Developmental profiling of microRNAs in the human embryonic inner ear

Abstract

Due to the extreme inaccessibility of fetal human inner ear tissue, defining of the microRNAs (miRNAs) that regulate development of the inner ear has relied on animal tissue. In the present study, we performed the first miRNA sequencing of otic precursors in human specimens. Using HTG miRNA Whole Transcriptome assays, we examined miRNA expression in the cochleovestibular ganglion (CVG), neural crest (NC), and otic vesicle (OV) from paraffin embedded (FFPE) human specimens in the Carnegie developmental stages 13–15. We found that in human embryonic tissues, there are different patterns of miRNA expression in the CVG, NC and OV. In particular, members of the miR-183 family (miR-96, miR-182, and miR-183) are differentially expressed in the CVG compared to NC and OV at Carnegie developmental stage 13. We further identified transcription factors that are differentially targeted in the CVG compared to the other tissues from stages 13–15, and we performed gene set enrichment analyses to determine differentially regulated pathways that are relevant to CVG development in humans. These findings not only provide insight into the mechanisms governing the development of the human inner ear, but also identify potential signaling pathways for promoting regeneration of the spiral ganglion and other components of the inner ear.

Distinct MicroRNA Profiles in the Perilymph and Serum of Patients With Menière's Disease

“…miRNA molecules are conserved throughout multiple species, have been identified in tissue and fluids throughout the body, and are known to play a significant role in various pathologies including cancer and other neurodegenerative diseases ( 25 , 26 ). miRNAs have also been shown to play a key role in inner ear development and show distinct expression patterns in patients with hearing loss compared to healthy controls, making them an intriguing biomarker ( 27 – 30 ). In previous work, we preliminary established Meniere's disease could be diagnosed based on perilymph miRNA profile alone, further validating miRNAs as a potential biomarker either through the perilymph or serum of patients ( 31 ).…”

Using Machine Learning to Predict Sensorineural Hearing Loss Based on Perilymph Micro RNA Expression Profile

“…Because miRNA play a critical role in cell gene expression, miRNA activity has been increasingly recognized as a critical component to many disease states making them a promising biomarker 5,23 . Interestingly, miRNA profiles have shown unique expression patterns to different diseases states, from heart failure 24 to individual cancers 7 (colon 25–27 , ovarian 28 , and clear cell carcinoma 29 ), neurodegenerative diseases 4 , different cell types 30 , and play an integral role embryonic development 8 . Pertinent to hearing loss, miRNA have shown to be a promising biomarker and diagnostic marker for otherwise difficult to diagnose neurodegenerative diseases such as Alzheimer’s and Parkinsons 4,5,31 .…”

“…MiRNAs are 19–23 base pair single stranded RNA sequences that regulate post translational gene expression 3 . These molecules have been identified in all body fluids and are recognized for their promising role as a diagnostic and prognostic marker for neurodegenerative diseases such as Alzheimer’s and various cancers 4–8 . We recently demonstrated that miRNA profiling within the inner ear is a feasible methodology and can potentially offer insight into what is occurring on a cellular and molecular level in various inner ear pathologies 9 .…”

A DNA damage repair gene‐associated signature predicts responses of patients with advanced soft‐tissue sarcoma to treatment with trabectedin

“…Negative control probes were used as quality control to evaluate baseline performance, as previously described by Chandly and colleagues. [17] Briefly, the mean of negative probes for each sample was calculated, and the difference between negative control average and the mean of all negative control probes was obtained (Δ mean ). Those samples with a Δ mean outside the bounds of +/-2 standard deviation were excluded from the study.…”