Dataset - An integrative multiparametric approach stratifies distinct phenotypes of blast phase chronic myelomonocytic leukemia with differential maturation status and drug sensitivity profiles

Published: 15 January 2025| Version 2 | DOI: 10.17632/vcsyd7ns8f.2
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Description

Approximately 30% of chronic myelomonocytic leukemia patients undergo transformation to a chemo-refractory blastic phase (BP-CMML). Seeking novel therapeutic approaches we profiled blast transcriptomes from 42 BP-CMMLs, observing extensive transcriptional heterogeneity and poor alignment to current AML classifications. BP-CMMLs displayed distinctive transcriptomic profiles, including enrichment for quiescence and variability in drug response signatures. Integrating clinical, immunophenotype and transcriptome parameters, RandomForest unsupervised clustering distinguished immature and mature subtypes characterized by differential expression of transcriptional modules, oncogenes, apoptotic regulators and patterns of surface marker expression. Subtypes differed in predicted response to AML drugs, validated ex vivo in primary samples. Iteratively refined stratification resolved a classification structure comprising five subtypes along a maturation spectrum, predictive of response to novel agents including consistent patterns for RTK, CDK, MTOR and MAPK inhibitors. Finally, we generated a clinically-applicable decision tree to stratify BP-CMML with high specificity and sensitivity, and potentially guide personalized drug selection for improved outcomes. ################### # Dataset description: # ################### Data included within this data repository is to be used as input for figure reproduction or further exploration. This dataset includes the following higher order folders: - Clinical: includes clinical data for the LAML TCGA cohort. Other clinical data were not shared due to data protection of patients' privacy. Please consult us if requiring this data. - Genotype: includes tabular data of genotypes for the collated cohorts, including binary mutation matrix and whole cohorts mutation data. - Immunophenotype: includes tabular data with mean fluorescent intensity (MFI) computed for each sample against various markers. - Oncoprint: includes oncoprint input data. - RandomForest: includes RF input data, model and clustering results. - Resources: includes RNAseq annotation file, gene metadata and collection of curated gene pathways. - RNASeq: includes results from downstream analysis of bulk RNAseq data.

Files

Steps to reproduce

1) Clone/Download the code from the GitHub/Mendeley Data repositories, both linked below. 2) Download the input data in the Data.zip file from the current Mendeley Data repository and decompress on the same folder containing the code. 3) Ensure having downloaded the right R/Python and packages versions, and run code according to order.

Institutions

The University of Manchester

Categories

Leukemia, Acute Myelogenous Leukemia, Chronic Myelomonocytic Leukemia

Funding

The Oglesby Charitable Trust

Licence