Estimating the Probability of Clonal Relatedness of Pairs of Tumors in Cancer Patients

Next generation sequencing panels are being used increasingly in cancer research to study tumor evolution. A specific statistical challenge is to compare the mutational profiles in different tumors from a patient to determine the strength of evidence that the tumors are clonally related, i.e. derived from a single, founder clonal cell. The presence of identical mutations in each tumor provides evidence of clonal relatedness, although the strength of evidence from a match is related to how commonly the mutation is seen in the tumor type under investigation. This evidence must be weighed against the evidence in favor of independent tumors from non-matching mutations. In this article we frame this challenge in the context of diagnosis using a novel random effects model. In this way, by analyzing a set of tumor pairs, we can estimate the proportion of cases that are clonally related in the sample as well as the individual diagnostic probabilities for each case. The method is illustrated using data from a study to determine the clonal relationship of lobular carcinoma in situ with subsequent invasive breast cancers where each tumor in the pair was subjected to whole exome sequencing. The statistical properties of the method are evaluated using simulations, demonstrating that the key model parameters are estimated with only modest bias in small samples

Preliminary Investigation Into the Effect of ACTN3 and ACE Polymorphisms on Muscle and Performance Characteristics

Preliminary investigation into the effect of ACTN3 and ACE polymorphisms on muscle and performance characteristics. J Strength Cond Res XX(X): 000-000, 2018-The purpose of this investigation was to explore the phenotypic and performance outcomes associated with ACTN3 and ACE polymorphisms. Ten trained men (age = 25.8 ± 3.0 years, height = 183.3 ± 4.1 cm, body mass = 92.3 ± 9.3 kg, and back squat to body mass ratio = 1.8 ± 0.3) participated. Blood samples were analyzed to determine ACTN3 and ACE polymorphisms. Standing ultrasonography images of the vastus lateralis (VL) were collected to determine whole muscle cross-sectional area (CSA-M), and a percutaneous muscle biopsy of the VL was collected to determine type I-specific CSA (CSA-T1), type II-specific CSA (CSA-T2), and type II to type I CSA ratio (CSA-R). Isometric squats were performed on force platforms with data used to determine peak force (IPF), allometrically scaled peak force (IPFa), and rate of force development (RFD) at various timepoints. One repetition maximum back squats were performed, whereby allometrically scaled dynamic strength (DSa) was determined. Cohen\u27s d effect sizes revealed ACTN3 RR and ACE DD tended to result in greater CSA-M but differ in how they contribute to performance. ACTN3 RR\u27s influence seems to be in the type II fibers, altering maximal strength, and ACE DD may influence RFD capabilities through a favorable CSA-R. Although the findings of the current investigation are limited by the sample size, the findings demonstrate the potential influence of ACTN3 and ACE polymorphisms on isometric and dynamic strength testing. This study may serve as a framework to generate hypotheses regarding the effect of genetics on performance

The National Lung Matrix Trial: translating the biology of stratification in advanced non-small-cell lung cancer

© The Author 2015.Background: The management of NSCLC has been transformed by stratified medicine. The National Lung Matrix Trial (NLMT) is a UK-wide study exploring the activity of rationally selected biomarker/targeted therapy combinations. Patients and methods: The Cancer Research UK (CRUK) Stratified Medicine Programme 2 is undertaking the large volume national molecular pre-screening which integrates with the NLMT. At study initiation, there are eight drugs being used to target 18 molecular cohorts. The aim is to determine whether there is sufficient signal of activity in any drug-biomarker combination to warrant further investigation. A Bayesian adaptive design that gives a more realistic approach to decision making and flexibility to make conclusions without fixing the sample size was chosen. The screening platform is an adaptable 28-gene Nextera next-generation sequencing platform designed by Illumina, covering the range of molecular abnormalities being targeted. The adaptive design allows new biomarker-drug combination cohorts to be incorporated by substantial amendment. The pre-clinical justification for each biomarker-drug combination has been rigorously assessed creating molecular exclusion rules and a trumping strategy in patients harbouring concomitant actionable genetic abnormalities. Discrete routes of pathway activation or inactivation determined by cancer genome aberrations are treated as separate cohorts. Key translational analyses include the deep genomic analysis of pre- and post-treatment biopsies, the establishment of patient-derived xenograft models and longitudinal ctDNA collection, in order to define predictive biomarkers, mechanisms of resistance and early markers of response and relapse. Conclusion: The SMP2 platform will provide large scale genetic screening to inform entry into the NLMT, a trial explicitly aimed at discovering novel actionable cohorts in NSCLC

QuickNGS elevates Next-Generation Sequencing data analysis to a new level of automation

BACKGROUND: Next-Generation Sequencing (NGS) has emerged as a widely used tool in molecular biology. While time and cost for the sequencing itself are decreasing, the analysis of the massive amounts of data remains challenging. Since multiple algorithmic approaches for the basic data analysis have been developed, there is now an increasing need to efficiently use these tools to obtain results in reasonable time. RESULTS: We have developed QuickNGS, a new workflow system for laboratories with the need to analyze data from multiple NGS projects at a time. QuickNGS takes advantage of parallel computing resources, a comprehensive back-end database, and a careful selection of previously published algorithmic approaches to build fully automated data analysis workflows. We demonstrate the efficiency of our new software by a comprehensive analysis of 10 RNA-Seq samples which we can finish in only a few minutes of hands-on time. The approach we have taken is suitable to process even much larger numbers of samples and multiple projects at a time. CONCLUSION: Our approach considerably reduces the barriers that still limit the usability of the powerful NGS technology and finally decreases the time to be spent before proceeding to further downstream analysis and interpretation of the data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1695-x) contains supplementary material, which is available to authorized users

Idelalisib sensitivity and mechanisms of disease progression in relapsed TCF3-PBX1 acute lymphoblastic leukemia

Peer reviewe

Insulin utilizes the PI 3-kinase pathway to inhibit SP-A gene expression in lung epithelial cells

BACKGROUND: It has been proposed that high insulin levels may cause delayed lung development in the fetuses of diabetic mothers. A key event in lung development is the production of adequate amounts of pulmonary surfactant. Insulin inhibits the expression of surfactant protein A (SP-A), the major surfactant-associated protein, in lung epithelial cells. In the present study, we investigated the signal transduction pathways involved in insulin inhibition of SP-A gene expression. METHODS: H441 cells, a human lung adenocarcinoma cell line, or human fetal lung explants were incubated with or without insulin. Transcription run-on assays were used to determine SP-A gene transcription rates. Northern blot analysis was used to examine the effect of various signal transduction inhibitors on SP-A gene expression. Immunoblot analysis was used to evaluate the levels and phosphorylation states of signal transduction protein kinases. RESULTS: Insulin decreased SP-A gene transcription in human lung epithelial cells within 1 hour. Insulin did not affect p44/42 mitogen-activated protein kinase (MAPK) phosphorylation and the insulin inhibition of SP-A mRNA levels was not affected by PD98059, an inhibitor of the p44/42 MAPK pathway. In contrast, insulin increased p70 S6 kinase Thr389 phosphorylation within 15 minutes. Wortmannin or LY294002, both inhibitors of phosphatidylinositol 3-kinase (PI 3-kinase), or rapamycin, an inhibitor of the activation of p70 S6 kinase, a downstream effector in the PI 3-kinase pathway, abolished or attenuated the insulin-induced inhibition of SP-A mRNA levels. CONCLUSION: Insulin inhibition of SP-A gene expression in lung epithelial cells probably occurs via the rapamycin-sensitive PI 3-kinase signaling pathway

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

Adsorption of choline benzoate ionic liquid on graphene, silicene, germanene and boron-nitride nanosheets: a DFT perspective

The adsorption of choline benzoate ([CH][BE]) ionic liquid (IL) on the surface of different hexagonal nanosheets has been studied using Density Functional Theory (DFT) methods. For this, the interaction mechanism, binding energies and electronic structure of [CH][BE] ionic liquid on four types of nanosheets, i.e., graphene, silicene, germanene and boron-nitride, were estimated and compared. The adsorption of [CH][BE] ionic liquid on different nanosheets is mainly featured by van der Waals forces, leading to strong benzoate ion–surface π-stacking. Likewise, there is also an important charge transfer from the anion to the sheet. The electronic structure analysis shows that Si- and Ge-based sheets lead to the largest changes in the HOMO and LUMO levels of choline benzoate. This paper provides new insights into the capability of DFT methods to provide useful information about the adsorption of ionic liquids on nanosheets and how ionic liquid features could be tuned through the adsorption on the suitable nanosheet.Ministerio de Economı´a y Competitividad (Spain, project CTQ2013-40476-R) and Junta de Castilla y León (Spain, project BU324U14)