Comprehensive Characterization of Somatic Mutations Impacting lncRNA Expression for Pan-Cancer

The pivotal role of long non-coding RNAs as potential biomarkers and modulators of chemoresistance in ovarian cancer (OC)

Ovarian cancer (OC) is a fatal gynecological disease that is often diagnosed at later stages due to its asymptomatic nature and the absence of efficient early-stage biomarkers. Previous studies have identified genes with abnormal expression in OC that couldn't be explained by methylation or mutation, indicating alternative mechanisms of gene regulation. Recent advances in human transcriptome studies have led to research on non-coding RNAs (ncRNAs) as regulators of cancer gene expression. Long non-coding RNAs (lncRNAs), a class of ncRNAs with a length greater than 200 nucleotides, have been identified as crucial regulators of physiological processes and human diseases, including cancer. Dysregulated lncRNA expression has also been found to play a crucial role in ovarian carcinogenesis, indicating their potential as novel and non-invasive biomarkers for improving OC management. However, despite the discovery of several thousand lncRNAs, only one has been approved for clinical use as a biomarker in cancer, highlighting the importance of further research in this field. In addition to their potential as biomarkers, lncRNAs have been implicated in modulating chemoresistance, a major problem in OC. Several studies have identified altered lncRNA expression upon drug treatment, further emphasizing their potential to modulate chemoresistance. In this review, we highlight the characteristics of lncRNAs, their function, and their potential to serve as tumor markers in OC. We also discuss a few databases providing detailed information on lncRNAs in various cancer types. Despite the promising potential of lncRNAs, further research is necessary to fully understand their role in cancer and develop effective strategies to combat this devastating disease.

LncRNAs: the good, the bad, and the unknown

Long non-coding RNAs (lncRNAs) are significant contributors in maintaining genomic integrity through epigenetic regulation. LncRNAs can interact with chromatin-modifying complexes in both cis and trans pathways, drawing them to specific genomic loci and influencing gene expression via DNA methylation, histone modifications, and chromatin remodeling. They can also operate as building blocks to assemble different chromatin-modifying components, facilitating their interactions and gene regulatory functions. Deregulation of these molecules has been associated with various human diseases, including cancer, cardiovascular disease, and neurological disorders. Thus, lncRNAs are implicated as potential diagnostic indicators and therapeutic targets. This review discusses the current understanding of how lncRNAs mediate epigenetic control, genomic integrity, and their putative functions in disease pathogenesis.

Getting to know ovarian cancer: Focusing on the effect of LncRNAs in this cancer and the effective signaling pathways

This article undertakes a comprehensive investigation of ovarian cancer, examining the complex nature of this challenging disease. The main focus is on understanding the role of long non-coding RNAs (lncRNAs) in the context of ovarian cancer (OC), and their regulatory functions in disease progression. Through extensive research, the article identifies specific lncRNAs that play significant roles in the intricate molecular processes of OC. Furthermore, the study examines the signaling pathways involved in the development of OC, providing a detailed comprehension of the underlying molecular mechanisms. By connecting lncRNA dynamics with signaling pathways, this exploration not only advances our understanding of ovarian cancer but also reveals potential targets for therapeutic interventions. The findings open up opportunities for targeted treatments, highlighting the importance of personalized approaches in addressing this complex disease and driving progress in ovarian cancer research and treatment strategies.

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

In this review, we provide a general overview of the current panorama of mining strategies for multi-omics data to investigate lncRNAs with an actual or potential role as biological markers in cancer. Several multi-omics studies focusing on lncRNAs have been performed in the past with varying scopes. Nevertheless, many questions remain regarding the pragmatic application of different molecular technologies and bioinformatics algorithms for mining multi-omics data. Here, we attempt to address some of the less discussed aspects of the practical applications using different study designs for incorporating bioinformatics and statistical analyses of multi-omics data. Finally, we discuss the potential improvements and new paradigms aimed at unraveling the role and utility of lncRNAs in cancer and their potential use as molecular markers for cancer diagnosis and outcome prediction.

An insight into the potential role of LINC00968 in luminal breast cancer: Case-control study and bioinformatics analysis

Background

Luminal A and B subtypes of breast cancer (BC) comprises up to 70% of all BC patients. LncRNAs can affect many biological and pathological processes, and dysregulation of them is related to human cancers. The potential role of lncRNA LINC00968 in luminal BC is still unclear.

Materials and methods

We analyzed the LINC00968 expression across 44 paired luminal BC tissues from the TCGA-BRCA RNA sequencing dataset. Besides, we used the GEPIA2 web server and GENEVESTIGATOR software, as well. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) assay was performed to confirm the LINC00968 expression in 71 paired luminal BC tissues and two luminal A cell lines (MCF7 and T47D). Moreover, to better understanding the potential role of LINC00968 in luminal BC, computational data analyses including co-expression analysis, functional annotation analysis, and genetic alteration analysis have been done.

Results

The results of data analyses retrieved from BRCA dataset and databases revealed the significant downregulation of LINC00968 in luminal A and B BC. Also, the results of qRT-PCR in luminal BC tissues and cell lines confirmed the earlier data. LINC00968 expression was negatively associated with tumor stage and lymph node metastasis. Additionally, functional annotation analyses revealed that LINC00968 might be involved in vascular development and angiogenesis, extracellular matrix organization, and cell motility and migration. LINC00968 might play role in some cancer-related signaling pathways.

Conclusion

Our study found that downregulation of LINC00968 might promote tumorigenesis, invasion, and metastasis of luminal BC.

Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges

The relevant study of transcriptome-wide variations and neurological disorders in the evolved field of genomic data science is on the rise. Deep learning has been highlighted utilizing algorithms on massive amounts of data in a human-like manner, and is expected to predict the dependency or druggability of hidden mutations within the genome. Enormous mutational variants in coding and noncoding transcripts have been discovered along the genome by far, despite of the fine-tuned genetic proofreading machinery. These variants could be capable of inducing various pathological conditions, including neurological disorders, which require lifelong care. Several limitations and questions emerge, including the use of conventional processes via limited patient-driven sequence acquisitions and decoding-based inferences as well as how rare variants can be deduced as a population-specific etiology. These puzzles require harnessing of advanced systems for precise disease prediction, drug development and drug applications. In this review, we summarize the pathophysiological discoveries of pathogenic variants in both coding and noncoding transcripts in neurological disorders, and the current advantage of deep learning applications. In addition, we discuss the challenges encountered and how to outperform them with advancing interpretation.

Emerging role of oncogenic long noncoding RNA as cancer biomarkers

The view of long noncoding RNAs as nonfunctional "garbage" has been definitely outdated by the large body of evidence indicating this class of ncRNAs as "golden junk", especially in precision oncology. Indeed, in light of their oncogenic role and the higher expression in multiple cancer types compared with paired adjacent tissues, the clinical interest for lncRNAs as diagnostic and/or prognostic biomarkers has been rapidly increasing. The emergence of large-scale sequencing technologies, their subsequent diffusion even in small research and clinical centers, the technological advances for the detection of low-copy lncRNAs in body fluids, coupled to the huge reduction of operating costs, have nowadays made possible to rapidly and comprehensively profile them in multiple tumors and large cohorts. In this review, we first summarize some relevant data about the oncogenic role of well-studied lncRNAs having a clinical relevance. Then, we focus on the description of their potential use as diagnostic/prognostic biomarkers, including an updated overview about licensed patents or clinical trials on lncRNAs in oncology.

Long non-coding RNA SLC25A21-AS1 inhibits the development of epithelial ovarian cancer by specifically inducing PTBP3 degradation

BACKGROUND

Epithelial ovarian cancer (EOC) is a highly prevalent disease that rapidly metastasizes and has poor prognosis. Most women are in the middle or late stages when diagnosed and have low survival rates. Recently, long non-coding RNAs (lncRNAs) were recognized to play pivotal roles in the development of EOC.

METHODS

The expression of SLC25A21 antisense RNA 1 (SLC25A21-AS1) and Polypyrimidine Tract Binding Protein 3 (PTBP3) in EOC cells was assessed via qPCR. The proliferation activity of these cells was detected by EdU and Cell counting kit-8 (CCK8) assays, while the death rate of apoptotic cells and the cell cycle were detected by flow cytometry. Detection of cell transfer rate by transwell assay. Protein expression was measured through western blotting. Interactions between SLC25A21-AS1 and PTBP3 were detected through RNA immunoprecipitation (RIP), IF-FISH co-localization experiments and electrophoretic mobility shift assay (EMSA). The in vivo importance of SLC25A21-AS1 as a tumor suppressor modulator was assessed using murine xenograft models.

RESULTS

The lncRNA SLC25A21-AS1 has negligible expression in ovarian cancer tissues compared with that in normal ovarian tissues. A series of functional experiments revealed that the upregulation of SLC25A21-AS1 markedly blocked the proliferation and metastasis of EOC cells in vitro, while its downregulation had the opposite effect. Overexpression of SLC25A21-AS1 in a nude mouse model of EOC in vivo resulted in slower tumor growth and weakened metastatic potential. Moreover, SLC25A21-AS1 reduced the protein stability of PTBP3 and promoted its degradation. A series of subsequent experiments found that SLC25A21-AS1 inhibits EOC cell proliferation and metastasis by modulating PTBP3 through the ubiquitin-proteasome pathway and that the combination of SLC25A21-AS1 and PTBP3 provides the necessary conditions for the for the function to be realized.

CONCLUSIONS

Our research reveals the effect of SLC25A21-AS1 in EOC development and suggests SLC25A21-AS1 can serve as a prognostic target by promoting the degradation of PTBP3 to improve patient survival.

A novel method to identify and characterize personalized functional driver lncRNAs in cancer samples

Cancer is a highly heterogeneous disease, and different individuals of the same cancer type can display different therapeutic effects and prognosis. Genetic variation of long non-coding RNA is the key factor driving tumor development, and plays an important role in genetic and biological heterogeneity. Therefore, it is of great significance to identify lncRNA as a driving factor in the non-coding region and explain its function in tumors for revealing the pathogenesis of cancer. In this study, we developed an integrated method to identify Personalized Functional Driver lncRNAs (PFD-lncRNAs) by integrating the DNA copy number data, gene expression data, and the biological subpathways information. Then, we applied the method to identify 2695 PFD-lncRNAs in 5334 samples across 19 cancer types. We performed an analysis of the association between PFD-lncRNAs and drug sensitivity, which provides medication guidance in disease therapy and drug discovery in the individual. Our research is of great significance for elucidating the biological roles of lncRNA genetic variation in cancer, revealing the related mechanism of cancer, and providing novel insights for individualized medicine.

Influence of Long Non-Coding RNA in the Regulation of Cancer Stem Cell Signaling Pathways

Over the past two decades, cancer stem cells (CSCs) have emerged as an immensely studied and experimental topic, however a wide range of questions concerning the topic still remain unanswered; in particular, the mechanisms underlying the regulation of tumor stem cells and their characteristics. Understanding the cancer stem-cell signaling pathways may pave the way towards a better comprehension of these mechanisms. Signaling pathways such as WNT, STAT, Hedgehog, NOTCH, PI3K/AKT/mTOR, TGF-β, and NF-κB are responsible not only for modulating various features of CSCs but also their microenvironments. Recently, the prominent roles of various non-coding RNAs such as small non-coding RNAs (sncRNAs) and long non-coding RNAs (lncRNAs) in developing and enhancing the tumor phenotypes have been unfolded. This review attempts to shed light on understanding the influence of long non- coding RNAs in the modulation of various CSC-signaling pathways and its impact on the CSCs and tumor properties; highlighting the protagonistic and antagonistic roles of lncRNAs.

Role of different non-coding RNAs as ovarian cancer biomarkers

Background

Among many gynecological malignancies ovarian cancer is the most prominent and leading cause of female mortality worldwide. Despite extensive research, the underlying cause of disease progression and pathology is still unknown. In the progression of ovarian cancer different non-coding RNAs have been recognized as important regulators. The biology of ovarian cancer which includes cancer initiation, progression, and dissemination is found to be regulated by different ncRNA. Clinically ncRNA shows high prognostic and diagnostic importance.

Results

In this review, we prioritize the role of different non-coding RNA and their perspective in diagnosis as potential biomarkers in the case of ovarian cancer. Summary of some of the few miRNAs involved in epithelial ovarian cancer their expression and clinical features are being provided in the table. Also, in cancer cell proliferation, apoptosis, invasion, and migration abnormal expression of piRNAs are emerging as a crucial regulator hence the role of few piRNAs is being given. Both tRFs and tiRNAs play important roles in tumorigenesis and are promising diagnostic biomarkers and therapeutic targets for cancer. lncRNA has shown a leading role in malignant transformation and potential therapeutic value in ovarian cancer therapy.

Conclusions

Hence in this review we demonstrated the role of different ncRNA that play an important role in serving strong potential as a therapeutic approach for the treatment of ovarian cancer.

Designing libraries for pooled CRISPR functional screens of long noncoding RNAs

Human and other genomes encode tens of thousands of long noncoding RNAs (lncRNAs), the vast majority of which remain uncharacterised. High-throughput functional screening methods, notably those based on pooled CRISPR-Cas perturbations, promise to unlock the biological significance and biomedical potential of lncRNAs. Such screens are based on libraries of single guide RNAs (sgRNAs) whose design is critical for success. Few off-the-shelf libraries are presently available, and lncRNAs tend to have cell-type-specific expression profiles, meaning that library design remains in the hands of researchers. Here we introduce the topic of pooled CRISPR screens for lncRNAs and guide readers through the three key steps of library design: accurate annotation of transcript structures, curation of optimal candidate sets, and design of sgRNAs. This review is a starting point and reference for researchers seeking to design custom CRISPR screening libraries for lncRNAs.

Pan-cancer analysis of the DNA methylation patterns of long non-coding RNA

Long non-coding RNA (lncRNA) regulated by abnormal DNA methylation (ADM-lncRNA) emerges as a biomarker for cancer diagnosis and treatment. This study comprehensively described the methylation patterns of lncRNA in pan-cancer using the cancer data set in The Cancer Genome Atlas (TCGA). Based on the cancer heterogeneity of ADM-lncRNA in pan-cancer, we constructed a co-expression network of pan-cancer ADM-lncRNA (pADM-lncRNA) in 10 cancers, highlighting the combined action mode of abnormal DNA methylation, and indicating the internal connection among different cancers. Functional analysis revealed the pan-carcinogenic pathway of pADM-lncRNA and suggested potential factors for cancer heterogeneity and tumor immune microenvironment changes. Survival analysis showed the potential of pADM-lncRNA-mRNA co-expression pair as cancer biomarkers. Revealing the action mode of lncRNA and DNA methylation in cancer may help understand the key molecular mechanisms of cell carcinogenesis.

Identification of a Genome Instability-Associated LncRNA Signature for Prognosis Prediction in Colon Cancer

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.

Identification of immune-associated lncRNAs as a prognostic marker for lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) accounts for the largest proportion of lung cancer patients and has the highest morbidity and mortality worldwide. Accumulating evidence shows that immune-associated long non-coding RNAs (lncRNAs) play a role in LUAD, although their predictive value for immunotherapy treatment and cancer-related death remains poorly investigated.

Methods

Gene expression profiles and clinical data were obtained from The Cancer Genome Atlas. We constructed a risk model by univariate and multivariate Cox regression and least absolute shrinkage and selection operator regression analysis and subsequently divided each sample into low- or high-risk category. Survival and receiver operating characteristic (ROC) analyses were applied to assess the prognostic value of the model. Additionally, immune and somatic mutation status were analysed between the two risk groups. Finally, the model was applied to pancreatic ductal adenocarcinoma (PDAC) samples to explore the applicability of the model in other cancers.

Results

We obtained data from 499 LUAD patients and randomised the samples into a training set (N=351) and validation set (N=148) at a 7:3 ratio. We detected 7 immune-associated lncRNAs (AP000695.2, AC026355.2, LINC01843, ITGB1-DT, LINC01150, AL590226.1 and AC091185.1) that were applicable for establishing a risk signature. Survival analysis revealed that patients categorised in the high-risk group had shorter overall survival (OS) than those in the low-risk group. ROC analyses showed excellent AUC values in all data sets (>0.65 at 1, 3, and 5 years). Notably, ESTIMATE algorithm and analysis of PCA, (ss)GSEA, and somatic mutations revealed that the high-risk group had a stronger immunosuppressive status and a higher tumour mutation burden (TMB). Moreover, patients in the low-risk group responded better to immunotherapy due to higher levels of immune-checkpoint receptor genes and TLS-related genes. Our model using the 7 immune-associated lncRNAs showed similar applicability for PDAC patients.

Conclusions

We constructed a model for risk signatures based on 7 immune-associated lncRNAs and showed its prognostic value for identifying immune and somatic mutation characteristics in LUAD patients, which may assist clinical treatment plans and elucidate molecular mechanisms of LUAD immunity.

LincSNP 3.0: an updated database for linking functional variants to human long non-coding RNAs, circular RNAs and their regulatory elements

We describe an updated comprehensive database, LincSNP 3.0 (http://bioinfo.hrbmu.edu.cn/LincSNP), which aims to document and annotate disease or phenotype-associated variants in human long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) or their regulatory elements. LincSNP 3.0 has updated with several novel features, including (i) more types of variants including single nucleotide polymorphisms (SNPs), linkage disequilibrium SNPs (LD SNPs), somatic mutations and RNA editing sites have been expanded; (ii) more regulatory elements including transcription factor binding sites (TFBSs), enhancers, DNase I hypersensitive sites (DHSs), topologically associated domains (TADs), footprintss, methylations and open chromatin regions have been added; (iii) the associations among circRNAs, regulatory elements and variants have been identified; (iv) more experimentally supported variant-lncRNA/circRNA-disease/phenotype associations have been manually collected; (v) the sources of lncRNAs, circRNAs, SNPs, somatic mutations and RNA editing sites have been updated. Moreover, four flexible online tools including Genome Browser, Variant Mapper, Circos Plotter and Functional Annotation have been developed to retrieve, visualize and analyze the data. Collectively, LincSNP 3.0 provides associations among functional variants, regulatory elements, lncRNAs and circRNAs in diseases. It will serve as an important and continually updated resource for investigating functions and mechanisms of lncRNAs and circRNAs in diseases.

The Role of cis- and trans-Acting RNA Regulatory Elements in Leukemia

RNA molecules are a source of phenotypic diversity and an operating system that connects multiple genetic and metabolic processes in the cell. A dysregulated RNA network is a common feature of cancer. Aberrant expression of long non-coding RNA (lncRNA), micro RNA (miRNA), and circular RNA (circRNA) in tumors compared to their normal counterparts, as well as the recurrent mutations in functional regulatory cis-acting RNA motifs have emerged as biomarkers of disease development and progression, opening avenues for the design of novel therapeutic approaches. This review looks at the progress, challenges and future prospects of targeting cis-acting and trans-acting RNA elements for leukemia diagnosis and treatment.

Identification of two molecular subtypes of dysregulated immune lncRNAs in ovarian cancer

Long non-coding RNA (lncRNA) has increasingly been identified as a key regulator in pathologies such as cancer. Multiple platforms were used for comprehensive analysis of ovarian cancer to identify molecular subgroups. However, lncRNA and its role in mapping the ovarian cancer subpopulation are still largely unknown. RNA-sequencing and clinical characteristics of ovarian cancer were acquired from The Cancer Genome Atlas database (TCGA). A total of 52 lncRNAs were identified as aberrant immune lncRNAs specific to ovarian cancer. We redefined two different molecular subtypes, C1(188) and C2(184 samples), in "iClusterPlus" R package, among which C2 grouped ovarian cancer samples have higher survival probability and longer median survival time (P <0.05) with activated IFN-gamma response, Wound Healing and Cytotoxic lymphocytes signal; 456 differentially expressed genes were acquired in C1 and C2 subtypes using limma (3.40.6) package, among which 419 were up-regulated and 37 were down-regulated, in TCGA dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis revealed that these genes were actively involved in ECM-receptor interaction, PI3K-Akt signaling pathway interaction KEGG pathway. Compared with the existing immune subtype, the Cluster2 sample showed a substantial increase in the proportion of the existing C2 immune subtype, accounting for 81.37%, which was associated with good prognosis. Our C1 subtype contains only 56.49% of the existing immune C1 and C4, which also explains the poor prognosis of C1. Furthermore, 52 immune-related lncRNAs were used to divide the TCGA-endometrial cancer and cervical cancer samples into two categories, and C2 had a good prognosis. The differentially expressed genes were highly correlated with immune-cell-related pathways. Based on lncRNA, two molecular subtypes of ovarian cancer were identified and had significant prognostic differences and immunological characteristics.

Frequent Germline and Somatic Single Nucleotide Variants in the Promoter Region of the Ribosomal RNA Gene in Japanese Lung Adenocarcinoma Patients

Ribosomal RNA (rRNA), the most abundant non-coding RNA species, is a major component of the ribosome. Impaired ribosome biogenesis causes the dysfunction of protein synthesis and diseases called “ribosomopathies,” including genetic disorders with cancer risk. However, the potential role of rRNA gene (rDNA) alterations in cancer is unknown. We investigated germline and somatic single-nucleotide variants (SNVs) in the rDNA promoter region (positions −248 to +100, relative to the transcription start site) in 82 lung adenocarcinomas (LUAC). Twenty-nine tumors (35.4%) carried germline SNVs, and eight tumors (9.8%) harbored somatic SNVs. Interestingly, the presence of germline SNVs between positions +1 and +100 (n = 12; 14.6%) was associated with significantly shorter recurrence-free survival (RFS) and overall survival (OS) by univariate analysis (p < 0.05, respectively), and was an independent prognostic factor for RFS and OS by multivariate analysis. LUAC cell line PC9, carrying rDNA promoter SNV at position +49, showed significantly higher ribosome biogenesis than H1650 cells without SNV. Upon nucleolar stress induced by actinomycin D, PC9 retained significantly higher ribosome biogenesis than H1650. These results highlight the possible functional role of SNVs at specific sites of the rDNA promoter region in ribosome biogenesis, the progression of LUAC, and their potential prognostic value.

Long non-coding RNAs in ovarian cancer: expression profile and functional spectrum

Long non-coding RNAs (lncRNAs), initially recognized as byproducts of the transcription process, have been proven to play crucial modulatory roles in preserving overall homoeostasis of cells and tissues. Furthermore, aberrant levels of these transcripts have been shown to contribute many diseases, including cancer. Among these, many aspects of ovarian cancer biology have been found to be regulated by lncRNAs, including cancer initiation, progression and dissemination. In this review, we summarize recent studies to highlight the various roles of lncRNAs in ovary in normal and pathological conditions, immune system, diagnosis, prognosis, and therapy. We address lncRNAs that have been extensively studied in ovarian cancer and their contribution to cellular dynamics.

LncRNAs in Cancer: From garbage to Junk

Sequencing-based transcriptomics has significantly redefined the concept of genome complexity, leading to the identification of thousands of lncRNA genes identification of thousands of lncRNA genes whose products possess transcriptional and/or post-transcriptional regulatory functions that help to shape cell functionality and fate. Indeed, it is well-established now that lncRNAs play a key role in the regulation of gene expression through epigenetic and posttranscriptional mechanims. The rapid increase of studies reporting lncRNAs alteration in cancers has also highlighted their relevance for tumorigenesis. Herein we describe the most prominent examples of well-established lncRNAs having oncogenic and/or tumor suppressive activity. We also discuss how technical advances have provided new therapeutic strategies based on their targeting, and also report the challenges towards their use in the clinical settings.

Upregulated expression of LncRNA nicotinamide nucleotide transhydrogenase antisense RNA 1 is correlated with unfavorable clinical outcomes in cancers

Background

The nicotinamide nucleotide transhydrogenase antisense RNA 1 (NNT-AS1) is a long non-coding RNA aberrantly expressed in human malignancies. We aimed to analyze available data to evaluate the correlation between NNT-AS1 expression and cancer prognosis.

Methods

Literature retrieval was performed by systematic searching related databases from inception to April 2, 2020. Studies regarding correlation between NNT-AS1 expression, survival outcomes and clinical characteristics of cancer patients were collected and pooled to calculate the the hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (95% CIs).

Results

Ten studies comprising 699 patients were included, all of which were conducted in China according to literature selection criteria. Overexpression of NNT-AS1 had a significant association with unfavorable overall survival (OS) (HR = 2.08, 95% CI: 1.84–2.36, P < 0.001). Stratified analysis showed that tumor type, sample size, follow-up months, and survival analysis approach did not change the predictive value of NNT-AS1 on OS. Furthermore, elevated NNT-AS1 level had significant association with distant metastasis (DM) (OR = 2.45, 95% CI: 1.39–4.30), lymph node metastasis (LNM) (OR = 3.92, 95% CI: 1.35–11.41), TNM stage (OR = 4.25, 95% CI: 1.71–10.56), and vascular invasion (OR = 3.98, 95% CI: 2.06–7.71), but was not associated with age and gender. The TCGA dataset further consistently showed that the NNT-AS1 expression was associated with poor OS and disease-free survival.

Conclusions

High expression of NNT-AS1 is associated with unfavorable survival outcomes and poor clinicopathologic characteristics. However, large-cohort data and geographical studies are still needed to further validate the prognostic value of NNT-AS1 in cancers.

Back to the Future: Rethinking the Great Potential of lncRNAS for Optimizing Chemotherapeutic Response in Ovarian Cancer

Ovarian cancer (OC) is one of the most fatal cancers in women worldwide. Currently, platinum- and taxane-based chemotherapy is the mainstay for the treatment of OC. Yet, the emergence of chemoresistance results in therapeutic failure and significant relapse despite a consistent rate of primary response. Emerging evidence substantiates the potential role of lncRNAs in determining the response to standard chemotherapy in OC. The objective of this narrative review is to provide an integrated, synthesized overview of the current state of knowledge regarding the role of lncRNAs in the emergence of resistance to platinum- and taxane-based chemotherapy in OC. In addition, we sought to develop conceptual frameworks for harnessing the therapeutic potential of lncRNAs in strategies aimed at enhancing the chemotherapy response of OC. Furthermore, we offered significant new perspectives and insights on the interplay between lncRNAs and the molecular circuitries implicated in chemoresistance to determine their impacts on therapeutic response. Although this review summarizes robust data concerning the involvement of lncRNAs in the emergence of acquired resistance to platinum- and taxane-based chemotherapy in OC, effective approaches for translating these lncRNAs into clinical practice warrant further investigation.

Construction of immune-related and prognostic lncRNA clusters and identification of their immune and genomic alterations characteristics in lung adenocarcinoma samples

Long non-coding RNAs (lncRNAs) play an important role in various biological processes of lung adenocarcinoma (LUAD), such as immune response regulation, tumor microenvironment remodeling and genomic alteration. Nevertheless, immune-related lncRNAs and their immune and genomic alterations characteristics in LUAD samples still remain unreported. Here, using various public databases, statistic and software tools, we constructed two immune-related lncRNA clusters with different immune and genomic alterations characteristics. Notably, cluster 1 had a stronger immunosuppressive tumor microenvironment (TME) and a higher mutation frequency than cluster 2, especially the mutant genes, such as Kelch-like ECH-associated protein 1 (KEAP1) and toll like receptor 4 (TLR4). In cluster 1, both the amplified and deleted portions of copy number variation (CNV) segments were enriched and cyclin dependent kinase inhibitor 2A (CDKN2A) was significantly deleted. GSVA analysis revealed that these immune-related lncRNAs may be involved in stem cell and EMT functions. Furthermore, cluster 1 was related to worse prognosis of LUAD patients. Therefore, we constructed two immune-related and prognostic lncRNA clusters and identified their immune and genomic alterations characteristics in LUAD samples, which could well divide LUAD patients into different immune phenotypes and help to understand immune molecular mechanisms of LUAD.