Functional microRNA screening using a comprehensive lentiviral human microRNA expression library

ABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are a class of small regulatory RNAs that target sequences in messenger RNAs (mRNAs) to inhibit their protein output. Dissecting the complexities of miRNA function continues to prove challenging as miRNAs are predicted to have thousands of targets, and mRNAs can be targeted by dozens of miRNAs. RESULTS: To systematically address biological function of miRNAs, we constructed and validated a lentiviral miRNA expression library containing 660 currently annotated and 422 candidate human miRNA precursors. The miRNAs are expressed from their native genomic backbone, ensuring physiological processing. The arrayed layout of the library renders it ideal for high-throughput screens, but also allows pooled screening and hit picking. We demonstrate its functionality in both short- and long-term assays, and are able to corroborate previously described results of well-studied miRNAs. CONCLUSIONS: With the miRNA expression library we provide a versatile tool for the systematic elucidation of miRNA function.

A functional screen identifies specific microRNAs capable of inhibiting human melanoma cell viability

Malignant melanoma is an aggressive form of skin cancer with poor prognosis. Despite improvements in awareness and prevention of this disease, its incidence is rapidly increasing. MicroRNAs (miRNAs) are a class of small RNA molecules that regulate cellular processes by repressing messenger RNAs (mRNAs) with partially complementary target sites. Several miRNAs have already been shown to attenuate cancer phenotypes, by limiting proliferation, invasiveness, tumor angiogenesis, and stemness. Here, we employed a genome-scale lentiviral human miRNA expression library to systematically survey which miRNAs are able to decrease A375 melanoma cell viability. We highlight the strongest inhibitors of melanoma cell proliferation, including the miR-15/16, miR-141/200a and miR-96/182 families of miRNAs and miR-203. Ectopic expression of these miRNAs resulted in long-term inhibition of melanoma cell expansion, both in vitro and in vivo. We show specifically miR-16, miR-497, miR-96 and miR-182 are efficient effectors when introduced as synthetic miRNAs in several melanoma cell lines. Our study provides a comprehensive interrogation of miRNAs that interfere with melanoma cell proliferation and viability, and offers a selection of miRNAs that are especially promising candidates for application in melanoma therapy

Transcriptome analysis after miR-203 transfection.

<p>(A) A375 cells were transfected with either miR-203 or scrambled control and the transcriptome was quantified by RNA-Seq. All differentially expressed genes are plotted in the left graph, while only the differentially expressed genes containing miR-203 target sites are plotted in the right graph. Genes with miR-203 target sites are much more likely to be downregulated after miR-203 overexpression, and downregulated genes are highly enriched for genes with miR-203 target sites (p<0.0001). (B) One of the differentially expressed genes after miR-203 transfection is BIRC5. Repression was examined at both the mRNA and the protein level by qPCR (left) and Western blot (right) respectively. The BIRC5 transcript and its protein product survivin are both reduced after miR-203 transfection, but also after siBRAF transfection.</p

Endogenous miRNA expression and expression after lentiviral transduction in A375 cells.

<p>qPCR data are relative to U6 small RNA. Endogenous: empty vector-transduced, ectopic: miRNA-transduced.</p

A genome-wide screen for miRNAs that inhibit A375 melanoma cell growth.

<p>(A) Inhibition of melanoma growth was measured by means of cell viability and cell count. For each sample a B-score was calculated and B-scores from both assays are plotted against each other. There is a strong correlation between both assays. The B-scores for one miRNA, miR-518b, fell outside the range of the graph: they were −6 for cell count and −12 for cell viability. (B) A comparison with a normal distribution shows that the cell viability screen is sensitive for identifying growth-inhibitory miRNAs. A concomitant estimate of the false discovery rate is shown in grey fill (secondary axis). (C) 55 potential inhibitory miRNAs were tested in a confirmation screen against 11 empty vector samples and a population of 28 miRNAs with small or no effects in the primary screen. Box plots show values between 25^th and 75^th percentile in boxes, and the outermost values as whiskers. 20 of 55 inhibitory miRNAs scored better than any of the control miRNAs (below dashed line). *p = 6.8*10⁻⁵, **p = 1.6*10⁻⁶, ***p = 5.4*10⁻¹⁰. (D) Individual hits selected for follow-up, and their relative effect on cell viability. A virus containing a short-hairpin construct targeting BRAF was used as a positive control. Error bars represent standard deviation of three samples.</p

Comparison of miRNA-induced effects in several melanoma cell lines.

<p>Cells were transfected with 10 nM (A375 and A2058) or 30 nM (SK-MEL-28 and SK-MEL-173) RNA and cell viability was measured 72 hours after transfection. Data are plotted relative to a mock-infected control. Error bars represent standard deviation of three samples.</p

Effect of introduction of synthetic miRNAs on A375 viability.

<p>A375 cells were transfected with a range of concentrations of different miRNAs, and 72 hours after transfection viability was measured by means of MTS assay. Effects are compared to a scrambled control and a pool of 4 siRNAs against BRAF (siBRAF) as a positive control for A375 growth inhibition. Specific effects of miRNAs are best observed at concentrations of 10 nM. Each panel shows a different subset of miRNA mimics, although miRNAs were assessed in the same experiment. Error bars represent standard deviation of three samples. A representative of three experiments is shown.</p

External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium

BACKGROUND: Identification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands).METHODS: Aliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18-21, and KRAS exon 2-3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance.RESULTS: A broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of &gt;0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately.CONCLUSIONS: Divergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine.</p