It often seems the best deals come in bundles. Bundle your internet, phone service, and cable package and those long hours in the lab become a bit less tempting. But now there’s a new sequencing bundle that will make you never want to leave the lab. scTrio-seq2 is a single-cell multiomic bundling that meets your genomic, epigenomic, and transcriptomic needs in a single assay. The original scTrio-seq combined DNA methylome sequencing with scRNA-seq to reveal DNA methylation and gene expression levels, as well as somatic copy number alterations (SCNAs). Now, the combined efforts from the labs of Jie Qiao, Fuchou Tang, and Wei Fu at Peking University (Beijing, China), have optimized this method to integrate the same multiomics analysis with single-cell whole-genome bisulfite sequencing, and used it to profile human colorectal cancer at the single-cell level.
A major difficulty in treating colorectal cancer comes from intratumoral heterogeneity, with each tumoral lineage having distinctive alterations at the genomic, epigenomic, and transcriptomic levels. This hard-working team used their scTrio-seq2 technique to analyze paired primary tumors and metastases from ten colorectal cancer patients at the single-cell level. They harnessed the SCNA data to construct cancer cell lineages and determine common progenitors for the metastases, then overlaid DNA methylation and gene expression data along these lineages. Here’s what they found:
- Cancer cells show genome-wide DNA hypomethylation when compared to normal colon cells, in a pattern consistent across all 10 patients
- Tumor cells originating from a common progenitor had similar genome-wide DNA methylation levels, but DNA methylation levels varied when comparing between lineages
- Hypomethylation was observed largely at LTRs, LINEs, and heterochromatin, while hypermethylation was found at CpG islands, H3K4me3, and open chromatin
- Metastases display DNA methylation profiles similar to primary tumors, and do not appear to undergo further de novo methylation changes
Overlapping single-cell multiomic datasets allows researchers to trace the progression of cancer cell lineages during metastasis. This monitoring of tumor heterogeneity could ultimately lead to better therapeutic strategies by identifying and treating the multitudes of uniquely malignant cells.
Don’t miss out on the full package; read the rest of the story in Science, November 2018.