Next generation sequencing for profiling expression of miRNAs: technical progress and applications in drug development

Liu, Jie; Jennings, Steven F.; Tong, Weida; Hong, Huasheng

doi:10.4236/jbise.2011.410083

Cited by 46 publications

(25 citation statements)

References 70 publications

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“…These problems are now overcome by Next Generation Sequencing (NGS) platforms [ 24 ]. NGS also offers the advantage of capturing not just miRNAs but a whole repertoire of small RNAs, even those present in low abundance [ 25 ], thus enabling a comprehensive analysis of small RNAome. However, despite several advantages offered by NGS, only few studies have utilized NGS platform to identify prognostic markers for BC [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer

et al. 2015

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BackgroundPrognostication of Breast Cancer (BC) relies largely on traditional clinical factors and biomarkers such as hormone or growth factor receptors. Due to their suboptimal specificities, it is challenging to accurately identify the subset of patients who are likely to undergo recurrence and there remains a major need for markers of higher utility to guide therapeutic decisions. MicroRNAs (miRNAs) are small non-coding RNAs that function as post-transcriptional regulators of gene expression and have shown promise as potential prognostic markers in several cancer types including BC.ResultsIn our study, we sequenced miRNAs from 104 BC samples and 11 apparently healthy normal (reduction mammoplasty) breast tissues. We used Case–control (CC) and Case-only (CO) statistical paradigm to identify prognostic markers. Cox-proportional hazards regression model was employed and risk score analysis was performed to identify miRNA signature independent of potential confounders. Representative miRNAs were validated using qRT-PCR. Gene targets for prognostic miRNAs were identified using in silico predictions and in-house BC transcriptome dataset. Gene ontology terms were identified using DAVID bioinformatics v6.7. A total of 1,423 miRNAs were captured. In the CC approach, 126 miRNAs were retained with predetermined criteria for good read counts, from which 80 miRNAs were differentially expressed. Of these, four and two miRNAs were significant for Overall Survival (OS) and Recurrence Free Survival (RFS), respectively. In the CO approach, from 147 miRNAs retained after filtering, 11 and 4 miRNAs were significant for OS and RFS, respectively. In both the approaches, the risk scores were significant after adjusting for potential confounders. The miRNAs associated with OS identified in our cohort were validated using an external dataset from The Cancer Genome Atlas (TCGA) project. Targets for the identified miRNAs were enriched for cell proliferation, invasion and migration.ConclusionsThe study identified twelve non-redundant miRNAs associated with OS and/or RFS. These signatures include those that were reported by others in BC or other cancers. Importantly we report for the first time two new candidate miRNAs (miR-574-3p and miR-660-5p) as promising prognostic markers. Independent validation of signatures (for OS) using an external dataset from TCGA further strengthened the study findings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1899-0) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer

et al. 2015

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“…There are some sources of microarray genotyping errors [ 11 ], including batch effect [ 12 , 13 , 14 , 15 ] and variation in genotype calling algorithms [ 16 , 17 , 18 ], which are considered part of the reason for why GWAS have not fully satisfied the expectations of scientists to completely decipher the human genetic architecture. Recently, next-generation sequencing (NGS) technologies have emerged as the most popular tools for deciphering human genetic variations [ 19 ], profiling miRNA [ 20 ], and identifying genetic biomarkers for clinical diagnosis [ 21 ] and prognosis [ 22 ]. Quality control is important for better utilization of NGS data [ 23 ] and proteomics data [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Alignment of Short Reads: A Crucial Step for Application of Next-Generation Sequencing Data in Precision Medicine

et al. 2015

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Precision medicine or personalized medicine has been proposed as a modernized and promising medical strategy. Genetic variants of patients are the key information for implementation of precision medicine. Next-generation sequencing (NGS) is an emerging technology for deciphering genetic variants. Alignment of raw reads to a reference genome is one of the key steps in NGS data analysis. Many algorithms have been developed for alignment of short read sequences since 2008. Users have to make a decision on which alignment algorithm to use in their studies. Selection of the right alignment algorithm determines not only the alignment algorithm but also the set of suitable parameters to be used by the algorithm. Understanding these algorithms helps in selecting the appropriate alignment algorithm for different applications in precision medicine. Here, we review current available algorithms and their major strategies such as seed-and-extend and q-gram filter. We also discuss the challenges in current alignment algorithms, including alignment in multiple repeated regions, long reads alignment and alignment facilitated with known genetic variants.

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“…Therefore, it is necessary to identify potential biomarkers that may open up new avenues for alternative therapeutic approach. The role of miRNAs in regulating angiogenesis and in stroke pathogenesis has been reported(Kuehbacher et al, 2008;Liu et al, 2011;Wang et al, 2008; 2015; Yuan et al, 2016), however their relevance to brain vascular malformations notably, CCM have not been so far elucidated. Here, we report for the first time genome-wide miRNA expression profiling in CCM patients and believe our dataset will be valuable for future research to discern the role of miRNAs in CCM pathology.Using a comprehensive genome-wide sequencing approach, we identified a total of 764 miRNAs expressed in CCM.…”

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confidence: 99%

Genome-Wide Sequencing Reveals MicroRNAs Downregulated in Cerebral Cavernous Malformations

et al. 2017

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Cerebral cavernous malformations (CCM) are vascular lesions associated with loss-of-function mutations in one of the three genes encoding KRIT1 (CCM1), CCM2, and PDCD10. Recent understanding of the molecular mechanisms that lead to CCM development is limited. The role of microRNAs (miRNAs) has been demonstrated in vascular pathologies resulting in loss of tight junction proteins, increased vascular permeability and endothelial cell dysfunction. Since the relevance of miRNAs in CCM pathophysiology has not been elucidated, the primary aim of the study was to identify the miRNA-mRNA expression network associated with CCM. Using small RNA sequencing, we identified a total of 764 matured miRNAs expressed in CCM patients compared to the healthy brains. The expression of the selected miRNAs was validated by qRT-PCR, and the results were found to be consistent with the sequencing data. Upon application of additional statistical stringency, five miRNAs (let-7b-5p, miR-361-5p, miR-370-3p, miR-181a-2-3p, and miR-95-3p) were prioritized to be top CCM-relevant miRNAs. Further in silico analyses revealed that the prioritized miRNAs have a direct functional relation with mRNAs, such as MIB1, HIF1A, PDCD10, TJP1, OCLN, HES1, MAPK1, VEGFA, EGFL7, NF1, and ENG, which are previously characterized as key regulators of CCM pathology. To date, this is the first study to investigate the role of miRNAs in CCM pathology. By employing cutting edge molecular and in silico analyses on clinical samples, the current study reports global miRNA expression changes in CCM patients and provides a rich source of data set to understand detailed molecular machinery involved in CCM pathophysiology.

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Next generation sequencing for profiling expression of miRNAs: technical progress and applications in drug development

Cited by 46 publications

References 70 publications

Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer

Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer

Alignment of Short Reads: A Crucial Step for Application of Next-Generation Sequencing Data in Precision Medicine

Genome-Wide Sequencing Reveals MicroRNAs Downregulated in Cerebral Cavernous Malformations

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