Whole-Genome Sequencing Can Identify Clinically Relevant Variants from a Single Sub-Punch of a Dried Blood Spot Specimen.

The collection of dried blood spots (DBS) facilitates newborn screening for a variety of rare, but very serious conditions in healthcare systems around the world. Sub-punches of varying sizes (1.5-6 mm) can be taken from DBS specimens to use as inputs for a range of biochemical assays. Advances in DNA sequencing workflows allow whole-genome sequencing (WGS) libraries to be generated directly from inputs such as peripheral blood, saliva, and DBS. We compared WGS metrics obtained from libraries generated directly from DBS to those generated from DNA extracted from peripheral blood, the standard input for this type of assay. We explored the flexibility of DBS as an input for WGS by altering the punch number and size as inputs to the assay. We showed that WGS libraries can be successfully generated from a variety of DBS inputs, including a single 3 mm or 6 mm diameter punch, with equivalent data quality observed across a number of key metrics of importance in the detection of gene variants. We observed no difference in the performance of DBS and peripheral-blood-extracted DNA in the detection of likely pathogenic gene variants in samples taken from individuals with cystic fibrosis or phenylketonuria. WGS can be performed directly from DBS and is a powerful method for the rapid discovery of clinically relevant, disease-causing gene variants.

Colorectal cancer residual disease at maximal response to EGFR blockade displays a druggable Paneth cell-like phenotype.

Blockade of epidermal growth factor receptor (EGFR) causes tumor regression in some patients with metastatic colorectal cancer (mCRC). However, residual disease reservoirs typically remain even after maximal response to therapy, leading to relapse. Using patient-derived xenografts (PDXs), we observed that mCRC cells surviving EGFR inhibition exhibited gene expression patterns similar to those of a quiescent subpopulation of normal intestinal secretory precursors with Paneth cell characteristics. Compared with untreated tumors, these pseudodifferentiated tumor remnants had reduced expression of genes encoding EGFR-activating ligands, enhanced activity of human epidermal growth factor receptor 2 (HER2) and HER3, and persistent signaling along the phosphatidylinositol 3-kinase (PI3K) pathway. Clinically, properties of residual disease cells from the PDX models were detected in lingering tumors of responsive patients and in tumors of individuals who had experienced early recurrence. Mechanistically, residual tumor reprogramming after EGFR neutralization was mediated by inactivation of Yes-associated protein (YAP), a master regulator of intestinal epithelium recovery from injury. In preclinical trials, Pan-HER antibodies minimized residual disease, blunted PI3K signaling, and induced long-term tumor control after treatment discontinuation. We found that tolerance to EGFR inhibition is characterized by inactivation of an intrinsic lineage program that drives both regenerative signaling during intestinal repair and EGFR-dependent tumorigenesis. Thus, our results shed light on CRC lineage plasticity as an adaptive escape mechanism from EGFR-targeted therapy and suggest opportunities to preemptively target residual disease.

Longitudinal Liquid Biopsy and Mathematical Modeling of Clonal Evolution Forecast Time to Treatment Failure in the PROSPECT-C Phase II Colorectal Cancer Clinical Trial.

Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. In this prospective phase II clinical trial of single-agent cetuximab in RAS wild-type patients, we combine genomic profiling of serial cfDNA and matched sequential tissue biopsies with imaging and mathematical modeling of cancer evolution. We show that a significant proportion of patients defined as RAS wild-type based on diagnostic tissue analysis harbor aberrations in the RAS pathway in pretreatment cfDNA and, in fact, do not benefit from EGFR inhibition. We demonstrate that primary and acquired resistance to cetuximab are often of polyclonal nature, and these dynamics can be observed in tissue and plasma. Furthermore, evolutionary modeling combined with frequent serial sampling of cfDNA allows prediction of the expected time to treatment failure in individual patients. This study demonstrates how integrating frequently sampled longitudinal liquid biopsies with a mathematical framework of tumor evolution allows individualized quantitative forecasting of progression, providing novel opportunities for adaptive personalized therapies.Significance: Liquid biopsies capture spatial and temporal heterogeneity underpinning resistance to anti-EGFR monoclonal antibodies in colorectal cancer. Dense serial sampling is needed to predict the time to treatment failure and generate a window of opportunity for intervention. Cancer Discov; 8(10); 1270-85. ©2018 AACR. See related commentary by Siravegna and Corcoran, p. 1213 This article is highlighted in the In This Issue feature, p. 1195.

The Spatiotemporal Evolution of Lymph Node Spread in Early Breast Cancer.

Purpose: The most significant prognostic factor in early breast cancer is lymph node involvement. This stage between localized and systemic disease is key to understanding breast cancer progression; however, our knowledge of the evolution of lymph node malignant invasion remains limited, as most currently available data are derived from primary tumors.Experimental Design: In 11 patients with treatment-naïve node-positive early breast cancer without clinical evidence of distant metastasis, we investigated lymph node evolution using spatial multiregion sequencing (n = 78 samples) of primary and lymph node deposits and genomic profiling of matched longitudinal circulating tumor DNA (ctDNA).Results: Linear evolution from primary to lymph node was rare (1/11), whereas the majority of cases displayed either early divergence between primary and nodes (4/11) or no detectable divergence (6/11), where both primary and nodal cells belonged to a single recent expansion of a metastatic clone. Divergence of metastatic subclones was driven in part by APOBEC. Longitudinal ctDNA samples from 2 of 7 subjects with evaluable plasma taken perioperatively reflected the two major evolutionary patterns and demonstrate that private mutations can be detected even from early metastatic nodal deposits. Moreover, node removal resulted in disappearance of private lymph node mutations in ctDNA.Conclusions: This study sheds new light on a crucial evolutionary step in the natural history of breast cancer, demonstrating early establishment of axillary lymph node metastasis in a substantial proportion of patients. Clin Cancer Res; 24(19); 4763-70. ©2018 AACR.

Patient-derived organoids model treatment response of metastatic gastrointestinal cancers.

Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from metastatic, heavily pretreated colorectal and gastroesophageal cancer patients recruited in phase 1/2 clinical trials. Phenotypic and genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. Molecular profiling of tumor organoids was matched to drug-screening results, suggesting that PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared responses to anticancer agents ex vivo in organoids and PDO-based orthotopic mouse tumor xenograft models with the responses of the patients in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic and could be implemented in personalized medicine programs.

Changes in selective pressures associated with human population expansion may explain metabolic and immune related pathways enriched for signatures of positive selection.

BACKGROUND: The study of local adaptation processes is a very important research topic in the field of population genomics. There is a particular interest in the study of human populations because they underwent a process of rapid spatial expansion and faced important environmental changes that translated into changes in selective pressures. New mutations may have been selected for in the new environment and previously existing genetic variants may have become detrimental. Immune related genes may have been released from the selective pressure exerted by pathogens in the ancestral environment and new variants may have been positively selected due to pathogens present in the newly colonized habitat. Also, variants that had a selective advantage in past environments may have become deleterious in the modern world due to external stimuli including climatic, dietary and behavioral changes, which could explain the high prevalence of some polygenic diseases such as diabetes and obesity. RESULTS: We performed an enrichment analysis to identify gene sets enriched for signals of positive selection in humans. We used two genome scan methods, XPCLR and iHS to detect selection using a dense coverage of SNP markers combined with two gene set enrichment approaches. We identified immune related gene sets that could be involved in the protection against pathogens especially in the African population. We also identified the glycolysis & gluconeogenesis gene set, related to metabolism, which supports the thrifty genotype hypothesis invoked to explain the current high prevalence of diseases such as diabetes and obesity. Extending our analysis to the gene level, we found signals for 23 candidate genes linked to metabolic syndrome, 13 of which are new candidates for positive selection. CONCLUSIONS: Our study provides a list of genes and gene sets associated with immunity and metabolic syndrome that are enriched for signals of positive selection in three human populations (Europeans, Africans and Asians). Our results highlight differences in the relative importance of pathogens as drivers of local adaptation in different continents and provide new insights into the evolution and high incidence of metabolic syndrome in modern human populations.

The Ess/Type VII secretion system of Staphylococcus aureus shows unexpected genetic diversity.

BACKGROUND: Type VII protein secretion (T7SS) is a specialised system for excreting extracellular proteins across bacterial cell membranes and has been associated with virulence in Staphylococcus aureus. The genetic diversity of the ess locus, which encodes the T7SS, and the functions of proteins encoded within it are poorly understood. RESULTS: We used whole genome sequence data from 153 isolates representative of the diversity of the species to investigate the genetic variability of T7SS across S. aureus. The ess loci were found to comprise of four distinct modules based on gene content and relative conservation. Modules 1 and 4, comprising of the 5' and 3' modules of the ess locus, contained the most conserved clusters of genes across the species. Module 1 contained genes encoding the secreted protein EsxA, and the EsaAB and EssAB components of the T7SS machinery, and Module 4 contained two functionally uncharacterized conserved membrane proteins. Across the species four variants of Module 2 were identified containing the essC gene, each of which was associated with a specific group of downstream genes. The most diverse module of the ess locus was Module 3 comprising a highly variable arrangement of hypothetical proteins. RNA-Seq was performed on representatives of the four Module 2 variants and demonstrated strain-specific differences in the levels of transcription in the conserved Module 1 components and transcriptional linkage Module 2, and provided evidence of the expression of genes the variable regions of the ess loci. CONCLUSIONS: The ess locus of S. aureus exhibits modularity and organisational variation across the species and transcriptional variation. In silico analysis of ess loci encoded hypothetical proteins identified potential novel secreted substrates for the T7SS. The considerable variety in operon arrangement between otherwise closely related isolates provides strong evidence for recombination at this locus. Comparison of these recombination regions with each other, and with the genomes of other Staphylococcal species, failed to identify evidence of intra- and inter-species recombination, however the analysis identified a novel T7SS in another pathogenic staphylococci, Staphylococcus lugdunensis.

Detection of selective sweeps in structured populations: a comparison of recent methods.

Identifying genomic regions targeted by positive selection has been a long-standing interest of evolutionary biologists. This objective was difficult to achieve until the recent emergence of next-generation sequencing, which is fostering the development of large-scale catalogues of genetic variation for increasing number of species. Several statistical methods have been recently developed to analyse these rich data sets, but there is still a poor understanding of the conditions under which these methods produce reliable results. This study aims at filling this gap by assessing the performance of genome-scan methods that consider explicitly the physical linkage among SNPs surrounding a selected variant. Our study compares the performance of seven recent methods for the detection of selective sweeps (iHS, nSL, EHHST, xp-EHH, XP-EHHST, XPCLR and hapFLK). We use an individual-based simulation approach to investigate the power and accuracy of these methods under a wide range of population models under both hard and soft sweeps. Our results indicate that XPCLR and hapFLK perform best and can detect soft sweeps under simple population structure scenarios if migration rate is low. All methods perform poorly with moderate-to-high migration rates, or with weak selection and very poorly under a hierarchical population structure. Finally, no single method is able to detect both starting and nearly completed selective sweeps. However, combining several methods (XPCLR or hapFLK with iHS or nSL) can greatly increase the power to pinpoint the selected region.

Widespread signals of convergent adaptation to high altitude in Asia and america.

Living at high altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean, and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can also be due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP data set from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high-altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.