Proposed Increases in Government Authority Over Research Misconduct Proceedings.

This Viewpoint discusses changes proposed by the US Department of Health and Human Services' Office of Research Integrity that would shift control of research misconduct proceedings from institutional oversight to federal authority.

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment.

MOTIVATION: Analysis of mutational signatures is a powerful approach for understanding the mutagenic processes that have shaped the evolution of a cancer genome. To evaluate the mutational signatures operative in a cancer genome, one first needs to quantify their activities by estimating the number of mutations imprinted by each signature. RESULTS: Here we present SigProfilerAssignment, a desktop and an online computational framework for assigning all types of mutational signatures to individual samples. SigProfilerAssignment is the first tool that allows both analysis of copy-number signatures and probabilistic assignment of signatures to individual somatic mutations. As its computational engine, the tool uses a custom implementation of the forward stagewise algorithm for sparse regression and nonnegative least squares for numerical optimization. Analysis of 2700 synthetic cancer genomes with and without noise demonstrates that SigProfilerAssignment outperforms four commonly used approaches for assigning mutational signatures. AVAILABILITY AND IMPLEMENTATION: SigProfilerAssignment is available under the BSD 2-clause license at https://github.com/AlexandrovLab/SigProfilerAssignment with a web implementation at https://cancer.sanger.ac.uk/signatures/assignment/.

Optimization of Aspergillus versicolor Culture and Aerosolization in a Murine Model of Inhalational Fungal Exposure.

Aspergillus versicolor is ubiquitous in the environment and is particularly abundant in damp indoor spaces. Exposure to Aspergillus species, as well as other environmental fungi, has been linked to respiratory health outcomes, including asthma, allergy, and even local or disseminated infection. However, the pulmonary immunological mechanisms associated with repeated exposure to A. versicolor have remained relatively uncharacterized. Here, A. versicolor was cultured and desiccated on rice then placed in an acoustical generator system to achieve aerosolization. Mice were challenged with titrated doses of aerosolized conidia to examine deposition, lymphoproliferative properties, and immunotoxicological response to repeated inhalation exposures. The necessary dose to induce lymphoproliferation was identified, but not infection-like pathology. Further, it was determined that the dose was able to initiate localized immune responses. The data presented in this study demonstrate an optimized and reproducible method for delivering A. versicolor conidia to rodents via nose-only inhalation. Additionally, the feasibility of a long-term repeated exposure study was established. This experimental protocol can be used in future studies to investigate the physiological effects of repeated pulmonary exposure to fungal conidia utilizing a practical and relevant mode of delivery. In total, these data constitute an important foundation for subsequent research in the field.

Defining "recklessness" in research misconduct proceedings.

To find research misconduct in research that has been supported by federal funds, an institution must determine that the misconduct was committed intentionally, knowingly, or recklessly. "Intentional" and "knowing" are straightforward standards. Yet "reckless" often mystifies institutions, which struggle to assess whether a respondent's conduct should be deemed "reckless," or merely negligent. This difficulty is most pronounced when allegations are lodged against the author under whose supervision the primary research was conducted - most often, the senior and/or corresponding author of a published paper who may not have been directly involved in performing the experiments or preparing the data under scrutiny. In these situations, investigation committees and the institutional "deciding official" must assess whether the supervising scientist is guilty of research misconduct - based on the theory that their supervision of the research and development of the publication containing falsified, fabricated, or plagiarized information was reckless - even if that person did not perform the experiment or assemble the research records in question. This paper seeks to provide a framework for evaluating the circumstances in which past supervisory conduct should be deemed "reckless" and thus a basis on which a finding of research misconduct may be made.

Topography of mutational signatures in human cancer.

The somatic mutations found in a cancer genome are imprinted by different mutational processes. Each process exhibits a characteristic mutational signature, which can be affected by the genome architecture. However, the interplay between mutational signatures and topographical genomic features has not been extensively explored. Here, we integrate mutations from 5,120 whole-genome-sequenced tumors from 40 cancer types with 516 topographical features from ENCODE to evaluate the effect of nucleosome occupancy, histone modifications, CTCF binding, replication timing, and transcription/replication strand asymmetries on the cancer-specific accumulation of mutations from distinct mutagenic processes. Most mutational signatures are affected by topographical features, with signatures of related etiologies being similarly affected. Certain signatures exhibit periodic behaviors or cancer-type-specific enrichments/depletions near topographical features, revealing further information about the processes that imprinted them. Our findings, disseminated via the COSMIC (Catalog of Somatic Mutations in Cancer) signatures database, provide a comprehensive online resource for exploring the interactions between mutational signatures and topographical features across human cancer.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.

BACKGROUND: All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no computationally efficient bioinformatics tool that allows visualizing and exploring these large-scale mutational events. RESULTS: Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. CONCLUSIONS: The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment.

Analysis of mutational signatures is a powerful approach for understanding the mutagenic processes that have shaped the evolution of a cancer genome. Here we present SigProfilerAssignment, a desktop and an online computational framework for assigning all types of mutational signatures to individual samples. SigProfilerAssignment is the first tool that allows both analysis of copy-number signatures and probabilistic assignment of signatures to individual somatic mutations. As its computational engine, the tool uses a custom implementation of the forward stagewise algorithm for sparse regression and nonnegative least squares for numerical optimization. Analysis of 2,700 synthetic cancer genomes with and without noise demonstrates that SigProfilerAssignment outperforms four commonly used approaches for assigning mutational signatures. SigProfilerAssignment is freely available at https://github.com/AlexandrovLab/SigProfilerAssignment with a web implementation at https://cancer.sanger.ac.uk/signatures/assignment/.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.

Background: All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no standard bioinformatics tool that allows visualizing and exploring these large-scale mutational events. Results: Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. Conclusions: The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor.

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

Applying Civil Rights Law to Clinical Research: Title VI's Equal Access Mandate.

Title VI of the Civil Rights Act of 1964 and its implementing regulations prohibit federally-funded educational institutions and healthcare centers from engaging in disparate impact discrimination "on the ground of race, color, or national origin" in all of their operations.

Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA.

Clustered somatic mutations are common in cancer genomes and previous analyses reveal several types of clustered single-base substitutions, which include doublet- and multi-base substitutions1-5, diffuse hypermutation termed omikli6, and longer strand-coordinated events termed kataegis3,7-9. Here we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome-sequenced cancers from 30 types of cancer10. Clustered mutations were highly enriched in driver genes and associated with differential gene expression and changes in overall survival. Several distinct mutational processes gave rise to clustered indels, including signatures that were enriched in tobacco smokers and homologous-recombination-deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, whereas most multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, which have previously been attributed to APOBEC3 activity6, accounted for a large proportion of clustered substitutions; however, only 16.2% of omikli matched APOBEC3 patterns. Kataegis was generated by multiple mutational processes, and 76.1% of all kataegic events exhibited mutational patterns that are associated with the activation-induced deaminase (AID) and APOBEC3 family of deaminases. Co-occurrence of APOBEC3 kataegis and extrachromosomal DNA (ecDNA), termed kyklonas (Greek for cyclone), was found in 31% of samples with ecDNA. Multiple distinct kyklonic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kyklonic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fuelling the evolution of ecDNA.

CX3CR1-Expressing Myeloid Cells Regulate Host-Helminth Interaction and Lung Inflammation.

Many helminth life cycles, including hookworm, involve a mandatory lung phase, where myeloid and granulocyte subsets interact with the helminth and respond to infection-induced lung injury. To evaluate these innate subsets in Nippostrongylus brasiliensis infection, reporter mice for myeloid cells (CX3CR1GFP ) and granulocytes (PGRPdsRED ) are employed. Nippostrongylus infection induces lung infiltration of reporter cells, including CX3CR1+ myeloid cells and PGRP+ eosinophils. Strikingly, CX3CR1GFP/GFP mice, which are deficient in CX3CR1, are protected from Nippostrongylus infection with reduced weight loss, lung leukocyte infiltration, and worm burden compared to CX3CR1+/+ mice. This protective effect is specific for CX3CR1 as CCR2-deficient mice do not exhibit reduced worm burdens. Nippostrongylus co-culture with lung Ly6C+ monocytes or CD11c+ cells demonstrates that CX3CR1GFP/GFP monocytes secrete more pro-inflammatory cytokines and actively bind the parasites causing reduced motility. RNA sequencing of Ly6C+ or CD11c+ cells shows Nippostrongylus-induced gene expression changes, particularly in monocytes, associated with inflammation, chemotaxis, and extracellular matrix remodeling pathways. Analysis reveals cytotoxic and adhesion molecules as potential effectors against the parasite, such as Gzma and Gzmb, which are elevated in CX3CR1GFP/GFP monocytes. These studies validate a dual innate cell reporter for lung helminth infection and demonstrate that CX3CR1 impairs monocyte-helminth interaction.

Demystifying Schrems II for the cross-border transfer of clinical research data.

The Courts of Justice of the European Union (CJEU) held in its July 2020 Schrems II decision that, in order for entities in other countries to import personal data from the European Economic Area (EEA), the importer must be able to provide data protections 'essentially equivalent' to those the EEA offers under its General Data Protection Regulation. The CJEU expressed particular concern that United States' national security intelligence gathering laws prevent U.S.-based entities from providing such protections. This decision has sharply limited the sharing of clinical research data from the EEA to the United States. After describing the pertinent aspects of the Schrems II decision, this article evaluates U.S. national security intelligence gathering frameworks, including Section 702 of the Foreign Intelligence Surveillance Act and Executive Order 12333. The article then leverages recent draft guidance from the European Data Protection Board to explain how entities may be able to adopt widely used contractual and technical measures, such as data pseudonymization, to provide 'essentially equivalent' protections in the clinical research context.

Cookstove Emissions and Performance Evaluation Using a New ISO Protocol and Comparison of Results with Previous Test Protocols.

In 2018, the International Organization for Standardization (ISO) 19867-1 "Harmonized laboratory test protocols" were released for establishing improved quality and comparability for data on cookstove air pollutant emissions, efficiency, safety, and durability. This is the first study that compares emissions [carbon dioxide, carbon monoxide, total hydrocarbons, methane, nitrogen oxides, fine particulate matter (PM2.5), organic carbon, elemental carbon, and ultrafine particles] and efficiency data between the ISO protocol and the Water Boiling Test (WBT). The study examines six stove/fuel combinations [liquefied petroleum gas (LPG), pellet, wood fan, wood rocket, three stone fire, and charcoal] tested in the same US EPA laboratory. Evaluation of the ISO protocol shows improvements over previous test protocols and that results are relatively consistent with former WBT data in terms of tier ratings for emissions and efficiency, as defined by the ISO 19867-3 "Voluntary Performance Targets." Most stove types remain similarly ranked using ISO and WBT protocols, except charcoal and LPG are in higher PM2.5 tiers with the ISO protocol. Additionally, emissions data including polycyclic aromatic hydrocarbons are utilized to compare between the ISO and Firepower Sweep Test (FST) protocols. Compared to the FST, the ISO protocol results in generally higher PM2.5 tier ratings.

Aspergillus versicolor Inhalation Triggers Neuroimmune, Glial, and Neuropeptide Transcriptional Changes.

Increasing evidence associates indoor fungal exposure with deleterious central nervous system (CNS) health, such as cognitive and emotional deficits in children and adults, but the specific mechanisms by which it might impact the brain are poorly understood. Mice were exposed to filtered air, heat-inactivated Aspergillus versicolor (3 × 105 spores), or viable A. versicolor (3 × 105 spores) via nose-only inhalation exposure 2 times per week for 1, 2, or 4 weeks. Analysis of cortex, midbrain, olfactory bulb, and cerebellum tissue from mice exposed to viable A. versicolor spores for 1, 2, and 4 weeks revealed significantly elevated pro-inflammatory (Tnf and Il1b) and glial activity (Gdnf and Cxc3r1) gene expression in several brain regions when compared to filtered air control, with the most consistent and pronounced neuroimmune response 48H following the 4-week exposure in the midbrain and frontal lobe. Bulk RNA-seq analysis of the midbrain tissue confirmed that 4 weeks of A. versicolor exposure resulted in significant transcriptional enrichment of several biological pathways compared to the filtered air control, including neuroinflammation, glial cell activation, and regulation of postsynaptic organization. Upregulation of Drd1, Penk, and Pdyn mRNA expression was confirmed in the 4-week A. versicolor exposed midbrain tissue, highlighting that gene expression important for neurotransmission was affected by repeated A. versicolor inhalation exposure. Taken together, these findings indicate that the brain can detect and respond to A. versicolor inhalation exposure with changes in neuroimmune and neurotransmission gene expression, providing much needed insight into how inhaled fungal exposures can affect CNS responses and regulate neuroimmune homeostasis.