Choline deficiency-related multi-omics characteristics are susceptible factors for chemotherapy-induced thrombocytopenia. (April 2022) - Yao, Houshan; Xu, Huilin; Qiu, Shi; Chen, Jiani; Lin, Zeshuai; Zhu, Jiawei; Sun, Xiaomeng; Gao, Qianmin; Chen, Xintao; Xi, Chaowen; Huang, Doudou; Zhang, Feng; et al.
Abstract: The XELOX chemotherapy protocol that includes capecitabine and oxaliplatin is the routine treatment for colorectal cancer (CRC), but it can cause chemotherapy-related adverse events such as thrombocytopenia (TCP). To identify predictive biomarkers and clarify the mechanism of TCP susceptibility, we conducted integrative analysis using normal colorectal tissue (CRT), plasma, and urine samples collected before CRC patients received adjuvant XELOX chemotherapy. RNA-sequencing and DNA methylation arrays were performed on CRT samples, while liquid chromatography-mass spectrometry was performed on CRT, plasma, and urine samples. Differentially expressed features (DEFs) from each uni-omics analysis were then subjected to integrative analysis using Multi-Omics Factor Analysis (MOFA). Choline-deficiency in plasma and CRT was found as the most critical TCP-related feature. Based on bioinformatic analysis and literature research, we further concluded that choline-deficiency was the possible reason for most of the other TCP-related multi-omics DEFs, including metabolites representing reduced sphingolipid de novo synthesis and elevated solute carrier-mediated transmembrane transportation in CRT and plasma, DNA hypermethylation and elevated expression of genes involved in neuronal system genes. In terms of thrombocytopoiesis, these TCP-related DEFs may cause atypical maintenance and differentiation of megakaryocyte, resulting a suppressed ability of thrombocytopoiesis, making patients more susceptible to chemotherapy-induced TCP. At last, prediction models were developed and validated with reasonably good discrimination. The area under curves (AUCs) of training sets were all > 0.9, while validation sets had AUCs between 0.778 and 0.926. In conclusion, our results produced reliable marker systems for predicting TCP and promising target for developing precision treatment to prevent TCP. Graphical Abstract: ga1