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	<title>RNA modifications in cancer progression &#8211; Science</title>
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	<title>RNA modifications in cancer progression &#8211; Science</title>
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		<title>New Database Reveals Hidden RNA Editing in Cancer&#8217;s Tiny Messengers</title>
		<link>https://scienmag.com/new-database-reveals-hidden-rna-editing-in-cancers-tiny-messengers/</link>
		
		<dc:creator><![CDATA[Nathaniel Bowman]]></dc:creator>
		<pubDate>Sat, 26 Sep 2026 02:38:40 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[ADAR]]></category>
		<category><![CDATA[blood-based cancer diagnostics]]></category>
		<category><![CDATA[cancer biomarkers]]></category>
		<category><![CDATA[cancer extracellular vesicles]]></category>
		<category><![CDATA[early cancer detection biomarkers]]></category>
		<category><![CDATA[EVmiRED]]></category>
		<category><![CDATA[EVmiRED database]]></category>
		<category><![CDATA[exosomes]]></category>
		<category><![CDATA[extracellular vesicle cargo analysis]]></category>
		<category><![CDATA[extracellular vesicles]]></category>
		<category><![CDATA[liquid biopsy]]></category>
		<category><![CDATA[metastasis]]></category>
		<category><![CDATA[microRNA]]></category>
		<category><![CDATA[microRNA abundance in plasma]]></category>
		<category><![CDATA[microRNA chemical modifications]]></category>
		<category><![CDATA[microRNA editing in cancer]]></category>
		<category><![CDATA[oncology]]></category>
		<category><![CDATA[RNA editing]]></category>
		<category><![CDATA[RNA editing in tumor microvesicles]]></category>
		<category><![CDATA[RNA modifications in cancer progression]]></category>
		<category><![CDATA[seed region]]></category>
		<category><![CDATA[small RNA sequencing]]></category>
		<category><![CDATA[systemic analysis of cancer vesicles]]></category>
		<category><![CDATA[tumor-derived microRNA profiling]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=216119</guid>

					<description><![CDATA[Researchers have launched EVmiRED, the first database cataloging microRNA editing events in tumor-derived extracellular vesicles, revealing that this hidden layer of RNA modification is far more abundant than previously known.]]></description>
										<content:encoded><![CDATA[<p>Cancer cells are chatterboxes. Long before a tumor spreads to the liver, lung, or brain, it dispatches fleets of microscopic sacs called extracellular vesicles, loaded with molecular instructions that prime distant tissues for invasion. Now researchers have built the first database dedicated to a hidden layer of that conversation: the chemical editing of microRNAs carried inside these vesicles. The resource, called EVmiRED, suggests that RNA editing in tumor messengers is far more widespread than scientists had assumed, and it could point toward new blood-based tools for detecting cancer early.</p>
<p>The team behind EVmiRED, led by researchers at Sun Yat-Sen University in Guangzhou, China, published the work in the journal Advanced Biotechnology. Their database integrates two kinds of information that had never been systematically combined before: how abundant each microRNA is inside extracellular vesicles, and how often specific positions within those microRNAs have been chemically altered. The current release covers 683 samples drawn from 12 tumor types and cell lines, most of them derived from human plasma, the liquid portion of blood in which vesicles circulate throughout the body.</p>
<p>To understand why this matters, it helps to know what microRNAs do. These are short RNA molecules, roughly 22 chemical letters long, that act as genetic volume knobs. By binding to messenger RNAs, the working copies of genes, microRNAs can trigger their destruction or block their translation into proteins. Because a single microRNA can regulate hundreds of target genes, even small changes to its sequence can ripple through entire gene networks. Disrupted microRNA function is a hallmark of cancer, and microRNAs carried by tumor-derived vesicles can even reprogram non-metastatic cells into metastatic ones.</p>
<p>But microRNAs are not fixed scripts. Enzymes called ADARs can chemically convert adenosine, one of the four RNA letters, into inosine, which the cellular machinery reads as guanosine. This adenosine-to-inosine editing, or A-to-I editing, can change how a microRNA precursor is processed, how stable the mature molecule is, and, most consequentially, which genes it targets. The seed region of a microRNA, positions 2 through 8, does most of the target recognition work, and editing there can be transformative. Previous research found that the overlap between predicted mRNA targets before and after editing averages only about 3 percent, meaning a single editing event can essentially rewire the microRNA&#8217;s entire regulatory network.</p>
<p>Despite this power, editing events in vesicle-borne microRNAs had barely been cataloged. Before this study, only 11 editing sites had ever been reported in extracellular vesicle microRNAs. Existing vesicle databases such as Vesiclepedia, ExoCarta, and EVpedia list vesicle contents but say nothing about editing, while resources like EVmiRNA and EVAtlas track microRNA abundance without capturing chemical modifications. EVmiRED closes that gap, and dramatically so: its analysis pipeline identified 151 edited sites, roughly 15 percent of all editing events cataloged in the curated reference database MiREDiBase, with a median of 22 editing sites detected per sample.</p>
<p>Detecting editing in mature microRNAs is technically brutal. Because the molecules are so short, sequencing reads carrying mismatches map poorly to the reference genome, making genuine edits hard to distinguish from sequencing errors. The team sidestepped this problem by anchoring their search to a set of high-confidence editing sites previously identified with a method called miR-mmPCR-seq. They built custom reference databases of edited pre-microRNAs, in which adenosines at known editing positions were replaced with guanosines, and then aligned cleaned sequencing reads first against unedited references and then against edited ones. Only sites supported by at least two editing reads, editing levels of at least 5 percent, and statistically significant modification relative to the sequencing error rate made the cut.</p>
<p>The quality controls were equally strict. Datasets were filtered according to guidelines from the International Society for Extracellular Vesicles, and reads with too many ambiguous bases, abnormal lengths, or poor quality scores were discarded. Any dataset retaining fewer than one million clean reads was excluded. Expression levels were normalized to reads per million, and batch effects arising from different sequencing platforms were corrected using a statistical tool called pyComBat, with both raw and corrected values made available to users.</p>
<p>The results revealed a striking pattern. Within plasma-derived samples, the team identified 86 high-confidence editing sites, and editing events clustered most frequently at positions 2 and 5, both inside the seed region where target recognition happens. Even more surprising, 84 of those 86 sites sat on the 5p strand of microRNAs. Although 5p microRNAs make up only 29 percent of the expressed high-confidence vesicle microRNAs, they harbor the overwhelming majority of editing events. In cellular microRNAs, the researchers&#8217; earlier work had found no such strand bias, hinting that vesicles possess additional, still-unidentified regulatory mechanisms that govern which strand gets edited.</p>
<p>A case study built into the database demonstrates its diagnostic potential. Analyzing a public plasma dataset, the researchers used principal component analysis to show that microRNA editing profiles cleanly separated healthy individuals from cancer patients. Specific events stood out: position 2 of hsa-miR-181a-5p showed significantly increased seed-region editing in colorectal cancer compared with healthy controls, while the same position in hsa-miR-455-5p showed a significant decrease. In prostate cancer, position 1 of hsa-miR-100-5p, located in the 5&#8242; anchor region, showed elevated editing. Target predictions run separately on unedited and edited sequences indicated that these seed-region changes could substantially alter which genes each microRNA silences.</p>
<p>The web interface at evmired.sysu.edu.cn is designed for researchers without bioinformatics expertise, offering search, comparison, and download modules that let users query individual microRNAs, visualize expression and editing patterns, and compare predicted mRNA targets before and after editing. The authors caution that their conservative strategy, restricted to previously reported editing sites, likely represents a lower bound on the true extent of vesicle microRNA editing. Future versions aim to discover novel events by generating matched pre-microRNA and vesicle sequencing data, expand coverage to more cancer subtypes and disease stages, and incorporate longitudinal samples collected before, during, and after therapy. If those efforts succeed, the hidden edits riding inside cancer&#8217;s tiny messengers could become powerful signals in liquid biopsies for early detection, treatment monitoring, and personalized oncology.</p>
<p><strong>Subject of Research:</strong> A curated database of microRNA editing events in extracellular vesicles across human cancers</p>
<p><strong>Article Title:</strong> EVmiRED: a curated database of miRNA editing landscape in extracellular vesicles</p>
<p><strong>Article References:</strong> EVmiRED: a curated database of miRNA editing landscape in extracellular vesicles. (n.d.). <a href="https://doi.org/10.1007/s44307-026-00107-w" rel="noopener noreferrer">https://doi.org/10.1007/s44307-026-00107-w</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s44307-026-00107-w" rel="noopener noreferrer">10.1007/s44307-026-00107-w</a></p>
<p><strong>Keywords:</strong> extracellular vesicles, microRNA, RNA editing, ADAR, cancer biomarkers, liquid biopsy, exosomes, metastasis, seed region, small RNA sequencing, EVmiRED, oncology</p>
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