Researchers in the US have developed an ‘atlas of cell states’ for acute myeloid leukaemia (AML), which it is hoped will support the development of immunotherapy and precision medicine.
The team used single-cell technologies and machine learning to create the detailed map, establishing a method to more reliably distinguish the varied cell types within tumours.
AML is difficult to study because the bone marrow of patients contains a variety of normal and malignant cell types. These include undifferentiated primitive cancer cells with stem cell-like properties and differentiated mature cancer cells. In addition, the branching of cancer cells into different lineages – known as ‘subclones’ – complicates matters further.
Writing in the latest edition of the journal Cell, the team describes how it used a new single-cell RNA (scRNA) sequencing method to capture the full transcriptomes of nearly 40,000 bone marrow cells gathered from 16 AML patients and five healthy donors.
Single-cell genotyping was carried also out on the bone marrow cells, screening for a set of known AML genetic markers to pick out cells which were cancerous. The technology used – long-read nanopore DNA sequencing – scans much longer DNA fragments, enhancing the ability to find mutations across the genome and helping to identify descendants of subclones.
They then used a machine learning algorithm to bring the scRNA sequencing and genotyping data together. This resulted in the ‘atlas’ of different AML cell types and the normal blood cell types with which they co-exist in the bone marrow environment. The researchers also discovered multiple subclonal populations within a single AML patient.
The team, which was led by Prof Bradley Bernstein at the Ludwig Center at Harvard Medical School, Massachusetts, USA, included engineers at MIT and the Broad Institute, as well as cancer researchers at the Massachusetts General Hospital, Dana-Farber Cancer Institute and Brigham and Women's Hospital.
Prof Bernstein said: “In at least one case, the two subclones behaved completely differently and had different gene expression profiles. One subclone was mostly differentiating while the other was arrested in a highly aggressive state, and the aggressive subclone had a mutation that was consistent with a poor patient prognosis.”
He added that their findings might explain why therapies that harness T cells of the immune system to target tumours have been relatively less successful against AML.
Source: van Galen, P., Hovestadt, V., Wadsworth II, M.H., Hughes, T.K., Griffin, G.K., Battaglia, S., Verga, J.A., Stephansky, J., Pastika, T.J., Lombardi Story, J., Pinkus, G.S., Pozdnyakova, O., Galinsky, I., Stone, R.M., Graubert, T.A., Shalek, A.K., Aster, J.C., Lane, A.A., Bernstein, B.E. (2019) “Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity”, Cell, available from doi: 10.1016/j.cell.2019.01.031
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