Oncolytic DNX-2401 Virus for Pediatric Diffuse Intrinsic Pontine Glioma.

BACKGROUND: Pediatric patients with diffuse intrinsic pontine glioma (DIPG) have a poor prognosis, with a median survival of less than 1 year. Oncolytic viral therapy has been evaluated in patients with pediatric gliomas elsewhere in the brain, but data regarding oncolytic viral therapy in patients with DIPG are lacking. METHODS: We conducted a single-center, dose-escalation study of DNX-2401, an oncolytic adenovirus that selectively replicates in tumor cells, in patients with newly diagnosed DIPG. The patients received a single virus infusion through a catheter placed in the cerebellar peduncle, followed by radiotherapy. The primary objective was to assess the safety and adverse-event profile of DNX-2401. The secondary objectives were to evaluate the effect of DNX-2401 on overall survival and quality of life, to determine the percentage of patients who have an objective response, and to collect tumor-biopsy and peripheral-blood samples for correlative studies of the molecular features of DIPG and antitumor immune responses. RESULTS: A total of 12 patients, 3 to 18 years of age, with newly diagnosed DIPG received 1×1010 (the first 4 patients) or 5×1010 (the subsequent 8 patients) viral particles of DNX-2401, and 11 received subsequent radiotherapy. Adverse events among the patients included headache, nausea, vomiting, and fatigue. Hemiparesis and tetraparesis developed in 1 patient each. Over a median follow-up of 17.8 months (range, 5.9 to 33.5), a reduction in tumor size, as assessed on magnetic resonance imaging, was reported in 9 patients, a partial response in 3 patients, and stable disease in 8 patients. The median survival was 17.8 months. Two patients were alive at the time of preparation of the current report, 1 of whom was free of tumor progression at 38 months. Examination of a tumor sample obtained during autopsy from 1 patient and peripheral-blood studies revealed alteration of the tumor microenvironment and T-cell repertoire. CONCLUSIONS: Intratumoral infusion of oncolytic virus DNX-2401 followed by radiotherapy in pediatric patients with DIPG resulted in changes in T-cell activity and a reduction in or stabilization of tumor size in some patients but was associated with adverse events. (Funded by the European Research Council under the European Union's Horizon 2020 Research and Innovation Program and others; EudraCT number, 2016-001577-33; ClinicalTrials.gov number, NCT03178032.).

Reprogramming human T cell function and specificity with non-viral genome targeting.

Decades of work have aimed to genetically reprogram T cells for therapeutic purposes1,2 using recombinant viral vectors, which do not target transgenes to specific genomic sites3,4. The need for viral vectors has slowed down research and clinical use as their manufacturing and testing is lengthy and expensive. Genome editing brought the promise of specific and efficient insertion of large transgenes into target cells using homology-directed repair5,6. Here we developed a CRISPR-Cas9 genome-targeting system that does not require viral vectors, allowing rapid and efficient insertion of large DNA sequences (greater than one kilobase) at specific sites in the genomes of primary human T cells, while preserving cell viability and function. This permits individual or multiplexed modification of endogenous genes. First, we applied this strategy to correct a pathogenic IL2RA mutation in cells from patients with monogenic autoimmune disease, and demonstrate improved signalling function. Second, we replaced the endogenous T cell receptor (TCR) locus with a new TCR that redirected T cells to a cancer antigen. The resulting TCR-engineered T cells specifically recognized tumour antigens and mounted productive anti-tumour cell responses in vitro and in vivo. Together, these studies provide preclinical evidence that non-viral genome targeting can enable rapid and flexible experimental manipulation and therapeutic engineering of primary human immune cells.

Next-generation sequencing of bile cell-free DNA for the early detection of patients with malignant biliary strictures.

OBJECTIVE: Despite significant progresses in imaging and pathological evaluation, early differentiation between benign and malignant biliary strictures remains challenging. Endoscopic retrograde cholangiopancreatography (ERCP) is used to investigate biliary strictures, enabling the collection of bile. We tested the diagnostic potential of next-generation sequencing (NGS) mutational analysis of bile cell-free DNA (cfDNA). DESIGN: A prospective cohort of patients with suspicious biliary strictures (n=68) was studied. The performance of initial pathological diagnosis was compared with that of the mutational analysis of bile cfDNA collected at the time of first ERCP using an NGS panel open to clinical laboratory implementation, the Oncomine Pan-Cancer Cell-Free assay. RESULTS: An initial pathological diagnosis classified these strictures as of benign (n=26), indeterminate (n=9) or malignant (n=33) origin. Sensitivity and specificity of this diagnosis were 60% and 100%, respectively, as on follow-up 14 of the 26 and eight of the nine initially benign or indeterminate strictures resulted malignant. Sensitivity and specificity for malignancy of our NGS assay, herein named Bilemut, were 96.4% and 69.2%, respectively. Importantly, one of the four Bilemut false positives developed pancreatic cancer after extended follow-up. Remarkably, the sensitivity for malignancy of Bilemut was 100% in patients with an initial diagnosis of benign or indeterminate strictures. Analysis of 30 paired bile and tissue samples also demonstrated the superior performance of Bilemut. CONCLUSION: Implementation of Bilemut at the initial diagnostic stage for biliary strictures can significantly improve detection of malignancy, reduce delays in the clinical management of patients and assist in selecting patients for targeted therapies.

Performance comparison of two next-generation sequencing panels to detect actionable mutations in cell-free DNA in cancer patients.

Background Genomic alterations studies in cell-free DNA (cfDNA) have increasing clinical use in oncology. Next-generation sequencing (NGS) technology provides the most complete mutational analysis, but nowadays limited data are available related to the comparison of results reported by different platforms. Here we compare two NGS panels for cfDNA: Oncomine™ Pan-Cancer Cell-Free Assay (Thermo Fisher Scientific), suitable for clinical laboratories, and Guardant360® (GuardantHealth), with more genes targeted but only available in an outsourcing laboratory. Methods Peripheral blood was obtained from 16 advanced cancer patients in which Guardant360® (G360) was requested as part of their clinical assistance. Blood samples were sent to be analyzed with G360 panel, and an additional blood sample was drawn to obtain and analyze cfDNA with Oncomine™ Pan-Cancer (OM) panel in an Ion GeneStudio S5™ System. Results cfDNA analysis globally rendered 101 mutations. Regarding the 55/101 mutations claimed to be included by manufacturers in both panels, 17 mutations were reported only by G360, 10 only by OM and 28 by both. In those coincident cases, there was a high correlation between the variant allele fractions (VAFs) calculated with each panel (r = 0.979, p < 0.01). Regarding the six actionable mutations with an FDA-approved therapy reported by G360, one was missed with OM. Also, 12 mutations with clinical trials available were reported by G360 but not by OM. Conclusions In summary, G360 and OM can produce different mutational profile in the same sample, even in genes included in both panels, which is especially important if these mutations are potentially druggable.

Reconstructing Native American population history.

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call 'First American'. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.

Estimating the Ages of Selection Signals from Different Epochs in Human History.

Genetic variation harbors signatures of natural selection driven by selective pressures that are often unknown. Estimating the ages of selection signals may allow reconstructing the history of environmental changes that shaped human phenotypes and diseases. We have developed an approximate Bayesian computation (ABC) approach to estimate allele ages under a model of selection on new mutations and under demographic models appropriate for human populations. We have applied it to two resequencing data sets: An ultra-high depth data set from a relatively small sample of unrelated individuals and a lower depth data set in a larger sample with transmission information. In addition to evaluating the accuracy of our method based on simulations, for each SNP, we assessed the consistency between the posterior probabilities estimated by the ABC approach and the ancient DNA record, finding good agreement between the two types of data and methods. Applying this ABC approach to data for eight single nucleotide polymorphisms (SNPs), we were able to rule out an onset of selection prior to the dispersal out-of-Africa for three of them and more recent than the spread of agriculture for an additional three SNPs.

Strong artificial selection in domestic mammals did not result in an increased recombination rate.

Recombination rates vary in intensity and location at the species, individual, sex and chromosome levels. Despite the fundamental biological importance of this process, the selective forces that operate to shape recombination rate and patterns are unclear. Domestication offers a unique opportunity to study the interplay between recombination and selection. In domesticates, intense selection for particular traits is imposed on small populations over many generations, resulting in organisms that differ, sometimes dramatically, in morphology and physiology from their wild ancestor. Although earlier studies suggested increased recombination rate in domesticates, a formal comparison of recombination rates between domestic mammals and their wild congeners was missing. In order to determine broad-scale recombination rate, we used immunolabeling detection of MLH1 foci as crossover markers in spermatocytes in three pairs of closely related wild and domestic species (dog and wolf, goat and ibex, and sheep and mouflon). In the three pairs, and contrary to previous suggestions, our data show that contemporary recombination rate is higher in the wild species. Subsequently, we inferred recombination breakpoints in sequence data for 16 genomic regions in dogs and wolves, each containing a locus associated with a dog phenotype potentially under selection during domestication. No difference in the number and distribution of recombination breakpoints was found between dogs and wolves. We conclude that our data indicate that strong directional selection did not result in changes in recombination in domestic mammals, and that both upper and lower bounds for crossover rates may be tightly regulated.

Olfactory Dysfunction in Older Adults is Associated with Feelings of Depression and Loneliness.

Olfactory dysfunction is a common complaint among physician visits. Olfactory loss affects quality of life and impairs function and activities of daily living. The purpose of our study was to assess the degree of odor identification associated with mental health. Olfactory function was measured using the brief smell identification test. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression scale. Loneliness was assessed by the de Jong-Gierveld Loneliness Scale. Cognition was measured by a battery of 19 cognitive tests. The frequency of olfactory dysfunction in our study was ~40%. Older subjects had worse olfactory performance, as previously found. More loneliness was associated with worse odor identification. Similarly, symptoms of depression were associated with worse olfaction (among men). Although better global cognitive function was strongly associated with better odor identification, after controlling for multiple factors, the associations with depression and loneliness were unchanged. Clinicians should assess these mental health conditions when treating older patients who present with olfactory deficits.

PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population.

Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.

The genetic architecture of adaptations to high altitude in Ethiopia.

Although hypoxia is a major stress on physiological processes, several human populations have survived for millennia at high altitudes, suggesting that they have adapted to hypoxic conditions. This hypothesis was recently corroborated by studies of Tibetan highlanders, which showed that polymorphisms in candidate genes show signatures of natural selection as well as well-replicated association signals for variation in hemoglobin levels. We extended genomic analysis to two Ethiopian ethnic groups: Amhara and Oromo. For each ethnic group, we sampled low and high altitude residents, thus allowing genetic and phenotypic comparisons across altitudes and across ethnic groups. Genome-wide SNP genotype data were collected in these samples by using Illumina arrays. We find that variants associated with hemoglobin variation among Tibetans or other variants at the same loci do not influence the trait in Ethiopians. However, in the Amhara, SNP rs10803083 is associated with hemoglobin levels at genome-wide levels of significance. No significant genotype association was observed for oxygen saturation levels in either ethnic group. Approaches based on allele frequency divergence did not detect outliers in candidate hypoxia genes, but the most differentiated variants between high- and lowlanders have a clear role in pathogen defense. Interestingly, a significant excess of allele frequency divergence was consistently detected for genes involved in cell cycle control and DNA damage and repair, thus pointing to new pathways for high altitude adaptations. Finally, a comparison of CpG methylation levels between high- and lowlanders found several significant signals at individual genes in the Oromo.

Adaptations to climate-mediated selective pressures in humans.

Humans inhabit a remarkably diverse range of environments, and adaptation through natural selection has likely played a central role in the capacity to survive and thrive in extreme climates. Unlike numerous studies that used only population genetic data to search for evidence of selection, here we scan the human genome for selection signals by identifying the SNPs with the strongest correlations between allele frequencies and climate across 61 worldwide populations. We find a striking enrichment of genic and nonsynonymous SNPs relative to non-genic SNPs among those that are strongly correlated with these climate variables. Among the most extreme signals, several overlap with those from GWAS, including SNPs associated with pigmentation and autoimmune diseases. Further, we find an enrichment of strong signals in gene sets related to UV radiation, infection and immunity, and cancer. Our results imply that adaptations to climate shaped the spatial distribution of variation in humans.

Gut microbiota produces biofilm-associated amyloids with potential for neurodegeneration.

Age-related neurodegenerative diseases involving amyloid aggregation remain one of the biggest challenges of modern medicine. Alterations in the gastrointestinal microbiome play an active role in the aetiology of neurological disorders. Here, we dissect the amyloidogenic properties of biofilm-associated proteins (BAPs) of the gut microbiota and their implications for synucleinopathies. We demonstrate that BAPs are naturally assembled as amyloid-like fibrils in insoluble fractions isolated from the human gut microbiota. We show that BAP genes are part of the accessory genomes, revealing microbiome variability. Remarkably, the abundance of certain BAP genes in the gut microbiome is correlated with Parkinson's disease (PD) incidence. Using cultured dopaminergic neurons and Caenorhabditis elegans models, we report that BAP-derived amyloids induce α-synuclein aggregation. Our results show that the chaperone-mediated autophagy is compromised by BAP amyloids. Indeed, inoculation of BAP fibrils into the brains of wild-type mice promote key pathological features of PD. Therefore, our findings establish the use of BAP amyloids as potential targets and biomarkers of α-synucleinopathies.

Building on the clinical applicability of ctDNA analysis in non-metastatic pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma represents one of the solid tumors showing the worst prognosis worldwide, with a high recurrence rate after adjuvant or neoadjuvant therapy. Circulating tumor DNA analysis raised as a promising non-invasive tool to characterize tumor genomics and to assess treatment response. In this study, surgical tumor tissue and sequential blood samples were analyzed by next-generation sequencing and were correlated with clinical and pathological characteristics. Thirty resectable/borderline pancreatic ductal adenocarcinoma patients treated at the Hospital Universitario de Navarra were included. Circulating tumoral DNA sequencing identified pathogenic variants in KRAS and TP53, and in other cancer-associated genes. Pathogenic variants at diagnosis were detected in patients with a poorer outcome, and were correlated with response to neoadjuvant therapy in borderline pancreatic ductal adneocarcinoma patients. Higher variant allele frequency at diagnosis was associated with worse prognosis, and thesum of variant allele frequency was greater in samples at progression. Our results build on the potential value of circulating tumor DNA for non-metastatic pancreatic ductal adenocarcinoma patients, by complementing tissue genetic information and as a non-invasive tool for treatment decision. Confirmatory studies are needed to corroborate these findings.

Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma.

BACKGROUND: Tobacco is the main risk factor for developing lung cancer. Yet, while some heavy smokers develop lung cancer at a young age, other heavy smokers never develop it, even at an advanced age, suggesting a remarkable variability in the individual susceptibility to the carcinogenic effects of tobacco. We characterized the germline profile of subjects presenting these extreme phenotypes with Whole Exome Sequencing (WES) and Machine Learning (ML). METHODS: We sequenced germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases) or who did not develop lung cancer at an advanced age (extreme controls), selected from databases including over 6600 subjects. We selected individual coding genetic variants and variant-rich genes showing a significantly different distribution between extreme cases and controls. We validated the results from our discovery cohort, in which we analysed by WES extreme cases and controls presenting similar phenotypes. We developed ML models using both cohorts. FINDINGS: Mean age for extreme cases and controls was 50.7 and 79.1 years respectively, and mean tobacco consumption was 34.6 and 62.3 pack-years. We validated 16 individual variants and 33 variant-rich genes. The gene harbouring the most validated variants was HLA-A in extreme controls (4 variants in the discovery cohort, p = 3.46E-07; and 4 in the validation cohort, p = 1.67E-06). We trained ML models using as input the 16 individual variants in the discovery cohort and tested them on the validation cohort, obtaining an accuracy of 76.5% and an AUC-ROC of 83.6%. Functions of validated genes included candidate oncogenes, tumour-suppressors, DNA repair, HLA-mediated antigen presentation and regulation of proliferation, apoptosis, inflammation and immune response. INTERPRETATION: Individuals presenting extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma show different germline profiles. Our strategy may allow the identification of high-risk subjects and the development of new therapeutic approaches. FUNDING: See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Colloquium paper: human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency.

Human populations use a variety of subsistence strategies to exploit an exceptionally broad range of ecoregions and dietary components. These aspects of human environments have changed dramatically during human evolution, giving rise to new selective pressures. To understand the genetic basis of human adaptations, we combine population genetics data with ecological information to detect variants that increased in frequency in response to new selective pressures. Our approach detects SNPs that show concordant differences in allele frequencies across populations with respect to specific aspects of the environment. Genic and especially nonsynonymous SNPs are overrepresented among those most strongly correlated with environmental variables. This provides genome-wide evidence for selection due to changes in ecoregion, diet, and subsistence. We find particularly strong signals associated with polar ecoregions, with foraging, and with a diet rich in roots and tubers. Interestingly, several of the strongest signals overlap with those implicated in energy metabolism phenotypes from genome-wide association studies, including SNPs influencing glucose levels and susceptibility to type 2 diabetes. Furthermore, several pathways, including those of starch and sucrose metabolism, are enriched for strong signals of adaptations to a diet rich in roots and tubers, whereas signals associated with polar ecoregions are overrepresented in genes associated with energy metabolism pathways.

NGS-Based Molecular Karyotyping of Multiple Myeloma: Results from the GEM12 Clinical Trial.

Next-generation sequencing (NGS) has greatly improved our ability to detect the genomic aberrations occurring in multiple myeloma (MM); however, its transfer to routine clinical labs and its validation in clinical trials remains to be established. We designed a capture-based NGS targeted panel to identify, in a single assay, known genetic alterations for the prognostic stratification of MM. The NGS panel was designed for the simultaneous study of single nucleotide and copy number variations, insertions and deletions, chromosomal translocations and V(D)J rearrangements. The panel was validated using a cohort of 149 MM patients enrolled in the GEM2012MENOS65 clinical trial. The results showed great global accuracy, with positive and negative predictive values close to 90% when compared with available data from fluorescence in situ hybridization and whole-exome sequencing. While the treatments used in the clinical trial showed high efficacy, patients defined as high-risk by the panel had shorter progression-free survival (p = 0.0015). As expected, the mutational status of TP53 was significant in predicting patient outcomes (p = 0.021). The NGS panel also efficiently detected clonal IGH rearrangements in 81% of patients. In conclusion, molecular karyotyping using a targeted NGS panel can identify relevant prognostic chromosomal abnormalities and translocations for the clinical management of MM patients.

Laboratory Cross-Comparison and Ring Test Trial for Tumor BRCA Testing in a Multicenter Epithelial Ovarian Cancer Series: The BORNEO GEICO 60-0 Study.

Germline and tumor BRCA testing constitutes a valuable tool for clinical decision-making in the management of epithelial ovarian cancer (EOC) patients. Tissue testing is able to identify both germline (g) and somatic (s) BRCA variants, but tissue preservation methods and the widespread implementation of NGS represent pre-analytical and analytical challenges that need to be managed. This study was carried out on a multicenter prospective GEICO cohort of EOC patients with known gBRCA status in order to determine the inter-laboratory reproducibility of tissue sBRCA testing. The study consisted of two independent experimental approaches, a bilateral comparison between two reference laboratories (RLs) testing 82 formalin-paraffin-embedded (FFPE) EOC samples each, and a Ring Test Trial (RTT) with five participating clinical laboratories (CLs) evaluating the performance of tissue BRCA testing in a total of nine samples. Importantly, labs employed their own locally adopted next-generation sequencing (NGS) analytical approach. BRCA mutation frequency in the RL sub-study cohort was 23.17%: 12 (63.1%) germline and 6 (31.6%) somatic. Concordance between the two RLs with respect to BRCA status was 84.2% (gBRCA 100%). The RTT study distributed a total of nine samples (three commercial synthetic human FFPE references, three FFPE, and three OC DNA) among five CLs. The median concordance detection rate among them was 64.7% (range: 35.3-70.6%). Analytical discrepancies were mainly due to the minimum variant allele frequency thresholds, bioinformatic pipeline filters, and downstream variant interpretation, some of them with consequences of clinical relevance. Our study demonstrates a wide range of concordance in the identification and interpretation of BRCA sequencing data, highlighting the relevance of establishing standard criteria for detecting, interpreting, and reporting BRCA variants.

Machine Learning-Based Approach Highlights the Use of a Genomic Variant Profile for Precision Medicine in Ovarian Failure.

Ovarian failure (OF) is a common cause of infertility usually diagnosed as idiopathic, with genetic causes accounting for 10-25% of cases. Whole-exome sequencing (WES) may enable identifying contributing genes and variant profiles to stratify the population into subtypes of OF. This study sought to identify a blood-based gene variant profile using accumulation of rare variants to promote precision medicine in fertility preservation programs. A case-control (n = 118, n = 32, respectively) WES study was performed in which only non-synonymous rare variants <5% minor allele frequency (MAF; in the IGSR) and coverage ≥ 100× were considered. A profile of 66 variants of uncertain significance was used for training an unsupervised machine learning model to separate cases from controls (97.2% sensitivity, 99.2% specificity) and stratify the population into two subtypes of OF (A and B) (93.31% sensitivity, 96.67% specificity). Model testing within the IGSR female population predicted 0.5% of women as subtype A and 2.4% as subtype B. This is the first study linking OF to the accumulation of rare variants and generates a new potential taxonomy supporting application of this approach for precision medicine in fertility preservation.