PapersFlow Research Brief
MicroRNA in disease regulation
Research Guide
What is MicroRNA in disease regulation?
MicroRNA in disease regulation is the study of how microRNAs (small endogenous RNAs) control gene expression programs whose dysregulation contributes to disease phenotypes, especially cancer initiation, progression, and treatment response.
The MicroRNA in disease regulation literature comprises 142,592 works focused on microRNA biogenesis, target recognition rules, and downstream effects on mRNA repression in pathological contexts, prominently cancer. "MicroRNAs: Target Recognition and Regulatory Functions" (2009) and "Most mammalian mRNAs are conserved targets of microRNAs" (2008) describe how microRNAs pair to mRNAs to direct post-transcriptional repression and why conserved targeting implies broad regulatory reach across genes. "MicroRNA expression profiles classify human cancers" (2005) establishes that microRNA expression patterns can be used to classify human cancers, framing microRNAs as both mechanistic regulators and clinically relevant molecular readouts.
Topic Hierarchy
Research Sub-Topics
MicroRNA Biogenesis Pathways
This sub-topic elucidates Drosha/DGCR8 processing, Dicer cleavage, and Argonaute loading in canonical and non-canonical miRNA pathways. Researchers use CRISPR screens and structural biology to uncover regulatory mechanisms.
MicroRNA Target Prediction Algorithms
This sub-topic develops and validates computational tools like TargetScan and miRanda for seed matching and conservation analysis. Researchers integrate CLIP-seq data to refine prediction accuracy.
MicroRNAs as Cancer Biomarkers
This sub-topic profiles circulating and tissue miRNAs for diagnosis, prognosis, and therapy response prediction in cancers. Researchers conduct meta-analyses of expression arrays and validate via qPCR.
MicroRNA Therapeutics in Oncology
This sub-topic explores miRNA mimics, antagomirs, and delivery systems like LNPs for tumor suppression or metastasis inhibition. Researchers test preclinical efficacy and toxicity in PDX models.
Circular RNA MicroRNA Sponges
This sub-topic investigates circRNAs competing endogenous RNA (ceRNA) networks sequestering oncogenic miRNAs in cancer. Researchers map circRNA-miRNA interactomes using AGO-CLIP and reporter assays.
Why It Matters
MicroRNA biology matters because it links a compact regulatory layer (microRNA–mRNA interactions) to measurable disease signatures and actionable biomedical uses such as tumor classification and extracellular vesicle (EV) biomarker development. For classification, "MicroRNA expression profiles classify human cancers" (2005) demonstrated that microRNA expression profiles can classify human cancers, motivating diagnostic and stratification workflows that use microRNA panels as molecular features rather than single-gene markers. For biofluid and intercellular-communication applications, EV-focused work provides operational standards and biological rationale: "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" (2018) defines community guidelines for EV studies, while "The biology , function , and biomedical applications of exosomes" (2020) describes exosomes as EVs carrying RNA cargo that can affect distant cells after uptake. Together, these papers support disease-regulation and biomarker pipelines in which microRNAs are profiled either directly from tissues (for classification) or from EV-associated RNA in biofluids (for minimally invasive sampling), provided studies follow standardized EV characterization and reporting practices (MISEV2018).
Reading Guide
Where to Start
Start with Victor Ambros’s "The functions of animal microRNAs" (2004) because it establishes what microRNAs are and the core idea of post-transcriptional regulation that underpins later disease-focused work.
Key Papers Explained
Ambros’s "The functions of animal microRNAs" (2004) introduces fundamental microRNA biology that is then mechanistically specified by Lewis, Burge, and Bartel’s "Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets" (2005), which formalizes seed-based targeting rules. Bartel’s "MicroRNAs: Target Recognition and Regulatory Functions" (2009) integrates targeting principles into a broader regulatory framework, while Friedman, Farh, Burge, and Bartel’s "Most mammalian mRNAs are conserved targets of microRNAs" (2008) emphasizes the scale and conservation of targeting, explaining why microRNA dysregulation can have wide disease impact. For disease-facing readouts and applications, Lü et al.’s "MicroRNA expression profiles classify human cancers" (2005) connects microRNA expression patterns to cancer classification, and Théry et al.’s "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" (2018) plus Kalluri and LeBleu’s "The biology , function , and biomedical applications of exosomes" (2020) situate microRNAs within EV/exosome biology and translational measurement contexts.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Advanced study often combines (i) mechanistic targeting rules from "MicroRNAs: Target Recognition and Regulatory Functions" (2009) and "Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets" (2005), (ii) network-scale consequences suggested by "Most mammalian mRNAs are conserved targets of microRNAs" (2008), and (iii) clinically oriented sampling/standardization via EV frameworks from "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" (2018) and the application focus in "The biology , function , and biomedical applications of exosomes" (2020). A parallel frontier is indirect regulation through circular RNAs described in "Circular RNAs are a large class of animal RNAs with regulatory potency" (2013) and "Natural RNA circles function as efficient microRNA sponges" (2013), which complicates causal interpretation of microRNA effects in disease.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | MicroRNAs: Target Recognition and Regulatory Functions | 2009 | Cell | 20.0K | ✓ |
| 2 | Conserved Seed Pairing, Often Flanked by Adenosines, Indicates... | 2005 | Cell | 11.8K | ✓ |
| 3 | The functions of animal microRNAs | 2004 | Nature | 10.7K | ✕ |
| 4 | Minimal information for studies of extracellular vesicles 2018... | 2018 | Journal of Extracellul... | 10.6K | ✓ |
| 5 | MicroRNA expression profiles classify human cancers | 2005 | Nature | 9.5K | ✕ |
| 6 | The biology <b>,</b> function <b>,</b> and biomedical applicat... | 2020 | Science | 9.5K | ✓ |
| 7 | Most mammalian mRNAs are conserved targets of microRNAs | 2008 | Genome Research | 8.4K | ✓ |
| 8 | Natural RNA circles function as efficient microRNA sponges | 2013 | Nature | 8.3K | ✕ |
| 9 | Circular RNAs are a large class of animal RNAs with regulatory... | 2013 | Nature | 8.3K | ✕ |
| 10 | Shedding light on the cell biology of extracellular vesicles | 2018 | Nature Reviews Molecul... | 7.9K | ✓ |
In the News
Craif Raises US＄22 million in Series C Funding ...
Craif is harnessing the power of miRNA in an easy to collect urine sample to detect diseases earlier than the standard of care in order to optimize treatment and improve outcomes. We have launched...
MicroRNAs in oncology: a translational perspective in the era of AI
8. Martino, M. T. D., Tagliaferri, P. & Tassone, P. MicroRNA in cancer therapy: breakthroughs and challenges in early clinical applications.*J. Exp. Clin. Cancer Res.***44**, 126 (2025).
microRNAs blaze into the clinic
DeFrancesco, L. microRNAs blaze into the clinic. _Nat Biotechnol_ **43**, 1583–1585 (2025). https://doi.org/10.1038/s41587-025-02870-y Download citation - Published: 14 October 2025 - Issue da...
MicroRNA in cancer therapy: breakthroughs and challenges in early clinical applications - PubMed
MicroRNAs (miRNAs) have emerged as pivotal regulators in cancer biology, influencing tumorigenesis, progression, and resistance to therapy. Their ability to modulate multiple oncogenic and tumor-su...
Taysha Gene Therapies Announces FDA Breakthrough ...
by delivering a functional form of*MECP2*to cells in the CNS. TSHA-102 utilizes a novel miRNA-Responsive Auto-Regulatory Element (miRARE) technology designed to mediate levels of*MECP2*in the CNS o...
Code & Tools
The misregulation of microRNA (miRNA) has been shown to cause diseases. Recently, we have proposed a computational method based on a random walk fr...
MicroRNAs (miRNAs) are short, non-coding RNA molecules that regulate gene expression by binding to specific mRNAs, inhibiting their translation. Th...
regularization and adaptive weight tensor into nonnegative tensor factorization, called SPLDHyperAWNTF, for the discovery of potential multiple typ...
# 🏎💨miRNA-disease association prediction methods # A survey of deep learning for detecting miRNA-disease associations: databases, computational ...
a myriad of biological processes and are involved in numerous diseases.
Recent Preprints
MicroRNAs in oncology: a translational perspective in the era of AI
Over the past three decades, knowledge of microRNA (miRNA) biology has advanced from the initial discovery of their regulatory functions to the finding of abnormal activity in leukaemias, and then ...
Regulatory QTLs affecting miRNA-mRNA interactions in cancer: mechanisms, methods, and clinical implications
MicroRNAs (miRNAs) are post-transcriptional regulators that play essential roles in cancer initiation, progression, and therapy response. Single nucleotide polymorphisms (SNPs) that affect miRNA-mR...
MicroRNAs in breast cancer—new frontiers in diagnosis, targeted therapy, and prognosis assessment
# MicroRNAs in breast cancer—new frontiers in diagnosis, targeted therapy, and prognosis assessment
The Life of MicroRNAs: Biogenesis, Function and Decay in Cancer
MicroRNAs (miRNAs) are small non-coding RNAs that play pivotal roles in post-transcriptional gene regulation, influencing development, differentiation, and disease pathogenesis. Since their discove...
ASU researchers uncover the rules that guide how microRNAs ...
The study establishes microRNA strand selection as a regulated and predictable process rather than a random one. That insight has broad implications for how scientists study gene regulation and dis...
Latest Developments
Recent developments in microRNA research related to disease regulation include studies on microRNA roles in cancer, neurodegenerative diseases, and aging, with advancements in understanding their biogenesis, function, and therapeutic potential as of early 2026 (Nature, Phys.org, Nature Reviews Clinical Oncology).
Sources
Frequently Asked Questions
What is meant by microRNA-mediated disease regulation at the molecular level?
"The functions of animal microRNAs" (2004) and "MicroRNAs: Target Recognition and Regulatory Functions" (2009) describe microRNAs as small endogenous RNAs that regulate gene expression by pairing to mRNAs and directing post-transcriptional repression. "Most mammalian mRNAs are conserved targets of microRNAs" (2008) frames this as a widespread regulatory layer because many seed-matched sites in mRNAs are conserved.
How do microRNAs recognize their mRNA targets, and what rules are most used in disease studies?
"Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets" (2005) identifies conserved seed pairing (nucleotides 2–7) as a core determinant of targeting and notes contextual sequence features such as flanking adenosines. "MicroRNAs: Target Recognition and Regulatory Functions" (2009) synthesizes these principles into a framework used to interpret how microRNA dysregulation can shift disease-relevant gene expression programs.
Which evidence supports using microRNA expression as a cancer classifier or biomarker?
"MicroRNA expression profiles classify human cancers" (2005) demonstrated that microRNA expression profiles can classify human cancers, establishing a direct connection between microRNA measurements and tumor type or state. This result is frequently used to justify microRNA panels as diagnostic or stratification features in cancer research workflows.
How are extracellular vesicles and exosomes connected to microRNAs in disease regulation?
"The biology , function , and biomedical applications of exosomes" (2020) describes exosomes as extracellular vesicles that contain RNA cargo and can affect recipient cells after uptake, providing a mechanism for microRNA-associated intercellular communication. "Shedding light on the cell biology of extracellular vesicles" (2018) reviews EV cell biology, and "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" (2018) provides standards that help make EV-associated microRNA studies interpretable and comparable.
Which non-coding RNA mechanisms can modulate microRNA activity in disease contexts?
"Natural RNA circles function as efficient microRNA sponges" (2013) and "Circular RNAs are a large class of animal RNAs with regulatory potency" (2013) describe circular RNAs as regulatory molecules that can sequester microRNAs (a “sponge” effect), thereby altering microRNA availability. This mechanism is commonly invoked in disease models where changes in circular RNA abundance could indirectly rewire microRNA–mRNA repression.
What is the current state of the field in terms of scope and foundational references?
The topic spans 142,592 works, reflecting broad use of microRNAs as both mechanistic regulators and disease-associated readouts in cancer research. Foundational targeting and function frameworks are provided by "The functions of animal microRNAs" (2004), "Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets" (2005), and "MicroRNAs: Target Recognition and Regulatory Functions" (2009), while cancer classification and EV/exosome applications are anchored by "MicroRNA expression profiles classify human cancers" (2005), "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" (2018), and "The biology , function , and biomedical applications of exosomes" (2020).
Open Research Questions
- ? Which microRNA–mRNA target interactions are most causally responsible for specific cancer phenotypes, given the broad conservation of seed-matched sites described in "Most mammalian mRNAs are conserved targets of microRNAs" (2008)?
- ? How should microRNA-target prediction and validation best incorporate sequence-context rules highlighted in "Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets" (2005) to reduce false positives in disease models?
- ? Which circular RNAs act as dominant microRNA sponges in particular disease states, and how can their net regulatory impact be quantified using the sponge concept from "Natural RNA circles function as efficient microRNA sponges" (2013)?
- ? How can EV/exosome-associated microRNA measurements be standardized across laboratories while remaining biologically informative, aligning mechanistic EV biology from "Shedding light on the cell biology of extracellular vesicles" (2018) with reporting requirements in "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" (2018)?
- ? Which microRNA expression signatures generalize across cohorts and platforms for robust cancer classification beyond the initial demonstrations in "MicroRNA expression profiles classify human cancers" (2005)?
Recent Trends
Within a large body of 142,592 works, recent emphasis has increasingly connected microRNAs to extracellular vesicles and exosomes as disease-relevant carriers and measurement substrates, anchored by "Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines" , "Shedding light on the cell biology of extracellular vesicles" (2018), and "The biology , function , and biomedical applications of exosomes" (2020).
2018In parallel, the circular RNA literature—"Circular RNAs are a large class of animal RNAs with regulatory potency" and "Natural RNA circles function as efficient microRNA sponges" (2013)—has become a standard interpretive layer for explaining why microRNA activity can change without proportional changes in microRNA abundance.
2013Across these directions, the field continues to rely on seed-based targeting rules from "Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets" and the integrative targeting framework in "MicroRNAs: Target Recognition and Regulatory Functions" (2009) when translating microRNA dysregulation into disease mechanisms and measurable signatures such as the cancer-classification patterns shown in "MicroRNA expression profiles classify human cancers" (2005).
2005Research MicroRNA in disease regulation with AI
PapersFlow provides specialized AI tools for Biochemistry, Genetics and Molecular Biology researchers. Here are the most relevant for this topic:
AI Literature Review
Automate paper discovery and synthesis across 474M+ papers
Paper Summarizer
Get structured summaries of any paper in seconds
Deep Research Reports
Multi-source evidence synthesis with counter-evidence
See how researchers in Life Sciences use PapersFlow
Field-specific workflows, example queries, and use cases.
Start Researching MicroRNA in disease regulation with AI
Search 474M+ papers, run AI-powered literature reviews, and write with integrated citations — all in one workspace.
See how PapersFlow works for Biochemistry, Genetics and Molecular Biology researchers