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PubMed2026

Clonotypic characterization defines B-cell drivers of clonal expansion and intratumor heterogeneity in IgM monoclonal gammopathies.

Waldenström macroglobulinemia (WM) and IgM monoclonal gammopathy of undetermined significance (MGUS) share the same cell of origin but differ in clonal size. Compared with other B-cell neoplasms, the lymphoplasmacytic clone in WM can be rather small, limiting our understanding of clonal expansion. We applied an integrative approach using single-cell RNA with B-cell receptor (BCR) sequencing, the assay for transposase-accessible chromatin, and whole-genome sequencing to characterize the tumor clone in patients with IgM MGUS, smoldering WM (SWM), and symptomatic WM (WM). IgM MGUS and low- or intermediate-risk SWM harbored multiple B-cell clones compared to WM. CD9, JCHAIN, RASSF6, and DUSP22 were the main markers of the dominant B-cell clone at gene expression and chromatin activity levels, with CD9 preferentially expressed in plasma cell-like tumor cells. POU2F2 had high activity in the tumor clone and was linked to CD9 regulatory regions. MYD88 and IGLL5 mutations, mainly associated with the mutational signature SBS5, were present in minor clones, whereas the MYD88 mutation was also detected in nonexpanded B-cells. The 6q deletion was present in tumor cells from high-risk patients, which harbored fitness advantage over copy-neutral tumor cells. Coding mutations clustered tumor and minor clones from oligoclonal patients and were associated with abnormal transcriptional programs. The B-cell clones also showed enriched predicted interactions with monocytes. Our integrative single-cell approach reveals the importance of clone size in IgM gammopathy and identifies key markers promoting clonal expansion.

Journal Article↗

PubMed2025

Fluctuating DNA methylation tracks cancer evolution at clinical scale.

Cancer development and response to treatment are evolutionary processes1,2, but characterizing evolutionary dynamics at a clinically meaningful scale has remained challenging3. Here we develop a new methodology called EVOFLUx, based on natural DNA methylation barcodes fluctuating over time4, that quantitatively infers evolutionary dynamics using only a bulk tumour methylation profile as input. We apply EVOFLUx to 1,976 well-characterized lymphoid cancer samples spanning a broad spectrum of diseases and show that initial tumour growth rate, malignancy age and epimutation rates vary by orders of magnitude across disease types. We measure that subclonal selection occurs only infrequently within bulk samples and detect occasional examples of multiple independent primary tumours. Clinically, we observe faster initial tumour growth in more aggressive disease subtypes, and that evolutionary histories are strong independent prognostic factors in two series of chronic lymphocytic leukaemia. Using EVOFLUx for phylogenetic analyses of aggressive Richter-transformed chronic lymphocytic leukaemia samples detected that the seed of the transformed clone existed decades before presentation. Orthogonal verification of EVOFLUx inferences is provided using additional genetic data, including long-read nanopore sequencing, and clinical variables. Collectively, we show how widely available, low-cost bulk DNA methylation data precisely measure cancer evolutionary dynamics, and provides new insights into cancer biology and clinical behaviour.

Humans↗