New Single-Cell Sequencing Method Effective in Distinguishing Between Healthy and Cancerous Cells in AML

According to research published in Nature Communications, investigators developed a new single-cell multi-omic approach to identify leukemic stem cells and characterized cancer stem cells in the context of acute myeloid leukemia (AML), which the investigators think may be able to translate to other tumor types.¹

MutaSeq, the new method created by investigators from the Centre for Genomic Regulation (CRG) and the European Molecular Biology Laboratory (EMBL), works to distinguish between pre-leukemic stem cells, leukemic stem cells, and healthy hematopoietic stem cells.²

“There are a huge number of small molecule drugs out there with demonstrated clinical safety, but deciding which cancers and more specifically which patients these drugs are well suited for is a daunting task,” Lars Steinmetz, professor at Stanford University and author of the paper, said in a press release. “Our method can identify drug targets that might not have been tested in the right context. These tests will need to be carried out in controlled clinical studies, but knowing what to try is an important first step.”

The research team utilized MutaSeq to determine if a single cell was a stem cell by measuring thousands of RNA simultaneously. Additional sequencing was used to determine if the cell was healthy or cancerous. Collecting these data assisted the team in tracking if stem cells are cancerous or healthy and helped them decide what makes the cancerous cells different.

While most cancerous tissue had cells with a limited capacity to rapidly divide, cancerous stem cells replicate indefinitely, resulting in long-term cancer growth and relapse. In AML specifically, leukemic stem cells are the underlying driver of mortality but remain difficult to isolate due to their low abundance.

Overall, an increase from a median of 1 target site covered per single cell to a median of 4 was observed with MutaSeq. Also, the MutaSeq method maintained a comparable transcriptome data quality and “recapitulated the variant allele frequencies estimated by exome sequencing with higher accuracy than Smart-seq2.”

“RNA provides vital information for human health. For example, PCR [polymerase chain reaction] tests for coronavirus detect its RNA to diagnose COVID-19. Subsequent sequencing can determine the virus variant,” explained Lars Velten, author of the paper, in a press release. “MutaSeq works like a PCR test for coronavirus, but at a much more complex level and with a single cell as starting material.”

The MutaSeq method implemented here was based off single-cell sequencing, which is becoming more commonly used to assist research teams to gather and interpret genome-wide data. This method of single-cell sequencing uses complex tissues and cancers to craft a detailed molecular profile for research.

“We have now brought together clinical researchers from Germany and Spain to apply this method in much larger clinical studies. We are also making the method much more streamlined,” explained Velten. “Our vision is to identify cancer stem cell specific drug targets in a personalized manner, making it ultimately as easy for patients and doctors to look for these treatments as it is testing for coronavirus.”

References

1. Velten L, Story BA, Hernández-Malmierca P, et al. Identification of leukemic and pre-leukemic stem cells by clonal tracking from single-cell transcriptomics. Nat Commun. 2021;12(1):1366. doi: 10.1038/s41467-021-21650-1

2. Single cell sequencing opens new avenues for eradicating leukemia at its source. News release. Center for Genomic Regulation. March 1, 2021. Accessed April 19, 2021. https://www.eurekalert.org/pub_releases/2021-03/cfgr-scs022521.php