Citations

Peripheral T cell lymphoma (PTCL) is a heterogeneous group of postthymic T cell neoplasms, with ~40% classified as PTCL–not otherwise specified (PTCL-NOS). PTCL-GATA3, a molecularly defined subtype, associated with T helper 2 (T H 2)–like differentiation and poor prognosis, has frequent co-occurrence of TP53 loss/mutation and heterozygous PTEN loss. CD4+ T cell conditional mouse models with Trp53 mutation/deletion and Pten loss demonstrated mature T cell lymphomas (mTCLs) with T H 2-like transcriptomic and immunophenotypic profiles. Molecular studies revealed that codeletion of Trp53/Pten induced T cell receptor and Janus kinase–signal transducer and activator of transcription signaling, promoting T H 2 differentiation while inhibiting T H 1 differentiation. These findings were validated by CRISPR editing of TP53/PTEN loss in human CD4+ T cells and mechanistically evaluated the p53 binding region in intron-3 of GATA3, resulting in transcriptional repression. Transcriptomic profiles of m-TCLs recapitulated human-PTCL-GATA3 transcriptome and distinguished PTCL-NOS subtypes. Preclinical assessment of m-TCLs with PI3Kγ/δ inhibitors significantly improved survival, supporting a therapeutic approach for the p53-aberrant PTCL-GATA3.

Abstract Basket, umbrella, and platform trial designs (master protocols) have emerged over the last decade to study precision medicine approaches in oncology. First-generation trials like NCI-MATCH (Molecular Analysis for Therapy Choice) have proven the principle that studying targeted therapies on a large scale is feasible both from the laboratory and clinical perspectives. However, single-agent targeted therapies have shown limited ability to control metastatic disease, despite careful matching of drug to target. As such, newer approaches employing combinations of targeted therapy, or targeted therapy with standard therapies, need to be considered. The NCI has recently embarked on three second-generation precision medicine trials to address this need: ComboMATCH, iMATCH, and myeloMATCH. The design of these trials and necessary infrastructure are discussed in the following perspective.

Abstract Summary Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels. Availability and implementation MiRKAT is available on CRAN as an R package. Supplementary information Supplementary data are available at Bioinformatics online.

Abstract Objectives To summarize cases submitted to the 2019 Society for Hematopathology/European Association for Haematopathology Workshop under the category of myeloid/lymphoid neoplasms with eosinophilia and PDGFRA, PDGFRB, or FGFR1 or with PCM1-JAK2 rearrangements, focusing on recent updates and relevant practice findings. Methods The cases were summarized according to their respective gene rearrangement to illustrate the spectrum of clinical, laboratory, and histopathology manifestations and to explore the appropriate molecular genetic tests. Results Disease presentations were heterogeneous, including myeloproliferative neoplasms (MPNs), myelodysplastic syndromes (MDSs), MDS/MPN, acute myeloid leukemia, acute B- or T-lymphoblastic lymphoma/acute lymphoblastic lymphoma (ALL/LBL), or mixed-lineage neoplasms. Frequent extramedullary involvement occurred. Eosinophilia was common but not invariably present. With the advancement of RNA sequencing, cryptic rearrangements were recognized in genes other than PDGFRA. Additional somatic mutations were more frequent in the FGFR1-rearranged cases. Cases with B-ALL presentations differed from Philadelphia-like B-ALL by the presence of an underlying MPN. Cases with FLT3 and ABL1 rearrangements could be potential candidates for future inclusion in this category. Conclusions Accurate diagnosis and classification of this category of myeloid/lymphoid neoplasms has important therapeutic implications. With the large number of submitted cases, we expand our understanding of these rare neoplasms and improve our ability to diagnose these genetically defined disorders.

Tissue microarrays (TMAs) are important tools to conserve precious tissue resources from increasingly smaller biopsies and to control experimental costs and variation across sample sets. The quality assurance assessment of TMA materials created at centralized biobanks has not been standardized. Herein, we outline 2 processes for the construction of TMAs (“recipient block” and “tape” methods) and the associated preconstruction quality control measures (pathology review, protein and RNA assessment, map creation, and storage conditions) developed by the AIDS Cancer Specimen Resource (ACSR) Network’s Science and Technology Core. These steps provide a suggested framework for quality assessment that allows end-users, receiving materials from tissue banks, confidence in their experimental results.

Abstract The growing body of genomic information collected and applied to mature aggressive B-cell lymphoma diagnosis and management has exploded over the last few years due to improved technologies with high-throughput capacity, suitable for use on routine formalin-fixed, paraffin-embedded tissue biopsies, and decreasing costs. These techniques have made evaluation of complete DNA sequences, RNA-expression patterns, translocations, copy-number alterations, loss of heterozygosity, and DNA-methylation patterns possible on a genome-wide level. This chapter will present a case of aggressive B-cell lymphoma and discuss the most important genomic abnormalities that characterize this group of entities in the recent update to the fourth edition of the World Health Organization (WHO) lymphoma classification system. Genomic abnormalities discussed will include those necessary for certain diagnoses such as translocations of MYC, BCL2, or BCL6; gene-expression-profiling categorization; the newly defined Burkitt-like lymphoma with 11q abnormalities; prognostic and predictive mutations, as well as tumor heterogeneity. Finally, our current practices for clinical triage of specimens with a potential diagnosis of aggressive B-cell lymphomas are also described. Options for treatment at relapse, in light of these genomic features, will be discussed in the third presentation from this session.

Abstract Motivation The human microbiome is notoriously variable across individuals, with a wide range of ‘healthy’ microbiomes. Paired and longitudinal studies of the microbiome have become increasingly popular as a way to reduce unmeasured confounding and to increase statistical power by reducing large inter-subject variability. Statistical methods for analyzing such datasets are scarce. Results We introduce a paired UniFrac dissimilarity that summarizes within-individual (or within-pair) shifts in microbiome composition and then compares these compositional shifts across individuals (or pairs). This dissimilarity depends on a novel transformation of relative abundances, which we then extend to more than two time points and incorporate into several phylogenetic and non-phylogenetic dissimilarities. The data transformation and resulting dissimilarities may be used in a wide variety of downstream analyses, including ordination analysis and distance-based hypothesis testing. Simulations demonstrate that tests based on these dissimilarities retain appropriate type 1 error and high power. We apply the method in two real datasets. Availability and implementation The R package pldist is available on GitHub at https://github.com/aplantin/pldist. Supplementary information Supplementary data are available at Bioinformatics online.