Dataset Information

Dual biomarkers long non-coding RNA GAS5 and microRNA-34a co-expression signature in common solid tumors.

ABSTRACT: Accumulating evidence indicates that non-coding RNAs including microRNAs (miRs) and long non-coding RNAs (lncRNAs) are aberrantly expressed in cancer, providing promising biomarkers for diagnosis, prognosis and/or therapeutic targets. We aimed in the current work to quantify the expression profile of miR-34a and one of its bioinformatically selected partner lncRNA growth arrest-specific 5 (GAS5) in a sample of Egyptian cancer patients, including three prevalent types of cancer in our region; renal cell carcinoma (RCC), glioblastoma (GB), and hepatocellular carcinoma (HCC) as well as to correlate these expression profiles with the available clinicopathological data in an attempt to clarify their roles in cancer. Quantitative real-time polymerase chain reaction analysis was applied. Different bioinformatics databases were searched to confirm the potential miRNAs-lncRNA interactions of the selected ncRNAs in cancer pathogenesis. The tumor suppressor lncRNA GAS5 was significantly under-expressed in the three types of cancer [0.08 (0.006-0.38) in RCC, p <0.001; 0.10 (0.003-0.89) in GB, p < 0.001; and 0.12 (0.015-0.74) in HCC, p < 0.001]. However, levels of miR-34a greatly varied according to the tumor type; it displayed an increased expression in RCC [4.05 (1.003-22.69), p <0.001] and a decreased expression in GB [0.35 (0.04-0.95), p <0.001]. Consistent to the computationally predicted miRNA-lncRNA interaction, negative correlations were observed between levels of GAS5 and miR-34a in RCC samples (r = -0.949, p < 0.001), GB (r = -0.518, p < 0.001) and HCC (r = -0.455, p = 0.013). Kaplan-Meier curve analysis revealed that RCC patients with down-regulated miR-34a levels had significantly poor overall survival than their corresponding (p < 0.05). Hierarchical clustering analysis showed RCC patients could be clustered by GAS5 and miR-34a co-expression profile. Our results suggest potential applicability of GAS5 and miR-34a with other conventional markers for various types of cancer. Further functional validation studies are warranted to confirm miR-34a/GAS5 interplay in cancer.

SUBMITTER: Toraih EA

PROVIDER: S-EPMC6173395 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Dual biomarkers long non-coding RNA GAS5 and microRNA-34a co-expression signature in common solid tumors.

Toraih Eman A EA Alghamdi Saleh Ali SA El-Wazir Aya A Hosny Marwa M MM Hussein Mohammad H MH Khashana Moataz S MS Fawzy Manal S MS

PloS one 20181005 10

Accumulating evidence indicates that non-coding RNAs including microRNAs (miRs) and long non-coding RNAs (lncRNAs) are aberrantly expressed in cancer, providing promising biomarkers for diagnosis, prognosis and/or therapeutic targets. We aimed in the current work to quantify the expression profile of miR-34a and one of its bioinformatically selected partner lncRNA growth arrest-specific 5 (GAS5) in a sample of Egyptian cancer patients, including three prevalent types of cancer in our region; ren ...[more]

PMID: 30289954

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Project description:Metastasis is the number one cause of cancer deaths. Expression microarrays have been widely used to study metastasis in various types of cancer. We hypothesize that a meta-analysis of publicly available gene expression datasets in various tumor types can identify a signature of metastasis that is common to multiple tumor types. This common signature of metastasis may help us to understand the shared steps in the metastatic process and identify useful biomarkers that could predict metastatic risk.We identified 18 publicly available gene expression datasets in the Oncomine database comparing distant metastases to primary tumors in various solid tumors which met our eligibility criteria. We performed a meta-analysis using a modified permutation counting method in order to obtain a common gene signature of metastasis. We then validated this signature in independent datasets using gene set expression comparison analysis with the LS-statistic.A common metastatic signature of 79 genes was identified in the metastatic lesions compared with primaries with a False Discovery Proportion of less than 0.1. Interestingly, all the genes in the signature, except one, were significantly down-regulated, suggesting that overcoming metastatic suppression may be a key feature common to all metastatic tumors. Pathway analysis of the significant genes showed that the genes were involved in known metastasis-associated pathways, such as integrin signaling, calcium signaling, and VEGF signaling. To validate the signature, we used an additional six expression datasets that were not used in the discovery study. Our results showed that the signature was significantly enriched in four validation sets with p-values less than 0.05.We have modified a previously published meta-analysis method and identified a common metastatic signature by comparing primary tumors versus metastases in various tumor types. This approach, as well as the gene signature identified, provides important insights to the common metastatic process and a foundation for future discoveries that could have broad application, such as drug discovery, metastasis prediction, and mechanistic studies.

Dataset Information

Dual biomarkers long non-coding RNA GAS5 and microRNA-34a co-expression signature in common solid tumors.

Publications

Dual biomarkers long non-coding RNA GAS5 and microRNA-34a co-expression signature in common solid tumors.

Similar Datasets

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