Literature DB >> 26484292

Microarray expression profile of circular RNAs in human pancreatic ductal adenocarcinoma.

Shibin Qu1, Wenjie Song1, Xisheng Yang1, Jianlin Wang1, Ruohan Zhang1, Zhuochao Zhang1, Hongtao Zhang1, Haimin Li1.   

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains a common and deadly cancer. Despite numerous efforts, no reliable biomarker is available for daily clinical practice. Circular RNAs (circRNAs) are an abundant, stable and conserved class of RNA molecules that exhibit tissue/developmental-stage-specific expression (Salzman et al., 2012; Jeck et al., 2013; Memczak et al., 2013). CircRNAs play a crucial role in disease, especially in cancer, and provide new potential diagnostic and therapeutic targets for disease (Hansen et al., 2013; Qu et al., 2015).This research was designed to explore the expression profile of circRNAs in PDAC to serve as new diagnosis and treatment strategies for PDAC. Microarray and sample annotation data were deposited in Gene Expression Omnibus (GEO) under accession number GSE69362.

Entities:  

Keywords:  Circular RNAs; Microarray; Noncoding RNAs; Pancreatic cancer

Year:  2015        PMID: 26484292      PMCID: PMC4583707          DOI: 10.1016/j.gdata.2015.07.017

Source DB:  PubMed          Journal:  Genom Data        ISSN: 2213-5960


Direct link to deposited data

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE69362

Experimental design, materials and methods

Tissue samples

The Ethics Review Board of Xijing Hospital (No: XJYYLL-2015075) approved the study. Tissue samples were prospectively collected from patients undergoing operation at the Department of Hepatobiliary Surgery at the Xijing Hospital. Tumor and adjacent normal pancreatic tissue samples were snap-frozen in liquid nitrogen immediately after resection and stored at − 130 °C until use. Histology of the tissue specimen was confirmed by two uropathologists.

RNA preparation

Total RNA was isolated from 4 PDAC samples and paired adjacent normal tissues using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), according to the manufacturer's protocol. Total RNA from each specimen was quantified and quality was verified using NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA). Additionally, RNA integrity was assessed by electrophoresis on a denaturing agarose gel.

Labeling and hybridization

Sample labeling and array hybridization were performed according to the manufacturer's protocol (Arraystar, Rockville, Maryland, USA). In short, circRNAs were treated with Ribonuclease R (RNase R) to remove linear RNAs according to the manufacturer's protocol (Epicenter, Madison, WI, USA). Then, each sample was amplified and transcribed into fluorescent cRNA utilizing a random priming method with a Super RNA Labeling Kit (Arraystar). The labeled cRNAs were purified using an RNeasy Mini Kit (Qiagen, Hilden, Germany). The concentration and specific activity of the labeled cRNAs (pmol Cy3/μg cRNA) were measured using NanoDrop ND-1000. Then, 1 μg of each labeled cRNA was fragmented by adding 5 μl 10 × Blocking Agent and 1 μl of 25 × Fragmentation Buffer. The mixture was heated at 60 °C for 30 min, and 25 μl 2 × Hybridization buffer was added to dilute the labeled cRNA. Then, 50 μl of the hybridization solution was dispensed into the gasket slide, which was assembled with Human Circular RNA Array slides. The slides were incubated for 17 h at 65 °C in an Agilent Hybridization Oven. The hybridized arrays were washed, fixed and scanned using an Agilent G2505C Scanner.

Microarray and quality control

Scanned images were imported into Agilent Feature Extraction software (version 11.0.1.1) for raw data extraction. Quantile normalization of raw data and subsequent data processing were performed using the R software package (R version 3.1.2). After quantile normalization of the raw data, low intensity filtering was performed, and circRNAs with at least 2 out of 8 samples that had flags in “P” or “M” (“All Targets Value”) were retained for further analyses. The log2-ratio was used for quantile normalization. CircRNAs differentially expressed between the two groups were conveniently estimated by fold-change filtering and Student's t-test. CircRNAs exhibiting fold changes ≥ 2.0 and p-values ≤ 0.05 were selected as significantly differentially expressed circRNAs. The experiment workflow is listed in Fig. 1.
Fig. 1

Experiment workflow of microarray expression profile of circular RNAs.

Discussion

Large amounts of circRNAs are recently discovered and represent a new special class of endogenous noncoding RNA. Recent researches have revealed that circRNAs are an abundant, stable, diverse and conserved class of RNA molecules [1], [2], [3]. Moreover, circRNAs can function as miRNA sponges or regulate parent gene expression to affect disease initiation and progression [4], [5], [6], [7]. These studies indicate that circRNAs have great potential to become diagnostic or predictive biomarkers of disease and provide new insights into the treatment of diseases. In this study, we have explored the expression profile of circRNAs in 4 PDAC samples and paired adjacent normal tissues. We have also revealed that the circRNA expression signatures of PDAC are dysregulated. The identification of novel differentially expressed circRNAs is a crucial step towards better understanding of PDAC. These findings indicate that circRNAs can be involved in the initiation and progression of PDAC.

Conflict of interest

The authors declare that there are no conflicts of interest.
Specifications
Organism/cell line/tissueHomo sapiens/pancreatic ductal adenocarcinoma and adjacent normal tissues
SexMale and female
Sequencer or array typeArraystar Human CircRNA Array (8 × 15K, Arraystar)
Data formatRaw and analyzed
Experimental factorsTumor vs. corresponding normal tissues from 4 pancreatic ductal adenocarcinoma patients
Experimental featuresMicroarray expression profile analysis of circular RNAs in human pancreatic ductal adenocarcinoma
ConsentAll patients provided written informed consent
Sample source locationXi'an, China
  7 in total

Review 1.  Circular RNA and miR-7 in cancer.

Authors:  Thomas B Hansen; Jørgen Kjems; Christian K Damgaard
Journal:  Cancer Res       Date:  2013-09-06       Impact factor: 12.701

Review 2.  Circular RNA: A new star of noncoding RNAs.

Authors:  Shibin Qu; Xisheng Yang; Xiaolei Li; Jianlin Wang; Yuan Gao; Runze Shang; Wei Sun; Kefeng Dou; Haimin Li
Journal:  Cancer Lett       Date:  2015-06-05       Impact factor: 8.679

3.  Exon-intron circular RNAs regulate transcription in the nucleus.

Authors:  Zhaoyong Li; Chuan Huang; Chun Bao; Liang Chen; Mei Lin; Xiaolin Wang; Guolin Zhong; Bin Yu; Wanchen Hu; Limin Dai; Pengfei Zhu; Zhaoxia Chang; Qingfa Wu; Yi Zhao; Ya Jia; Ping Xu; Huijie Liu; Ge Shan
Journal:  Nat Struct Mol Biol       Date:  2015-02-09       Impact factor: 15.369

4.  Circular RNAs are abundant, conserved, and associated with ALU repeats.

Authors:  William R Jeck; Jessica A Sorrentino; Kai Wang; Michael K Slevin; Christin E Burd; Jinze Liu; William F Marzluff; Norman E Sharpless
Journal:  RNA       Date:  2012-12-18       Impact factor: 4.942

5.  Circular RNAs are a large class of animal RNAs with regulatory potency.

Authors:  Sebastian Memczak; Marvin Jens; Antigoni Elefsinioti; Francesca Torti; Janna Krueger; Agnieszka Rybak; Luisa Maier; Sebastian D Mackowiak; Lea H Gregersen; Mathias Munschauer; Alexander Loewer; Ulrike Ziebold; Markus Landthaler; Christine Kocks; Ferdinand le Noble; Nikolaus Rajewsky
Journal:  Nature       Date:  2013-02-27       Impact factor: 49.962

6.  Natural RNA circles function as efficient microRNA sponges.

Authors:  Thomas B Hansen; Trine I Jensen; Bettina H Clausen; Jesper B Bramsen; Bente Finsen; Christian K Damgaard; Jørgen Kjems
Journal:  Nature       Date:  2013-02-27       Impact factor: 49.962

7.  Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types.

Authors:  Julia Salzman; Charles Gawad; Peter Lincoln Wang; Norman Lacayo; Patrick O Brown
Journal:  PLoS One       Date:  2012-02-01       Impact factor: 3.240

  7 in total
  49 in total

1.  Research progress on circularRNAs in pancreatic cancer: emerging but promising.

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Journal:  Cancer Biol Ther       Date:  2019-05-28       Impact factor: 4.742

2.  Circular RNA mediates cardiomyocyte death via miRNA-dependent upregulation of MTP18 expression.

Authors:  Kun Wang; Tian-Yi Gan; Na Li; Cui-Yun Liu; Lu-Yu Zhou; Jin-Ning Gao; Chao Chen; Kao-Wen Yan; Murugavel Ponnusamy; Yu-Hui Zhang; Pei-Feng Li
Journal:  Cell Death Differ       Date:  2017-05-12       Impact factor: 15.828

3.  Downregulation of lncRNA-ATB correlates with clinical progression and unfavorable prognosis in pancreatic cancer.

Authors:  Shibin Qu; Xisheng Yang; Wenjie Song; Wei Sun; Xiaolei Li; Jianlin Wang; Yue Zhong; Runze Shang; Bai Ruan; Zhuochao Zhang; Xuan Zhang; Haimin Li
Journal:  Tumour Biol       Date:  2015-10-19

4.  Potential functions and implications of circular RNA in gastrointestinal cancer.

Authors:  Xiaoxia Ren; Yongxing Du; Lei You; Yupei Zhao
Journal:  Oncol Lett       Date:  2017-10-03       Impact factor: 2.967

Review 5.  Circular RNAs in cardiovascular diseases.

Authors:  Xiaohan Mei; Shi-You Chen
Journal:  Pharmacol Ther       Date:  2021-09-27       Impact factor: 12.310

6.  Screening of up- and downregulation of circRNAs in HBV-related hepatocellular carcinoma by microarray.

Authors:  Shichang Cui; Zhiling Qian; Yuhan Chen; Lei Li; Peng Li; Huiguo Ding
Journal:  Oncol Lett       Date:  2017-10-25       Impact factor: 2.967

Review 7.  Circular RNAs as potential biomarkers for cancer diagnosis and therapy.

Authors:  Fengling Wang; Adil J Nazarali; Shaoping Ji
Journal:  Am J Cancer Res       Date:  2016-06-01       Impact factor: 6.166

Review 8.  Circular RNAs as Promising Biomarkers: A Mini-Review.

Authors:  Nadiah Abu; Rahman Jamal
Journal:  Front Physiol       Date:  2016-08-18       Impact factor: 4.566

Review 9.  Circular RNAs are a novel type of non-coding RNAs in ROS regulation, cardiovascular metabolic inflammations and cancers.

Authors:  Fatma Saaoud; Charles Drummer I V; Ying Shao; Yu Sun; Yifan Lu; Keman Xu; Dong Ni; Xiaohua Jiang; Hong Wang; Xiaofeng Yang
Journal:  Pharmacol Ther       Date:  2020-10-24       Impact factor: 12.310

10.  Expression Profiles of Circular RNAs in Human Papillary Thyroid Carcinoma Based on RNA Deep Sequencing.

Authors:  Chengzhou Lv; Wei Sun; Jiapeng Huang; Yuan Qin; Xiaoyu Ji; Hao Zhang
Journal:  Onco Targets Ther       Date:  2021-06-21       Impact factor: 4.147

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