LncSpA: LncRNA Spatial Atlas of Expression across Normal and Cancer Tissues

Innovative therapeutic strategies to overcome radioresistance in breast cancer

Despite a comparatively favorable prognosis relative to other malignancies, breast cancer continues to significantly impact women's health globally, partly due to its high incidence rate. A critical factor in treatment failure is radiation resistance - the capacity of tumor cells to withstand high doses of ionizing radiation. Advancements in understanding the cellular and molecular mechanisms underlying radioresistance, coupled with enhanced characterization of radioresistant cell clones, are paving the way for the development of novel treatment modalities that hold potential for future clinical application. In the context of combating radioresistance in breast cancer, potential targets of interest include long non-coding RNAs (lncRNAs), micro RNAs (miRNAs), and their associated signaling pathways, along with other signal transduction routes amenable to pharmacological intervention. Furthermore, technical, and methodological innovations, such as the integration of hyperthermia or nanoparticles with radiotherapy, have the potential to enhance treatment responses in patients with radioresistant breast cancer. This review endeavors to provide a comprehensive survey of the current scientific landscape, focusing on novel therapeutic advancements specifically addressing radioresistant breast cancer.

Widespread transcriptomic alterations of transient receptor potential channel genes in cancer

Ion channels, in particular transient-receptor potential (TRP) channels, are essential genes that play important roles in many physiological processes. Emerging evidence has demonstrated that TRP genes are involved in a number of diseases, including various cancer types. However, we still lack knowledge about the expression alterations landscape of TRP genes across cancer types. In this review, we comprehensively reviewed and summarised the transcriptomes from more than 10 000 samples in 33 cancer types. We found that TRP genes were widespreadly transcriptomic dysregulated in cancer, which was associated with clinical survival of cancer patients. Perturbations of TRP genes were associated with a number of cancer pathways across cancer types. Moreover, we reviewed the functions of TRP family gene alterations in a number of diseases reported in recent studies. Taken together, our study comprehensively reviewed TRP genes with extensive transcriptomic alterations and their functions will directly contribute to cancer therapy and precision medicine.

Preferential formation of Z-RNA over intercalated motifs in long noncoding RNA

Secondary structure is a principal determinant of lncRNA function, predominantly regarding scaffold formation and interfaces with target molecules. Noncanonical secondary structures that form in nucleic acids have known roles in regulating gene expression and include G-quadruplexes (G4s), intercalated motifs (iMs), and R-loops (RLs). In this paper, we used the computational tools G4-iM Grinder and QmRLFS-finder to predict the formation of each of these structures throughout the lncRNA transcriptome in comparison to protein-coding transcripts. The importance of the predicted structures in lncRNAs in biological contexts was assessed by combining our results with publicly available lncRNA tissue expression data followed by pathway analysis. The formation of predicted G4 (pG4) and iM (piM) structures in select lncRNA sequences was confirmed in vitro using biophysical experiments under near-physiological conditions. We find that the majority of the tested pG4s form highly stable G4 structures, and identify many previously unreported G4s in biologically important lncRNAs. In contrast, none of the piM sequences are able to form iM structures, consistent with the idea that RNA is unable to form stable iMs. Unexpectedly, these C-rich sequences instead form Z-RNA structures, which have not been previously observed in regions containing cytosine repeats and represent an interesting and underexplored target for protein-RNA interactions. Our results highlight the prevalence and potential structure-associated functions of noncanonical secondary structures in lncRNAs, and show G4 and Z-RNA structure formation in many lncRNA sequences for the first time, furthering the understanding of the structure-function relationship in lncRNAs.

LncRNA SOX9-AS1 triggers a transcriptional program involved in lipid metabolic reprogramming, cell migration and invasion in triple-negative breast cancer

At the molecular level, triple-negative breast cancer (TNBC) is frequently categorized as PAM50 basal-like subtype, but despite the advances in molecular analyses, the clinical outcome for these subtypes is uncertain. Long non-coding RNAs (lncRNAs) are master regulators of genes involved in hallmarks of cancer, which makes them suitable biomarkers for breast cancer (BRCA) diagnosis and prognosis. Here, we evaluated the regulatory role of lncRNA SOX9-AS1 in these subtypes. Using the BRCA-TCGA cohort, we observed that SOX9-AS1 was significantly overexpressed in basal-like and TNBC in comparison with other BRCA subtypes. Survival analyzes showed that SOX9-AS1 overexpression was associated with a favorable prognosis in TNBC and basal-like patients. To study the functions of SOX9-AS1, we determined the expression levels in a panel of nine BRCA cell lines finding increased levels in MDA-MB-468 and HCC1187 TNBC. Using subcellular fractionation in these cell lines, we ascertained that SOX9-AS1 was located in the cytoplasmic compartment. In addition, we performed SOX9-AS1 gene silencing using two short-harping constructs, which were transfected in both cell models and performed a genome-wide RNA-seq analysis. Data showed that 351 lncRNAs and 740 mRNAs were differentially expressed in MDA-MB-468 while 56 lncRNAs and 100 mRNAs were modulated in HCC1187 cells (Log2FC < - 1.5 and > 1.5, p.adj value < 0.05). Pathway analysis revealed that the protein-encoding genes potentially regulate lipid metabolic reprogramming, and epithelial-mesenchymal transition (EMT). Expression of lipid metabolic-related genes LIPE, REEP6, GABRE, FBP1, SCD1, UGT2B11, APOC1 was confirmed by RT-qPCR. Functional analysis demonstrated that the knockdown of SOX9-AS1 increases the triglyceride synthesis, cell migration and invasion in both two TNBC cell lines. In conclusion, high SOX9-AS1 expression predicts an improved clinical course in patients, while the loss of SOX9-AS1 expression enhances the aggressiveness of TNBC cells.

CancerProteome: a resource to functionally decipher the proteome landscape in cancer

Advancements in mass spectrometry (MS)-based proteomics have greatly facilitated the large-scale quantification of proteins and microproteins, thereby revealing altered signalling pathways across many different cancer types. However, specialized and comprehensive resources are lacking for cancer proteomics. Here, we describe CancerProteome (http://bio-bigdata.hrbmu.edu.cn/CancerProteome), which functionally deciphers and visualizes the proteome landscape in cancer. We manually curated and re-analyzed publicly available MS-based quantification and post-translational modification (PTM) proteomes, including 7406 samples from 21 different cancer types, and also examined protein abundances and PTM levels in 31 120 proteins and 4111 microproteins. Six major analytical modules were developed with a view to describe protein contributions to carcinogenesis using proteome analysis, including conventional analyses of quantitative and the PTM proteome, functional enrichment, protein-protein associations by integrating known interactions with co-expression signatures, drug sensitivity and clinical relevance analyses. Moreover, protein abundances, which correlated with corresponding transcript or PTM levels, were evaluated. CancerProteome is convenient as it allows users to access specific proteins/microproteins of interest using quick searches or query options to generate multiple visualization results. In summary, CancerProteome is an important resource, which functionally deciphers the cancer proteome landscape and provides a novel insight for the identification of tumor protein markers in cancer.

LncSEA 2.0: an updated platform for long non-coding RNA related sets and enrichment analysis

Long non-coding RNAs (lncRNAs) possess a wide range of biological functions, and research has demonstrated their significance in regulating major biological processes such as development, differentiation, and immune response. The accelerating accumulation of lncRNA research has greatly expanded our understanding of lncRNA functions. Here, we introduce LncSEA 2.0 (http://bio.liclab.net/LncSEA/index.php), aiming to provide a more comprehensive set of functional lncRNAs and enhanced enrichment analysis capabilities. Compared with LncSEA 1.0, we have made the following improvements: (i) We updated the lncRNA sets for 11 categories and extremely expanded the lncRNA scopes for each set. (ii) We newly introduced 15 functional lncRNA categories from multiple resources. This update not only included a significant amount of downstream regulatory data for lncRNAs, but also covered numerous epigenetic regulatory data sets, including lncRNA-related transcription co-factor binding, chromatin regulator binding, and chromatin interaction data. (iii) We incorporated two new lncRNA set enrichment analysis functions based on GSEA and GSVA. (iv) We adopted the snakemake analysis pipeline to track data processing and analysis. In summary, LncSEA 2.0 offers a more comprehensive collection of lncRNA sets and a greater variety of enrichment analysis modules, assisting researchers in a more comprehensive study of the functional mechanisms of lncRNAs.

Systematical analyses of large-scale transcriptome reveal viral infection-related genes and disease comorbidities

Perturbation of transcriptome in viral infection patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent transcriptome and identification of robust biomarkers is not complete. In this study, we manually collected 23 datasets related to 6,197 blood transcriptomes across 16 types of respiratory virus infections. We applied a comprehensive systems biology approach starting with whole-blood transcriptomes combined with multilevel bioinformatics analyses to characterize the expression, functional pathways, and protein-protein interaction (PPI) networks to identify robust biomarkers and disease comorbidities. Robust gene markers of infection with different viruses were identified, which can accurately classify the normal and infected patients in train and validation cohorts. The biological processes (BP) of different viruses showed great similarity and enriched in infection and immune response pathways. Network-based analyses revealed that a variety of viral infections were associated with nervous system diseases, neoplasms and metabolic diseases, and significantly correlated with brain tissues. In summary, our manually collected transcriptomes and comprehensive analyses reveal key molecular markers and disease comorbidities in the process of viral infection, which could provide a valuable theoretical basis for the prevention of subsequent public health events for respiratory virus infections.

Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Long noncoding RNAs (lncRNA) play an important role in gene regulation and contribute to tumorigenesis. While pan-cancer studies of lncRNA expression have been performed for adult malignancies, the lncRNA landscape across pediatric cancers remains largely uncharted. Here, we curated RNA sequencing data for 1,044 pediatric leukemia and extracranial solid tumors and integrated paired tumor whole genome sequencing and epigenetic data in relevant cell line models to explore lncRNA expression, regulation, and association with cancer. A total of 2,657 lncRNAs were robustly expressed across six pediatric cancers, including 1,142 exhibiting histotype-elevated expression. DNA copy number alterations contributed to lncRNA dysregulation at a proportion comparable to protein coding genes. Application of a multidimensional framework to identify and prioritize lncRNAs impacting gene networks revealed that lncRNAs dysregulated in pediatric cancer are associated with proliferation, metabolism, and DNA damage hallmarks. Analysis of upstream regulation via cell type-specific transcription factors further implicated distinct histotype-elevated and developmental lncRNAs. Integration of these analyses prioritized lncRNAs for experimental validation, and silencing of TBX2-AS1, the top-prioritized neuroblastoma-specific lncRNA, resulted in significant growth inhibition of neuroblastoma cells, confirming the computational predictions. Taken together, these data provide a comprehensive characterization of lncRNA regulation and function in pediatric cancers and pave the way for future mechanistic studies.

SIGNIFICANCE

Comprehensive characterization of lncRNAs in pediatric cancer leads to the identification of highly expressed lncRNAs across childhood cancers, annotation of lncRNAs showing histotype-specific elevated expression, and prediction of lncRNA gene regulatory networks.

Downregulated liver-elevated long intergenic noncoding RNA (LINC02428) is a tumor suppressor that blocks KDM5B/IGF2BP1 positive feedback loop in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses worldwide. Many studies have reported that long noncoding RNAs (lncRNAs) are related to the progression and prognosis of HCC. However, the functions of downregulated liver-elevated (LE) lncRNAs in HCC remain elusive. Here we report the roles and mechanisms of downregulated LE LINC02428 in HCC. Downregulated LE lncRNAs played significant roles in HCC genesis and development. LINC02428 was upregulated in liver tissues compared with other normal tissues and showed low expression in HCC. The low expression of LINC02428 was attributed to poor HCC prognosis. Overexpressed LINC02428 suppressed the proliferation and metastasis of HCC in vitro and in vivo. LINC02428 was predominantly located in the cytoplasm and bound to insulin-like growth factor-2 mRNA-binding protein 1 (IGF2BP1) to prevent it from binding to lysine demethylase 5B (KDM5B) mRNA, which decreased the stability of KDM5B mRNA. KDM5B was found to preferentially bind to the promoter region of IGF2BP1 to upregulate its transcription. Therefore, LINC02428 interrupts the KDM5B/IGF2BP1 positive feedback loops to inhibit HCC progression. The KDM5B/IGF2BP1 positive feedback loop is involved in tumorigenesis and progression of HCC.

Comprehensive analysis of the RNA transcriptome expression profiles and construction of the ceRNA network in heart failure patients with sacubitril/valsartan therapeutic heterogeneity after acute myocardial infarction

Sacubitril/valsartan has a noteworthy advantage in improving ventricular remodelling, as well as reducing cardiovascular mortality and the rate of heart failure (HF) readmission. However, clinically, some patients with HF still have low sensitivity to sacubitril/valsartan, indicating sacubitril/valsartan resistance (SVR). A total of 46 patients with HF after AMI (23 SVR and 23 non-sacubitril/valsartan resistance (NSVR)) were selected. Five SVR and 5 matched NSVR samples were screened for differentially expressed ncRNAs along with mRNAs. A total of 124 differentially expressed miRNAs, 137 circRNAs, 237 lncRNAs and 50 mRNAs were screened by RNA sequencing technology. After quantitative real-time PCR (qRT‒PCR) verification of selected biomarkers in 18 pairs of samples, we found that for patients with SVR, hsa-miR-543, hsa-miR-642b-5p, hsa-miR-760, hsa_circ_0137499, ENST00000474394, ENST00000528337, E2F1, NEAT1, and YTHDF2 were upregulated, and hsa-miR-424-5p, hsa-miR-21-3p, hsa_circRNA_0003275, hsa_circRNA_0004494, hsa_circ_0093522, ENST00000467951, ENST00000558177, ACTA2, ANPEP, and CAMP were downregulated. Then, with the help of our constructed ceRNA network and functional annotation enrichment, we speculated that inflammatory pathways (such as the apelin signalling pathway) and lipid metabolism pathways (such as fatty acid metabolism) may be involved in the regulation of SVR. These discoveries lay a foundation for further mechanistic research and provide a direction for individualized drug administration.

Spatial RNA sequencing methods show high resolution of single cell in cancer metastasis and the formation of tumor microenvironment

Cancer metastasis often leads to death and therapeutic resistance. This process involves the participation of a variety of cell components, especially cellular and intercellular communications in the tumor microenvironment (TME). Using genetic sequencing technology to comprehensively characterize the tumor and TME is therefore key to understanding metastasis and therapeutic resistance. The use of spatial transcriptome sequencing enables the localization of gene expressions and cell activities in tissue sections. By examining the localization change as well as gene expression of these cells, it is possible to characterize the progress of tumor metastasis and TME formation. With improvements of this technology, spatial transcriptome sequencing technology has been extended from local regions to whole tissues, and from single sequencing technology to multimodal analysis combined with a variety of datasets. This has enabled the detection of every single cell in tissue slides, with high resolution, to provide more accurate predictive information for tumor treatments. In this review, we summarize the results of recent studies dealing with new multimodal methods and spatial transcriptome sequencing methods in tumors to illustrate recent developments in the imaging resolution of micro-tissues.

Single-cell RNA binding protein regulatory network analyses reveal oncogenic HNRNPK-MYC signalling pathway in cancer

RNA-binding proteins (RBPs) are key players of gene expression and perturbations of RBP-RNA regulatory network have been observed in various cancer types. Here, we propose a computational method, RBPreg, to identify the RBP regulators by integration of single cell RNA-Seq (N = 233,591) and RBP binding data. Pan-cancer analyses suggest that RBP regulators exhibit cancer and cell specificity and perturbations of RBP regulatory network are involved in cancer hallmark-related functions. We prioritize an oncogenic RBP-HNRNPK, which is highly expressed in tumors and associated with poor prognosis of patients. Functional assays performed in cancer cells reveal that HNRNPK promotes cancer cell proliferation, migration, and invasion in vitro and in vivo. Mechanistic investigations further demonstrate that HNRNPK promotes tumorigenesis and progression by directly binding to MYC and perturbed the MYC targets pathway in lung cancer. Our results provide a valuable resource for characterizing RBP regulatory networks in cancer, yielding potential biomarkers for precision medicine.

Spatial transcriptome analysis of long non-coding RNAs reveals tissue specificity and functional roles in cancer

Long non-coding RNAs (lncRNAs) play a significant role in maintaining tissue morphology and functions, and their precise regulatory effectiveness is closely related to expression patterns. However, the spatial expression patterns of lncRNAs in humans are poorly characterized. Here, we constructed five comprehensive transcriptomic atlases of human lncRNAs covering thousands of major tissue samples in normal and disease states. The lncRNA transcriptomes exhibited high consistency within the same tissues across resources, and even higher complexity in specialized tissues. Tissue-elevated (TE) lncRNAs were identified in each resource and robust TE lncRNAs were refined by integrative analysis. We detected 1 to 4684 robust TE lncRNAs across tissues; the highest number was in testis tissue, followed by brain tissue. Functional analyses of TE lncRNAs indicated important roles in corresponding tissue-related pathways. Moreover, we found that the expression features of robust TE lncRNAs made them be effective biomarkers to distinguish tissues; TE lncRNAs also tended to be associated with cancer, and exhibited differential expression or were correlated with patient survival. In summary, spatial classification of lncRNAs is the starting point for elucidating the function of lncRNAs in both maintenance of tissue morphology and progress of tissue-constricted diseases.

Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management

In the complex and articulated machinery of the human genome, less than 2% of the transcriptome encodes for proteins, while at least 75% is actively transcribed into non-coding RNAs (ncRNAs). Among the non-coding transcripts, those ≥200 nucleotides long (lncRNAs) are receiving growing attention for their involvement in human diseases, particularly cancer. Genomic studies have revealed the multiplicity of processes, including neoplastic transformation and tumor progression, in which lncRNAs are involved by regulating gene expression at epigenetic, transcriptional, and post-transcriptional levels by mechanism(s) that still need to be clarified. In breast cancer, several lncRNAs were identified and demonstrated to have either oncogenic or tumor-suppressive roles. The functional understanding of the mechanisms of lncRNA action in this disease could represent a potential for translational applications, as these molecules may serve as novel biomarkers of clinical use and potential therapeutic targets. This review highlights the relationship between lncRNAs and the principal hallmark of the luminal breast cancer phenotype, estrogen receptor α (ERα), providing an overview of new potential ways to inhibit estrogenic signaling via this nuclear receptor toward escaping resistance to endocrine therapy.

Dynamic transcriptome analyses reveal m6A regulated immune non-coding RNAs during dengue disease progression

Dengue infection is one of the most prevalent arthropod-borne viral diseases, which can result in severe complications. Identification of genes and long non-coding RNAs (lncRNAs) involved in dengue infection would help in deciphering potential mechanisms responsible for the disease progression. We comprehensively analyzed the dynamic transcriptome during dengue disease progression and identified critical genes and lncRNAs with expression perturbations. Our findings revealed that the expression of genes (i.e., CCR10 and GNG7) and lncRNAs (i.e., CTBP1-AS and MAFG-AS1) were potentially regulated by m6A RNA methylation. Interestingly, dengue viral proteins prevalently interact with genes or lncRNAs with expression perturbations, which are involved in cell cycle, inflammation signaling pathways and immune response. Dynamically expressed genes and lncRNAs were likely to locate in the central regions of human protein-protein network, which play crucial roles in mediating signaling spread and helping viral replication. Immune microenvironments analysis revealed that plasma cells levels were increased and T cells infiltrations were decreased during dengue disease progression. Dynamically expressed genes and lncRNAs were correlated with immune cell infiltrations. Moreover, network analysis reveals the associations between dengue viral infections and human complex diseases (i.e., digestive diseases and neoplasms). Our comprehensive transcriptome analysis of dengue disease progression identified potential gene and lncRNA biomarkers, providing novel insights for understanding the pathogenesis of and developing effective therapeutic strategies for dengue infection.

Whole transcriptome sequencing reveals core genes related to spermatogenesis in Bactrian camels

Bactrian camels survive and reproduce better in extreme climatic conditions than other domestic animals can. However, the reproductive efficiency of camels under their natural pastoral conditions is low. Several factors affect mammalian reproductive performance, including testicular development, semen quality, libido, and mating ability. Testis is a main reproductive organ of the male and is responsible for producing spermatozoa and hormones. However, our understanding of the expression patterns of the genes in camel testis is minimal. Thus, we performed total RNA-sequencing to investigate the gene expression pattern. As a result, 1,538 differential expressed mRNAs (DEmRNAs), 702 differential expressed long non-coding RNAs (DElncRNAs), and 61 differential expressed microRNAs (DEmiRNAs) were identified between pubertal and adult Bactrian camel testes. Then the genomic features, length distribution, and other characteristics of the lncRNAs and mRNAs in the Bactrian camel testis were investigated. Target genes of the DEmiRNAs and DEmRNAs were further subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Genes, such as AMHR2, FGF1, ACTL7A, GATA4, WNT4, ID2, LAMA1, IGF1, INHBB, and TLR2, were mainly involved in the TGF-β, PI3K-AKT, Wnt, GnRH, and Hippo signaling pathways which relate to spermatogenesis. Some of the DEmiRNAs were predicted to be associated with numerous DElncRNAs and DEmRNAs through competing endogenous RNA (ceRNA) regulatory network. At last, the candidate genes were validated by RT-qPCR, dual fluorescent reporter gene, and a fluorescence in situ hybridization (FISH) assay. This research provides high-throughput RNA sequencing data of the testes of Bactrian camels across different developmental stages. It lays the foundation for further investigations on lncRNAs, miRNAs, and mRNAs that involved in Bactrian camel spermatogenesis.

Long Non-Coding RNAs as Epigenetic Regulators of Immune Checkpoints in Cancer Immunity

In recent years, cancer treatment has undergone significant changes, predominantly in the shift towards immunotherapeutic strategies using immune checkpoint inhibitors. Despite the clinical efficacy of many of these inhibitors, the overall response rate remains modest, and immunotherapies for many cancers have proved ineffective, highlighting the importance of knowing the tumor microenvironment and heterogeneity of each malignancy in patients. Long non-coding RNAs (lncRNAs) have attracted increasing attention for their ability to control various biological processes by targeting different molecular pathways. Some lncRNAs have a regulatory role in immune checkpoints, suggesting they might be utilized as a target for immune checkpoint treatment. The focus of this review is to describe relevant lncRNAs and their targets and functions to understand key regulatory mechanisms that may contribute in regulating immune checkpoints. We also provide the state of the art on super-enhancers lncRNAs (selncRNAs) and circular RNAs (circRNAs), which have recently been reported as modulators of immune checkpoint molecules within the framework of human cancer. Other feasible mechanisms of interaction between lncRNAs and immune checkpoints are also reported, along with the use of miRNAs and circRNAs, in generating new tumor immune microenvironments, which can further help avoid tumor evasion.

ImmCluster: an ensemble resource for immunology cell type clustering and annotations in normal and cancerous tissues

Single-cell transcriptome has enabled the transcriptional profiling of thousands of immune cells in complex tissues and cancers. However, subtle transcriptomic differences in immune cell subpopulations and the high dimensionality of transcriptomic data make the clustering and annotation of immune cells challenging. Herein, we introduce ImmCluster (http://bio-bigdata.hrbmu.edu.cn/ImmCluster) for immunology cell type clustering and annotation. We manually curated 346 well-known marker genes from 1163 studies. ImmCluster integrates over 420 000 immune cells from nine healthy tissues and over 648 000 cells from different tumour samples of 17 cancer types to generate stable marker-gene sets and develop context-specific immunology references. In addition, ImmCluster provides cell clustering using seven reference-based and four marker gene-based computational methods, and the ensemble method was developed to provide consistent cell clustering than individual methods. Five major analytic modules were provided for interactively exploring the annotations of immune cells, including clustering and annotating immune cell clusters, gene expression of markers, functional assignment in cancer hallmarks, cell states and immune pathways, cell-cell communications and the corresponding ligand-receptor interactions, as well as online tools. ImmCluster generates diverse plots and tables, enabling users to identify significant associations in immune cell clusters simultaneously. ImmCluster is a valuable resource for analysing cellular heterogeneity in cancer microenvironments.

IEAtlas: an atlas of HLA-presented immune epitopes derived from non-coding regions

Cancer-related epitopes can engage the immune system against tumor cells, thus exploring epitopes derived from non-coding regions is emerging as a fascinating field in cancer immunotherapies. Here, we described a database, IEAtlas (http://bio-bigdata.hrbmu.edu.cn/IEAtlas), which aims to provide and visualize the comprehensive atlas of human leukocyte antigen (HLA)-presented immunogenic epitopes derived from non-coding regions. IEAtlas reanalyzed publicly available mass spectrometry-based HLA immunopeptidome datasets against our integrated benchmarked non-canonical open reading frame information. The current IEAtlas identified 245 870 non-canonical epitopes binding to HLA-I/II allotypes across 15 cancer types and 30 non-cancerous tissues, greatly expanding the cancer immunopeptidome. IEAtlas further evaluates the immunogenicity via several commonly used immunogenic features, including HLA binding affinity, stability and T-cell receptor recognition. In addition, IEAtlas provides the biochemical properties of epitopes as well as the clinical relevance of corresponding genes across major cancer types and normal tissues. Several flexible tools were also developed to aid retrieval and to analyze the epitopes derived from non-coding regions. Overall, IEAtlas will serve as a valuable resource for investigating the immunogenic capacity of non-canonical epitopes and the potential as therapeutic cancer vaccines.

Long noncoding RNA LINC01132 enhances immunosuppression and therapy resistance via NRF1/DPP4 axis in hepatocellular carcinoma

Background

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in various types of cancer. Current developments in transcriptome analyses unveiled the existence of lncRNAs; however, their functional characterization remains a challenge.

Methods

A bioinformatics screen was performed by integration of multiple omics data in hepatocellular carcinoma (HCC) prioritizing a novel oncogenic lncRNA, LINC01132. Expression of LINC01132 in HCC and control tissues was validated by qRT-PCR. Cell viability and migration activity was examined by MTT and transwell assays. Finally, our results were confirmed in vivo mouse model and ex vivo patient derived tumor xenograft experiments to determine the mechanism of action and explore LINC01132-targeted immunotherapy.

Results

Systematic investigation of lncRNAs genome-wide expression patterns revealed LINC01132 as an oncogene in HCC. LINC01132 is significantly overexpressed in tumor and associated with poor overall survival of HCC patients, which is mainly driven by copy number amplification. Functionally, LINC01132 overexpression promoted cell growth, proliferation, invasion and metastasis in vitro and in vivo. Mechanistically, LINC01132 acts as an oncogenic driver by physically interacting with NRF and enhancing the expression of DPP4. Notably, LINC01132 silencing triggers CD8+ T cells infiltration, and LINC01132 knockdown combined with anti-PDL1 treatment improves antitumor immunity, which may prove a new combination therapy in HCC.

Conclusions

LINC01132 functions as an oncogenic driver that induces HCC development via the NRF1/DPP4 axis. Silencing LINC01132 may enhance the efficacy of anti-PDL1 immunotherapy in HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02478-z.

Identification and functional analysis of N6-methyladenine (m6 A)-related lncRNA across 33 cancer types

BACKGROUND

N6-methyladenosine (m⁶ A) plays an essential role in tumorigenesis and cancer progression. Long noncoding RNAs (lncRNAs) are discovered to be important targets of m⁶ A modification, and they play fundamental roles in diverse biological processes. However, there is still a lack of knowledge with regards to the association between m⁶ A and lncRNAs in human tumors.

METHODS

The relationship between lncRNAs and 21 m⁶ A regulators was comprehensively explored, through the integration of multi-omics data from M6A2Target, m6A-Atlas, and TCGA (The Cancer Genome Atlas). In order to explore the potential roles of m6A-related lncRNAs in human tumors, three applicable methods were introduced, which include the construction of ceRNA networks, drug sensitivity estimation, and survival analysis.

RESULTS

A substantial number of positive correlation events across 33 cancer types were found. Moreover, cancer-specific lncRNAs were associated with tissue specificity, and cancer-common lncRNAs were conserved in cancer-related biological function. In particular, the m⁶ A-related lncRNA FGD5-AS1 was found to be associated with cancer treatment, through its influence on cisplatin resistance in breast cancer patients. Finally, a user-friendly interface Lnc2m6A, which is enriched with various browsing sections resource for the exhibition of relationships and putative biogenesis between lncRNAs and m⁶ A modifications, is offered in http://hainmu-biobigdata.com/Lnc2m6A.

CONCLUSIONS

In summary, the results from this paper will provide a valuable resource that guides both mechanistic and therapeutic roles of m⁶ A-related lncRNAs in human tumors.

Pediatric Pan-Central Nervous System Tumor Methylome Analyses Reveal Immune-Related LncRNAs

Pediatric central nervous system (CNS) tumors are the second most common cancer diagnosis among children. Long noncoding RNAs (lncRNAs) emerge as critical regulators of gene expression, and they play fundamental roles in immune regulation. However, knowledge on epigenetic changes in lncRNAs in diverse types of pediatric CNS tumors is lacking. Here, we integrated the DNA methylation profiles of 2,257 pediatric CNS tumors across 61 subtypes with lncRNA annotations and presented the epigenetically regulated landscape of lncRNAs. We revealed the prevalent lncRNA methylation heterogeneity across pediatric pan-CNS tumors. Based on lncRNA methylation profiles, we refined 14 lncRNA methylation clusters with distinct immune microenvironment patterns. Moreover, we found that lncRNA methylations were significantly correlated with immune cell infiltrations in diverse tumor subtypes. Immune-related lncRNAs were further identified by investigating their correlation with immune cell infiltrations and potentially regulated target genes. LncRNA with methylation perturbations potentially regulate the genes in immune-related pathways. We finally identified several candidate immune-related lncRNA biomarkers (i.e., SSTR5-AS1, CNTN4-AS1, and OSTM1-AS1) in pediatric cancer for further functional validation. In summary, our study represents a comprehensive repertoire of epigenetically regulated immune-related lncRNAs in pediatric pan-CNS tumors, and will facilitate the development of immunotherapeutic targets.

Pan-cancer analyses reveal the genetic and pharmacogenomic landscape of transient receptor potential channels

Transient-receptor potential (TRP) channels comprise a diverse family of ion channels, which play important roles in regulation of intracellular calcium. Emerging evidence has revealed the critical roles of TRP channels in tumor development and progression. However, we still lack knowledge about the genetic and pharmacogenomics landscape of TRP genes across cancer types. Here, we comprehensively characterized the genetic and transcriptome alterations of TRP genes across >10,000 patients of 33 cancer types. We revealed prevalent somatic mutations and copy number variation in TRP genes. In particular, mutations located in transmembrane regions of TRP genes were likely to be deleterious mutations (p-values < 0.001). Genetic alterations were correlated with transcriptome dysregulation of TRP genes, and we found that TRPM2, TRPM8, and TPRA1 showed extent dysregulation in cancer. Patients with TRP gene alterations were with significantly higher hypoxia scores, tumor mutation burdens, tumor stages and grades, and poor survival. The alterations of TRP genes were significantly associated with the activity of cancer-related pathways. Moreover, we found that the expression of TRP genes were potentially useful for development of targeted therapies. Our study provided the landscape of genomic and transcriptomic alterations of TPRs across 33 cancer types, which is a comprehensive resource for guiding both mechanistic and therapeutic analyses of the roles of TRP genes in cancer. Identifying the TRP genes with extensive genetic alterations will directly contribute to cancer therapy in the context of predictive, preventive, and personalized medicine.

Comprehensive characterization of human-virus protein-protein interactions reveals disease comorbidities and potential antiviral drugs

The protein-protein interactions (PPIs) between human and viruses play important roles in viral infection and host immune responses. Rapid accumulation of experimentally validated human-virus PPIs provides an unprecedented opportunity to investigate the regulatory pattern of viral infection. However, we are still lack of knowledge about the regulatory patterns of human-virus interactions. We collected 27,293 experimentally validated human-virus PPIs, covering 8 virus families, 140 viral proteins and 6059 human proteins. Functional enrichment analysis revealed that the viral interacting proteins were likely to be enriched in cell cycle and immune-related pathways. Moreover, we analysed the topological features of the viral interacting proteins and found that they were likely to locate in central regions of human PPI network. Based on network proximity analyses of diseases genes and human-virus interactions in the human interactome, we revealed the associations between complex diseases and viral infections. Network analysis also implicated potential antiviral drugs that were further validated by text mining. Finally, we presented the Human-Virus Protein-Protein Interaction database (HVPPI, http://bio-bigdata.hrbmu.edu.cn/HVPPI), that provides experimentally validated human-virus PPIs as well as seamlessly integrates online functional analysis tools. In summary, comprehensive understanding the regulatory pattern of human-virus interactome will provide novel insights into fundamental infectious mechanism discovery and new antiviral therapy development.

Shedding light on the hidden human proteome expands immunopeptidome in cancer

Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.

Long non-coding RNA SNHG10 upregulates BIN1 to suppress the tumorigenesis and epithelial-mesenchymal transition of epithelial ovarian cancer via sponging miR-200a-3p

Epithelial ovarian cancer (EOC) is one of the most frequent and fatal gynecologic malignant tumors resulting in an unsatisfying prognosis. Long non-coding RNAs (lncRNAs) play pivotal roles in the tumorigenesis and progression of EOC. However, the profile of lncRNAs involved in EOC remains to be expanded to further improve clinical treatment strategy. In present study, we identified a novel tumor-suppressive lncRNA small nucleolar RNA host gene 10 (SNHG10) in EOC. Kaplan–Meier analysis and COX proportional hazard progression model showed that low expression of SNHG10 was correlated with a poor prognosis of EOC patients. Overexpressing SNHG10 suppressed the proliferation, colony formation, migration, and invasion of EOC cells. Furthermore, SNHG10 was predicted to sponge miR-200a-3p in EOC cells according to the LncBase v.2 experimental module. Then, the binding of SNHG10 and miR-200a-3p was confirmed by performing quantitative real-time PCR (qRT-PCR) and luciferase reporter assays. RNA immunoprecipitation (RIP) showed that SNHG10 and miR-200a-3p occupied the same Ago2 protein to form an RNA-induced silencing complex (RISC). By overlapping the results from the bioinformatics algorithms, tumor-suppressor bridging integrator-1 (BIN1) was found to be a main downstream target of the SNHG10/miR-200a-3p axis. Low expression of BIN1 in EOC tissues was detected by using immunohistochemistry (IHC). Besides, BIN1 and SNHG10 expression was positively correlated in EOC tissues. By performing miRNA rescue experiments, a SNHG10/miR-200a-3p/BIN1 axis and its promoting effects on malignant behaviors and epithelial–mesenchymal transition (EMT) process were verified in EOC cells. Moreover, SNHG10 overexpression significantly suppressed the tumorigenesis and EMT of EOC cells in vivo. Altogether, SNHG10 sponges miR-200a-3p to upregulate BIN1 and thereby exerting its tumor-suppressive effects in EOC. Therefore, the SNHG10/miR-200a-3p/BIN1 axis may act as a potential predictive biomarker and therapeutic target for treating EOC.

Novel prognostic marker LINC00205 promotes tumorigenesis and metastasis by competitively suppressing miRNA-26a in gastric cancer

Rapid proliferation and metastasis of gastric cancer (GC) resulted in a poor prognosis in the clinic. Previous studies elucidated that long non-coding RNA (LncRNA) LINC00205 was upregulated in various tumors and participated in tumor progression. The aim of our study was to investigate the regulating role of LINC00205 in tumorigenesis and metastasis of GC. Both public datasets and our data showed that the LINC00205 was highly expressed in GC tissues and several cell lines. Notably, GC patients with high level of LINC00205 had a poor prognosis in our cohort. Mechanistically, knockdown of LINC00205 by shRNAs suppressed GC cells proliferation, migration, invasion remarkably, and induced cell cycle arrest. Based on bioinformatics prediction, we found that LINC00205 might act as a competitive endogenous RNA (ceRNA) through targeting miR-26a. The level of miR-26a had negatively correlated with LINC00205 expression and was decreased among GC cell lines, tissues, and serum samples. Our results for the first time confirmed that miR-26a was a direct target of LINC00205 and might have the potential to become a plasma marker for clinical tumor diagnosis. Indeed, LINC00205 knockdown resulted in the dramatic promotion of miR-26a expression as well as inhibition of miR-26a potential downstream targets, such as HMGA2, EZH2, and USP15. These targets were essential for cell survival and epithelial-mesenchymal transition. Importantly, LINC00205 was able to remodel the miR-26a-mediated downstream silence, which identified a new mechanism of malignant transformation of GC cells. In conclusion, this study revealed the regulating role of the LINC00205/miR-26a axis in GC progression and provided a new potential therapeutic strategy for GC treatment.

ImmReg: the regulon atlas of immune-related pathways across cancer types

Immune system gene regulation perturbation has been found to be a major cause of the development of various types of cancer. Numbers of mechanisms contribute to gene expression regulation, thus, systematically identification of potential regulons of immune-related pathways is critical to cancer immunotherapy. Here, we comprehensively chart the landscape of transcription factors, microRNAs, RNA binding proteins and long noncoding RNAs regulation in 17 immune-related pathways across 33 cancers. The potential immunology regulons are likely to exhibit higher expressions in immune cells, show expression perturbations in cancer, and are significantly correlated with immune cell infiltrations. We also identify a panel of clinically relevant immunology regulons across cancers. Moreover, the regulon atlas of immune-related pathways helps prioritizing cancer-related genes (i.e. ETV7, miR-146a-5p, ZFP36 and HCP5). We further identified two molecular subtypes of glioma (cold and hot tumour phenotypes), which were characterized by differences in immune cell infiltrations, expression of checkpoints, and prognosis. Finally, we developed a user-friendly resource, ImmReg (http://bio-bigdata.hrbmu.edu.cn/ImmReg/), with multiple modules to visualize, browse, and download immunology regulation. Our study provides a comprehensive landscape of immunology regulons, which will shed light on future development of RNA-based cancer immunotherapies.

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.

Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas

Long non-coding RNAs (lncRNAs) are increasingly recognized as functional units in cancer and powerful biomarkers; however, most remain uncharacterized. Here, we analyze 5,592 prognostic lncRNAs in 9,446 cancers of 30 types using machine learning. We identify 166 lncRNAs whose expression correlates with survival and improves the accuracy of common clinical variables, molecular features, and cancer subtypes. Prognostic lncRNAs are often characterized by switch-like expression patterns. In low-grade gliomas, HOXA10-AS activation is a robust marker of poor prognosis that complements IDH1/2 mutations, as validated in another retrospective cohort, and correlates with developmental pathways in tumor transcriptomes. Loss- and gain-of-function studies in patient-derived glioma cells, organoids, and xenograft models identify HOXA10-AS as a potent onco-lncRNA that regulates cell proliferation, contact inhibition, invasion, Hippo signaling, and mitotic and neuro-developmental pathways. Our study underscores the pan-cancer potential of the non-coding transcriptome for identifying biomarkers and regulators of cancer progression.

(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.

TransLnc: a comprehensive resource for translatable lncRNAs extends immunopeptidome

LncRNAs are not only well-known as non-coding elements, but also serve as templates for peptide translation, playing important roles in fundamental cellular processes and diseases. Here, we describe a database, TransLnc (http://bio-bigdata.hrbmu.edu.cn/TransLnc/), which aims to provide comprehensive experimentally supported and predicted lncRNA peptides in multiple species. TransLnc currently documents approximate 583 840 peptides encoded by 33 094 lncRNAs. Six types of direct and indirect evidences supporting the coding potential of lncRNAs were integrated, and 65.28% peptides entries were with at least one type of evidence. Considering the strong tissue-specific expression of lncRNAs, TransLnc allows users to access lncRNA peptides in any of the 34 tissues involved in. In addition, both the unique characteristic and homology relationship were also predicted and provided. Importantly, TransLnc provides computationally predicted tumour neoantigens from peptides encoded by lncRNAs, which would provide novel insights into cancer immunotherapy. There were 220 791 and 237 915 candidate neoantigens binding by major histocompatibility complex (MHC) class I or II molecules, respectively. Several flexible tools were developed to aid retrieve and analyse, particularly lncRNAs tissue expression patterns, clinical relevance across cancer types. TransLnc will serve as a valuable resource for investigating the translation capacity of lncRNAs and greatly extends the cancer immunopeptidome.

SPMLMI: predicting lncRNA-miRNA interactions in humans using a structural perturbation method

Long non-coding RNA (lncRNA)-microRNA (miRNA) interactions are quickly emerging as important mechanisms underlying the functions of non-coding RNAs. Accordingly, predicting lncRNA-miRNA interactions provides an important basis for understanding the mechanisms of action of ncRNAs. However, the accuracy of the established prediction methods is still limited. In this study, we used structural consistency to measure the predictability of interactive links based on a bilayer network by integrating information for known lncRNA-miRNA interactions, an lncRNA similarity network, and an miRNA similarity network. In particular, by using the structural perturbation method, we proposed a framework called SPMLMI to predict potential lncRNA-miRNA interactions based on the bilayer network. We found that the structural consistency of the bilayer network was higher than that of any single network, supporting the utility of bilayer network construction for the prediction of lncRNA-miRNA interactions. Applying SPMLMI to three real datasets, we obtained areas under the curves of 0.9512 ± 0.0034, 0.8767 ± 0.0033, and 0.8653 ± 0.0021 based on 5-fold cross-validation, suggesting good model performance. In addition, the generalizability of SPMLMI was better than that of the previously established methods. Case studies of two lncRNAs (i.e., SNHG14 and MALAT1) further demonstrated the feasibility and effectiveness of the method. Therefore, SPMLMI is a feasible approach to identify novel lncRNA-miRNA interactions underlying complex biological processes.

Suppression of circulating AP001429.1 long non-coding RNA in obese patients with breast cancer

Long non-coding RNAs (lncRNAs), a type of cellular RNA, play a critical regulatory role in several physiological developments and pathological processes, such as tumorigenesis and tumor progression. Obesity is a risk factor for a number of serious health conditions, including breast cancer (BC). However, the underlying mechanisms behind the association between obesity and increased BC incidence and mortality remain unclear. Several studies have reported changes in lncRNA expression due to obesity and BC, independently encouraging further investigation of the relationship between the two in connection with lncRNAs. The present study was designed to first screen for the expression of 29 selected lncRNAs that showed a link to cancer or obesity in the blood of a selected cohort of 6 obese and 6 non-obese patients with BC. The expression levels of significantly expressed lncRNAs, AP001429.1, PCAT6, P5549, P19461 and P3134, were further investigated in a larger cohort of 69 patients with BC (36 obese and 33 non-obese), using reverse transcription-quantitative polymerase chain reaction. Results showed not only that AP001429.1 remained significantly downregulated in the larger cohort (P=0.002), but also that it was associated with several clinicopathological characteristics, such as negative HER2 status, negative E-cadherin expression, negative vascular invasion, negative margin invasion and LCIS. These findings suggest that obesity may have a role in inhibiting AP001429.1 expression, which may serve as a novel potential biomarker and therapeutic target for BC.

Approaches to Identify and Characterise the Post-Transcriptional Roles of lncRNAs in Cancer

It is becoming increasingly evident that the non-coding genome and transcriptome exert great influence over their coding counterparts through complex molecular interactions. Among non-coding RNAs (ncRNA), long non-coding RNAs (lncRNAs) in particular present increased potential to participate in dysregulation of post-transcriptional processes through both RNA and protein interactions. Since such processes can play key roles in contributing to cancer progression, it is desirable to continue expanding the search for lncRNAs impacting cancer through post-transcriptional mechanisms. The sheer diversity of mechanisms requires diverse resources and methods that have been developed and refined over the past decade. We provide an overview of computational resources as well as proven low-to-high throughput techniques to enable identification and characterisation of lncRNAs in their complex interactive contexts. As more cancer research strategies evolve to explore the non-coding genome and transcriptome, we anticipate this will provide a valuable primer and perspective of how these technologies have matured and will continue to evolve to assist researchers in elucidating post-transcriptional roles of lncRNAs in cancer.

A comprehensive survey for human transcription factors on expression, regulation, interaction, phenotype and cancer survival

Transcription factors (TFs) act as key regulators in biological processes through controlling gene expression. Here, we conducted a systematic study for all human TFs on the expression, regulation, interaction, mutation, phenotype and cancer survival. We revealed that the average expression levels of TFs in normal tissues were lower than 50% expression of non-TFs, whereas TF expression was increased in cancers. TFs that are specifically expressed in an individual tissue or cancer may be potential marker genes. For instance, TGIF2LX/Y were preferentially expressed in testis and NEUROG1, PRDM14, SRY, ZNF705A and ZNF716 were specifically highly expressed in germ cell tumors. We found different distributions of target genes and TF co-regulations in different TF families. Some small TF families have huge protein interaction pairs, suggesting their central roles in transcriptional regulation. The bZIP family is a small family involving many signaling pathways. Survival analysis indicated that most TFs significantly affect survival of one or more cancers. Some survival-related TFs were also specifically highly expressed in the corresponding cancer types, which may be potential targets for cancer therapy. Finally, we identified 43 TFs whose mutations were closely correlated to survival, suggesting their cancer-driven roles. The systematic analysis of TFs provides useful clues for further investigation of TF regulatory mechanisms and the role of TFs in diseases.

NONCODEV6: an updated database dedicated to long non-coding RNA annotation in both animals and plants

NONCODE (http://www.noncode.org/) is a comprehensive database of collection and annotation of noncoding RNAs, especially long non-coding RNAs (lncRNAs) in animals. NONCODEV6 is dedicated to providing the full scope of lncRNAs across plants and animals. The number of lncRNAs in NONCODEV6 has increased from 548 640 to 644 510 since the last update in 2017. The number of human lncRNAs has increased from 172 216 to 173 112. The number of mouse lncRNAs increased from 131 697 to 131 974. The number of plant lncRNAs is 94 697. The relationship between lncRNAs in human and cancer were updated with transcriptome sequencing profiles. Three important new features were also introduced in NONCODEV6: (i) updated human lncRNA-disease relationships, especially cancer; (ii) lncRNA annotations with tissue expression profiles and predicted function in five common plants; iii) lncRNAs conservation annotation at transcript level for 23 plant species. NONCODEV6 is accessible through http://www.noncode.org/.

Secondary Structural Model of MALAT1 Becomes Unstructured in Chronic Myeloid Leukemia and Undergoes Structural Rearrangement in Cervical Cancer

Long noncoding RNAs (lncRNAs) influence cellular function through binding events that often depend on the lncRNA secondary structure. One such lncRNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), is upregulated in many cancer types and has a myriad of protein- and miRNA-binding sites. Recently, a secondary structural model of MALAT1 in noncancerous cells was proposed to form 194 hairpins and 13 pseudoknots. That study postulated that, in cancer cells, the MALAT1 structure likely varies, thereby influencing cancer progression. This work analyzes how that structural model is expected to change in K562 cells, which originated from a patient with chronic myeloid leukemia (CML), and in HeLa cells, which originated from a patient with cervical cancer. Dimethyl sulfate-sequencing (DMS-Seq) data from K562 cells and psoralen analysis of RNA interactions and structure (PARIS) data from HeLa cells were compared to the working structural model of MALAT1 in noncancerous cells to identify sites that likely undergo structural alterations. MALAT1 in K562 cells is predicted to become more unstructured, with almost 60% of examined hairpins in noncancerous cells losing at least half of their base pairings. Conversely, MALAT1 in HeLa cells is predicted to largely maintain its structure, undergoing 18 novel structural rearrangements. Moreover, 50 validated miRNA-binding sites are affected by putative secondary structural changes in both cancer types, such as miR-217 in K562 cells and miR-20a in HeLa cells. Structural changes unique to K562 cells and HeLa cells provide new mechanistic leads into how the structure of MALAT1 may mediate cancer in a cell-type specific manner.

Web tools to perform long non-coding RNAs analysis in oncology research

Accumulated evidence suggests that the widely expressed long-non-coding RNAs (lncRNAs) are involved in biogenesis. Some aberrant lncRNAs are closely related to pathological changes, for instance, in cancer. Both in tumorigenesis and cancer progression, depending on the interplay with cellular molecules, lncRNAs can modulate transcriptional interference, chromatin remodeling, post-translational regulation and protein modification, and further interfere with signaling pathways. Aiming to the diagnosis/ prognosis markers or potential therapeutical targets, it is important to figure out the specific mechanism and the tissue-specific expressing patterns of lncRNAs. Generally, the bioinformatics analysis is the first step. More and more in silico databases are increasing. But the existing integrative online platforms’ functions are not only having their unique features but also share some common features, which may lead to a waste of time for researchers. Here, we reviewed these web tools according to the functions. For each database, we clarified the data source, analysis method and the evidence that the analysis result is derived from. This review also illustrated examples in practical use for a specific lncRNA by these web tools. It will provide convenience for researchers to quickly choose the appropriate bioinformatics web tools in oncology studies.