Differential Activity of ATR and WEE1 Inhibitors in a Highly Sensitive Subpopulation of DLBCL Linked to Replication Stress.

DNA damage checkpoint kinases ATR and WEE1 are among key regulators of DNA damage response pathways protecting cells from replication stress, a hallmark of cancer that has potential to be exploited for therapeutic use. ATR and WEE1 inhibitors are in early clinical trials and success will require greater understanding of both their mechanism of action and biomarkers for patient selection. Here, we report selective antitumor activity of ATR and WEE1 inhibitors in a subset of non-germinal center B-cell (GCB) diffuse large B-cell lymphoma (DLBCL) cell lines, characterized by high MYC protein expression and CDKN2A/B deletion. Activity correlated with the induction of replication stress, indicated by increased origin firing and retardation of replication fork progression. However, ATR and WEE1 inhibitors caused different amounts of DNA damage and cell death in distinct phases of the cell cycle, underlying the increased potency observed with WEE1 inhibition. ATR inhibition caused DNA damage to manifest as 53BP1 nuclear bodies in daughter G1 cells leading to G1 arrest, whereas WEE1 inhibition caused DNA damage and arrest in S phase, leading to earlier onset apoptosis. In vivo xenograft DLBCL models confirmed differences in single-agent antitumor activity, but also showed potential for effective ATR inhibitor combinations. Importantly, insights into the different inhibitor mechanisms may guide differentiated clinical development strategies aimed at exploiting specific vulnerabilities of tumor cells while maximizing therapeutic index. Our data therefore highlight clinical development opportunities for both ATR and WEE1 inhibitors in non-GCB DLBCL subtypes that represent an area of unmet clinical need. SIGNIFICANCE: ATR and WEE1 inhibitors demonstrate effective antitumor activity in preclinical models of DLBCL associated with replication stress, but new mechanistic insights and biomarkers of response support a differentiated clinical development strategy.

Evaluating Robustness and Sensitivity of the NanoString Technologies nCounter Platform to Enable Multiplexed Gene Expression Analysis of Clinical Samples.

Analysis of clinical trial specimens such as formalin-fixed paraffin-embedded (FFPE) tissue for molecular mechanisms of disease progression or drug response is often challenging and limited to a few markers at a time. This has led to the increasing importance of highly multiplexed assays that enable profiling of many biomarkers within a single assay. Methods for gene expression analysis have undergone major advances in biomedical research, but obtaining a robust dataset from low-quality RNA samples, such as those isolated from FFPE tissue, remains a challenge. Here, we provide a detailed evaluation of the NanoString Technologies nCounter platform, which provides a direct digital readout of up to 800 mRNA targets simultaneously. We tested this system by examining a broad set of human clinical tissues for a range of technical variables, including sensitivity and limit of detection to varying RNA quantity and quality, reagent performance over time, variability between instruments, the impact of the number of fields of view sampled, and differences between probe sequence locations and overlapping genes across CodeSets. This study demonstrates that Nanostring offers several key advantages, including sensitivity, reproducibility, technical robustness, and utility for clinical application.

Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with distinct molecular subtypes. The most established subtyping approach, the "Cell of Origin" (COO) algorithm, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. Recently developed immunohistochemical (IHC) techniques and other established methodologies can deliver discordant results and have various technical limitations. We evaluated the NanoString nCounter gene expression system to address issues with current platforms. EXPERIMENTAL DESIGN: We devised a scoring system using 145 genes from published datasets to categorize DLBCL samples. After cell line validation, clinical tissue segmentation was tested using commercially available diagnostic DLBCL samples. Finally, we profiled biopsies from patients with relapsed/refractory DLBCL enrolled in the fostamatinib phase IIb clinical trial using three independent RNA expression platforms: NanoString, Affymetrix, and qNPA. RESULTS: Diagnostic samples showed a typical spread of subtypes with consistent gene expression profiles across matched fresh, frozen, and formalin-fixed paraffin-embedded tissues. Results from biopsy samples across platforms were remarkably consistent, in contrast to published IHC data. Interestingly, COO segmentation of longitudinal fostamatinib biopsies taken at initial diagnosis and then again at primary relapse showed 88% concordance (15/17), suggesting that COO designation remains stable over the course of disease progression. CONCLUSIONS: DLBCL segmentation of patient tumor samples is possible using a number of expression platforms. However, we found that NanoString offers the most flexibility and fewest limitations in regards to robust clinical tissue subtype characterization. These subtype distinctions should help guide disease prognosis and treatment options within DLBCL clinical practice.