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Multiomic analysis of microRNA-mediated regulation reveals a proliferative axis involving miR-10b in fibrolamellar carcinoma
Adam B. Francisco, … , Nabeel Bardeesy, Praveen Sethupathy
Adam B. Francisco, … , Nabeel Bardeesy, Praveen Sethupathy
Published April 28, 2022
Citation Information: JCI Insight. 2022;7(11):e154743. https://doi.org/10.1172/jci.insight.154743.
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Research Article Oncology

Multiomic analysis of microRNA-mediated regulation reveals a proliferative axis involving miR-10b in fibrolamellar carcinoma

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Abstract

Fibrolamellar carcinoma (FLC) is an aggressive liver cancer primarily afflicting adolescents and young adults. Most patients with FLC harbor a heterozygous deletion on chromosome 19 that leads to the oncogenic gene fusion, DNAJB1-PRKACA. There are currently no effective therapeutics for FLC. To address that, it is critical to gain deeper mechanistic insight into FLC pathogenesis. We assembled a large sample set of FLC and nonmalignant liver tissue (n = 52) and performed integrative multiomic analysis. Specifically, we carried out small RNA sequencing to define altered microRNA expression patterns in tumor samples and then coupled this analysis with RNA sequencing and chromatin run-on sequencing data to identify candidate master microRNA regulators of gene expression in FLC. We also evaluated the relationship between DNAJB1-PRKACA and microRNAs of interest in several human and mouse cell models. Finally, we performed loss-of-function experiments for a specific microRNA in cells established from a patient-derived xenograft (PDX) model. We identified miR-10b-5p as the top candidate pro-proliferative microRNA in FLC. In multiple human cell models, overexpression of DNAJB1-PRKACA led to significant upregulation of miR-10b-5p. Inhibition of miR-10b in PDX-derived cells increased the expression of several potentially novel target genes, concomitant with a significant reduction in metabolic activity, proliferation, and anchorage-independent growth. This study highlights a potentially novel proliferative axis in FLC and provides a rich resource for further investigation of FLC etiology.

Authors

Adam B. Francisco, Matt Kanke, Andrew P. Massa, Timothy A. Dinh, Ramja Sritharan, Khashayar Vakili, Nabeel Bardeesy, Praveen Sethupathy

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Figure 3

miR-10b is among the most upregulated microRNAs in both primary and metastatic FLC.

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miR-10b is among the most upregulated microRNAs in both primary and meta...
(A) Principal component analysis of VST normalized counts with tumor type information overlaid. NML (n = 10), primary (n = 18), and metastatic (n = 19) samples are shown in green, yellow, and orange, respectively. (B) Principal component analysis of VST normalized counts with metastatic location information overlaid. Extrahepatic, liver, lung, lymph node, peritoneal, and unknown locations are shown red, brown, green, teal, blue, and purple, respectively. (C) Volcano plot showing microRNAs that are significantly differentially expressed in primary FLC versus NML (average normalized counts > 1000 in either NML or primary FLC). Dashed lines represent the log2 FC of expression –2/+2 (vertical) and adjusted P = 0.05 (horizontal). Up- or downregulated microRNAs are colored red or blue, respectively. (D) Volcano plot showing microRNAs that are significantly differentially expressed in metastatic FLC versus NML; analysis criteria identical to C. Dashed lines represent the log2 FC of expression –2/+2 (vertical) and adjusted P = 0.05 (horizontal). Up- or downregulated microRNAs are colored red or blue, respectively. (E). Heatmap showing the expression of microRNAs upregulated in primary FLC versus NML. MicroRNAs are listed in rows and individual patients are listed in columns. Expression is scaled by row with a max/min of +2/–2 shown. (F) Heatmap showing the expression of upregulated microRNAs in metastatic FLC versus NML; sample arrangement is identical to E. Expression is scaled by row with a max/min of +2/–2 shown.

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