Craif has developed a simple and effective method for exosome
enrichment using nano-fabrication technology
Extracellular vesicles, including exosomes and incorporated microRNAs(miRNAs), are recently attracting attention for its close connection with diseases and their pathology. However, miRNA concentrations tend to be low and effective methods to extract them did not exist in the past. The solution? Our nanowire microfluid device— capable of extracting urinal exosomes efficiently with a simple procedure.
Exosomes are 20-150 nm-sized vesicles which function as a vital medium for cellular communication. It encapsulates miRNAs, a non-coding RNA, which are known as gene expression modulators, and strongly relates with physiological conditions like disease status. Exosomes secreted by malignant cells are considered to work as intercellular communication tools, proving its vast potential as biomarkers.
Our original device, which consists of zinc oxide nanowire embedded in a microfluidic channel, can efficiently collect urinary miRNA. Despite the limited miRNA found in urine, our device captures more urinary miRNA than any competitor in the market, making it possible to detect cancer in the early stages.
MicroRNA (miRNA) is a biological material secreted from cells with a profile that is different between cancer and normal cells. miRNA is now attracting attention as an early cancer biomarker. It is secreted even from the early stages of cancer that could not be detected by conventional diagnostic methods, such as blood tests, image diagnoses, and endoscopy.
Craif is developing a cancer diagnosis algorithm by combining our original miRNA database with machine learning technology. Analyzing miRNA profiles with the algorithm enables us to identify biomarkers and ultimately detect cancer early.
Cancer cells need to communicate with other cells to survive by secreting exosomes that contain various proteins, mRNAs, and miRNAs. Communications between cancer and its microenvironment, including stromal and distant cells, can promote tumor growth, metastasis, and escape from immune surveillance. By capturing exosomes comprehensively, we can understand not only the characteristics of the cancer cells, but also its microenvironment reflecting the host response to the disease. To put it simply, we can catch a glimpse of the cancer-host conversations from the extracted exosomes. It is through this means that we can detect cancer even in a very early stage, in which cancer tissue is not large enough to be detected by other approaches such as CTC and cfDNA analysis. By measuring urinal microRNA from exosome extracted by this device and analyzing the samples using machine learning algorithms, we sucessfully developed an algorithm to distinguish cancer from non-cancer samples with high sensitivity and specificity in two cancer types (lung cancer, brain tumor).