MicroRNA-Driven Diagnosis and Prognosis in Gastric Cancer

MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and have emerged as robust biomarkers for gastric cancer due to their stability in tissues, blood and exosomes. Aberrant microRNA expression contributes to tumour initiation, progression and metastasis through pathways such as epithelial–mesenchymal transition, apoptosis regulation and signalling cascades including Wnt and PI3K/Akt. Advances in high-throughput sequencing, quantitative reverse transcription polymerase chain reaction and machine-learning approaches have enabled the discovery of microRNA panels capable of distinguishing early-stage disease, predicting patient survival and monitoring treatment response. Exosomal microRNAs further offer minimally invasive access to tumour-derived information, supporting point-of-care diagnostics. Integration of bioinformatic analyses with clinical cohorts has yielded signatures that improve sensitivity and specificity over conventional markers, paving the way for personalised management and global implementation of microRNA-based assays in gastric cancer care.

Research from Nature Portfolio

Recent studies have applied machine-learning algorithms to large genomic databases to derive highly predictive microRNA panels. One investigation used support vector machines, random forests and k-nearest neighbours to identify a 29-microRNA signature, achieving an accuracy of 93% and an area under the receiver-operating characteristic curve of 0.885 for gastric cancer detection. Key microRNAs such as miR-21, miR-133a, miR-146b and miR-29c were linked to patient survival. Earlier foundational work established a five-microRNA plasma signature (miR-185, miR-20a, miR-210, miR-25 and miR-92b) with consistently high diagnostic performance (AUC 0.86–0.87), demonstrating stability across training, testing and external validation cohorts and highlighting the clinical feasibility of circulating microRNA assays.

MicroRNA-Driven Diagnosis and Prognosis in Gastric Cancer publication trend

The graph below shows the total number of articles in microrna-driven diagnosis and prognosis in gastric cancer across all publications each year (not limited to Nature Index journals).

Technical terms

MicroRNA: Short non-coding RNA molecules (~22 nucleotides) that regulate gene expression.

Exosome: Small extracellular vesicle (30–150 nm) that transports biomolecules, including microRNAs, between cells.

Quantitative reverse transcription polymerase chain reaction (qRT-PCR): Technique for quantifying RNA levels through reverse transcription followed by real-time PCR amplification.

Epithelial–mesenchymal transition (EMT): Biological process by which epithelial cells acquire migratory and invasive properties.

Receiver-operating characteristic (ROC) curve: Graphical plot illustrating diagnostic test performance; the area under the curve indicates accuracy.

References

1. Machine learning algorithms reveal potential miRNAs biomarkers in gastric cancer. Scientific Reports (2023).
2. Diagnostic value of a plasma microRNA signature in gastric cancer: a microRNA expression analysis. Scientific Reports (2015).
3. Nucleic Acid Amplification Circuit‐Based Hydrogel (NACH) Assay for One‐Step Detection of Metastatic Gastric Cancer‐Derived Exosomal miRNA. Advanced Science (2024).
4. A three-miRNA signature as promising non-invasive diagnostic marker for gastric cancer. Molecular Cancer (2015).
5. Potential Diagnostic, Prognostic and Therapeutic Targets of MicroRNAs in Human Gastric Cancer. International Journal of Molecular Sciences (2016).
6. A systematic review of microRNA expression profiling studies in human gastric cancer. Cancer Medicine (2014).