TrAp: a Tree Approach for Fingerprinting Subclonal Tumor Composition

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide an overview of an aggregate of numerous cells, rather than subclonal-specific quantification of aberrations such as single nucleotide variants (SNVs). Computational approaches to de-mix a single collective signal from the mixed cell population of a tumor sample into its individual components are currently not available. Herein we propose a framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. The method is based on the plausible biological assumption that tumor progression is an evolutionary process where each individual aberration event stems from a unique subclone and is present in all its descendants subclones. We have developed an efficient algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation datasets. We applied TrAp to SNV frequency profile from Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of twenty single cells of the same tumor. Despite the large experimental noise, specific co-occurring mutations found in clones inferred by TrAp are also present in some of these single cells. Finally, we deconvolve Exome-Seq data from three distinct metastases from different body compartments of one melanoma patient and exhibit the evolutionary relationships of their subpopulations

Paths to a malaria vaccine illuminated by parasite genomics.

More human death and disease is caused by malaria parasites than by all other eukaryotic pathogens combined. As early as the sequencing of the first human genome, malaria parasite genomics was prioritized to fuel the discovery of vaccine candidate antigens. This stimulated increased research on malaria, generating new understanding of the cellular and molecular mechanisms of infection and immunity. This review of recent developments illustrates how new approaches in parasite genomics, and increasingly large amounts of data from population studies, are helping to identify antigens that are promising lead targets. Although these results have been encouraging, effective discovery and characterization need to be coupled with more innovation and funding to translate findings into newly designed vaccine products for clinical trials

T. thermophila group I introns that cleave amide bonds

The present invention relates to nucleic acid enzymes or enzymatic RNA molecules that are capable of cleaving a variety of bonds, including phosphodiester bonds and amide bonds, in a variety of substrates. Thus, the disclosed enzymatic RNA molecules are capable of functioning as nucleases and/or peptidases. The present invention also relates to compositions containing the disclosed enzymatic RNA molecule and to methods of making, selecting, and using such enzymes and compositions

Fast and scalable inference of multi-sample cancer lineages.

Somatic variants can be used as lineage markers for the phylogenetic reconstruction of cancer evolution. Since somatic phylogenetics is complicated by sample heterogeneity, novel specialized tree-building methods are required for cancer phylogeny reconstruction. We present LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution), a novel method that automates the phylogenetic inference of cancer progression from multiple somatic samples. LICHeE uses variant allele frequencies of somatic single nucleotide variants obtained by deep sequencing to reconstruct multi-sample cell lineage trees and infer the subclonal composition of the samples. LICHeE is open source and available at http://viq854.github.io/lichee

Detecting copy number status and uncovering subclonal markers in heterogeneous tumor biopsies

<p>Abstract</p> <p>Background</p> <p>Genomic aberrations can be used to determine cancer diagnosis and prognosis. Clinically relevant novel aberrations can be discovered using high-throughput assays such as Single Nucleotide Polymorphism (SNP) arrays and next-generation sequencing, which typically provide aggregate signals of many cells at once. However, heterogeneity of tumor subclones dramatically complicates the task of detecting aberrations.</p> <p>Results</p> <p>The aggregate signal of a population of subclones can be described as a linear system of equations. We employed a measure of allelic imbalance and total amount of DNA to characterize each locus by the copy number status (gain, loss or neither) of the strongest subclonal component. We designed simulated data to compare our measure to existing approaches and we analyzed SNP-arrays from 30 melanoma samples and transcriptome sequencing (RNA-Seq) from one melanoma sample.</p> <p>We showed that any system describing aggregate subclonal signals is underdetermined, leading to non-unique solutions for the exact copy number profile of subclones. For this reason, our illustrative measure was more robust than existing Hidden Markov Model (HMM) based tools in inferring the aberration status, as indicated by tests on simulated data. This higher robustness contributed in identifying numerous aberrations in several loci of melanoma samples. We validated the heterogeneity and aberration status within single biopsies by fluorescent <it>in situ </it>hybridization of four affected and transcriptionally up-regulated genes E2F8, ETV4, EZH2 and FAM84B in 11 melanoma cell lines. Heterogeneity was further demonstrated in the analysis of allelic imbalance changes along single exons from melanoma RNA-Seq.</p> <p>Conclusions</p> <p>These studies demonstrate how subclonal heterogeneity, prevalent in tumor samples, is reflected in aggregate signals measured by high-throughput techniques. Our proposed approach yields high robustness in detecting copy number alterations using high-throughput technologies and has the potential to identify specific subclonal markers from next-generation sequencing data.</p

Intratumoral Genetic and Functional Heterogeneity in Pediatric Glioblastoma.

Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand the mechanisms of tumor evolution in this cancer, we performed whole-genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of nonsynonymous single-nucleotide variants being shared in diagnostic-recurrent pairs. To track the origins of the mutational events observed in pGBM, we generated whole-genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to nondividing cells. Interestingly, radiation and antimitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, because slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and therefore would accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM. SIGNIFICANCE: This work challenges several assumptions regarding the genetic organization of pediatric GBM and highlights mutagenic programs that start during early prenatal development.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/9/2111/F1.large.jpg.Wellcome Trust Royal Societ

1: To Know Ourselves

AT THE END OF THE ROAD in Little Cottonwood Canyon, near Salt Lake City, Alta is a place of near-mythic renown among skiers. In time it may well assume similar status among molecular geneticists. In December 1984, a conference there, co-sponsored by the U.S. Department of Energy, pondered a single question: Does modern DNA research offer a way of detecting tiny genetic mutations—and, in particular, of observing any increase in the mutation rate among the survivors of the Hiroshima and Nagasaki bombings and their descendants? In short the answer was, Not yet. But in an atmosphere of rare intellectual fertility, the seeds were sown for a project that would make such detection possible in the future—the Human Genome Project

Mitochondrial DNA Analysis by Denaturing High-Performance Liquid Chromatography for the Characterization and Separation of Mixtures in Forensic Samples

A mixture of different mtDNA molecules in a single sample is a significant obstacle to the successful use of standard methods of mtDNA analysis (i.e., dideoxy dye-terminator sequencing). Forensic analysts often encounter either naturally occurring mixtures (e.g., heteroplasmy) or situational mixtures typically arising from a combination of body fluids from separate individuals. The ability to accurately resolve and interpret these types of samples in a timely and cost efficient manner would substantially increase the power of mtDNA analysis and potentially provide valuable investigative information by allowing its use in cases where the current approach is limited or fails. Therefore, this research was aimed at developing a strategy for the use of Denaturing High-Performance Liquid Chromatography (DHPLC) as a developmentally-validated forensic application for resolving mixtures of mtDNA. To facilitate the adoption of this technology by the forensic community, a significant effort has been made to ensure that this technology meets the Scientific Working Group on DNA Analysis Methods (SWGDAM) developmental validation criteria and interfaces smoothly with previously validated methods of forensic mtDNA analysis. To do this, the method developed using DHPLC employs mtDNA amplicons, PCR conditions and DNA sequencing protocols validated for use in forensic laboratories. These factors are essential in implementing DHPLC analysis in a forensic casework environment and for the admissibility of DHPLC and Linkage Phase Analysis in court