Long non-coding RNAs (lncRNAs) are associated with human diseases. Although lncRNA–disease associations have received significant attention, no online repository is available to collect lncRNA-mediated regulatory mechanisms, key downstream targets, and important biological functions driven by disease-related lncRNAs in human diseases. We thus developed LncTarD (http://biocc.hrbmu.edu.cn/LncTarD/ or http://bio-bigdata.hrbmu.edu.cn/LncTarD), a manually-curated database that provides a comprehensive resource of key lncRNA–target regulations, lncRNA-influenced functions, and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD offers (i) 2822 key lncRNA–target regulations involving 475 lncRNAs and 1039 targets associated with 177 human diseases; (ii) 1613 experimentally-supported functional regulations and 1209 expression associations in human diseases; (iii) important biological functions driven by disease-related lncRNAs in human diseases; (iv) lncRNA–target regulations responsible for drug resistance or sensitivity in human diseases and (v) lncRNA microarray, lncRNA sequence data and transcriptome data of an 11 373 pan-cancer patient cohort from TCGA to help characterize the functional dynamics of these lncRNA–target regulations. LncTarD also provides a user-friendly interface to conveniently browse, search, and download data. LncTarD will be a useful resource platform for the further understanding of functions and molecular mechanisms of lncRNA deregulation in human disease, which will help to identify novel and sensitive biomarkers and therapeutic targets.

Aberrant expression of long non-coding RNAs (lncRNA) is associated with altered DNA methylation and histone modifications during carcinogenesis. However, identifying epigenetically dysregulated lncRNAs and characterizing their functional mechanisms in different cancer subtypes are still major challenges for cancer studies. In this study, we systematically analyzed the epigenetic alterations of lncRNAs at important regulatory elements in three breast cancer subtypes. We identified 87, 691, and 1,197 epigenetically dysregulated lncRNAs in luminal, basal, and claudin-low subtypes of breast cancer, respectively. The landscape of epigenetically dysregulated lncRNAs at enhancer elements revealed that epigenetic changes of the majority of lncRNAs occurred in a subtype-specific manner and contributed to subtype-specific biological functions. We identified six acetylation of lysine 27 on histone H3 (H3K27ac)-dysregulated lncRNAs and three DNA methylation-dysregulated lncRNAs (CTC-303L1.2, RP11-738B7.1, and SLC26A4-AS1) as prognostic biomarkers of basal subtype. These lncRNAs were involved in immune response-related biological functions. Treatment of the basal breast cancer cell line MDA-MB-468 with CREBBP/EP300 bromodomain inhibitors downregulated H3K27 acetylation levels and caused a decrease in the expression of five H3K27ac-dysregulated lncRNAs (LINC00393, KB-1836B5.1, RP1-140K8.5, AC005162.1, and AC020916.2) and inhibition of the growth of breast cancer cells. One epigenetically dysregulated lncRNA (LINC01983) and four lncRNA regulators (UCA1, RP11-221J22.2, RP11-221J22.1, and RP1-212P9.3) were identified as prognostic biomarkers of the luminal molecular subtype of breast cancer by controlling the tumor necrosis factor (TNF) signaling pathway, T helper (Th)17 cell differentiation, and T cell migration. Finally, our results highlighted a profound role of enhancer-related H3K27ac-dysregulated lncRNAs, DNA methylation-dysregulated lncRNAs, and lncRNA regulators in breast cancer subtype carcinogenesis and their potential prognostic value.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA–target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.0 is freely available at (http://bio-bigdata.hrbmu.edu.cn/LncTarD or https://lnctard.bio-database.com/). LncTarD 2.0 was updated with several new features, including (i) an increased number of disease-associated lncRNA entries, where the current release provides 8360 key lncRNA–target regulations, with 419 disease subtypes and 1355 lncRNAs; (ii) predicted 3312 out of 8360 lncRNA–target regulations as potential diagnostic or therapeutic biomarkers in circulating tumor cells (CTCs); (iii) addition of 536 new, experimentally supported lncRNA–target regulations that modulate properties of cancer stem cells; (iv) addition of an experimentally supported clinical application section of 2894 lncRNA–target regulations for potential clinical application. Importantly, LncTarD 2.0 provides RNA-seq/microarray and single-cell web tools for customizable analysis and visualization of lncRNA–target regulations in diseases. RNA-seq/microarray web tool was used to mining lncRNA–target regulations in both disease tissue samples and CTCs blood samples. The single-cell web tools provide single-cell lncRNA–target annotation from the perspectives of pan-cancer analysis and cancer-specific analysis at the single-cell level. LncTarD 2.0 will be a useful resource and mining tool for the investigation of the functions and mechanisms of lncRNA deregulation in human disease.

Background Genomic studies of colorectal cancer have revealed the complex genomic heterogeneity of the tumor. The acquisition and selection of genomic alterations may be critical to understanding the initiation and progression of this disease. Methods In this study, we have systematically characterized the clonal architecture of 97 driver genes in 536 colorectal cancer patients from TCGA. Results A high proportion of clonal mutations in 93 driver genes were observed. 40 genes showed significant associations between their clonality and multiple clinicopathologic factors. Kaplan–Meier analysis suggested that the mutation clonality of ANK1, CASP8, SMAD2, and ARID1A had a significant impact on the CRC patients' outcomes. Multivariable analysis revealed that subclonal ANK1 mutations, clonal CASP8 mutations, and clonal SMAD2 mutations independently predicted for shorter overall survival after adjusting for clinicopathological factors. The poor outcome of the subclonal ANK1 mutation may be caused by upregulation of IL4I1, IDO1, IFNG and MAPK12 which showed potential roles in tumor immune evasion through accumulation of immunosuppressive cells such as regulatory T cells and myeloid derived suppressor cells. Conclusion These results suggested that the clonality of driver genes could act as prognostic markers and potential therapeutic targets in human colorectal cancer.

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