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Identification of biomarker microRNAs for predicting the response of colorectal cancer to neoadjuvant chemoradiotherapy based on microRNA regulatory network.

ABSTRACT: Preoperative radiotherapy or chemoradiotherapy has become a standard procedure for treatment of patients with locally advanced colorectal cancer (CRC). However, patients' responses to treatment are different and personalized. MicroRNAs (miRNAs) are promising biomarkers for predicting personalized responses. In this study, we collected 30 publicly reported miRNAs associated with chemoradiotherapy of CRC. We extracted 46 differentially expressed miRNAs from samples of responders and non-responders to preoperative radiotherapy from the Gene Expression Omnibus dataset (Student's t test, p-value < 0.05 and |fold-change| > 2). We performed a systematic and integrative bioinformatics analysis to identify biomarker miRNAs for prediction of CRC responses to chemoradiotherapy. Using the bioinformatics model, miR-198, miR-765, miR-671-5p, miR-630, miR-371-5p, miR-575, miR-202, miR-483-5p and miR-513a-5p were screened as putative biomarkers for treatment response. Literature validation and functional enrichment analysis were exploited to confirm the reliability of the predicted miRNAs. Quantitative polymerase chain reaction showed that seven of the candidates were significantly differentially expressed between radiosensitive and insensitive CRC cell lines. The unique target genes of miR-198 and miR-765 were altered significantly upon transfection of specific miRNA mimics in the radiosensitive cell line. These results demonstrated the predictive power of our model and suggested that miR-198, miR-765, miR-630, miR-371-5p, miR-575, miR-202 and miR-513a-5p could be used for predicting the response of CRC to preoperative chemoradiotherapy.

SUBMITTER: Zhu Y

PROVIDER: S-EPMC5356795 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Identification of biomarker microRNAs for predicting the response of colorectal cancer to neoadjuvant chemoradiotherapy based on microRNA regulatory network.

Zhu Yaqun Y Peng Qiliang Q Lin Yuxin Y Zou Li L Shen Peipei P Chen Feifei F Min Ming M Shen Li L Chen Jiajia J Shen Bairong B

Oncotarget 20170101 2

Preoperative radiotherapy or chemoradiotherapy has become a standard procedure for treatment of patients with locally advanced colorectal cancer (CRC). However, patients' responses to treatment are different and personalized. MicroRNAs (miRNAs) are promising biomarkers for predicting personalized responses. In this study, we collected 30 publicly reported miRNAs associated with chemoradiotherapy of CRC. We extracted 46 differentially expressed miRNAs from samples of responders and non-responders ...[more]

PMID: 27903980

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Project description:BACKGROUND: MicroRNA (miRNA) is a class of small RNAs of ~22nt which play essential roles in many crucial biological processes and numerous human diseases at post-transcriptional level of gene expression. It has been revealed that miRNA genes tend to be clustered, and the miRNAs organized into one cluster are usually transcribed coordinately. This implies a coordinated regulation mode exerted by clustered miRNAs. However, how the clustered miRNAs coordinate their regulations on large scale gene expression is still unclear. RESULTS: We constructed the miRNA-transcription factor regulatory network that contains the interactions between transcription factors (TFs), miRNAs and non-TF protein-coding genes, and made a genome-wide study on the regulatory coordination of clustered miRNAs. We found that there are two types of miRNA clusters, i.e. homo-clusters that contain miRNAs of the same family and hetero-clusters that contain miRNAs of various families. In general, the homo-clustered as well as the hetero-clustered miRNAs both exhibit coordinated regulation since the miRNAs belonging to one cluster tend to be involved in the same network module, which performs a relatively isolated biological function. However, the homo-clustered miRNAs show a direct regulatory coordination that is realized by one-step regulation (i.e. the direct regulation of the coordinated targets), whereas the hetero-clustered miRNAs show an indirect regulatory coordination that is realized by a regulation comprising at least three steps (e.g. the regulation on the coordinated targets by a miRNA through a sequential action of two TFs). The direct and indirect regulation target different categories of genes, the former predominantly regulating genes involved in emergent responses, the latter targeting genes that imply long-term effects. CONCLUSION: The genomic clustering of miRNAs is closely related to the coordinated regulation in the gene regulatory network. The pattern of regulatory coordination is dependent on the composition of the miRNA cluster. The homo-clustered miRNAs mainly coordinate their regulation rapidly, while the hetero-clustered miRNAs exert control with a delay. The diverse pattern of regulatory coordination suggests distinct roles of the homo-clustered and the hetero-clustered miRNAs in biological processes.

Project description:To date, little evidence of miRNA expression/deregulation in multiple myeloma (MM) has been reported. To characterize miRNA expression profiling of MM plasma cells (PCs) and integrate miRNA expression data with other molecular features of MM patients, global miRNA expression profiles were generated for PCs isolated from BM biopsies of 38 newly diagnosed MM, 2 plasma cell leukemia patients, and 3 healthy donors; the samples were also profiled for global gene expression, and nineteen of them underwent genome-wide DNA analysis using high-density SNP-microarrays. Differential miRNA expression patterns were mainly identified in association with the major IGH translocations: in particular, t(4;14) showed specific over-expression of let-7e, miR-125a-5p and miR-99b belonging to a cluster at 19q13.33. The occurrence of other lesions, such as 1q gain, 13q and 17p deletions, and hyperdiploidy, was less well characterized by specific miRNA signatures. Genome-wide analysis showed that some allelic imbalances led to the significantly altered expression of miRNAs located in the involved regions, such as let-7b at 22q13.31 loss and miR-142-3p at 17q22 gain. The integrative analysis based on computational target prediction, miRNA and mRNA profiling defined a network of putative functional miRNA-target regulatory relations supported by expression data. This series of microarray experiments contains the microRNA profiles of purified plasma cells (PCs) obtained from 3 normal donor (N), 38 multiple myeloma (MM) and 2 plasma cell leukemia (PCL) at diagnosis. PCs were purified from bone marrow specimens after red blood cell lysis with 0.86% ammonium chloride using CD138 immunomagnetic microbeads. The purity of the positively selected PCs was assessed by morphology and flow cytometry and was >90% in all cases. 500 nanograms of total RNA was processed in accordance with the manufacturer's protocols (Agilent Technologies) to generate Cy3-labeled RNA which were purified on chromatography columns (Micro Biospin 6, Bio-Rad, Hercules, CA) and hybridized on an Agilent microarray (G4470B) at 55Â°C for 17 hr in a rotating oven. Images at 5 um resolution were generated using an Agilent scanner G2505B. The Feature Extraction 9.5 software (Agilent Technologies) was used to obtain the raw microarray data. The human miRNAs included in the platform were annotated according to Sanger miRBase Release 12.0. After discarding non-human miRNAs, the data were normalized using the Aroma Light package for Bioconductor. To overcome scaling biases due to background subtraction, the data were converted to obtain positive values throughout the dataset, at a minimum value of 1. The global gene expression raw data used in this study was originally deposited as GSE13591 and renormalized for this study. The genome wide profile (DNA) analysis was originally deposited as GSE16121.

Dataset Information

Identification of biomarker microRNAs for predicting the response of colorectal cancer to neoadjuvant chemoradiotherapy based on microRNA regulatory network.

Publications

Identification of biomarker microRNAs for predicting the response of colorectal cancer to neoadjuvant chemoradiotherapy based on microRNA regulatory network.

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