As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

Most patients with chronic lymphocytic leukemia (CLL) are diagnosed with early stage disease and managed with active surveillance. The individual course of subjects with early stage CLL is heterogeneous and their probability of needing treatment is hardly anticipated at diagnosis. We aimed at developing an international prognostic score to predict time to first treatment (TTFT) in CLL patients with early, asymptomatic disease (IPS-E). Individual patient data from 11 international cohorts of patients with early stage CLL (n=4933) were analyzed to build and validate the prognostic score. Three covariates were consistently and independently correlated with TTFT: unmutated IGHV genes, absolute lymphocyte count >15 x10⁹/l, and presence of palpable lymph nodes. The IPS-E was the sum of the covariates (one point each), and separated low-risk (score 0), intermediate-risk (score 1) and high-risk patients (score 2-3) showing a distinct TTFT. The score accuracy was validated in 9 cohorts staged by the Binet system and 1 cohort staged by the Rai system. The c-index was 0.74 in the training series and 0.70 in the aggregate of validation series. By meta-analysis of the training and validation cohorts, the 5-year cumulative risk of treatment start was 8.4%, 28.4%, and 61.2% among low-risk, intermediate-risk, and high-risk patients, respectively. The IPS-E is a simple and robust prognostic model that predicts the likelihood of treatment requirement in patients with early stage CLL. The IPS-E can be useful in clinical management and in the design of early intervention clinical trials.

Splenic marginal zone B-cell lymphoma (SMZL) is a heterogeneous clinico-biological entity. The clinical course is variable, multiple genes are mutated with no unifying mechanism, and essential regulatory pathways and surrounding microenvironments are diverse. We sought to clarify the heterogeneity of SMZL by resolving different subgroups and their underlying genomic abnormalities, pathway signatures, and microenvironment compositions to uncover biomarkers and therapeutic vulnerabilities. We studied 303 SMZL spleen samples collected through the IELSG46 multicenter international study (NCT02945319) by using a multiplatform approach. We carried out genetic and phenotypic analyses, defined self-organized signatures, validated the findings in independent primary tumor metadata and determined correlations with outcome data. We identified 2 prominent genetic clusters in SMZL, termed NNK (58% of cases, harboring NF-κB, NOTCH, and KLF2 modules) and DMT (32% of cases, with DNA-damage response, MAPK, and TLR modules). Genetic aberrations in multiple genes as well as cytogenetic and immunogenetic features distinguished NNK- from DMT-SMZLs. These genetic clusters not only have distinct underpinning biology, as judged by differences in gene-expression signatures, but also different outcomes, with inferior survival in NNK-SMZLs. Digital cytometry and in situ profiling segregated 2 basic types of SMZL immune microenvironments termed immune-suppressive SMZL (50% of cases, associated with inflammatory cells and immune checkpoint activation) and immune-silent SMZL (50% of cases, associated with an immune-excluded phenotype) with distinct mutational and clinical connotations. In summary, we propose a nosology of SMZL that can implement its classification and also aid in the development of rationally targeted treatments.

BIRC3 is a recurrently mutated gene in chronic lymphocytic leukemia (CLL) but the functional implications of BIRC3 mutations are largely unexplored. Furthermore, little is known about the prognostic impact of BIRC3 mutations in CLL cohorts homogeneously treated with first-line fludarabine, cyclophosphamide, and rituximab (FCR). By immunoblotting analysis, we showed that the non-canonical nuclear factor-κB pathway is active in BIRC3-mutated cell lines and in primary CLL samples, as documented by the stabilization of MAP3K14 and by the nuclear localization of p52. In addition, BIRC3-mutated primary CLL cells are less sensitive to flu-darabine. In order to confirm in patients that BIRC3 mutations confer resistance to fludarabine-based chemoimmunotherapy, a retrospective multicenter cohort of 287 untreated patients receiving first-line FCR was analyzed by targeted next-generation sequencing of 24 recurrently mutated genes in CLL. By univariate analysis adjusted for multiple comparisons BIRC3 mutations identify a poor prognostic subgroup of patients in whom FCR treatment fails (median progression-free survival: 2.2 years, P<0.001) similar to cases harboring TP53 mutations (median progression-free survival: 2.6 years, P<0.0001). BIRC3 mutations maintained an independent association with an increased risk of progression with a hazard ratio of 2.8 (95% confidence interval 1.4-5.6, P=0.004) in multivariate analysis adjusted for TP53 mutation, 17p deletion and IGHV mutation status. If validated, BIRC3 mutations may be used as a new molecular predictor to select high-risk patients for novel frontline therapeutic approaches.

PURPOSE: Patients with Diffuse Large B-cell Lymphoma (DLBCL) in need of immediate therapy are largely under-represented in clinical trials. The diagnosis-to-treatment interval (DTI) has recently been described as a metric to quantify such patient selection bias, with short DTI being associated with adverse risk factors and inferior outcomes. Here, we characterized the relationships between DTI, circulating tumor DNA (ctDNA), conventional risk factors, and clinical outcomes, with the goal of defining objective disease metrics contributing to selection bias. PATIENTS AND METHODS: We evaluated pretreatment ctDNA levels in 267 patients with DLBCL treated across multiple centers in Europe and the United States using Cancer Personalized Profiling by Deep Sequencing. Pretreatment ctDNA levels were correlated with DTI, total metabolic tumor volumes (TMTVs), the International Prognostic Index (IPI), and outcome. RESULTS: Short DTI was associated with advanced-stage disease ( P < .001) and higher IPI ( P < .001). We also found an inverse correlation between DTI and TMTV ( R_S = −0.37; P < .001). Similarly, pretreatment ctDNA levels were significantly associated with stage, IPI, and TMTV (all P < .001), demonstrating that both DTI and ctDNA reflect disease burden. Notably, patients with shorter DTI had higher pretreatment ctDNA levels ( P < .001). Pretreatment ctDNA levels predicted short DTI independent of the IPI ( P < .001). Although each risk factor was significantly associated with event-free survival in univariable analysis, ctDNA level was prognostic of event-free survival independent of DTI and IPI in multivariable Cox regression (ctDNA: hazard ratio, 1.5; 95% CI [1.2 to 2.0]; IPI: 1.1 [0.9 to 1.3]; −DTI: 1.1 [1.0 to 1.2]). CONCLUSION: Short DTI largely reflects baseline tumor burden, which can be objectively measured using pretreatment ctDNA levels. Pretreatment ctDNA levels therefore have utility for quantifying and guarding against selection biases in prospective DLBCL clinical trials.