Mark A. Murakami

Integration of gene mutations in risk prognostication for patients receiving first-line immunochemotherapy for follicular lymphoma: a retrospective analysis of a prospective clinical trial and validation in a population-based registry

BACKGROUND Follicular lymphoma is a clinically and genetically heterogeneous disease, but the prognostic value of somatic mutations has not been systematically assessed. We aimed to improve risk stratification of patients receiving first-line immunochemotherapy by integrating gene mutations into a prognostic model. METHODS We did DNA deep sequencing to retrospectively analyse the mutation status of 74 genes in 151 follicular lymphoma biopsy specimens that were obtained from patients within 1 year before beginning immunochemotherapy consisting of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). These patients were recruited between May 4, 2000, and Oct 20, 2010, as part of a phase 3 trial (GLSG2000). Eligible patients had symptomatic, advanced stage follicular lymphoma and were previously untreated. The primary endpoints were failure-free survival (defined as less than a partial remission at the end of induction, relapse, progression, or death) and overall survival calculated from date of treatment initiation. Median follow-up was 7·7 years (IQR 5·5-9·3). Mutations and clinical factors were incorporated into a risk model for failure-free survival using multivariable L1-penalised Cox regression. We validated the risk model in an independent population-based cohort of 107 patients with symptomatic follicular lymphoma considered ineligible for curative irradiation. Pretreatment biopsies were taken between Feb 24, 2004, and Nov 24, 2009, within 1 year before beginning first-line immunochemotherapy consisting of rituximab, cyclophosphamide, vincristine, and prednisone (R-CVP). Median follow-up was 6·7 years (IQR 5·7-7·6). FINDINGS We established a clinicogenetic risk model (termed m7-FLIPI) that included the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the Follicular Lymphoma International Prognostic Index (FLIPI), and Eastern Cooperative Oncology Group (ECOG) performance status. In the training cohort, m7-FLIPI defined a high-risk group (28%, 43/151) with 5-year failure-free survival of 38·29% (95% CI 25·31-57·95) versus 77·21% (95% CI 69·21-86·14) for the low-risk group (hazard ratio [HR] 4·14, 95% CI 2·47-6·93; p<0·0001; bootstrap-corrected HR 2·02), and outperformed a prognostic model of only gene mutations (HR 3·76, 95% CI 2·10-6·74; p<0·0001; bootstrap-corrected HR 1·57). The positive predictive value and negative predictive value for 5-year failure-free survival were 64% and 78%, respectively, with a C-index of 0·80 (95% CI 0·71-0·89). In the validation cohort, m7-FLIPI again defined a high-risk group (22%, 24/107) with 5-year failure-free survival of 25·00% (95% CI 12·50-49·99) versus 68·24% (58·84-79·15) in the low-risk group (HR 3·58, 95% CI 2·00-6·42; p<0.0001). The positive predictive value for 5-year failure-free survival was 72% and 68% for negative predictive value, with a C-index of 0·79 (95% CI 0·69-0·89). In the validation cohort, risk stratification by m7-FLIPI outperformed FLIPI alone (HR 2·18, 95% CI 1·21-3·92), and FLIPI combined with ECOG performance status (HR 2·03, 95% CI 1·12-3·67). INTERPRETATION Integration of the mutational status of seven genes with clinical risk factors improves prognostication for patients with follicular lymphoma receiving first-line immunochemotherapy and is a promising approach to identify the subset at highest risk of treatment failure. FUNDING Deutsche Krebshilfe, Terry Fox Research Institute.

The Public Repository of Xenografts Enables Discovery and Randomized Phase II-like Trials in Mice

More than 90% of drugs with preclinical activity fail in human trials, largely due to insufficient efficacy. We hypothesized that adequately powered trials of patient-derived xenografts (PDX) in mice could efficiently define therapeutic activity across heterogeneous tumors. To address this hypothesis, we established a large, publicly available repository of well-characterized leukemia and lymphoma PDXs that undergo orthotopic engraftment, called the Public Repository of Xenografts (PRoXe). PRoXe includes all de-identified information relevant to the primary specimens and the PDXs derived from them. Using this repository, we demonstrate that large studies of acute leukemia PDXs that mimic human randomized clinical trials can characterize drug efficacy and generate transcriptional, functional, and proteomic biomarkers in both treatment-naive and relapsed/refractory disease.

Activation of the unfolded protein response is associated with impaired granulopoiesis in transgenic mice expressing mutant Elane

Severe congenital neutropenia (SCN) is an inborn disorder of granulopoiesis that in many cases is caused by mutations of the ELANE gene, which encodes neutrophil elastase (NE). Recent data suggest a model in which ELANE mutations result in NE protein misfolding, induction of endoplasmic reticulum (ER) stress, activation of the unfolded protein response (UPR), and ultimately a block in granulocytic differentiation. To test this model, we generated transgenic mice carrying a targeted mutation of Elane (G193X) reproducing a mutation found in SCN. The G193X Elane allele produces a truncated NE protein that is rapidly degraded. Granulocytic precursors from G193X Elane mice, though without significant basal UPR activation, are sensitive to chemical induction of ER stress. Basal and stress granulopoiesis after myeloablative therapy are normal in these mice. Moreover, inaction of protein kinase RNA-like ER kinase (Perk), one of the major sensors of ER stress, either alone or in combination with G193X Elane, had no effect on basal granulopoiesis. However, inhibition of the ER-associated degradation (ERAD) pathway using a proteosome inhibitor resulted in marked neutropenia in G193X Elane. The selective sensitivity of G913X Elane granulocytic cells to ER stress provides new and strong support for the UPR model of disease patho-genesis in SCN.

Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate

Assays that can determine the response of tumor cells to cancer therapeutics could greatly aid the selection of drug regimens for individual patients. However, the utility of current functional assays is limited, and predictive genetic biomarkers are available for only a small fraction of cancer therapies. We found that the single-cell mass accumulation rate (MAR), profiled over many hours with a suspended microchannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cell acute lymphocytic leukemia cells. MAR revealed heterogeneity in drug sensitivity not only between different tumors, but also within individual tumors and tumor-derived cell lines. MAR measurement predicted drug response using samples as small as 25 μl of peripheral blood while maintaining cell viability and compatibility with downstream characterization. MAR measurement is a promising approach for directly assaying single-cell therapeutic responses and for identifying cellular subpopulations with phenotypic resistance in heterogeneous tumors.

Erratum: The Public Repository of Xenografts Enables Discovery and Randomized Phase II-like Trials in Mice (Cancer Cell (2016) 29 (574–586))

Elizabeth C. Townsend, Mark A. Murakami, Alexandra Christodoulou, Amanda L. Christie, Johannes Köster, Tiffany A. DeSouza, Elizabeth A. Morgan, Scott P. Kallgren, Huiyun Liu, Shuo-Chieh Wu, Olivia Plana, Joan Montero, Kristen E. Stevenson, Prakash Rao, Raga Vadhi, Michael Andreeff, Philippe Armand, Karen K. Ballen, Patrizia Barzaghi-Rinaudo, Sarah Cahill, Rachael A. Clark, Vesselina G. Cooke, Matthew S. Davids, Daniel J. DeAngelo, David M. Dorfman, Hilary Eaton, Benjamin L. Ebert, Julia Etchin, Brant Firestone, David C. Fisher, Arnold S. Freedman, Ilene A. Galinsky, Hui Gao, Jacqueline S. Garcia, Francine Garnache-Ottou, Timothy A. Graubert, Alejandro Gutierrez, Ensar Halilovic, Marian H. Harris, Zachary T. Herbert, Steven M. Horwitz, Giorgio Inghirami, Andrew M. Intlekofer, Moriko Ito, Shai Izraeli, Eric D. Jacobsen, Caron A. Jacobson, Sébastien Jeay, Irmela Jeremias, Michelle A. Kelliher, Raphael Koch, Marina Konopleva, Nadja Kopp, Steven M. Kornblau, Andrew L. Kung, Thomas S. Kupper, Nicole R. LeBoeuf, Ann S. LaCasce, Emma Lees, Loretta S. Li, A. Thomas Look, Masato Murakami, Markus Muschen, Donna Neuberg, Samuel Y. Ng, Oreofe O. Odejide, Stuart H. Orkin, Rachel R. Paquette, Andrew E. Place, Justine E. Roderick, Jeremy A. Ryan, Stephen E. Sallan, Brent Shoji, Lewis B. Silverman, Robert J. Soiffer, David P. Steensma, Kimberly Stegmaier, Richard M. Stone, Jerome Tamburini, Aaron R. Thorner, Paul van Hummelen, Martha Wadleigh, Marion Wiesmann, Andrew P. Weng, Jens U. Wuerthner, David A. Williams, Bruce M. Wollison, Andrew A. Lane, Anthony Letai, Monica M. Bertagnolli, Jerome Ritz, Myles Brown, Henry Long, Jon C. Aster, Margaret A. Shipp, James D. Griffin, and David M. Weinstock* *Correspondence: dweinstock@partners.org http://dx.doi.org/10.1016/j.ccell.2016.06.008

PDX-MI: Minimal Information for Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patients tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62-66. ©2017 AACR.

Targeting minimal residual disease: a path to cure?

Therapeutics that block kinases, transcriptional modifiers, immune checkpoints and other biological vulnerabilities are transforming cancer treatment. As a result, many patients achieve dramatic responses, including complete radiographical or pathological remission, yet retain minimal residual disease (MRD), which results in relapse. New functional approaches can characterize clonal heterogeneity and predict therapeutic sensitivity of MRD at a single-cell level. Preliminary evidence suggests that iterative detection, profiling and targeting of MRD would meaningfully improve outcomes and may even lead to cure.

Cancer models: The next best thing

&NA; A patients tumour cells can be transplanted into a mouse to provide a model for analysis and drug testing. A panel of paediatric solid tumour models has been extensively characterized and made freely available. See Letter p.96

An ED pilot intervention to facilitate outpatient acute care for cancer patients.

INTRODUCTION Unplanned hospitalizations are common in patients with cancer, and most hospitalizations originate in the emergency department (ED). METHODS We implemented an ED-based pilot intervention designed to reduce hospitalizations among patients with solid tumors. The intervention, piloted at a single academic medical center, involved a medical oncologist embedded in the ED during evening hours. We used a quasiexperimental preimplementation/postimplementation study design to evaluate the proportion of ED visits that resulted in inpatient hospital admission, before and after pilot implementation. General estimating equations were used to evaluate the association between the intervention and hospital admission. RESULTS There were 390 ED visits by eligible cancer patients in the preintervention period and 418 visits in the intervention period. During the intervention period, 158 (38%) of 418 ED visits were identified by the embedded oncologist during the evening intervention shift. The proportion of ED visits leading to hospitalization was 70% vs 69% in the preintervention and intervention periods (odds ratio, 0.93 [95% confidence interval, 0.69-1.24]; P= .62). There were no differences between periods in ED length of stay or subsequent use of acute care. Among patients with initial ED presentation during the operating hours of the intervention, the proportion of ED visits leading to hospitalization was 77% vs 67% in the preintervention and intervention periods (odds ratio, 0.62 [0.36-1.08]; P= .08). CONCLUSION Embedding an oncologist in the ED of an academic medical center did not significantly reduce hospital admissions. Novel approaches are needed to strengthen outpatient acute care for patients with cancer.

Pan-SRC kinase inhibition blocks B-cell receptor oncogenic signaling in non-Hodgkin lymphoma.

In diffuse large B-cell lymphoma (DLBCL), activation of the B-cell receptor (BCR) promotes multiple oncogenic signals, which are essential for tumor proliferation. Inhibition of the Brutons tyrosine kinase (BTK), a BCR downstream target, is therapeutically effective only in a subgroup of patients with DLBCL. Here, we used lymphoma cells isolated from patients with DLBCL to measure the effects of targeted therapies on BCR signaling and to anticipate response. In lymphomas resistant to BTK inhibition, we show that blocking BTK activity enhanced tumor dependencies from alternative oncogenic signals downstream of the BCR, converging on MYC upregulation. To completely ablate the activity of the BCR, we genetically and pharmacologically repressed the activity of the SRC kinases LYN, FYN, and BLK, which are responsible for the propagation of the BCR signal. Inhibition of these kinases strongly reduced tumor growth in xenografts and cell lines derived from patients with DLBCL independent of their molecular subtype, advancing the possibility to be relevant therapeutic targets in broad and diverse groups of DLBCL patients.