Prediction of future relapse in MLL-rearranged infant ALL by single-cell RNA sequencing

In this blog, we describe how single-cell RNA sequencing allowed to predict which MLL- rearranged infant acute lymphoblastic leukemia (MLL-r iALL) patients are at risk of relapse. Furthermore, it allowed for characterization of the nature of relapse-predicting cells.

Acute lymphoblastic leukemia (ALL) in infants is often driven by a specific mutation, in which a part of the mixed lineage leukemia (MLL) gene is translocated to another gene. This MLL-rearranged infant ALL (MLL-r iALL) is rare but a highly aggressive type of cancer.

Also, this childhood cancer is often resistant to therapy and many patients experience a relapse during which the leukemia reemerges. The best predictor for relapse is the response to the glucocorticoid drug prednisone prior to induction therapy.

In this study, single-cell RNA sequencing is used to uncover the interplay between the sensitivity to prednisone, cell heterogeneity, and relapse occurrence in MLL-r iALL. The results of this study were published in Leukemia in July 2021.

Prediction of leukemia relapse

The main finding of this study is that leukemic cells in MLL-r iALL patients are either resistant or sensitive to treatment and quantification of these two groups can be used to predict the occurrence of future relapse.

Furthermore, cells associated with relapse are characterized by basal activation of a glucocorticoid response, are smaller, and have a quiescent gene expression program, with stem cell properties.

Single-cell RNA sequencing

In this study, two single-cell RNA sequencing techniques are used: SORT-seq and 10x Genomics*. 15 diagnosis samples, either derived from the bone marrow or from peripheral blood, were used for single-cell RNA sequencing.

Cells were classified as sensitive or resistant to therapy based on the expression of two gene modules. These gene modules were based on differential gene expression data comparing naïve and prednisone-treated samples, which was previously published. The percentage of cells classified as sensitive or resistant for each sample yielded a strong distinction between patients with and without relapse, indicating that this percentage predicts relapse of the patients.

In addition, looking at groups of genes that correlate to the resistance module, several gene sets could be identified. Genes related to glucocorticoid response, which is important for treatment with prednisone, drug resistance and cell stemness correlate to the resistance module.

Future research should focus on translating this knowledge to the clinic to prevent relapse of MLL-r iALL patients. Click on the link below to read the full article.

*10x Genomics data is not generated by Single Cell Discoveries