAIRM1. Among them, HOXA2 and HOXA3 were identified as being upregulated in GSCs and contributed to the self-renewal of these stem cells. Taken together, our results demonstrate that HOTAIRM1 plays a critical role in the self-renewal of GSCs. These data also suggest that overexpression of HOTAIRM1 can be a negative prognostic factor for patient survival in malignant glioma and may be a promising potential therapeutic target.

LncRNA profile study reveals a seven-lncRNA signature predicts the prognosis of patients with colorectal cancer

Background

The prognosis of colorectal cancer (CRC) is still challenging to evaluate or predict. Recently, long non-coding RNAs (lncRNAs) have been found to play an important role in tumorigenesis and prognosis, however, few lncRNAs have been identified in CRC progression. We aimed to establish a lncRNA signature to improve prognosis prediction of CRC.

Methods

In the present study, we profiled lncRNA expression with a lncRNA-mining approach in two CRC data sets from Gene Expression Ominus (GEO) (GSE39582, N = 557 and GSE17538, N = 200). LncRNAs were analyzed to determine a prognostic signature by Cox regression and Robust likelihood-based survival model. We identified seven lncRNAs that significantly associated with the disease free survival (DFS) in the training group. A risk score formula was constructed to evaluate the performance of this lncRNA panel.

Results

A seven-lncRNA signature was established to predict prognosis of CRC patients. The prognostic value of this signature was verified in the training group, internal validation group and external validation cohort, respectively. Receiver operating characteristic (ROC) analysis suggested a powerful discrimination ability of the seven-gene signature. Finally, Cox regression analyzed this signature as an independent influencing factor and subsequent pathway or network analysis implicated a potential mechanism of these lncRNAs.

Conclusions

In summary, the seven-lncRNA signature we identified can effectively classify patients. This risk score model could serve as an independent biomarker to predict prognosis of CRC patients.

Recurrence-Associated Multi-RNA Signature to Predict Disease-Free Survival for Ovarian Cancer Patients

Ovarian cancer (OvCa) is an intractable gynecological malignancy due to the high recurrence rate. Several molecular biomarkers have been previously screened for early identifying patients with a high recurrence risk and poor prognosis. However, all the known studies focused on a single type of RNAs, not integrating various types. This study was to construct a new multi-RNA-based model to predict the recurrence and prognosis for OvCa patients by using the messenger RNA (mRNA, including long noncoding RNA (lncRNA)) and microRNA (miRNA) sequencing data of The Cancer Genome Atlas database. After univariate Cox regression and least absolute shrinkage and selection operator analyses, a multi-RNA-based signature (2 miRNAs: hsa-miR-508, hsa-miR-506; 1 lncRNA: TM4SF1-AS1; 11 mRNAs: MAGI3, SLAMF7, GLI2, PDK1, ARID3A, PLEKHG4B, TNFAIP8L3, C1QTNF3, NDUFAF1, CH25H, TMEM129) was generated and used to establish a risk score model. The high- and low-risk patients classified by the median risk score exhibited significantly different recurrence risks (89% versus 61%, p < 0.001) and survival time (the area under the receiver operating characteristic curve (AUC) = 0.901 for 5-year disease-free survival (DFS)). This risk model was independent of other clinical features and superior to pathologic staging for DFS prediction (AUC, 0.906 versus 0.524; C-index, 0.633 versus 0.510). Furthermore, some new interaction axes were revealed to explain the possible functions of these RNAs (competing endogenous RNA: TM4SF1-AS1-miR-186-STEAP2, LINC00536-miR-508-STEAP2, LINC00475-miR-506-TMEM129; coexpression: LINC00598-PLEKHG4B). In conclusion, this multi-RNA-based risk model may be clinically useful to stratify OvCa patients with different recurrence risks and survival outcomes and included RNAs may be potential therapeutic targets.

Long Non-coding RNAs Involved in Resistance to Chemotherapy in Ovarian Cancer

Ovarian cancer (OC) accounts for more than 150,000 deaths worldwide every year. Patients are often diagnosed at an advanced stage with metastatic dissemination. Although platinum- and taxane-based chemotherapies are effective treatment options, they are rarely curative and eventually, the disease will progress due to acquired resistance. Emerging evidence suggests a crucial role of long non-coding RNAs (lncRNAs) in the response to therapy in OC. Transcriptome profiling studies using high throughput approaches have identified differential expression patterns of lncRNAs associated with disease recurrence. Furthermore, several aberrantly expressed lncRNAs in resistant OC cells have been related to increased cell division, improved DNA repair, up-regulation of drug transporters or reduced susceptibility to apoptotic stimuli, supporting their involvement in acquired resistance. In this review, we will discuss the key aspects of lncRNAs associated with the development of resistance to platinum- and taxane-based chemotherapy in OC. The molecular landscape of OC will be introduced, to provide a background for understanding the role of lncRNAs in the acquisition of malignant properties. We will focus on the interplay between lncRNAs and molecular pathways affecting drug response to evaluate their impact on treatment resistance. Additionally, we will discuss the prospects of using lncRNAs as biomarkers or targets for precision medicine in OC. Although there is still plenty to learn about lncRNAs and technical challenges to be solved, the evidence of their involvement in OC and the development of acquired resistance are compelling and warrant further investigation for clinical applications.

HOTAIRM1 suppresses cell proliferation and invasion in ovarian cancer through facilitating ARHGAP24 expression by sponging miR-106a-5p

AIMS

Ovarian cancer (OC) is the most lethal gynecologic malignant tumors all over the world. HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) has been reported as an important regulator in multiple tumors. However, the functions of HOTAIRM1 in OC and its possible molecular mechanisms remain unclear.

MAIN METHODS

qRT-PCR analysis was performed to detect the expression levels of HOTAIRM1, miR-106a-5p and ARHGAP24 mRNA in OC tissues and cells. The functional effects of HOTAIRM1, miR-106a-5p and ARHGAP24 on OC cells were determined by MTT, colony formation, flow cytometry and Transwell assays. Luciferase reporter, RIP and RNA pull-down assays were used to examine the interaction between miR-106a-5p and HOTAIRM1 or ARHGAP24. Tumor xenografts were constructed in nude mice to confirm the roles of HOTAIRM1 in OC in vivo.

KEY FINDINGS

HOTAIRM1 expression was lowered in OC tumor tissues and cells. Decreased HOTAIRM1 expression was associated with advanced FIGO stages and lymphatic metastasis. Up-regulation of HOTAIRM1 suppressed OC cell proliferation and invasion, and promoted apoptosis. Also, HOTAIRM1 slowed OC tumor growth in vivo. Moreover, HOTAIRM1 could serve as a competing endogenous RNA (ceRNA) of miR-106a-5p to derepress ARHGAP24 expression. HOTAIRM1-mediated inhibitory effect on OC progression was partly reversed following the restoration of miR-106a-5p expression. Furthermore, ARHGAP24 overexpression repressed OC progression in vitro.

SIGNIFICANCE

In conclusion, our study showed that HOTAIRM1 suppressed OC progression through derepression of ARHGAP24 by sponging miR-106a-5p. This finding provides novel insights into the mechanisms of HOTAIRM1 in OC and highlights a potential therapeutic strategy for the treatment of OC.

A seven-long noncoding RNA signature predicts overall survival for patients with early stage non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common cancer and cause of cancer-related mortality globally. Increasing evidence suggested that the long non-coding RNAs (lncRNAs) were involved in cancer-related death. To explore the possible prognostic lncRNA biomarkers for NSCLC patients, in the present study, we conducted a comprehensive lncRNA profiling analysis based on 1902 patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. In the discovery phase, we employed 682 patients from the combination of four GEO datasets (GSE30219, GSE31546, GSE33745 and GSE50081) and conducted a seven-lncRNA formula to predict overall survival (OS). Next, we validated our risk-score formula in two independent datasets, TCGA (n=994) and GSE31210 (n=226). Stratified analysis revealed that the seven-lncRNA signature was significantly associated with OS in stage I patients from both discovery and validation groups (all P<0.001). Additionally, the prognostic value of the seven-lncRNA signature was also found to be favorable in patients carrying wild-type KRAS or EGFR. Bioinformatical analysis suggested that the seven-lncRNA signature affected patients’ prognosis by influencing cell cycle-related pathways. In summary, our findings revealed a seven-lncRNA signature that predicted OS of NSCLC patients, especially in those with early tumor stage and carrying wild-type KRAS or EGFR.

An eight-long non-coding RNA signature as a candidate prognostic biomarker for bladder cancer

Backgroud: Bladder cancer (BLCA) is one of the most fatal types of cancer worldwide. However, there are limited methods for us to provide a prognostic prediction of BLCA patients. Therefore, we aimed at developing a lncRNA signature to improve the prognosis prediction of BLCA.

RESULTS

An eight-lncRNA signature was significantly associated with recurrence free survival in BLCA patients from both discovery and validation groups. Furthermore, genes involved in the signature were enriched in extracellular matrix organization pathway. Finally, functional experiments demonstrated that six out of the eight lncRNAs significantly regulated the invasion of BLCA cells.

METHOD

A total of 343 BLCA patients from The Cancer Genome Atlas (TCGA) were employed and randomly divided into training (n=172) and validating (n=171) groups. The lncRNA expression profiles of BLCA patients were screened and a risk-score formula were created and validated according to the Cox regression analysis. Next, WGCNA method was employed to cluster genes that highly correlated with the risk scores based on the profiling data of TCGA dataset and transwell assay was also performed to further investigate the role of these lncRNAs.

CONCLUSIONS

Our results suggested that the eight-lncRNA signature was a candidate prognostic biomarker for predicting tumor recurrence of patients with BLCA.

A novel risk score system for assessment of ovarian cancer based on co-expression network analysis and expression level of five lncRNAs

Background

Ovarian cancer (OC) is the most deadly gynaecological cancer, contributing significantly to female cancer-related deaths worldwide. Improving the outlook for OC patients depends on the identification of more reliable prognostic biomarkers for early diagnosis and survival prediction. The various roles of long non-coding RNAs (lncRNAs) in OC have attracted increasing attention. This study aimed to identify a lncRNA-based signature for survival prediction in OC patients.

Methods

RNA expression data and clinical information from a large number of OC patients were downloaded from a public database. These data were regarded as a training set to construct a weighed gene co-expression network analysis (WGCNA) network, mine stable modules, and screen differentially expressed lncRNAs. The prognostic lncRNAs were screened using univariate Cox regression analysis and the optimal prognosis lncRNA combination was screened using a Cox-PH model. The finalised lncRNA combination was used to construct the risk score system, which was validated and assessed for effectiveness using other independent datasets. Further functional pathway enrichment was performed using gene set enrichment analysis (GSEA).

Results

A co-expression network was constructed and four stable modules with OC-related biological functions were obtained. A total of 19 lncRNAs significantly related to prognosis of ovarian cancer were obtained using univariate Cox regression analysis, and the 5 prognostic signature lncRNAs GAS5, HCP5, PART1, SNHG11, and SNHG5 were used to establish a risk assessment system. The reliability of the prognostic scoring system was further confirmed using validation sets, which indicated that the risk assessment system could be used as an independent prognostic factor. Pathway enrichment analysis revealed that the network modules related to the above five prognostic genes were significantly associated with cell local adhesion, cancer signaling pathways, JAK-STAT signalling, and endogenous cell receptor interaction.

Conclusions

The risk score system established in this study could provide a novel reliable method to identify individuals at high risk of OC. In addition, the five prognostic lncRNAs identified here are promising potential prognostic biomarkers that could help to elucidate the pathogenesis of OC.

LncRNAs in ovarian cancer

Ovarian cancer is one of the most common gynecologic malignancies and has a poor prognosis. Recently, long noncoding RNAs (lncRNAs) have been identified as key regulators of cancer development. Studies have shown that the dysregulation of lncRNAs is frequently observed in ovarian cancer and greatly contributes to malignant phenotypical changes. In this review, we provide perspectives on the involvement of lncRNAs in the proliferation, apoptosis, cell cycle, migration, invasion, metastasis and drug resistance of ovarian cancer based on recent discoveries. Then, we discuss the role of lncRNAs in predicting the prognosis of ovarian cancer. Finally, we provide insight into the potential of lncRNAs for evaluating the diagnosis and prognosis of ovarian cancer.

LINC01118 Modulates Paclitaxel Resistance of Epithelial Ovarian Cancer by Regulating miR-134/ABCC1

BACKGROUND Epithelial ovarian cancer (EOC) has a high mortality rate and is a common malignant tumor of women, seriously impairing health. Chemoresistance is one of the major causes of poor prognosis. Therefore, analyzing the molecular mechanism of paclitaxel resistance has great significance. MATERIAL AND METHODS We analyzed aberrantly expressed lncRNAs in chemoresistant EOC cells by microarray and confirmed LINC01118 expression by real-time PCR. The paclitaxel sensitivity alternation was analyzed by MTS, flow cytometry, and Transwell assay, while wound healing assays were performed to assess apoptosis, migration, and invasion in vitro. The interaction between LINC01118 and miR-134 was confirmed by luciferase assay. RESULTS LINC01118 was highly expressed in EOC tissues and chemoresistant cells. Biological function experiments showed LINC01118 could facilitate paclitaxel resistance and promote migration and invasion while inhibiting apoptosis of EOC cells. Moreover, LINC01118 targets miR-134 and then affects ABCC1 expression. CONCLUSIONS LINC01118 acted as an oncogene and modulated EOC paclitaxel sensitivity by regulating miR-134/ABCC1.

Downregulation of lncRNA CASC2 promotes the postoperative local recurrence of early oral squamous cell carcinoma

PURPOSE

LncRNA CASC2 plays a role as tumor suppressor gene in different types of human malignancies, while its involvement in oral squamous cell carcinoma (OSCC) is unknown. The present study aimed to investigate the involvement of lncRNA CASC2 in OSCC.

METHODS

In this study, the expression of lncRNA CASC2 in tumor tissues, adjacent healthy tissues, and plasma of 122 OSCC patients as well as in plasma of 52 healthy controls was detected by RT-qPCR. Diagnostic value of lncRNA CASC2 for OSCC was evaluated by ROC curve analysis. Patients were followed up for 5 years to record recurrence. LncRNA CASC2 expression vectors were transfected into cells of human OSCC cell lines, and the effects on cancer cell proliferation and miRNA-21 expression were analyzed by CCK-8 assay and RT-qPCR, respectively.

RESULTS

We found that CASC2 was significantly downregulated in OSCC patients than in healthy controls. Downregulation of CASC2 distinguished OSCC patients from healthy controls. Local recurrence was observed in 26 out of 122 patients and no distant recurrence was observed during follow-up. Compared with pretreatment levels, plasma levels of CASC2 were significantly increased in patients with local recurrence than in patients without recurrence. Transfection of CASC2 expression vectors led to significantly inhibited tumor cell proliferation and reduced miRNA-21 expression levels.

CONCLUSIONS

We, therefore, conclude that downregulation of lncRNA CASC2 may participate in the postoperative local recurrence of early OSCC through miRNA-21.

Long noncoding RNA HOTAIRM1 inhibits cell progression by regulating miR-17-5p/ PTEN axis in gastric cancer

OBJECTIVES

This study was conducted to identify the significantly altered long noncoding RNAs (lncRNAs), messenger RNA (mRNA) and pathways in gastric cancer (GC).

METHODS

We used microarray analysis to identify differentially expressed lncRNAs and mRNAs, whereas the obviously changed pathways were found by gene set enrichment analysis. The coexpression network of lncRNA and mRNA was constructed by Cytoscape, and their target relationships with miRNAs were predicted by miRcode and TargetScan. qRT-PCR and Western blot were performed to determine the expression levels of mRNAs and proteins in tissues and cell lines. Dual-luciferase reporter assay was applied to achieve the determination of the specific target relationships. Cell viability, migration, and apoptosis were detected by MTT assay, wound healing assay and flow cytometry, respectively. Through the xenograft assay, the gastric tumor was implanted into nude mice to investigate the influence of HOTAIRM1 in vivo.

RESULTS

HOTAIRM1 and phosphatase and tensin homolog (PTEN) were both downregulated in GC, whereas miR-17-5p was upregulated. Moreover, the PI3K/AKT pathway was found activated in GC. HOTAIRM1 targeted miR-17-5p, whereas PTEN was the downstream target gene of miR-17-5p. HOTAIRM1 suppressed proliferation and migration of GC cell line and induced their apoptosis, whereas miR-17-5p played the opposite role on GC cell line. HOTAIRM1 also postponed tumor growth in vivo and inhibited the PI3K/AKT pathway in GC.

CONCLUSIONS

LncRNA HORAIRM1 suppressed the PI3K/AKT pathway in GC and inhibited the progression of GC by serving as a competing endogenous RNA of miR-17-5p, mediating the expression of PTEN.

Prediction of candidate RNA signatures for recurrent ovarian cancer prognosis by the construction of an integrated competing endogenous RNA network

Tumor recurrence hinders treatment of ovarian cancer. The present study aimed to identify potential biomarkers for ovarian cancer recurrence prognosis and explore relevant mechanisms. RNA-sequencing of data from the TCGA database and GSE17260 dataset was carried out. Samples of the data were grouped according to tumor recurrence information. Following data normalization, differentially expressed genes/micro RNAs (miRNAs)/long non-coding (lncRNAs) (DEGs/DEMs/DELs) were selected between recurrent and non-recurrent samples. Their correlations with clinical information were analyzed to identify prognostic RNAs. A support vector machine classifier was used to find the optimal gene set with feature genes that could conclusively distinguish different samples. A protein-protein interaction (PPI) network was established for DEGs using relevant protein databases. An integrated ‘lncRNA/miRNA/mRNA’ competing endogenous RNA (ceRNA) network was constructed to reveal potential regulatory relationships among different RNAs. We identified 36 feature genes (e.g. TP53 and RBPMS) for the classification of recurrent and non-recurrent ovarian cancer samples. Prediction with this gene set had a high accuracy (91.8%). Three DELs (WT1-AS, NBR2 and ZNF883) were highly associated with the prognosis of recurrent ovarian cancer. Predominant DEMs with their targets were hsa-miR-375 (target: RBPMS), hsa-miR-141 (target: RBPMS), and hsa-miR-27b (target: TP53). Highlighted interactions in the ceRNA network were ‘WT1-AS-hsa-miR-375-RBPMS’ and ‘WT1-AS-hsa-miR-27b-TP53’. TP53, RBPMS, hsa-miR-375, hsa-miR-141, hsa-miR-27b, and WT1-AS may be biomarkers for recurrent ovarian cancer. The interactions of ‘WT1-AS-hsa-miR-375-RBPMS’ and ‘WT1-AS-hsa-miR-27b-TP53’ may be potential regulatory mechanisms during cancer recurrence.

Long non-coding RNAs in ovarian cancer

Long non-coding RNAs (lncRNAs) refer to functional cellular RNAs molecules longer than 200 nucleotides in length. Unlike microRNAs, which have been widely studied, little is known about the enigmatic role of lncRNAs. However, lncRNAs have motivated extensively attention in the past few years and are emerging as potentially important regulators in pathological processes, including in cancer. We now understand that lncRNAs play role in cancer through their interactions with DNA, protein, and RNA in many instances. Moreover, accumulating evidence has recognized that large classes of lncRNAs are functional for ovarian cancer. Nevertheless, the biological phenomena and molecular mechanisms of lncRNAs in ovarian cancer remain to be better identified. In this review, we outline the dysregulated expression of lncRNAs and their potential clinical implications in ovarian cancer, with a particular emphasis on discussing the well characterized mechanisms underlying lncRNAs in ovarian cancer.

MALAT1: a druggable long non-coding RNA for targeted anti-cancer approaches

The deeper understanding of non-coding RNAs has recently changed the dogma of molecular biology assuming protein-coding genes as unique functional biological effectors, while non-coding genes as junk material of doubtful significance. In the last decade, an exciting boom of experimental research has brought to light the pivotal biological functions of long non-coding RNAs (lncRNAs), representing more than the half of the whole non-coding transcriptome, along with their dysregulation in many diseases, including cancer.In this review, we summarize the emerging insights on lncRNA expression and functional role in cancer, focusing on the evolutionary conserved and abundantly expressed metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) that currently represents the best characterized lncRNA. Altogether, literature data indicate aberrant expression and dysregulated activity of MALAT1 in human malignancies and envision MALAT1 targeting as a novel treatment strategy against cancer.

Role of lncRNAs in ovarian cancer: defining new biomarkers for therapeutic purposes

Long noncoding RNAs (lncRNAs) are a class of noncoding RNA, involved in regulation of diverse physiological and pathological processes. Ovarian cancer is the leading cause of death among all gynecological malignancies in the world and its underlying mechanism is still unclear. LncRNAs exhibit multiple biological functions in various stages of ovarian cancer development. We will discuss and summarize the new and important lncRNAs and their involvement in disease, which might represent promising therapeutic targets. Therapeutic intervention based on silencing or functional inhibition of target lncRNAs will be beneficial for ovarian cancer patients.

Non-coding RNAs: long non-coding RNAs and microRNAs in endocrine-related cancers

The human genome is 'pervasively transcribed' leading to a complex array of non-coding RNAs (ncRNAs) that far outnumber coding mRNAs. ncRNAs have regulatory roles in transcription and post-transcriptional processes as well numerous cellular functions that remain to be fully described. Best characterized of the 'expanding universe' of ncRNAs are the ~22 nucleotide microRNAs (miRNAs) that base-pair to target mRNA's 3' untranslated region within the RNA-induced silencing complex (RISC) and block translation and may stimulate mRNA transcript degradation. Long non-coding RNAs (lncRNAs) are classified as >200 nucleotides in length, but range up to several kb and are heterogeneous in genomic origin and function. lncRNAs fold into structures that interact with DNA, RNA and proteins to regulate chromatin dynamics, protein complex assembly, transcription, telomere biology and splicing. Some lncRNAs act as sponges for miRNAs and decoys for proteins. Nuclear-encoded lncRNAs can be taken up by mitochondria and lncRNAs are transcribed from mtDNA. Both miRNAs and lncRNAs are dysregulated in endocrine cancers. This review provides an overview on the current understanding of the regulation and function of selected lncRNAs and miRNAs, and their interaction, in endocrine-related cancers: breast, prostate, endometrial and thyroid.

Developing a genetic signature to predict drug response in ovarian cancer

There is a lack of personalized treatment options for women with recurrent platinum-resistant ovarian cancer. Outside of bevacizumab and a group of poly ADP-ribose polymerase inhibitors, few options are available to women that relapse. We propose that efficacious drug combinations can be determined via molecular characterization of ovarian tumors along with pre-established pharmacogenomic profiles of repurposed compounds. To that end, we selectively performed multiple two-drug combination treatments in ovarian cancer cell lines that included reactive oxygen species inducers and HSP90 inhibitors. This allowed us to select cell lines that exhibit disparate phenotypes of proliferative inhibition to a specific drug combination of auranofin and AUY922. We profiled altered mechanistic responses from these agents in both reactive oxygen species and HSP90 pathways, as well as investigated PRKCI and lncRNA expression in ovarian cancer cell line models. Generation of dual multi-gene panels implicated in resistance or sensitivity to this drug combination was produced using RNA sequencing data and the validity of the resistant signature was examined using high-density RT-qPCR. Finally, data mining for the prevalence of these signatures in a large-scale clinical study alluded to the prevalence of resistant genes in ovarian tumor biology. Our results demonstrate that high-throughput viability screens paired with reliable in silico data can promote the discovery of effective, personalized therapeutic options for a currently untreatable disease.

CTD-2020K17.1, a Novel Long Non-Coding RNA, Promotes Migration, Invasion, and Proliferation of Serous Ovarian Cancer Cells In Vitro

Background

Ovarian cancer is the most lethal malignant tumor of the female reproductive system, and the metastasis is one of the major factors that contribute to the poor outcome of patients with OC. Accumulating evidence indicates that lncRNAs are expressed and play important regulatory roles in ovarian cancer.

Material/Methods

Aberrant lncRNAs in primary ovarian cancer tissues (POCTs) and paired omental metastasis tissues (OMTs) of patients with HGSOC were studied via lncRNA microarray. Real-time PCR was performed to examine CTD-2020K17.1 expression in HGSOC tissues from 38 patients, a normal ovarian surface epithelium cell line, and 4 ovarian cancer cell lines. Additionally, Transwell assays, wound healing assays, CCK-8 proliferation assays, and flow cytometry were used to explore the biological function of CTD-2020K17.1 in ovarian cancer cells. Finally, Western blot analysis was used to verify the potential target gene of CTD-2020K17.1.

Results

A novel lncRNA named CTD-2020K17.1 was identified via microarray analysis. Expression of CTD-2020K17.1 was significantly increased in OMTs and in 4 ovarian cancer cell lines compared with POCTs (P<0.05) or normal ovarian surface epithelial cell line (P<0.05). Moreover, CTD-2020K17.1 overexpression promoted migration, invasion, and proliferation of ovarian cancer cells, and CTD-2020K17.1 regulated the expression of CARD11.

Conclusions

CTD-2020K17.1 is significantly upregulated in OMTs and ovarian cancer cell lines. It can promote the migration, invasion, and proliferation of ovarian cancer cells, and CARD11 is regulated by CTD-2020K17.1.

Crosstalk between prognostic long noncoding RNAs and messenger RNAs as transcriptional hallmarks in gastric cancer

AIM

Our study investigated the significance of the crosstalk between long noncoding RNAs (lncRNAs) and mRNAs in gastric cancer (GC).

METHODS

lncRNA and mRNA expression profiling data in 671 GC tumors and 77 nontumorous gastric tissues were retrieved from the gene expression omnibus database: GSE54129, GSE13911, GSE19826, GSE79973, GSE15459 and GSE66229. Differentially expressed analysis, RNA coexpression network construction, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were conducted in this study.

RESULTS

Using differentially expressed and prognostic lncRNAs or mRNAs in GC, we constructed the lncRNA-mRNA coexpression networks. This network involved with vital GO and KEGG pathways.

CONCLUSION

Our study reveals coexpressed lncRNAs and mRNAs as transcriptional hallmarks in GC patients which provide interesting information regarding the incidence and outcome of GC.

Expression and clinical role of long non-coding RNA in high-grade serous carcinoma

OBJECTIVE

To profile long non-coding RNA (lncRNA) expression at the various anatomic sites of high-grades serous carcinoma (HGSC) and in effusion-derived exosomes.

METHODS

LncRNA profiling was performed on 60 HGSC specimens, including 10 ovarian tumors, 10 solid metastases and 10 malignant effusions, as well as exosomes from 30 effusion supernatants. Anatomic site-related expression of ESRG, Link-A, GAS5, MEG3, GATS, PVT1 H19, Linc-RoR, HOTAIR and MALAT1 was validated by quantitative PCR and assessed for clinical relevance in a series of 77 HGSC effusions, 40 ovarian carcinomas, 21 solid metastases and 42 supernatant exosomes.

RESULTS

Significantly different (p<0.05) expression of 241, 406 and 3634 lncRNAs was found in comparative analysis of the ovarian tumors to solid metastases, effusions and exosomes, respectively. Cut-off at two-fold change in lncRNA expression identified 54 lncRNAs present at the 3 anatomic sites and in exosomes. Validation analysis showed significantly different expression of 5 of 10 lncRNAs in the 4 specimen groups (ESRG, Link-A, MEG3, GATS and PVT1, all p<0.001). Higher ESRG levels in HGSC effusions were associated with longer overall survival in the entire effusion cohort (p=0.023) and in patients with pre-chemotherapy effusions tapped at diagnosis (p=0.048). Higher Link-A levels were associated with better overall (p=0.015) and progression-free (p=0.023) survival for patients with post-chemotherapy effusions. Link-A was an independent prognostic marker in Cox multivariate analysis in the latter group (p=0.045).

CONCLUSIONS

We present the first evidence of differential LncRNA expression as function of anatomic site in HGSC. LncRNA levels in HGSC effusions are candidate prognostic markers.

Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma

Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs (LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

Expression profiles analysis reveals an integrated miRNA-lncRNA signature to predict survival in ovarian cancer patients with wild-type BRCA1/2

Emerging evidence shows that dysregulated expression of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) were closely linked with disease progression, including cancers. However, the joint predictive power of miRNAs and lncRNAs in prognosis for ovarian cancer (OV) patients with wild-type BRCA1/2 is as yet unknown. In this study, we sought to assess the joint predictive power of miRNAs and lncRNAs by integrating miRNA and lncRNA expression profiles and clinical data of 281 OV patients with wild-type BRCA1/2 from The Cancer Genome Atlas (TCGA) project. Finally, we identified an integrated miRNA-lncRNA signature composing of two lncRNAs (LINC01234 and CCDC144NL-AS1) and two miRNAs (miR-637 and miR-129-5p) which can effectively classify OV patients with wild-type BRCA1/2 into groups with the good and poor outcome. The prognostic value of the integrated miRNA-lncRNA signature was validated in the testing cohort and entire TCGA cohort. Multivariate analysis demonstrated the independence of the integrated miRNA-lncRNA signature of known other clinical factors. Further analysis suggested that patients who were in the low-risk group based on the signature achieved a better CR from platinum-based chemotherapy compared with patients in the high-risk group. Our results indicated that this integrated miRNA-lncRNA signature may have important clinical implications for risk stratification of ovarian cancer patients with wild-type BRCA1/2.

A six-long non-coding RNAs signature as a potential prognostic marker for survival prediction of ER-positive breast cancer patients

Dysregulated expression of lncRNAs has been observed in various human complex diseases (including cancers) by recent transcriptional profiling studies, highlighting potentials of lncRNAs as biomarkers for cancer diagnosis and prognosis. Despite some efforts have been made to search for novel lncRNA signature in breast cancer, the prognostic value of lncRNAs for ER-positive breast cancer patients still needs to be systematically investigated. In this study, we analyzed lncRNA expression profiles in a large of more than 600 breast cancer patients with ER-positive status from The Cancer Genome Atlas (TCGA) and identified six lncRNAs that are significantly associated with survival. Then a linear risk score model comprising six prognostic lncRNAs, termed six-lncRNA signature, was developed to identify high-risk patients from low-risk cases. The results of Kaplan-Meier analysis and ROC curves demonstrated the good sensitivity and specificity in survival prediction both in the training and testing datasets. Multivariate Cox regression analysis and stratified analysis showed that the six-lncRNA signature is an independent prognostic marker in survival prediction for ER-positive breast cancer patients. The GO enrichment analysis suggested that the six-lncRNA might involve with known breast cancer-related biological processes. With further experimental validation, these identified prognostic lncRNAs might have clinical implications for more personalized risk assessment for ER-positive breast cancer patients.