Novel Insights Into Breast Cancer Copy Number Genetic Heterogeneity Revealed by Single-Cell Genome Sequencing

Copy number alterations (CNAs) play an important role in molding the genomes of breast cancers and have been shown to be clinically useful for prognostic and therapeutic purposes. However, our knowledge of intra-tumoral genetic heterogeneity of this important class of somatic alterations is limited. Here, using single-cell sequencing, we comprehensively map out the facets of copy number alteration heterogeneity in a cohort of breast cancer tumors. Ou/var/www/html/elife/12-05-2020/backup/r analyses reveal: genetic heterogeneity of non-tumor cells (i.e. stroma) within the tumor mass; the extent to which copy number heterogeneity impacts breast cancer genomes and the importance of both the genomic location and dosage of sub-clonal events; the pervasive nature of genetic heterogeneity of chromosomal amplifications; and the association of copy number heterogeneity with clinical and biological parameters such as polyploidy and estrogen receptor negative status. Our data highlight the power of single-cell genomics in dissecting, in its many forms, intra-tumoral genetic heterogeneity of CNAs, the magnitude with which CNA heterogeneity affects the genomes of breast cancers, and the potential importance of CNA heterogeneity in phenomena such as therapeutic resistance and disease relapse

A classification model for distinguishing copy number variants from cancer-related alterations

<p>Abstract</p> <p>Background</p> <p>Both somatic copy number alterations (CNAs) and germline copy number variants (CNVs) that are prevalent in healthy individuals can appear as recurrent changes in comparative genomic hybridization (CGH) analyses of tumors. In order to identify important cancer genes CNAs and CNVs must be distinguished. Although the Database of Genomic Variants (DGV) contains a list of all known CNVs, there is no standard methodology to use the database effectively.</p> <p>Results</p> <p>We develop a prediction model that distinguishes CNVs from CNAs based on the information contained in the DGV and several other variables, including segment's length, height, closeness to a telomere or centromere and occurrence in other patients. The models are fitted on data from glioblastoma and their corresponding normal samples that were collected as part of The Cancer Genome Atlas project and hybridized to Agilent 244 K arrays.</p> <p>Conclusions</p> <p>Using the DGV alone CNVs in the test set can be correctly identified with about 85% accuracy if the outliers are removed before segmentation and with 72% accuracy if the outliers are included, and additional variables improve the prediction by about 2-3% and 12%, respectively. Final models applied to data from ovarian tumors have about 90% accuracy with all the variables and 86% accuracy with the DGV alone.</p

Chromosomal instability drives metastasis through a cytosolic DNA response

Chromosomal instability is a hallmark of cancer that results from ongoing errors in chromosome segregation during mitosis. Although chromosomal instability is a major driver of tumour evolution, its role in metastasis has not been established. Here we show that chromosomal instability promotes metastasis by sustaining a tumour cell-autonomous response to cytosolic DNA. Errors in chromosome segregation create a preponderance of micronuclei whose rupture spills genomic DNA into the cytosol. This leads to the activation of the cGAS–STING (cyclic GMP-AMP synthase–stimulator of interferon genes) cytosolic DNA-sensing pathway and downstream noncanonical NF-κB signalling. Genetic suppression of chromosomal instability markedly delays metastasis even in highly aneuploid tumour models, whereas continuous chromosome segregation errors promote cellular invasion and metastasis in a STING-dependent manner. By subverting lethal epithelial responses to cytosolic DNA, chromosomally unstable tumour cells co-opt chronic activation of innate immune pathways to spread to distant organs

Mutant-IDH1-dependent chromatin state reprogramming, reversibility, and persistence

Mutations in IDH1 and IDH2 (encoding isocitrate dehydrogenase 1 and 2) drive the development of gliomas and other human malignancies. Mutant IDH1 induces epigenetic changes that promote tumorigenesis, but the scale and reversibility of these changes are unknown. Here, using human astrocyte and glioma tumorsphere systems, we generate a large-scale atlas of mutant-IDH1-induced epigenomic reprogramming. We characterize the reversibility of the alterations in DNA methylation, the histone landscape, and transcriptional reprogramming that occur following IDH1 mutation. We discover genome-wide coordinate changes in the localization and intensity of multiple histone marks and chromatin states. Mutant IDH1 establishes a CD24+ population with a proliferative advantage and stem-like transcriptional features. Strikingly, prolonged exposure to mutant IDH1 results in irreversible genomic and epigenetic alterations. Together, these observations provide unprecedented high-resolution molecular portraits of mutant-IDH1-dependent epigenomic reprogramming. These findings have substantial implications for understanding of mutant IDH function and for optimizing therapeutic approaches to targeting IDH-mutant tumors

Timesheet assistant: Mining and reporting developer effort

Timesheets are an important instrument used to track time spent by team members in a software project on the tasks assigned to them. In a typical project, developers fill timesheets manually on a periodic basis. This is often tedious, time consuming and error prone. Over or under reporting of time spent on tasks causes errors in billing development costs to customers and wrong estimation baselines for future work, which can have serious business consequences. In order to assist developers in filling their timesheets accurately, we present a tool called Timesheet Assistant (TA) that non-intrusively mines developer activities and uses statistical analysis on historical data to estimate the actual effort the developer may have spent on individual assigned tasks. TA further helps the developer or project manager by presenting the details of the activities along with effort data so that the effort may be seen in the context of the actual work performed. We report on an empirical study of TA in a software maintenance project at IBM that provides preliminary validation of its feasibility and usefulness. Some of the limitations of the TA approach and possible ways to address those are also discussed.</p

Effective reuse via modeling, managing and searching of business process assets

Cost and competitive pressures are forcing business organizations to reuse assets from repositories, rather than develop them from scratch. But this has been hampered by some issues that have not been addressed so far. First, there is a lack of a mechanism for the representation of business process assets as variants and versions in repositories. Second, there is no formal means to compare between different variants and versions of an asset and determine which is the best to select for reuse. Third, there is a lack of a technique to determine the extent to which a business process asset could be customized for reuse. In this paper, we address the above research issues by presenting an integrated approach for modeling, analyzing, and searching business process assets in a repository for enhancing reuse. We demonstrate our approach on a large repository of business process assets in the insurance domain

In-Space Robotic Assembly and Servicing of High-Value Infrastructure

With the advances in Robotics, Automation and Autonomous Systems (RAAS), the horizon of space exploration has grown, and there is a need to develop space-qualified intelligent robots for future missions. Building upon the heritage of successful surface exploration rover and lander missions to the Moon, Mars and Asteroids, the space community worldwide is now pushing the frontiers of in-orbit robotics. Doubtlessly, RAAS will facilitate a range of manufacturing, assembly, servicing and active debris removal missions. Resources published by space agencies and major companies worldwide clearly indicate that mankind will start witnessing in-orbit robotic missions within the next decade. This includes but not limited to building modular Large-Aperture Space Telescopes (LAST), synthetic aperture radar, radiofrequency antennas, in-space power generation stations, mobile servicing stations for repairing and maintenance of satellites and possibly large-scale infrastructure for space tourism. Out of the many potential missions RAAS could support, in-orbit robotic assembly and construction of LAST is gaining more popularity with the intent to understand the rate of growth of the cosmos and also for Earth Observation (EO). However, there are numerous technical challenges associated with assembling LAST in space, including its manufacturing and stowing into current and planned launch vehicles. To address these issues, a segmented design approach for LAST is considered in this paper; the modular mirror units will be robotically assembled in orbit. The in-space assembly of a modular 25m LAST mission concept is presented using a five Degrees-of-Freedom End- Over-End Walking Robot (E-Walker). The design and gait pattern of the E-Walker is introduced first. The key mission requirements including the requirements for the Robotic System, Space Telescope and Assembly are discussed along with the strategies for scheduling the assembly process. Four main mission scenarios, subcategorised into eleven mission scenarios are discussed in detail with a maximum of four E-Walkers. A trade-off analysis was conducted to identify feasible mission scenarios and inferences are drawn accordingly to the best mission concept of operations (ConOps) to realise the assembly of the 25m LAST. The results are based on the overall mission mass-power budget, cost, control and motion planning complexity for the different mission scenarios addressed in this paper. This study is a stepping stone towards proving the feasibility of the E-Walker for assembling LAST; such advancements in orbital robotics will prove advantageous for building and servicing other high-value infrastructure in space

Genomic imbalance defines three prognostic groups for risk stratification of patients with chronic lymphocytic leukemia

Array comparative genomic hybridization (aCGH) has yet to be fully leveraged in a prognostic setting in chronic lymphocytic leukemia (CLL). Genomic imbalance was assessed in 288 CLL specimens using a targeted array. Based on 20 aberrations in a hierarchical manner, all 228 treatment-naive specimens were classified into a group with poor outcome (20.6%) exhibiting at least one aberration that was univariately associated with adverse outcome (gain: 2p, 3q, 8q, 17q, loss: 7q, 8p, 11q, 17p, 18p), good outcome (32.5%) showing 13q14 loss without any of the other 10 aberrations (gain: 1p, 7p, 12, 18p, 18q, 19, loss: 4p, 5p, 6q, 7p) or intermediate outcome (remainder). The three groups were significantly separated with respect to time to first treatment and overall survival (p \u3c 0.001), and validation of the stratification scheme was performed in two independent datasets. Gain of 3q and 8q, and 17p loss were determined to be independent unfavorable prognostic biomarkers. TP53, NOTCH1 and SF3B1 mutations correlated with the presence of one poor outcome aCGH marker, at a considerably higher frequency than when only considering poor risk aberrations routinely detected by fluorescence in situ hybridization (FISH). These data support genomic imbalance evaluation in CLL by aCGH to assist in risk stratification