Integrated analysis of dosage effect lncRNAs in lung adenocarcinoma based on comprehensive network.

Accumulating evidences indicate that cancer-related lncRNAs occur frequent somatic copy number alternation (SCNA). Although individual SCNA lncRNAs have been implicated in tumor biology, their regulatory mechanism has not been assessed in a systematic way. In order to explore the expression characteristics and biological functions of SCNA lncRNAs in cancer, we built a computational framework based on lncRNA expression profiles, lncRNA copy numbers and dosage sensitivity score (DSS). First, we found that the lncRNAs with different DSS were involved in distinct biological processes, while those with the same DSS had similar functions. Second, some of the lncRNAs participated in the progression and metastasis of lung adenocarcinoma (LUAD) through cis-acting regulation. In lncRNA-TF-mRNA network, lncRNAs interacted with 4 TFs and affected the immune system, and further influenced LUAD progression. Third, competing endogenous RNA network analysis inferred that lncRNA ENSG00000240990 competed with HOXA10 to absorb hsa-let-7a/b/f/g-5p and affected patient prognosis in LUAD. Last but not least, by integrating target information of miRNA we also provided a new perspective for the discovery of potential small molecule drugs. In summary, we systematically analyzed the regulatory role of SCNA lncRNAs. This work may facilitate cancer research and serve as the basis for future efforts to understand the role of SCNA lncRNAs, develop novel biomarkers and improve knowledge of tumor biology.

The characteristic landscape of lncRNAs classified by RBP-lncRNA interactions across 10 cancers.

RNA-binding proteins (RBPs) are key regulators of gene expression. Some long non-coding RNAs (lncRNAs) affect gene expression by interacting with RBPs. However, whether this influences the biological characteristics of lncRNAs in diseases still remains unknown. Here, we classify lncRNAs into two categories, using the interaction information between lncRNAs and RBPs: the lncRNAs that interact with RBPs (Rlncs) and the lncRNAs that do not interact with RBPs (NRlncs). Then we systematically analyze the basic attributes and functions of the two categories of lncRNAs across 10 cancers. By comparing the two categories, we find that the attributes of Rlncs are significantly higher than those of NRlncs in different aspects such as expression level, protein-coding potential, and evolutionary conservation. Furthermore, functional enrichment analysis reveals that the two categories of lncRNAs are involved in different functions and biological pathways. Finally, the prognostic analysis results suggest that the two categories of lncRNAs affect the overall survival of patients through participating in different functions. Our systematic characterization of Rlncs and NRlncs provides a new perspective for understanding the role of lncRNAs, and improves knowledge of cancer biology.

The functional consequences and prognostic value of dosage sensitivity in ovarian cancer.

Copy number alteration (CNA) represents an important class of genetic variations that may contribute to tumorigenesis, tumor growth and metastatic spread. CNA can directly affect the expression of genes within the CNA regions; however, genes within the CNA regions exhibit heterogeneity in gene dosage sensitivity. In this study, a computational framework was built to identify 1170 dosage-sensitive genes (DSGs) and 1215 dosage-resistant genes (DRGs) that were related to ovarian serous cystadenocarcinoma (OV) through the association between CNA and gene expression. To analyze the different functions of the genes within the two groups, the functional annotation results indicated that DRGs were involved in cancer-related processes like immune response, cell death and apoptosis, while DSGs were enriched in essential processes like the cell cycle and the DNA metabolic process. Meanwhile, two three-dimensional regulatory networks for differentially expressed miRNAs, differentially expressed transcription factors (TFs) and DSGs or DRGs were constructed based on feed-forward loops. We identified key regulators (such as miR-16-5p, miR-98-5p, MYB and HOXA5) and cancer prognosis-related network motifs (such as miR-98-5p-HOXA5-TP53 and miR-16-5p-MYB-IGF1R) after the analysis of network topological features. Our results lead us to speculate that these genes and associated regulators may be potential mechanistic biomarkers for tumorigenesis and progression of cancer. Research on the network characteristics and the role of feed-forward loops in OV tumorigenesis and development could lead to feasible suggestions for the prevention and early diagnosis of OV, which will shed light on understanding the functional mechanism of CNA in cancer.

Optimization of cell lines as tumour models by integrating multi-omics data.

Cell lines are widely used as in vitro models of tumorigenesis. However, an increasing number of researchers have found that cell lines differ from their sourced tumour samples after long-term cell culture. The application of unsuitable cell lines in experiments will affect the experimental accuracy and the treatment of patients. Therefore, it is imperative to identify optimal cell lines for each cancer type. Here, we review the methods used to evaluate cell lines since 2005. Furthermore, gene expression, copy number and mutation profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia are used to calculate similarity between tumours and cell lines. Then, the ideal cell lines to use for experiments for eight types of cancers are found by combining the results with Gene Ontology functional similarity. After verification, the optimal cell lines have the same genomic characteristics as their homologous tumour samples. The contaminated cell lines identified in previous research are also determined to be unsuitable in vitro cancer models here. Moreover, our study suggests that some of the commonly used cell lines are not suitable cancer models. In summary, we provide a reference for ideal cell lines to use in in vitro experiments and contribute to improving the accuracy of future cancer research. Furthermore, this research provides a foundation for identifying more effective treatment strategies.

A comparative analysis reveals the dosage sensitivity and regulatory patterns of lncRNA in prostate cancer.

Although the key roles of long non-coding RNAs (lncRNAs) in multiple diseases are well documented, the relationship between the lncRNA copy number and expression is unknown. Here, we present a comprehensive study that demonstrates the impact of miRNA-TF co-regulatory motifs on the dosage effects of protein-coding genes (PCGs) and lncRNAs in prostate cancer. By integrating copy number profiles, expression profiles and regulatory relationships with miRNAs and transcription factors, we reveal that lncRNAs and PCGs correlate with distinct dosage sensitivity and regulatory pattern characteristics. We also show that lncRNAs from different genomic regions have different features. Using a custom-built framework, we identified 24 candidate prostate cancer-related lncRNAs based on the known properties of established prostate-related lncRNAs. Our method will enable the identification of cancer-related lncRNAs, which will provide new insights into cancer lncRNA biology.

An integrated approach to reveal miRNAs' impacts on the functional consequence of copy number alterations in cancer.

Copy number alteration (CNA) is known to induce gene expression changes mainly through dosage effect, and therefore affect the initiation and progression of tumor. However, tumor samples exhibit heterogeneity in gene dosage sensitivity due to the complicated mechanisms of transcriptional regulation. Currently, no high-throughput method has been available for identifying the regulatory factors affecting the functional consequences of CNA, and determining their effects on cancer. In view of the important regulatory role of miRNA, we investigated the influence of miRNAs on the dosage sensitivities of genes within the CNA regions. By integrating copy number, mRNA expression, miRNA expression profiles of three kinds of cancer, we observed a tendency for high dosage-sensitivity genes to be more targeted by miRNAs in cancer, and identified the miRNAs regulating the dosage sensitivity of amplified/deleted target genes. The results show that miRNAs can modulate oncogenic biological functions by regulating the genes within the CNA regions, and thus play a role as a trigger or balancer in cancer, affecting cancer processes, even survival. This work provided a framework for analyzing the regulation of dosage effect, which will shed a light on understanding the oncogenic and tumor suppressive mechanisms of CNA. Besides, new cancer-related miRNAs were identified.