LncRNA IGBP1-AS1/miR-24-1/ZIC3 loop regulates the proliferation and invasion ability in breast cancer

Identification of methylation driver genes for predicting the prognosis of pancreatic cancer patients based on whole-genome DNA methylation sequencing technology

This study was based on the use of whole-genome DNA methylation sequencing technology to identify DNA methylation biomarkers in tumor tissue that can predict the prognosis of patients with pancreatic cancer (PCa). TCGA database was used to download PCa-related DNA methylation and transcriptome atlas data. Methylation driver genes (MDGs) were obtained using the MethylMix package. Candidate genes in the MDGs were screened for prognostic relevance to PCa patients by univariate Cox analysis, and a prognostic risk score model was constructed based on the key MDGs. ROC curve analysis was performed to assess the accuracy of the prognostic risk score model. The effects of PIK3C2B knockdown on malignant phenotypes of PCa cells were investigated in vitro. A total of 2737 differentially expressed genes were identified, with 649 upregulated and 2088 downregulated, using 178 PCa samples and 171 normal samples. MethylMix was employed to identify 71 methylation-driven genes (47 hypermethylated and 24 hypomethylated) from 185 TCGA PCa samples. Cox regression analyses identified eight key MDGs (LEF1, ZIC3, VAV3, TBC1D4, FABP4, MAP3K5, PIK3C2B, IGF1R) associated with prognosis in PCa. Seven of them were hypermethylated, while PIK3C2B was hypomethylated. A prognostic risk prediction model was constructed based on the eight key MDGs, which was found to accurately predict the prognosis of PCa patients. In addition, the malignant phenotypes of PANC-1 cells were decreased after the knockdown of PIK3C2B. Therefore, the prognostic risk prediction model based on the eight key MDGs could accurately predict the prognosis of PCa patients.

HetFCM: functional co-module discovery by heterogeneous network co-clustering

Functional molecular module (i.e., gene-miRNA co-modules and gene-miRNA-lncRNA triple-layer modules) analysis can dissect complex regulations underlying etiology or phenotypes. However, current module detection methods lack an appropriate usage and effective model of multi-omics data and cross-layer regulations of heterogeneous molecules, causing the loss of critical genetic information and corrupting the detection performance. In this study, we propose a heterogeneous network co-clustering framework (HetFCM) to detect functional co-modules. HetFCM introduces an attributed heterogeneous network to jointly model interplays and multi-type attributes of different molecules, and applies multiple variational graph autoencoders on the network to generate cross-layer association matrices, then it performs adaptive weighted co-clustering on association matrices and attribute data to identify co-modules of heterogeneous molecules. Empirical study on Human and Maize datasets reveals that HetFCM can find out co-modules characterized with denser topology and more significant functions, which are associated with human breast cancer (subtypes) and maize phenotypes (i.e., lipid storage, drought tolerance and oil content). HetFCM is a useful tool to detect co-modules and can be applied to multi-layer functional modules, yielding novel insights for analyzing molecular mechanisms. We also developed a user-friendly module detection and analysis tool and shared it at http://www.sdu-idea.cn/FMDTool.

ER Negative Breast Cancer and miRNA: There Is More to Decipher Than What the Pathologist Can See!

Breast cancer (BC), the most prevalent cancer in women, is a heterogenous disease. Despite advancements in BC diagnosis, prognosis, and therapeutics, survival rates have drastically decreased in the metastatic setting. Therefore, BC still remains a medical challenge. The evolution of high-throughput technology has highlighted gaps in the classification system of BCs. Of particular interest is the notorious triple negative BC, which was recounted as being heterogenous itself and it overlaps with distinct subtypes, namely molecular apocrine (MA) and luminal androgen (LAR) BCs. These subtypes are, even today, still misdiagnosed and poorly treated. As such, researchers and clinicians have been looking for ways through which to refine BC classification in order to properly understand the initiation, development, progression, and the responses to the treatment of BCs. One tool is biomarkers and, specifically, microRNA (miRNA), which are highly reported as associated with BC carcinogenesis. In this review, the diverse roles of miRNA in estrogen receptor negative (ER-) and androgen receptor positive (AR+) BC are depicted. While highlighting their oncogenic and tumor suppressor functions in tumor progression, we will discuss their diagnostic, prognostic, and predictive biomarker potentials, as well as their drug sensitivity/resistance activity. The association of several miRNAs in the KEGG-reported pathways that are related to ER-BC carcinogenesis is presented. The identification and verification of accurate miRNA panels is a cornerstone for tackling BC classification setbacks, as is also the deciphering of the carcinogenesis regulators of ER - AR + BC.

DLK2 Acts as a Potential Prognostic Biomarker for Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common RCC subtype with a high mortality. It has been reported that delta-like 1 homologue (DLK1) participates in the tumor microenvironmental remodeling of ccRCC, but the relationship between delta-like 2 homologue (DLK2, a DLK1 homologue) and ccRCC is still unclear. Thus, this study aims to investigate the role of DLK2 in the biological function and disease prognosis of ccRCC using bioinformatics analysis. The TNMplot database showed that DLK2 was upregulated in ccRCC tissues. From the UALCAN analysis, the overexpression of DLK2 was associated with advanced stage and high grade in ccRCC. Moreover, the Kaplan-Meier plotter (KM Plotter) database showed that DLK2 upregulation was associated with poor survival outcome in ccRCC. By the LinkedOmics analysis, DLK2 signaling may participated in the modulation of ccRCC extracellular matrix (ECM), cell metabolism, ribosome biogenesis, TGF-β signaling and Notch pathway. Besides, Tumor Immune Estimation Resource (TIMER) analysis showed that the macrophage and CD8⁺ T cell infiltrations were associated with good prognosis in ccRCC patients. Finally, DLK2 overexpression was associated with the reduced macrophage recruitments and the M1–M2 polarization of macrophage in ccRCC tissues. Together, DLK2 may acts as a novel biomarker, even therapeutic target in ccRCC. However, this study lacks experimental validation, and further studies are required to support this viewpoint.

Versatile role of miR-24/24-1*/24-2* expression in cancer and other human diseases

MiRNAs (miRs) have been proven to be well-validated therapeutic targets. Emerging evidence has demonstrated that intricate, intrinsic and paradoxical functions of miRs are context-dependent because of their multiple upstream regulators, broad spectrum of downstream molecular targets and distinct expression in various tissues, organs and disease states. Targeted therapy has become an emerging field of research. One key for the development of successful miR-based/targeted therapy is to acquire integrated knowledge of its regulatory network and its association with disease phenotypes to identify critical nodes of the underlying pathogenesis. Herein, we systematically summarized the comprehensive role of miR-24-3p (miR-24), along with its passenger strands miR-24-1-5p* (miR-24-1) and miR-24-2-5p* (miR-24-2), emphasizing their microenvironment, intracellular targets, and associated gene networks and regulatory phenotypes in 18 different cancer types and 13 types of other disorders. MiR-24 targets and regulates numerous genes in various cancer types and enhances the expression of several oncogenes (e.g., cMyc, BCL2 and HIF1), which are challenging in terms of druggability. In contrast, several tumor suppressor proteins (p21 and p53) have been reported to be downregulated by miR-24. MiR-24 also regulates the cell cycle and is associated with numerous cancer hallmarks such as apoptosis, proliferation, metastasis, invasion, angiogenesis, autophagy, drug resistance and other diseases pathogenesis. Overall, miR-24 plays an emerging role in the diagnosis, prognosis and pathobiology of various diseases. MiR-24 is a potential target for targeted therapy in the era of precision medicine, which expands the landscape of targetable macromolecules, including undruggable proteins.

The regulatory role of antisense lncRNAs in cancer

Antisense long non-coding RNAs (antisense lncRNAs), transcribed from the opposite strand of genes with either protein coding or non-coding function, were reported recently to play a crucial role in the process of tumor onset and development. Functionally, antisense lncRNAs either promote or suppress cancer cell proliferation, migration, invasion, and chemoradiosensitivity. Mechanistically, they exert their regulatory functions through epigenetic, transcriptional, post-transcriptional, and translational modulations. Simultaneously, because of nucleotide sequence complementarity, antisense lncRNAs have a special role on its corresponding sense gene. We highlight the functions and molecular mechanisms of antisense lncRNAs in cancer tumorigenesis and progression. We also discuss the potential of antisense lncRNAs to become cancer diagnostic biomarkers and targets for tumor treatment.

LncRNA ADAMTS9-AS1 Restrains the Aggressive Traits of Breast Carcinoma Cells via Sponging miR-513a-5p

Purpose

Long noncoding RNAs (lncRNAs) exert important functions in the progression of cancers. Currently, we aim to investigate the potential roles of lncRNA ADAM Metallopeptidase with Thrombospondin Type 1 Motif 9 Antisense RNA 1 (ADAMTS9-AS1) in breast carcinoma.

Materials and Methods

The expressions of ADAMTS9-AS1 and miR-513a-5p in breast carcinoma tissues and cell lines were detected using qRT-PCR. Cell Counting Kit-8 (CCK-8) and transwell assays were used to assess the viability and invasive ability of breast cancer cells. The direct interaction between ADAMTS9-AS1 and miR-513a-5p was predicted using bioinformatics tools. The target of miR-513a-5p, ZFP36 Ring Finger Protein (ZFP36) was validated by luciferase assay. The expression of ZFP36 was measured using Western blot assay. Breast cancer MDA-MB-231 cells growth in vivo was evaluated using xenograft tumor assay.

Results

ADAMTS9-AS1 was downregulated in breast cancer tissues as well as cell lines. Upregulation of ADAMTS9-AS1 suppressed the growth and invasiveness of breast carcinoma cells in vitro as well as inhibiting cellgrowth in vivo. Furthermore, ZFP36 was manifested as the target gene of miR-513a-5p and negatively modulated by ADAMTS9-AS1. In addition, overexpression of ADAMTS9-AS1 neutralized the promoting impact of miR-513a-5p on the aggressiveness of breast cancer cells.

Conclusion

In conclusion, lncRNA ADAMTS9-AS1 inhibited the aggressive phenotypes of breast carcinoma cells via sponging miR-513a-5p and regulating ZFP36.

Linc01094 Accelerates the Growth and Metastatic-Related Traits of Glioblastoma by Sponging miR-126-5p

Background

Long intergenic non-coding RNAs (lincRNAs) are associated with the progression of glioblastoma (GBM). However, how linc01094 contributes to the growth and metastatic phenotypes of GBM remains not fully studied.

Methods

The expression levels of linc01094 and miR-126-5p in GBM tissues and cell lines were analyzed using qRT-PCR. Loss-of-function experiments were performed to detect the biological activity of linc01094 in GBM. Glioblastoma tumor model was constructed to explore the impact of linc01094 on GBM cell growth in vivo. Linc01094-sponged miR-126-5p was certified by luciferase reporter assay and RNA immunoprecipitation (RIP). The protein expression of miRNA target gene, dynactin subunit 4 (DCTN4) was detected using Western blotting assay.

Results

Herein, we observed that the level of linc01094 was higher in GBM tissues. Silencing of linc01094 restrained the growth and invasive abilities of GBM cell. Moreover, linc01094 level was negatively associated with miR-126-5p level in GBM and linc01094 acted as a “sponge” for miR-126-5p. Reintroduction of linc01094 reversed the tumor-inhibiting effects of miR-126-5p in GBM.

Conclusion

Altogether, linc01094 promoted the tumorigenesis and metastatic phenotypes of GBM cell by modulating of miR-1126-5p/DCTN4 signaling axis.