Peking University, Dec. 4, 2018: On Friday, 30 November, researchers at Peking University, led by Professor Tang Fuchou, Fu Wei, and Qiao Jie, published a report paper in the journal Science, entitled ‘Single-cell multiomics sequencing and analyses of human colorectal cancer’. This research provide new insights into the molecular heterogeneity of human colorectal cancer.
Colorectal cancer (CRC), one of the major causes of mortality worldwide, is characterized by alterations of the genome, epigenome, and transcriptome. Intratumoral heterogeneity is a major barrier for effective cancer diagnosis and treatment, and can lead to drug resistance and relapse. However, previous studies have been limited to analysis of bulk cells which consist of non-tumor cells and complex sub-clones, and therefore only reflect the average profiles of tumor samples. The dynamics of tumor genetic lineages, DNA methylome and transcriptome, and their relationship still remain elusive.
In this study, researchers introduced scTrio-seq2, an improved new version of single-cell multi-omics sequencing technique (scTrio-seq), which can assess somatic copy number alterations (SCNAs), whole-genome DNA methylation, and transcriptome information simultaneously from an individual cell with high detection efficiencies. They performed multi-regional sampling of the primary tumor, lymphatic and distant metastases, and generated scTrio-seq2 profiles for 12 CRC patients.
Overview of the workflow.
The major findings are as follows.
(1) Genetic sub-lineages of individual tumor cells were reconstructed based on SCNA breakpoints. For 5 patients with methylation data (> 90 cells), cancer cells were classified into several genetic sub-lineages. The primary tumors usually showed more complex sub-clonal structures than the metastases.
(2) The DNA methylation heterogeneity of cancer cells were revealed. Compared with paired normal cells, genome-wide DNA hypomethylation was detected in every individual cancer cell. Moreover, the demethylation degrees may vary drastically between individual cells even of the same patient.
(3) DNA methylation-based subpopulations are in general consistent with genetic subpopulations. DNA methylation levels were relatively homogenous within a genetic subpopulation but showed discrepancies among different subpopulations. The differences between the primary tumors and metastases in DNA methylation levels could be mainly caused by the differences in the composition of subpopulations, but not de novo methylation or demethylation during metastasis.
(4) Characterization of the relationships between DNA methylome and transcriptome. Globally, the correlations between DNA methylation levels and gene expression levels were negative in promoter regions but positive in gene body regions in individual cells. However, the transcriptome groups are not necessarily consistent with DNA methylation groups or genetic lineages.
(5) Tracing the dynamics of DNA methylation and gene expression during metastasis within the same genetic lineage. For the tumor cells within the same genetic lineage, the global DNA methylation levels were relatively stable during metastasis, accompanied by changes in focal regions, such as promoters. No obvious changes pre- or post-metastasis were observed in the expression levels or DNA methylation levels of epithelial–mesenchymal transition-related genes.
(6) The DNA demethylation patterns are consistent among all sequenced patients. The genomic regions with higher DNA methylation levels in normal cells tended to undergo stronger demethylation in cancer cells (both absolute levels and relative ratios of demethylation). During tumorigenesis and progression, repeat sequence L1 and heterochromatin regions experienced aberrant DNA demethylation, breaking the rules in normal development.
(7) The chromosomal patterns of aberrant DNA methylation and genome instability of CRC are revealed. There are 6 chromosomes (4, 5, 8, 13, 18, and X) exhibiting stronger DNA demethylation than others; 3 of the them also recurrently generated SCNAs (chromosomes 8, 13, 18)
In summary, the DNA methylation and RNA expression patterns among different tumor genetic sub-clones as well as their dynamic changes during metastasis were systematically revealed.
Edited by: Zhang Jiang
Source: Biomedical Pioneering Innovation Center
