Explore prognostic marker of colorectal cancer based on ceRNA network

Colorectal cancer (CRC) is one of the most common malignant tumors in the world. With the deepening of people's understanding of CRC at the molecular level, the survival and prognosis of CRC have been significantly improved with the help of surgery, radiotherapy, and chemotherapy, molecular targeted biological therapy and early detection of diseases. The research of different disciplines and the development of multihistological analysis in recent years have proved that the occurrence and development of CRC is a complex biological process with the common action of multiple factors, which involves the huge changes of various histological levels such as the genome, transcriptome, and epigenome. At present, the abnormal expression of protein products in the transcription process has attracted more and more attention. Based on the sensitivity and timeliness of its changes, it has become a hot topic to study the occurrence and development mechanism of CRC through transcriptome changes, so as to provide markers for early diagnosis and prognosis. In recent years, competitive endogenous RNA (ceRNA) has become one of the hot topics in cancer research. The ceRNA hypothesis holds that transcripts such as long noncoding RNA can competitively bind microRNA (miRNA), thus preventing miRNA from binding to messenger RNA (mRNA) and thereby regulating the expression of mRNA. At present, the interaction mechanism of ceRNA in CRC is still unclear, and exploring its interaction relationship is of great significance to elucidate the occurrence and development mechanism of CRC. In this study, we used The Cancer Genome Atlas (TCGA) RNA ‐ seq data of colorectal Cancer and microRnas ‐ seq data to construct colorectal Cancer ceRNA topology network to mine key RNAs that influence the prognosis of colorectal cancer, providing potential RNA biomarkers. We used The Cancer Genome Atlas RNA—seq data of colorectal cancer in and microRNAs—seq data to construct colorectal cancer endogenous RNA topology network to mine key RNAs that influence the prognosis of colorectal cancer, providing potential RNA biomarkers.