PDF(Pubmed)
Abstract：
The incidence of early-onset colorectal cancer (EOCRC) has increased significantly worldwide. Uncovering biomarkers that are unique to EOCRC is of great importance to facilitate the prevention and detection of this growing cancer subtype. Although efforts have been made in the data curation about CRC, there is no integrated platform that gives access to data specifically related to young CRC patients. Here, we constructed a user-friendly open integrated resource called CRCDB (URL: http://crcdb-hust.com) which contains multi-omics data of 785 EOCRC, 4898 late-onset CRCs (LOCRC), and 1110 normal control samples from tissue, whole blood, platelets, and serum exosomes. CRCDB manages the differential analysis, survival analysis, co-expression analysis, and immune cell infiltration comparison analysis results in different CRC groups. Meta-analysis results were also provided for users for further data interpretation. Using the resource in CRCDB, we identified that genes associated with the metabolic process were less expressed in EOCRC patients, while up regulated genes most associated with the mitosis process might play an important role in the molecular pathogenesis of LOCRC. Survival-related genes were most enriched in oxidoreduction pathways in EOCRC while in immune-related pathways in LOCRC. With all the data gathered and processed, we anticipate that CRCDB could be a practical data mining platform to help explore potential applications of omics data and develop effective prevention and therapeutic strategies for the specific group of CRC patients.
摘要：
早发性结直肠癌(EOCRC)的发病率在全球范围内显著增加。发现EOCRC特有的生物标志物对于促进这种不断增长的癌症亚型的预防和检测非常重要。尽管已经在有关CRC的数据管理方面做出了努力，没有一个综合平台可以访问与年轻CRC患者特别相关的数据.这里,我们构建了一个用户友好的开放式集成资源，称为CRCDB（URL：http://crcdb-hust.com），其中包含785EOCRC的多组学数据，4898晚发型CRC（LOCRC），和1110个来自组织的正常对照样本，全血,血小板,和血清外泌体。CRCDB管理差异分析，生存分析,共表达分析，并对不同CRC组的免疫细胞浸润结果进行比较分析。还提供了Meta分析结果，供用户进一步解释数据。使用CRCDB中的资源，我们发现与代谢过程相关的基因在EOCRC患者中表达较少，而与有丝分裂过程相关的上调基因可能在LOCRC的分子发病机制中起重要作用。生存相关基因在EOCRC中的氧化还原途径中最富集，而在LOCRC中的免疫相关途径中最富集。收集和处理了所有数据，我们预计,CRCDB可能是一个实用的数据挖掘平台,有助于探索组学数据的潜在应用,并为特定的CRC患者组制定有效的预防和治疗策略.
