Identifying lncRNA-mediated regulatory modules via ChIA-PET network analysis

Long non‑coding RNA DANCR aggravates breast cancer through the miR‑34c/E2F1 feedback loop

Emerging scientific evidence has suggested that the long non‑coding (lnc)RNA differentiation antagonizing non‑protein coding RNA (DANCR) serves a significant role in human tumorigenesis and cancer progression; however, the precise mechanism of its function in breast cancer remains to be fully understood. Therefore, the objective of the present study was to manipulate DANCR expression in MCF7 and MDA‑MB‑231 cells using lentiviral vectors to knock down or overexpress DANCR. This manipulation, alongside the analysis of bioinformatics data, was performed to investigate the potential mechanism underlying the role of DANCR in cancer. The mRNA and/or protein expression levels of DANCR, miR‑34c‑5p and E2F transcription factor 1 (E2F1) were assessed using reverse transcription‑quantitative PCR and western blotting, respectively. The interactions between these molecules were validated using chromatin immunoprecipitation and dual‑luciferase reporter assays. Additionally, fluorescence in situ hybridization was used to confirm the subcellular localization of DANCR. Cell proliferation, migration and invasion were determined using 5‑ethynyl‑2'‑deoxyuridine, wound healing and Transwell assays, respectively. The results of the present study demonstrated that DANCR had a regulatory role as a competing endogenous RNA and upregulated the expression of E2F1 by sequestering miR‑34c‑5p in breast cancer cells. Furthermore, E2F1 promoted DANCR transcription by binding to its promoter in breast cancer cells. Notably, the DANCR/miR‑34c‑5p/E2F1 feedback loop enhanced cell proliferation, migration and invasion in breast cancer cells. Thus, these findings suggested that targeting DANCR may potentially provide a promising future therapeutic strategy for breast cancer treatment.

Identification of Regulatory Functions of LncRNAs Associated With T. circumcincta Infection in Adult Sheep

Several recent studies have demonstrated the role of long non-coding RNAs (lncRNAs) in regulating the defense mechanism against parasite infections, but no studies are available that investigated their relevance for immune response to nematode infection in sheep. Thus, the aim of the current study was to (i) detect putative lncRNAs that are expressed in the abomasal lymph node of adult sheep after an experimental infection with the gastrointestinal nematode (GIN) Teladorsagia circumcincta and (ii) to elucidate their potential functional role associated with the differential host immune response. We hypothesized that putative lncRNAs differentially expressed (DE) between samples from animals that differ in resistance to infection may play a significant regulatory role in response to nematode infection in adult sheep. To obtain further support for our hypothesis, we performed co-expression and functional gene enrichment analyses with the differentially expressed lncRNAs (DE lncRNAs). In a conservative approach, we included for this predictive analysis only those lncRNAs that are confirmed and supported by documentation of expression in gastrointestinal tissues in the current sheep gene atlas. We identified 9,105 putative lncRNA transcripts corresponding to 7,124 gene loci. Of these, 457 were differentially expressed lncRNA loci (DELs) with 683 lncRNA transcripts. Based on a gene co-expression analysis via weighted gene co-expression network analysis, 12 gene network modules (GNMs) were found significantly correlated with at least one of 10 selected target DE lncRNAs. Based on the principle of “guilt-by-association,” the DE genes from each of the three most significantly correlated GNMs were subjected to a gene enrichment analysis. The significant pathways associated with DE lncRNAs included ERK5 Signaling, SAPK/JNK Signaling, RhoGDI Signaling, EIF2 Signaling, Regulation of eIF4 and p70S6K Signaling and Oxidative Phosphorylation pathways. They belong to signaling pathway categories like Cellular Growth, Proliferation and Development, Cellular Stress and Injury, Intracellular and Second Messenger Signaling and Apoptosis. Overall, this lncRNA study conducted in adult sheep after GIN infection provided first insights into the potential functional role of lncRNAs in the differential host response to nematode infection.

Integrated Analysis of the Transcriptome Profile Reveals the Potential Roles Played by Long Noncoding RNAs in Immunotherapy for Sarcoma

Background

Long-term survival is still low for high-risk patients with soft tissue sarcoma treated with standard management options, including surgery, radiation, and chemotherapy. Immunotherapy is a promising new potential treatment paradigm. However, the application of immune checkpoint inhibitors for the treatment of patients with sarcoma did not yield promising results in a clinical trial. Therefore, there is a considerable need to identify factors that may lead to immune checkpoint inhibitor resistance.

Methods

In this study, we performed a bioinformatic analysis of The Cancer Genome Atlas (TCGA) to detect key long noncoding RNAs (lncRNAs) that were correlated with immune checkpoint inhibitory molecules in sarcoma. The expression levels of these lncRNAs and their correlation with patient prognosis were explored. The upstream long noncoding RNAs were also examined via 450K array data from the TCGA. The potential roles of these lncRNAs were further examined via KEGG and GO analysis using DAVID online software. Finally, the relationship between these lncRNAs and immune cell infiltration in tumors and their effect on immune checkpoint inhibitors were further explored.

Results

We identified lncRNAs correlated with tumor cell immune evasion in sarcoma. The expression of these lncRNAs was upregulated and correlated with worse prognosis in sarcoma and other human cancer types. Moreover, low DNA methylation occupation of these lncRNA loci was detected. Negative correlations between DNA methylation and lncRNA expression were also found in sarcoma and other human cancer types. KEGG and GO analyses indicated that these lncRNAs correlated with immune evasion and negative regulation of the immune response in sarcoma. Finally, high expression of these lncRNAs correlated with more suppressive immune cell infiltration and reduced sensitivity to immune checkpoint inhibitors in sarcoma and other human cancer types.

Conclusion

Our results suggest that long noncoding RNAs confer immune checkpoint inhibitor resistance in human cancer. Further characterization of these lncRNAs may help to elucidate the mechanisms underlying immune checkpoint inhibitor resistance and uncover a novel therapeutic intervention point for immunotherapy.

Transcriptome-wide high-throughput mapping of protein-RNA occupancy profiles using POP-seq

Interaction between proteins and RNA is critical for post-transcriptional regulatory processes. Existing high throughput methods based on crosslinking of the protein–RNA complexes and poly-A pull down are reported to contribute to biases and are not readily amenable for identifying interaction sites on non poly-A RNAs. We present Protein Occupancy Profile-Sequencing (POP-seq), a phase separation based method in three versions, one of which does not require crosslinking, thus providing unbiased protein occupancy profiles on whole cell transcriptome without the requirement of poly-A pulldown. Our study demonstrates that ~ 68% of the total POP-seq peaks exhibited an overlap with publicly available protein–RNA interaction profiles of 97 RNA binding proteins (RBPs) in K562 cells. We show that POP-seq variants consistently capture protein–RNA interaction sites across a broad range of genes including on transcripts encoding for transcription factors (TFs), RNA-Binding Proteins (RBPs) and long non-coding RNAs (lncRNAs). POP-seq identified peaks exhibited a significant enrichment (p value < 2.2e−16) for GWAS SNPs, phenotypic, clinically relevant germline as well as somatic variants reported in cancer genomes, suggesting the prevalence of uncharacterized genomic variation in protein occupied sites on RNA. We demonstrate that the abundance of POP-seq peaks increases with an increase in expression of lncRNAs, suggesting that highly expressed lncRNA are likely to act as sponges for RBPs, contributing to the rewiring of protein–RNA interaction network in cancer cells. Overall, our data supports POP-seq as a robust and cost-effective method that could be applied to primary tissues for mapping global protein occupancies.

Regulation of human Mcl-1 by a divergently-expressed antisense transcript

Mcl-1 is a member of the Bcl-2 anti-apoptotic protein family with important roles in the development, lifespan and metabolism of lymphocytes, as well as oncogenesis. Mcl-1 displays the shortest half-life of all Bcl-2 family members, with miRNA interference and proteasomal degradation being major pathways for Mcl-1 downregulation. In this study, we have identified a previously undescribed control mechanism active at the RNA level. A divergently transcribed lncRNA LOC107985203 (named here mcl1-AS1) negatively modulated Mcl-1 expression resulting in downregulation of Mcl-1 at both mRNA and protein level in a time-dependent manner. Using reporter assays, we confirmed that the mcl1-AS1 lncRNA promoter was located within Mcl-1 coding region. We next placed mcl1-AS1 under tetracycline-inducible control and demonstrated decreased viability in HEK293 cells upon doxycycline induction. Inhibition of mcl1-AS1 with shRNA reversed drug sensitivity. Bioinformatics surveys predicted direct mcl1-AS1 lncRNA binding to Mcl-1 transcripts, suggesting its mechanism in Mcl-1 expression is at the transcriptional level, consistent with a common role for anti-sense transcripts. The identification of a bi-directional promoter and lncRNA controlling Mcl-1 expression will have implications for controlling Mcl-1 activity in cancer cells, or for the purpose of enhancing the lifespan and quality of anti-cancer T lymphocytes.

FAL1: A critical oncogenic long non-coding RNA in human cancers

Long noncoding RNAs (lncRNAs) are characterized as a group of endogenous RNAs that are more than 200 nucleotides in length and have no protein-encoding function. More and more evidence indicates that lncRNAs play vital roles in various human diseases, especially in tumorigenesis. Focally amplified lncRNA on chromosome 1 (FAL1), a novel lncRNA with enhancer-like activity, has been identified as an oncogene in multiple cancers and high expression level of FAL1 is usually associated with poor prognosis. Dysregulation of FAL1 has been shown to promote the proliferation and metastasis of cancer cells. In the present review, we summarized and illustrated the functions and underlying molecular mechanisms of FAL1 in the occurrence and development of different cancers and other diseases. FAL1 has the potential to appear as a feasible diagnostic and prognostic tool and new therapeutic target for cancer patients though further investigation is needed so as to accelerate clinical application.

Non-coding RNA regulatory networks

It is well established that the vast majority of human RNA transcripts do not encode for proteins and that non-coding RNAs regulate cell physiology and shape cellular functions. A subset of them is involved in gene regulation at different levels, from epigenetic gene silencing to post-transcriptional regulation of mRNA stability. Notably, the aberrant expression of many non-coding RNAs has been associated with aggressive pathologies. Rapid advances in network biology indicates that the robustness of cellular processes is the result of specific properties of biological networks such as scale-free degree distribution and hierarchical modularity, suggesting that regulatory network analyses could provide new insights on gene regulation and dysfunction mechanisms. In this study we present an overview of public repositories where non-coding RNA-regulatory interactions are collected and annotated, we discuss unresolved questions for data integration and we recall existing resources to build and analyse networks.

DNA Rchitect: an R based visualizer for network analysis of chromatin interaction data

MOTIVATION

Visualization of multiple genomic data generally requires the use of public or commercially hosted browsers. Flexible visualization of chromatin interaction data as genomic features and network components offer informative insights to gene expression. An open source application for visualizing HiC and chromatin conformation-based data as 2D-arcs accompanied by interactive network analyses is valuable.

RESULTS

DNA Rchitect is a new tool created to visualize HiC and chromatin conformation-based contacts at high (Kb) and low (Mb) genomic resolutions. The user can upload their pre-filtered HiC experiment in bedpe format to the DNA Rchitect web app that we have hosted or to a version they themselves have deployed. Using DNA Rchitect, the uploaded data allows the user to visualize different interactions of their sample, perform simple network analyses, while also offering visualization of other genomic data types. The user can then download their results for additional network functionality offered in network based programs such as Cytoscape.

AVAILABILITY AND IMPLEMENTATION

DNA Rchitect is freely available both as a web application written primarily in R available at http://shiny.immgen.org/DNARchitect/ and as an open source released under an MIT license at: https://github.com/alosdiallo/DNA_Rchitect.