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Olsson-Strömberg, U.

Publications and source records attributed to Olsson-Strömberg, U..

2 recordsLinked to original sources

Integrated analysis of leukemic mutations and transcriptomes at the single-cell level

Single-cell RNA-sequencing-based characterization of cells that belong to the neoplastic clone is a major challenge in hematologic neoplasms, where malignant and normal cells coexist. Confident molecular profiling requires simultaneous analysis of gene expression and genetic mutations in individual cells, an ability that is not supported by the standard 10X Genomics workflow. Here, we systematically evaluated the potential and limitations of repurposing amplified cDNA generated during the 10X Genomics 3' workflow for post-hoc genotyping of individual cells. We first established a mixed leukemic cell line system comprising one cell line with KIT point mutations and another with the BCR::ABL1 fusion gene. Targeted long-read PacBio sequencing enabled post-hoc assignment of mutation data to transcriptionally profiled cells, but recovery differed between targets. Consistent with ambient RNA in microfluidics-based single-cell workflows, mutation-associated transcripts were detected in cells not expected to carry the corresponding mutations, illustrating how transcript recovery complicates cell-level genotype assignment. Target-specific thresholds mitigated this source of misclassification. In primary chronic myeloid leukemia samples, the post-hoc approach detected BCR::ABL1-positive cells at diagnosis, but not during imatinib treatment. Together, we present a framework for adding mutation status to cells already profiled using the 10X Genomics workflow and highlight broader considerations for transcript-based single-cell genotyping.

cancer biology↗

Deep single-cell immune and signaling profiles predict long term therapy response in chronic myeloid leukemia within hours

Chronic myeloid leukemia (CML) is effectively treated with small molecule BCR::ABL1 tyrosine kinase inhibitors (TKIs) but like in all cancers, early identification of suboptimal- and non-responders is a challenge. Through mass cytometry analysis of peripheral blood leukocytes, we collected high-dimensional data from de novo chronic phase CML patients enrolled in two multicenter clinical trials (clinicaltrials.gov NCT01725204 and NCT01061177). In leukocytes, dasatinib and nilotinib inhibited intracellular signaling within one or three hours after first per oral dose, and each TKI had a unique signaling signature reflecting its kinase specificity profile beyond BCR::ABL1. An immune and signaling profile was constructed for each patient, predicting the treatment response (BCR::ABL1IS, %) the first 12 months of treatment. These results show that single cell immune and signaling profiles within hours of first dose can predict 12 months treatment response, anticipating future optimalization of kinase inhibitor treatment within days rather than months.

cancer biology↗