Double-Blind Phase III Trial of Adjuvant Chemotherapy With and Without Bevacizumab in Patients With Lymph Node-Positive and High-Risk Lymph Node-Negative Breast Cancer (E5103)

Purpose Bevacizumab improves progression-free survival but not overall survival in patients with metastatic breast cancer. E5103 tested the effect of bevacizumab in the adjuvant setting in patients with human epidermal growth factor receptor 2-negative disease. Patients and Methods Patients were assigned 1:2:2 to receive placebo with doxorubicin and cyclophosphamide (AC) followed by weekly paclitaxel (arm A), bevacizumab only during AC and paclitaxel (arm B), or bevacizumab during AC and paclitaxel followed by bevacizumab monotherapy for 10 cycles (arm C). Random assignment was stratified and bevacizumab dose adjusted for choice of AC schedule. Radiation and hormonal therapy were administered concurrently with bevacizumab in arm C. The primary end point was invasive disease-free survival (IDFS). Results Four thousand nine hundred ninety-four patients were enrolled. Median age was 52 years; 64% of patients were estrogen receptor positive, 27% were lymph node negative, and 78% received dose-dense AC. Chemotherapy-associated adverse events including myelosuppression and neuropathy were similar across all arms. Grade ≥ 3 hypertension was more common in bevacizumab-treated patients, but thrombosis, proteinuria, and hemorrhage were not. The cumulative incidence of clinical congestive heart failure at 15 months was 1.0%, 1.9%, and 3.0% in arms A, B, and C, respectively. Bevacizumab exposure was less than anticipated, with approximately 24% of patients in arm B and approximately 55% of patients in arm C discontinuing bevacizumab before completing planned therapy. Five-year IDFS was 77% (95% CI, 71% to 81%) in arm A, 76% (95% CI, 72% to 80%) in arm B, and 80% (95% CI, 77% to 83%) in arm C. Conclusion Incorporation of bevacizumab into sequential anthracycline- and taxane-containing adjuvant therapy does not improve IDFS or overall survival in patients with high-risk human epidermal growth factor receptor 2-negative breast cancer. Longer duration bevacizumab therapy is unlikely to be feasible given the high rate of early discontinuation

Rabbits, stoats and the predator problem: Why a strong animal rights position need not call for human intervention to protect prey from predators

Animal rights positions face the ‘predator problem’: the suggestion that if the rights of nonhuman animals are to be protected, then we are obliged to interfere in natural ecosystems to protect prey from predators. Generally, rather than embracing this conclusion, animal ethicists have rejected it, basing this objection on a number of different arguments. This paper considers but challenges three such arguments, before defending a fourth possibility. Rejected are Peter Singer’s suggestion that interference will lead to more harm than good, Sue Donaldson and Will Kymlicka’s suggestion that respect for nonhuman sovereignty necessitates non-interference in normal circumstances, and Alasdair Cochrane’s solution based on the claim that predators cannot survive without killing prey. The possibility defended builds upon Tom Regan’s suggestion that predators, as moral patients but not moral agents, cannot violate the rights of their prey, and so the rights of the prey, while they do exist, do not call for intervention. This idea is developed by a consideration of how moral agents can be more or less responsible for a given event, and defended against criticisms offered by thinkers including Alasdair Cochrane and Dale Jamieson

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder