Chronic lymphocytic leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex vivo drug response data from 217 patients with CLL. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to known biomarkers. We validated its presence and clinical relevance in four independent cohorts (n = 547 patients). We found that this axis captures the proliferative drive (PD) of CLL cells, as it associates with lymphocyte doubling rate, global hypomethylation, accumulation of driver aberrations and response to pro-proliferative stimuli. CLL–PD was linked to the activation of mTOR–MYC–oxidative phosphorylation through transcriptomic, proteomic and single-cell resolution analysis. CLL–PD is a key determinant of disease outcome in CLL. Our multi-table integration approach may be applicable to other tumors whose inter-individual differences are currently unexplained.

慢性淋巴细胞白血病 (CLL) 具有复杂的驱动突变模式，其大部分临床多样性仍无法解释。我们设计了一种跨多种数据类型同时进行亚组发现的方法，并将其应用于 217 名 CLL 患者的基因组、转录组、DNA 甲基化和离体药物反应数据。我们发现了与临床行为密切相关且与已知生物标志物正交的异质性生物学轴。我们在四个独立队列（ n = 547 名患者）中验证了它的存在和临床相关性。我们发现该轴捕获了 CLL 细胞的增殖驱动 (PD)，因为它与淋巴细胞倍增率、整体低甲基化、驱动畸变的积累以及对促增殖刺激的反应相关。通过转录组、蛋白质组和单细胞分辨率分析，CLL-PD 与 mTOR-MYC-氧化磷酸化的激活有关。 CLL-PD 是 CLL 疾病结果的关键决定因素。我们的多表整合方法可能适用于目前无法解释个体间差异的其他肿瘤。