The targeted delivery of multicomponent cargos to cancer cells by nanoporous particle-supported lipid bilayers.

Encapsulation of drugs within nanocarriers that selectively target malignant cells promises to mitigate side effects of conventional chemotherapy and to enable delivery of the unique drug combinations needed for personalized medicine. To realize this potential, however, targeted nanocarriers must simultaneously overcome multiple challenges, including specificity, stability and a high capacity for disparate cargos. Here we report porous nanoparticle-supported lipid bilayers (protocells) that synergistically combine properties of liposomes and nanoporous particles. Protocells modified with a targeting peptide that binds to human hepatocellular carcinoma exhibit a 10,000-fold greater affinity for human hepatocellular carcinoma than for hepatocytes, endothelial cells or immune cells. Furthermore, protocells can be loaded with combinations of therapeutic (drugs, small interfering RNA and toxins) and diagnostic (quantum dots) agents and modified to promote endosomal escape and nuclear accumulation of selected cargos. The enormous capacity of the high-surface-area nanoporous core combined with the enhanced targeting efficacy enabled by the fluid supported lipid bilayer enable a single protocell loaded with a drug cocktail to kill a drug-resistant human hepatocellular carcinoma cell, representing a 10(6)-fold improvement over comparable liposomes

Association of immunophenotype with expression of topoisomerase II α and β in adult acute myeloid leukemia.

Anthracyclines used in the treatment of acute myelogenous leukemia (AML) inhibit the activity of the mammalian topoisomerase II (topo II) isoforms, topo II α and topo IIβ. In 230 patients with non-M3 AML who received frontline ara-C/daunorubicin we determined expression of topo IIα and topo IIβ by RT-PCR and its relationship to immunophenotype (IP) and outcomes. Treatment outcomes were analyzed by logistic or Cox regression. In 211 patients, available for analysis, topo IIα expression was significantly lower than topo IIβ (P \u3c 0.0001). In contrast to topo IIα, topo IIβ was significantly associated with blast percentage in marrow or blood (P = 0.0001), CD7 (P = 0.01), CD14 (P \u3c 0.0001) and CD54 (P \u3c 0.0001). Event free survival was worse for CD56-negative compared to CD56-high (HR = 1.9, 95% CI [1.0-3.5], p = 0.04), and overall survival was worse for CD-15 low as compared to CD15-high (HR = 2.2, 95% CI [1.1-4.2], p = 0.02). Ingenuity pathway analysis indicated topo IIβ and immunophenotype markers in a network associated with cell-to-cell signaling, hematological system development/function and inflammatory response. Topo IIβ expression reflects disease biology of highly proliferative disease and distinct IP but does not appear to be an independent variable influencing outcome in adult AML patients treated with anthracycline-based therapy

AML risk stratification models utilizing ELN-2017 guidelines and additional prognostic factors: a SWOG report.

Background: The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice. Methods: In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, Results: Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age \u3c 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for Conclusions: While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification

Priorities to Promote Participant Engagement in the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network.

BACKGROUND: Engaging diverse populations in cancer genomics research is of critical importance and is a fundamental goal of the NCI Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Established as part of the Cancer Moonshot, PE-CGS is a consortium of stakeholders including clinicians, scientists, genetic counselors, and representatives of potential study participants and their communities. Participant engagement is an ongoing, bidirectional, and mutually beneficial interaction between study participants and researchers. PE-CGS sought to set priorities in participant engagement for conducting the network\u27s research. METHODS: PE-CGS deliberatively engaged its stakeholders in the following four-phase process to set the network\u27s research priorities in participant engagement: (i) a brainstorming exercise to elicit potential priorities; (ii) a 2-day virtual meeting to discuss priorities; (iii) recommendations from the PE-CGS External Advisory Panel to refine priorities; and (iv) a virtual meeting to set priorities. RESULTS: Nearly 150 PE-CGS stakeholders engaged in the process. Five priorities were set: (i) tailor education and communication materials for participants throughout the research process; (ii) identify measures of participant engagement; (iii) identify optimal participant engagement strategies; (iv) understand cancer disparities in the context of cancer genomics research; and (v) personalize the return of genomics findings to participants. CONCLUSIONS: PE-CGS is pursuing these priorities to meaningfully engage diverse and underrepresented patients with cancer and posttreatment cancer survivors as participants in cancer genomics research and, subsequently, generate new discoveries. IMPACT: Data from PE-CGS will be shared with the broader scientific community in a manner consistent with participant informed consent and community agreement

Genomic analyses identify recurrent MEF2D fusions in acute lymphoblastic leukemia

Chromosomal rearrangements are initiating events in acute lymphoblastic leukaemia (ALL). Here using RNA sequencing of 560 ALL cases, we identify rearrangements between MEF2D (myocyte enhancer factor 2D) and five genes (BCL9, CSF1R, DAZAP1, HNRNPUL1 and SS18) in 22 B progenitor ALL (B-ALL) cases with a distinct gene expression profile, the most common of which is MEF2DBCL9. Examination of an extended cohort of 1,164 B-ALL cases identified 30 cases with MEF2D rearrangements, which include an additional fusion partner, FOXJ2; thus, MEF2D-rearranged cases comprise 5.3% of cases lacking recurring alterations. MEF2D-rearranged ALL is characterized by a distinct immunophenotype, DNA copy number alterations at the rearrangement sites, older diagnosis age and poor outcome. The rearrangements result in enhanced MEF2D transcriptional activity, lymphoid transformation, activation of HDAC9 expression and sensitive to histone deacetylase inhibitor treatment. Thus, MEF2D-rearranged ALL represents a distinct form of high-risk leukaemia, for which new therapeutic approaches should be considered.This work was supported in part by the American Lebanese Syrian Associated Charities of St. Jude Children’s Research Hospital; by a Stand Up to Cancer Innovative Research Grant and St. Baldrick’s Foundation Scholar Award (to C.G.M.); by a St. Baldrick’s Consortium Award (S.P.H.), by a Leukemia and Lymphoma Society Specialized Center of Research grant (S.P.H. and C.G.M.), by a Lady Tata Memorial Trust Award (I.I.), by a Leukemia and Lymphoma Society Special Fellow Award and Alex’s Lemonade Stand Foundation Young Investigator Awards (K.R.), by an Alex’s Lemonade Stand Foundation Award (M.L.) and by National Cancer Institute Grants CA21765 (St Jude Cancer Center Support Grant), U01 CA157937 (C.L.W. and S.P.H.), U24 CA114737 (to Dr Gastier-Foster), NCI Contract HHSN261200800001E (to Dr Gastier-Foster), U10 CA180820 (ECOG-ACRIN Operations) and CA180827 (E.P.); U10 CA180861 (C.D.B. and G.M.); U24 CA196171 (The Alliance NCTN Biorepository and Biospecimen Resource); CA145707 (C.L.W. and C.G.M.); and grants to the COG: U10 CA98543 (Chair’s grant and supplement to support the COG ALL TARGET project), U10 CA98413 (Statistical Center) and U24 CA114766 (Specimen Banking). This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract Number HHSN261200800001E

Deregulation of DUX4 and ERG in acute lymphoblastic leukemia

Chromosomal rearrangements deregulating hematopoietic transcription factors are common in acute lymphoblastic leukemia (ALL).1,2 Here, we show that deregulation of the homeobox transcription factor gene DUX4 and the ETS transcription factor gene ERG are hallmarks of a subtype of B-progenitor ALL that comprises up to 7% of B-ALL. DUX4 rearrangement and overexpression was present in all cases, and was accompanied by transcriptional deregulation of ERG, expression of a novel ERG isoform, ERGalt, and frequent ERG deletion. ERGalt utilizes a non-canonical first exon whose transcription was initiated by DUX4 binding. ERGalt retains the DNA-binding and transactivating domains of ERG, but inhibits wild-type ERG transcriptional activity and is transforming. These results illustrate a unique paradigm of transcription factor deregulation in leukemia, in which DUX4 deregulation results in loss-of-function of ERG, either by deletion or induction of expression of an isoform that is a dominant negative inhibitor of wild type ERG function

High throughput instruments, methods, and informatics for systems biology.

High throughput instruments and analysis techniques are required in order to make good use of the genomic sequences that have recently become available for many species, including humans. These instruments and methods must work with tens of thousands of genes simultaneously, and must be able to identify the small subsets of those genes that are implicated in the observed phenotypes, or, for instance, in responses to therapies. Microarrays represent one such high throughput method, which continue to find increasingly broad application. This project has improved microarray technology in several important areas. First, we developed the hyperspectral scanner, which has discovered and diagnosed numerous flaws in techniques broadly employed by microarray researchers. Second, we used a series of statistically designed experiments to identify and correct errors in our microarray data to dramatically improve the accuracy, precision, and repeatability of the microarray gene expression data. Third, our research developed new informatics techniques to identify genes with significantly different expression levels. Finally, natural language processing techniques were applied to improve our ability to make use of online literature annotating the important genes. In combination, this research has improved the reliability and precision of laboratory methods and instruments, while also enabling substantially faster analysis and discovery

Application of multidisciplinary analysis to gene expression.

Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from microarrays, we have made progress by combining very different analytic approaches