Ultra-Sensitive Mutation Detection and Genome-Wide DNA Copy Number Reconstruction by Error-Corrected Circulating Tumor DNA Sequencing.

BACKGROUND: Circulating free DNA sequencing (cfDNA-Seq) can portray cancer genome landscapes, but highly sensitive and specific technologies are necessary to accurately detect mutations with often low variant frequencies. METHODS: We developed a customizable hybrid-capture cfDNA-Seq technology using off-the-shelf molecular barcodes and a novel duplex DNA molecule identification tool for enhanced error correction. RESULTS: Modeling based on cfDNA yields from 58 patients showed that this technology, requiring 25 ng of cfDNA, could be applied to >95% of patients with metastatic colorectal cancer (mCRC). cfDNA-Seq of a 32-gene, 163.3-kbp target region detected 100% of single-nucleotide variants, with 0.15% variant frequency in spike-in experiments. Molecular barcode error correction reduced false-positive mutation calls by 97.5%. In 28 consecutively analyzed patients with mCRC, 80 out of 91 mutations previously detected by tumor tissue sequencing were called in the cfDNA. Call rates were similar for point mutations and indels. cfDNA-Seq identified typical mCRC driver mutations in patients in whom biopsy sequencing had failed or did not include key mCRC driver genes. Mutations only called in cfDNA but undetectable in matched biopsies included a subclonal resistance driver mutation to anti-EGFR antibodies in KRAS, parallel evolution of multiple PIK3CA mutations in 2 cases, and TP53 mutations originating from clonal hematopoiesis. Furthermore, cfDNA-Seq off-target read analysis allowed simultaneous genome-wide copy number profile reconstruction in 20 of 28 cases. Copy number profiles were validated by low-coverage whole-genome sequencing. CONCLUSIONS: This error-corrected, ultradeep cfDNA-Seq technology with a customizable target region and publicly available bioinformatics tools enables broad insights into cancer genomes and evolution. CLINICALTRIALSGOV IDENTIFIER: NCT02112357.

Autosomal dominant osteopetrosis associated with renal tubular acidosis is due to a CLCN7 mutation.

The aim of this study was to identify the causative mutation in a family with an unusual presentation of autosomal dominant osteopetrosis (OPT), proximal renal tubular acidosis (RTA), renal stones, epilepsy, and blindness, a combination of features not previously reported. We undertook exome sequencing of one affected and one unaffected family member, followed by targeted analysis of known candidate genes to identify the causative mutation. This identified a missense mutation (c.643G>A; p.Gly215Arg) in the gene encoding the chloride/proton antiporter 7 (gene CLCN7, protein CLC-7), which was confirmed by amplification refractory mutation system (ARMS)-PCR, and to be present in the three available patients. CLC-7 mutations are known to cause autosomal dominant OPT type 2, also called Albers-Schonberg disease, which is characterized by osteosclerosis, predominantly of the spine, pelvis and skull base, resulting in bone fragility and fractures. Albers-Schonberg disease is not reported to be associated with RTA, but autosomal recessive OPT type 3 (OPTB3) with RTA is associated with carbonic anhydrase type 2 (CA2) mutations. No mutations were detected in CA2 or any other genes known to cause proximal RTA. Neither CLCN7 nor CA2 mutations have previously been reported to be associated with renal stones or epilepsy. Thus, we identified a CLCN7 mutation in a family with autosomal dominant osteopetrosis, RTA, renal stones, epilepsy, and blindness. © 2016 Wiley Periodicals, Inc.

Recessive mutations in SPTBN2 implicate ß-III spectrin in both cognitive and motor development.

ß-III spectrin is present in the brain and is known to be important in the function of the cerebellum. Heterozygous mutations in SPTBN2, the gene encoding ß-III spectrin, cause Spinocerebellar Ataxia Type 5 (SCA5), an adult-onset, slowly progressive, autosomal-dominant pure cerebellar ataxia. SCA5 is sometimes known as "Lincoln ataxia," because the largest known family is descended from relatives of the United States President Abraham Lincoln. Using targeted capture and next-generation sequencing, we identified a homozygous stop codon in SPTBN2 in a consanguineous family in which childhood developmental ataxia co-segregates with cognitive impairment. The cognitive impairment could result from mutations in a second gene, but further analysis using whole-genome sequencing combined with SNP array analysis did not reveal any evidence of other mutations. We also examined a mouse knockout of ß-III spectrin in which ataxia and progressive degeneration of cerebellar Purkinje cells has been previously reported and found morphological abnormalities in neurons from prefrontal cortex and deficits in object recognition tasks, consistent with the human cognitive phenotype. These data provide the first evidence that ß-III spectrin plays an important role in cortical brain development and cognition, in addition to its function in the cerebellum; and we conclude that cognitive impairment is an integral part of this novel recessive ataxic syndrome, Spectrin-associated Autosomal Recessive Cerebellar Ataxia type 1 (SPARCA1). In addition, the identification of SPARCA1 and normal heterozygous carriers of the stop codon in SPTBN2 provides insights into the mechanism of molecular dominance in SCA5 and demonstrates that the cell-specific repertoire of spectrin subunits underlies a novel group of disorders, the neuronal spectrinopathies, which includes SCA5, SPARCA1, and a form of West syndrome.

Periventricular heterotopia in 6q terminal deletion syndrome: role of the C6orf70 gene.

Periventricular nodular heterotopia is caused by defective neuronal migration that results in heterotopic neuronal nodules lining the lateral ventricles. Mutations in filamin A (FLNA) or ADP-ribosylation factor guanine nucleotide-exchange factor 2 (ARFGEF2) cause periventricular nodular heterotopia, but most patients with this malformation do not have a known aetiology. Using comparative genomic hybridization, we identified 12 patients with developmental brain abnormalities, variably combining periventricular nodular heterotopia, corpus callosum dysgenesis, colpocephaly, cerebellar hypoplasia and polymicrogyria, harbouring a common 1.2 Mb minimal critical deletion in 6q27. These anatomic features were mainly associated with epilepsy, ataxia and cognitive impairment. Using whole exome sequencing in 14 patients with isolated periventricular nodular heterotopia but no copy number variants, we identified one patient with periventricular nodular heterotopia, developmental delay and epilepsy and a de novo missense mutation in the chromosome 6 open reading frame 70 (C6orf70) gene, mapping in the minimal critical deleted region. Using immunohistochemistry and western blots, we demonstrated that in human cell lines, C6orf70 shows primarily a cytoplasmic vesicular puncta-like distribution and that the mutation affects its stability and subcellular distribution. We also performed in utero silencing of C6orf70 and of Phf10 and Dll1, the two additional genes mapping in the 6q27 minimal critical deleted region that are expressed in human and rodent brain. Silencing of C6orf70 in the developing rat neocortex produced periventricular nodular heterotopia that was rescued by concomitant expression of wild-type human C6orf70 protein. Silencing of the contiguous Phf10 or Dll1 genes only produced slightly delayed migration but not periventricular nodular heterotopia. The complex brain phenotype observed in the 6q terminal deletion syndrome likely results from the combined haploinsufficiency of contiguous genes mapping to a small 1.2 Mb region. Our data suggest that, of the genes within this minimal critical region, C6orf70 plays a major role in the control of neuronal migration and its haploinsufficiency or mutation causes periventricular nodular heterotopia.

Next generation sequencing for molecular diagnosis of neurological disorders using ataxias as a model.

Many neurological conditions are caused by immensely heterogeneous gene mutations. The diagnostic process is often long and complex with most patients undergoing multiple invasive and costly investigations without ever reaching a conclusive molecular diagnosis. The advent of massively parallel, next-generation sequencing promises to revolutionize genetic testing and shorten the 'diagnostic odyssey' for many of these patients. We performed a pilot study using heterogeneous ataxias as a model neurogenetic disorder to assess the introduction of next-generation sequencing into clinical practice. We captured 58 known human ataxia genes followed by Illumina Next-Generation Sequencing in 50 highly heterogeneous patients with ataxia who had been extensively investigated and were refractory to diagnosis. All cases had been tested for spinocerebellar ataxia 1-3, 6, 7 and Friedrich's ataxia and had multiple other biochemical, genetic and invasive tests. In those cases where we identified the genetic mutation, we determined the time to diagnosis. Pathogenicity was assessed using a bioinformatics pipeline and novel variants were validated using functional experiments. The overall detection rate in our heterogeneous cohort was 18% and varied from 8.3% in those with an adult onset progressive disorder to 40% in those with a childhood or adolescent onset progressive disorder. The highest detection rate was in those with an adolescent onset and a family history (75%). The majority of cases with detectable mutations had a childhood onset but most are now adults, reflecting the long delay in diagnosis. The delays were primarily related to lack of easily available clinical testing, but other factors included the presence of atypical phenotypes and the use of indirect testing. In the cases where we made an eventual diagnosis, the delay was 3-35 years (mean 18.1 years). Alignment and coverage metrics indicated that the capture and sequencing was highly efficient and the consumable cost was ∼£400 (€460 or US$620). Our pathogenicity interpretation pathway predicted 13 different mutations in eight different genes: PRKCG, TTBK2, SETX, SPTBN2, SACS, MRE11, KCNC3 and DARS2 of which nine were novel including one causing a newly described recessive ataxia syndrome. Genetic testing using targeted capture followed by next-generation sequencing was efficient, cost-effective, and enabled a molecular diagnosis in many refractory cases. A specific challenge of next-generation sequencing data is pathogenicity interpretation, but functional analysis confirmed the pathogenicity of novel variants showing that the pipeline was robust. Our results have broad implications for clinical neurology practice and the approach to diagnostic testing.

PepSite: prediction of peptide-binding sites from protein surfaces.

Complex biological functions emerge through intricate protein-protein interaction networks. An important class of protein-protein interaction corresponds to peptide-mediated interactions, in which a short peptide stretch from one partner interacts with a large protein surface from the other partner. Protein-peptide interactions are typically of low affinity and involved in regulatory mechanisms, dynamically reshaping protein interaction networks. Due to the relatively small interaction surface, modulation of protein-peptide interactions is feasible and highly attractive for therapeutic purposes. Unfortunately, the number of available 3D structures of protein-peptide interfaces is very limited. For typical cases where a protein-peptide structure of interest is not available, the PepSite web server can be used to predict peptide-binding spots from protein surfaces alone. The PepSite method relies on preferred peptide-binding environments calculated from a set of known protein-peptide 3D structures, combined with distance constraints derived from known peptides. We present an updated version of the web server that is orders of magnitude faster than the original implementation, returning results in seconds instead of minutes or hours. The PepSite web server is available at http://pepsite2.russelllab.org.

Driver mutations in GNAQ and GNA11 genes as potential targets for precision immunotherapy in uveal melanoma patients.

Uveal melanoma (UM) is the most common ocular malignancy in adults. Nearly 95% of UM patients carry the mutually exclusive mutations in the homologous genes GNAQ (amino acid change Q209L/Q209P) and GNA11 (aminoacid change Q209L). UM is located in an immunosuppressed organ and does not suffer immunoediting. Therefore, we hypothesize that driver mutations in GNAQ/11 genes could be recognized by the immune system. Genomic and transcriptomic data from primary uveal tumors were collected from the TCGA-UM dataset (n = 80) and used to assess the immunogenic potential for GNAQ/GNA11 Q209L/Q209P mutations using a variety of tools and HLA type information. All prediction tools showed stronger GNAQ/11 Q209L binding to HLA than GNAQ/11 Q209P. The immunogenicity analysis revealed that Q209L is likely to be presented by more than 73% of individuals in 1000 G databases whereas Q209P is only predicted to be presented in 24% of individuals. GNAQ/11 Q209L showed a higher likelihood to be presented by HLA-I molecules than almost all driver mutations analyzed. Finally, samples carrying Q209L had a higher immune-reactive phenotype. Regarding cancer risk, seven HLA genotypes with low Q209L affinity show higher frequency in uveal melanoma patients than in the general population. However, no clear association was found between any HLA genotype and survival. Results suggest a high potential immunogenicity of the GNAQ/11 Q209L variant that could allow the generation of novel therapeutic tools to treat UM like neoantigen vaccinations.

Copy number architectures define treatment-mediated selection of lethal prostate cancer clones.

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient evolutionary relationships of metastases that evade treatment, we perform genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 167 metastatic regions from 11 organs harvested post-mortem from 10 men who died from prostate cancer. We identify diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number changes, we confirm a common clone of origin across metastases and diagnostic biopsies, and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. These autosome-defined clusters are characterized by cluster-specific AR gene architectures, and in two index cases are topologically more congruent than by chance (p-values 3.07 × 10-8 and 6.4 × 10-4). Integration with anatomical sites suggests patterns of spread and points of genomic divergence. Here, we show that copy number boundaries identify treatment-selected clones with putatively distinct lethal trajectories.

Next-generation sequencing in health-care delivery: lessons from the functional analysis of rhodopsin.

PURPOSE: The interpretation of genetic information has always been challenging, but next-generation sequencing produces data on such a vast scale that many more variants of uncertain pathogenicity will be found. We exemplify this issue with reference to human rhodopsin, in which pathogenic mutations can lead to autosomal dominant retinitis pigmentosa. METHODS: Rhodopsin variants, with unknown pathogenicity, were found in patients by next-generation and Sanger sequencing and a multidisciplinary approach was used to determine their functional significance. RESULTS: Four variants in rhodopsin were identified: F45L, P53R, R69H, and M39R, with the latter two substitutions being novel. We investigated the cellular transport and photopigment function of all four human substitutions and found that the F45L and R69H variants behave like wild-type and are highly unlikely to be pathogenic. By contrast, P53R (a de novo change) and M39R were retained in the endoplasmic reticulum with significantly reduced functionality and are clearly pathogenic. CONCLUSION: Potential pathogenicity of variants requires careful assessment using clinical, genetic, and functional data. We suggest that a multidisciplinary pathway of assessment, using several functional assays, will be required if next-generation sequencing is to be used effectively, reliably, and safely in the clinical environment.

Exome sequencing can detect pathogenic mosaic mutations present at low allele frequencies.

The development of next generation sequencing (NGS) has radically transformed the scientific landscape, making it possible to sequence the exome of any given individual in a cost-effective way. The power of this approach has been demonstrated by a number of groups who have identified pathogenic mutations in small pedigrees that have been resistant to traditional genetic mapping. Recently it has become clear that exome sequencing has great potential with respect to sporadic disease and the identification of de novo mutations. This is highlighted by studies reporting whole-exome sequencing of patient-parental trios affected by learning disability, autism and schizophrenia. It is widely anticipated that the introduction of this technique into a clinical setting will revolutionise genetic diagnosis. However, the sensitivity of NGS exome sequencing is currently unclear. Here, we describe the exome sequencing of DNA samples from a patient with double cortex syndrome and her parents, resulting in the detection of a mosaic splicing mutation in LIS1. This variant was found at an allele frequency of just 18%, demonstrating that NGS methods have the capacity to identify pathogenic mosaic mutations present at a low level.

Accumulation of copy number alterations and clinical progression across advanced prostate cancer.

BACKGROUND: Genomic copy number alterations commonly occur in prostate cancer and are one measure of genomic instability. The clinical implication of copy number change in advanced prostate cancer, which defines a wide spectrum of disease from high-risk localised to metastatic, is unknown. METHODS: We performed copy number profiling on 688 tumour regions from 300 patients, who presented with advanced prostate cancer prior to the start of long-term androgen deprivation therapy (ADT), in the control arm of the prospective randomised STAMPEDE trial. Patients were categorised into metastatic states as follows; high-risk non-metastatic with or without local lymph node involvement, or metastatic low/high volume. We followed up patients for a median of 7 years. Univariable and multivariable Cox survival models were fitted to estimate the association between the burden of copy number alteration as a continuous variable and the hazard of death or disease progression. RESULTS: The burden of copy number alterations positively associated with radiologically evident distant metastases at diagnosis (P=0.00006) and showed a non-linear relationship with clinical outcome on univariable and multivariable analysis, characterised by a sharp increase in the relative risk of progression (P=0.003) and death (P=0.045) for each unit increase, stabilising into more modest increases with higher copy number burdens. This association between copy number burden and outcome was similar in each metastatic state. Copy number loss occurred significantly more frequently than gain at the lowest copy number burden quartile (q=4.1 × 10-6). Loss of segments in chromosome 5q21-22 and gains at 8q21-24, respectively including CHD1 and cMYC occurred more frequently in cases with higher copy number alteration (for either region: Kolmogorov-Smirnov distance, 0.5; adjusted P<0.0001). Copy number alterations showed variability across tumour regions in the same prostate. This variance associated with increased risk of distant metastases (Kruskal-Wallis test P=0.037). CONCLUSIONS: Copy number alteration in advanced prostate cancer associates with increased risk of metastases at diagnosis. Accumulation of a limited number of copy number alterations associates with most of the increased risk of disease progression and death. The increased likelihood of involvement of specific segments in high copy number alteration burden cancers may suggest an order underlying the accumulation of copy number changes. TRIAL REGISTRATION: ClinicalTrials.gov NCT00268476 , registered on December 22, 2005. EudraCT  2004-000193-31 , registered on October 4, 2004.

The Immunogenic Potential of Recurrent Cancer Drug Resistance Mutations: An In Silico Study.

Cancer somatic mutations have been identified as a source of antigens that can be targeted by cancer immunotherapy. In this work, expanding on previous studies, we analyze the HLA-presentation properties of mutations that are known to drive resistance to cancer targeted-therapies. We survey a large dataset of mutations that confer resistance to different drugs and occur in numerous genes and tumor types. We show that a significant number of them are predicted in silico to be potentially immunogenic across a large proportion of the human population. Further, by analyzing a cohort of patients carrying a small subset of these resistance mutations, we provide evidence that what is observed in the general population may be indicative of the mutations' immunogenic potential in resistant patients. Two of the mutations in our dataset had previously been experimentally validated by others and it was confirmed that some of their associated neopeptides elicit T-cell responses in vitro. The identification of potent cancer-specific antigens can be instrumental for developing more effective immunotherapies. In this work, we propose a novel list of drug-resistance mutations, several of which are recurrent, that could be of particular interest in the context of off-the-shelf precision immunotherapies such as therapeutic cancer vaccines.

Extreme intratumour heterogeneity and driver evolution in mismatch repair deficient gastro-oesophageal cancer.

Mismatch repair deficient (dMMR) gastro-oesophageal adenocarcinomas (GOAs) show better outcomes than their MMR-proficient counterparts and high immunotherapy sensitivity. The hypermutator-phenotype of dMMR tumours theoretically enables high evolvability but their evolution has not been investigated. Here we apply multi-region exome sequencing (MSeq) to four treatment-naive dMMR GOAs. This reveals extreme intratumour heterogeneity (ITH), exceeding ITH in other cancer types >20-fold, but also long phylogenetic trunks which may explain the exquisite immunotherapy sensitivity of dMMR tumours. Subclonal driver mutations are common and parallel evolution occurs in RAS, PIK3CA, SWI/SNF-complex genes and in immune evasion regulators. MSeq data and evolution analysis of single region-data from 64 MSI GOAs show that chromosome 8 gains are early genetic events and that the hypermutator-phenotype remains active during progression. MSeq may be necessary for biomarker development in these heterogeneous cancers. Comparison with other MSeq-analysed tumour types reveals mutation rates and their timing to determine phylogenetic tree morphologies.

Clinical BRCA1/2 Reversion Analysis Identifies Hotspot Mutations and Predicted Neoantigens Associated with Therapy Resistance.

Reversion mutations in BRCA1 or BRCA2 are associated with resistance to PARP inhibitors and platinum. To better understand the nature of these mutations, we collated, codified, and analyzed more than 300 reversions. This identified reversion "hotspots" and "deserts" in regions encoding the N and C terminus, respectively, of BRCA2, suggesting that pathogenic mutations in these regions may be at higher or lower risk of reversion. Missense and splice-site pathogenic mutations in BRCA1/2 also appeared less likely to revert than truncating mutations. Most reversions were <100 bp deletions. Although many deletions exhibited microhomology, this was not universal, suggesting that multiple DNA-repair processes cause reversion. Finally, we found that many reversions were predicted to encode immunogenic neopeptides, suggesting a route to the treatment of reverted disease. As well as providing a freely available database for the collation of future reversion cases, these observations have implications for how drug resistance might be managed in BRCA-mutant cancers. SIGNIFICANCE: Reversion mutations in BRCA genes are a major cause of clinical platinum and PARP inhibitor resistance. This analysis of all reported clinical reversions suggests that the position of BRCA2 mutations affects the risk of reversion. Many reversions are also predicted to encode tumor neoantigens, providing a potential route to targeting resistance.This article is highlighted in the In This Issue feature, p. 1426.

Author Correction: Extreme intratumour heterogeneity and driver evolution in mismatch repair deficient gastro-oesophageal cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genome-wide plasma DNA methylation features of metastatic prostate cancer.

Tumor DNA circulates in the plasma of cancer patients admixed with DNA from noncancerous cells. The genomic landscape of plasma DNA has been characterized in metastatic castration-resistant prostate cancer (mCRPC) but the plasma methylome has not been extensively explored. Here, we performed next-generation sequencing (NGS) on plasma DNA with and without bisulfite treatment from mCRPC patients receiving either abiraterone or enzalutamide in the pre- or post-chemotherapy setting. Principal component analysis on the mCRPC plasma methylome indicated that the main contributor to methylation variance (principal component one, or PC1) was strongly correlated with genomically determined tumor fraction (r = -0.96; P < 10-8) and characterized by hypermethylation of targets of the polycomb repressor complex 2 components. Further deconvolution of the PC1 top-correlated segments revealed that these segments are comprised of methylation patterns specific to either prostate cancer or prostate normal epithelium. To extract information specific to an individual's cancer, we then focused on an orthogonal methylation signature, which revealed enrichment for androgen receptor binding sequences and hypomethylation of these segments associated with AR copy number gain. Individuals harboring this methylation pattern had a more aggressive clinical course. Plasma methylome analysis can accurately quantitate tumor fraction and identify distinct biologically relevant mCRPC phenotypes.

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.

BACKGROUND: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (DeltaDeltaG) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. RESULTS: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which DeltaDeltaG >or= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. CONCLUSION: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration.

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data.

BACKGROUND: Targeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs). METHODS: To address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection. RESULTS: Our tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments. CONCLUSIONS: AmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve .

In Vivo Modeling of Chemoresistant Neuroblastoma Provides New Insights into Chemorefractory Disease and Metastasis.

Neuroblastoma is a pediatric cancer that is frequently metastatic and resistant to conventional treatment. In part, a lack of natively metastatic, chemoresistant in vivo models has limited our insight into the development of aggressive disease. The Th-MYCN genetically engineered mouse model develops rapidly progressive chemosensitive neuroblastoma and lacks clinically relevant metastases. To study tumor progression in a context more reflective of clinical therapy, we delivered multicycle treatment with cyclophosphamide to Th-MYCN mice, individualizing therapy using MRI, to generate the Th-MYCN CPM32 model. These mice developed chemoresistance and spontaneous bone marrow metastases. Tumors exhibited an altered immune microenvironment with increased stroma and tumor-associated fibroblasts. Analysis of copy number aberrations revealed genomic changes characteristic of human MYCN-amplified neuroblastoma, specifically copy number gains at mouse chromosome 11, syntenic with gains on human chromosome 17q. RNA sequencing revealed enriched expression of genes associated with 17q gain and upregulation of genes associated with high-risk neuroblastoma, such as the cell-cycle regulator cyclin B1-interacting protein 1 (Ccnb1ip1) and thymidine kinase (TK1). The antiapoptotic, prometastatic JAK-STAT3 pathway was activated in chemoresistant tumors, and treatment with the JAK1/JAK2 inhibitor CYT387 reduced progression of chemoresistant tumors and increased survival. Our results highlight that under treatment conditions that mimic chemotherapy in human patients, Th-MYCN mice develop genomic, microenvironmental, and clinical features reminiscent of human chemorefractory disease. The Th-MYCN CPM32 model therefore is a useful tool to dissect in detail mechanisms that drive metastasis and chemoresistance, and highlights dysregulation of signaling pathways such as JAK-STAT3 that could be targeted to improve treatment of aggressive disease. SIGNIFICANCE: An in vivo mouse model of high-risk treatment-resistant neuroblastoma exhibits changes in the tumor microenvironment, widespread metastases, and sensitivity to JAK1/2 inhibition.

Genomic and Transcriptomic Determinants of Therapy Resistance and Immune Landscape Evolution during Anti-EGFR Treatment in Colorectal Cancer.

Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRCs). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF1 and non-canonical RAS/RAF aberrations with primary resistance and validated transcriptomic CRC subtypes as non-genetic predictors of benefit. Sixty-four percent of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype at baseline to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PD-L1 and LAG3 immune checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy.