Multi‐omics analysis of intra‐tumoural and inter‐tumoural heterogeneity in pancreatic ductal adenocarcinoma. Issue 1 (21st January 2022) - Liu, Xiaoqian; Wang, Wenqian; Liu, Xiaoding; Zhang, Zhiwen; Yu, Lianyuan; Li, Ruiyu; Guo, Dan; Cai, Weijing; Quan, Xueping; Wu, Huanwen; Dai, Menghua; Liang, Zhiyong
Abstract: The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is associated with the tumour heterogeneity. To explore intra‐ and inter‐tumoural heterogeneity in PDAC, we analysed the multi‐omics profiles of 61 PDAC lesion samples, along with the matched pancreatic normal tissue samples, from 19 PDAC patients. Haematoxylin and Eosin (H&E) staining revealed that diversely differentiated lesions coexisted both within and across individual tumours. Whole exome sequencing (WES) of samples from multi‐region revealed diverse types of mutations in diverse genes between cancer cells within a tumour and between tumours from different individuals. The copy number variation (CNV) analysis also showed that PDAC exhibited intra‐ and inter‐tumoural heterogeneity in CNV and that high average CNV burden was associated poor prognosis of the patients. Phylogenetic tree analysis and clonality/timing analysis of mutations displayed diverse evolutionary pathways and spatiotemporal characteristics of genomic alterations between different lesions from the same or different tumours. Hierarchical clustering analysis illustrated higher inter‐tumoural heterogeneity than intra‐tumoural heterogeneity of PDAC at the transcriptional levels as lesions from the same patients are grouped into a single cluster. Immune marker genes are differentially expressed in different regions and tumour samples as shown by tumour microenvironment (TME) analysis. TME appeared to be more heterogeneous than tumour cells in the same patient. Lesion‐specific differentially methylated regions (DMRs) were identified by methylated DNA immunoprecipitation sequencing (MeDIP‐seq). Furthermore, the integration analysis of multi‐omics data showed that the mRNA levels of some genes, such as PLCB4, were significantly correlated with the gene copy numbers. The mRNA expressions of potential PDAC biomarkers ZNF521 and KDM6A were correlated with copy number alteration and methylation, respectively. Taken together, our results provide a comprehensive view of molecular heterogeneity and evolutionary trajectories of PDAC and may guide personalised treatment strategies in PDAC therapy. Abstract : Our results provide a comprehensive view of molecular heterogeneity and evolutionary trajectories of PDAC and may guide personalized treatment strategies in PDAC therapy.