MicroRNAs (miRNAs) are endogenous single-stranded non-coding RNAs approximately 22 ​nt in length, which play a regulatory role in various biological processes by targeting and inhibiting protein-coding gene transcripts. Among the wide range of miRNAs, miR-668 exhibits abnormal expression patterns in different diseases, including head and neck squamous cell carcinoma (HNSC), hepatocellular carcinoma (HCC), breast cancer (BrC), ischemic acute kidney injury (ischemic AKI), myocardial infarction (MI), ischemic stroke (IS), Parkinson’s disease (PD), smoking-related interstitial fibrosis (SRIF), premature aging, and non-segmental vitiligo (NSV), among others. The expression of miR-668 is regulated by various upstream factors, including other non-coding RNAs and endogenous proteins. Functionally, miR-668 targets 6 protein-coding genes (SDF-1, Dvl1, BTG2, MTFP1, FHIT, and NFKBIA) and is involved in 3 signaling pathways: the Drp signaling pathway, NF-κB signaling pathway, and NLRP3 signaling pathway. Notably, miR-668 has contrasting effects depending on the context; it can promote the development and metastasis of HCC and induce radiation resistance in BrC cells, while also promoting aging and inhibiting HNSC progression in human keratinocytes. Furthermore, miR-668 exhibits anti-apoptotic effects, alleviates ischemia/reperfusion injury, improves intracerebral expansion, relieves hydrocephalus, and has prognostic value in gastric cancer (GC), HCC, and BrC, with high expression predicting poor outcomes. Notably, the cancer drugs melatonin and Pterostilbene (Ptero) exert their therapeutic effects by modulating miR-668. Future studies should focus on validating the reliability of miR-668 as a biomarker and elucidating the specific mechanisms through which miR-668 participates in cancer therapy.

A breast scan for detecting cancer takes less than a minute using an experimental system that combines photoacoustic and ultrasound imaging, according to a study in IEEE Transactions on Medical Imaging. The system does not require painful compression like mammography. In tests, it produced clear, artificial intelligence-powered 3D images of common breast cancer subtypes such as Luminal A, Luminal B and Triple-Negative Breast Cancer.