HELLS and PRDM9 form a pioneer complex to open chromatin at meiotic recombination hot spots.

Chromatin barriers prevent spurious interactions between regulatory elements and DNA-binding proteins. One such barrier, whose mechanism for overcoming is poorly understood, is access to recombination hot spots during meiosis. Here we show that the chromatin remodeler HELLS and DNA-binding protein PRDM9 function together to open chromatin at hot spots and provide access for the DNA double-strand break (DSB) machinery. Recombination hot spots are decorated by a unique combination of histone modifications not found at other regulatory elements. HELLS is recruited to hot spots by PRDM9 and is necessary for both histone modifications and DNA accessibility at hot spots. In male mice lacking HELLS, DSBs are retargeted to other sites of open chromatin, leading to germ cell death and sterility. Together, these data provide a model for hot spot activation in which HELLS and PRDM9 form a pioneer complex to create a unique epigenomic environment of open chromatin, permitting correct placement and repair of DSBs.

A panel-based mutational signature of homologous recombination deficiency associates with response to PARP inhibition in metastatic castration-resistant prostate cancer.

BACKGROUND: The PARP inhibitor (PARPi) olaparib is approved for homologous recombination repair (HRR) gene-altered metastatic castration-resistant prostate cancer (mCRPC). However, there is significant heterogeneity in response to PARPi in patients with mCRPC. Better clinical biomarkers are needed to identify patients likely to benefit from PARPi. METHODS: Patients with prostate adenocarcinoma and panel sequencing at Dana-Farber Cancer Institute were identified. Mutational signature analysis was performed using SigMA to characterize tumors as HRR deficient (HRD). The validity of SigMA to identify patients likely to benefit from olaparib was compared to the current FDA label (presence of a deleterious alteration in one of 14 HRR genes). RESULTS: 546 patients were identified, of which 34% were HRD. Among patients with HRR gene alterations, only patients with BRCA2 two-copy loss (2CL) were more likely to be HRD compared to patients without HRR gene alterations (74% vs 31%; P = 9.1 × 10-7). 28 patients with mCRPC received olaparib, of which 13 were HRD and 9 had BRCA2 2CL. SigMA improved upon the current FDA label for predicting PSA50 (sensitivity: 100% vs 90%; specificity: 83% vs 44%; PPV: 77% vs 47%; NPV: 100% vs 89%) and rPFS > 6 months (sensitivity: both 92%; specificity: 93% vs 53%; PPV: 92% vs 63%; NPV: 93% vs 89%). On multivariate analysis, incorporating prognostic clinical factors and HR gene alterations, SigMA-predicted HRD independently associated with improved PSA-PFS (HR = 0.086, p = 0.00082) and rPFS (HR = 0.078, p = 0.0070). CONCLUSIONS: SigMA-predicted HRD may better identify patients likely to benefit from olaparib as compared to the current FDA label. Larger studies are needed for further validation.

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology.

Late-Onset Alzheimer's disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5×10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.

Discovery of a new predominant cytosine DNA modification that is linked to gene expression in malaria parasites.

DNA cytosine modifications are key epigenetic regulators of cellular processes in mammalian cells, with their misregulation leading to varied disease states. In the human malaria parasite Plasmodium falciparum, a unicellular eukaryotic pathogen, little is known about the predominant cytosine modifications, cytosine methylation (5mC) and hydroxymethylation (5hmC). Here, we report the first identification of a hydroxymethylcytosine-like (5hmC-like) modification in P. falciparum asexual blood stages using a suite of biochemical methods. In contrast to mammalian cells, we report 5hmC-like levels in the P. falciparum genome of 0.2-0.4%, which are significantly higher than the methylated cytosine (mC) levels of 0.01-0.05%. Immunoprecipitation of hydroxymethylated DNA followed by next generation sequencing (hmeDIP-seq) revealed that 5hmC-like modifications are enriched in gene bodies with minimal dynamic changes during asexual development. Moreover, levels of the 5hmC-like base in gene bodies positively correlated to transcript levels, with more than 2000 genes stably marked with this modification throughout asexual development. Our work highlights the existence of a new predominant cytosine DNA modification pathway in P. falciparum and opens up exciting avenues for gene regulation research and the development of antimalarials.

Accurate typing of short tandem repeats from genome-wide sequencing data and its applications.

Short tandem repeats (STRs) are implicated in dozens of human genetic diseases and contribute significantly to genome variation and instability. Yet profiling STRs from short-read sequencing data is challenging because of their high sequencing error rates. Here, we developed STR-FM, short tandem repeat profiling using flank-based mapping, a computational pipeline that can detect the full spectrum of STR alleles from short-read data, can adapt to emerging read-mapping algorithms, and can be applied to heterogeneous genetic samples (e.g., tumors, viruses, and genomes of organelles). We used STR-FM to study STR error rates and patterns in publicly available human and in-house generated ultradeep plasmid sequencing data sets. We discovered that STRs sequenced with a PCR-free protocol have up to ninefold fewer errors than those sequenced with a PCR-containing protocol. We constructed an error correction model for genotyping STRs that can distinguish heterozygous alleles containing STRs with consecutive repeat numbers. Applying our model and pipeline to Illumina sequencing data with 100-bp reads, we could confidently genotype several disease-related long trinucleotide STRs. Utilizing this pipeline, for the first time we determined the genome-wide STR germline mutation rate from a deeply sequenced human pedigree. Additionally, we built a tool that recommends minimal sequencing depth for accurate STR genotyping, depending on repeat length and sequencing read length. The required read depth increases with STR length and is lower for a PCR-free protocol. This suite of tools addresses the pressing challenges surrounding STR genotyping, and thus is of wide interest to researchers investigating disease-related STRs and STR evolution.

Exome sequencing reveals pathogenic mutations in 91 strains of mice with Mendelian disorders.

Spontaneously arising mouse mutations have served as the foundation for understanding gene function for more than 100 years. We have used exome sequencing in an effort to identify the causative mutations for 172 distinct, spontaneously arising mouse models of Mendelian disorders, including a broad range of clinically relevant phenotypes. To analyze the resulting data, we developed an analytics pipeline that is optimized for mouse exome data and a variation database that allows for reproducible, user-defined data mining as well as nomination of mutation candidates through knowledge-based integration of sample and variant data. Using these new tools, putative pathogenic mutations were identified for 91 (53%) of the strains in our study. Despite the increased power offered by potentially unlimited pedigrees and controlled breeding, about half of our exome cases remained unsolved. Using a combination of manual analyses of exome alignments and whole-genome sequencing, we provide evidence that a large fraction of unsolved exome cases have underlying structural mutations. This result directly informs efforts to investigate the similar proportion of apparently Mendelian human phenotypes that are recalcitrant to exome sequencing.

Molecular Genetic Analysis of Ovarian Brenner Tumors and Associated Mucinous Epithelial Neoplasms: High Variant Concordance and Identification of Mutually Exclusive RAS Driver Mutations and MYC Amplification.

Benign ovarian Brenner tumors often are associated with mucinous cystic neoplasms, which are hypothesized to share a histogenic origin and progression, however, supporting molecular characterization is limited. Our goal was to identify molecular mechanisms linking these tumors. DNA from six Brenner tumors with paired mucinous tumors, two Brenner tumors not associated with a mucinous neoplasm, and two atypical proliferative (borderline) Brenner tumors was extracted from formalin-fixed, paraffin-embedded tumor samples and sequenced using a 358-gene next-generation sequencing assay. Variant calls were compared within tumor groups to assess somatic mutation profiles. There was high concordance of the variants between paired samples (40% to 75%; P < 0.0001). Four of the six tumor pairs showed KRAS hotspot driver mutations specifically in the mucinous tumor. In the two paired samples that lacked KRAS mutations, MYC amplification was detected in both of the mucinous and the Brenner components; MYC amplification also was detected in a third Brenner tumor. Five of the Brenner tumors had no reportable potential driver alterations. The two atypical proliferative (borderline) Brenner tumors both had RAS mutations. The high degree of coordinate variants between paired Brenner and mucinous tumors supports a shared origin or progression. Differences observed in affected genes and pathways, particularly involving RAS and MYC, may point to molecular drivers of a divergent phenotype and progression of these tumors.

Microsatellite interruptions stabilize primate genomes and exist as population-specific single nucleotide polymorphisms within individual human genomes.

Interruptions of microsatellite sequences impact genome evolution and can alter disease manifestation. However, human polymorphism levels at interrupted microsatellites (iMSs) are not known at a genome-wide scale, and the pathways for gaining interruptions are poorly understood. Using the 1000 Genomes Phase-1 variant call set, we interrogated mono-, di-, tri-, and tetranucleotide repeats up to 10 units in length. We detected ∼26,000-40,000 iMSs within each of four human population groups (African, European, East Asian, and American). We identified population-specific iMSs within exonic regions, and discovered that known disease-associated iMSs contain alleles present at differing frequencies among the populations. By analyzing longer microsatellites in primate genomes, we demonstrate that single interruptions result in a genome-wide average two- to six-fold reduction in microsatellite mutability, as compared with perfect microsatellites. Centrally located interruptions lowered mutability dramatically, by two to three orders of magnitude. Using a biochemical approach, we tested directly whether the mutability of a specific iMS is lower because of decreased DNA polymerase strand slippage errors. Modeling the adenomatous polyposis coli tumor suppressor gene sequence, we observed that a single base substitution interruption reduced strand slippage error rates five- to 50-fold, relative to a perfect repeat, during synthesis by DNA polymerases α, ß, or η. Computationally, we demonstrate that iMSs arise primarily by base substitution mutations within individual human genomes. Our biochemical survey of human DNA polymerase α, ß, δ, κ, and η error rates within certain microsatellites suggests that interruptions are created most frequently by low fidelity polymerases. Our combined computational and biochemical results demonstrate that iMSs are abundant in human genomes and are sources of population-specific genetic variation that may affect genome stability. The genome-wide identification of iMSs in human populations presented here has important implications for current models describing the impact of microsatellite polymorphisms on gene expression.

The origin, evolution, and functional impact of short insertion-deletion variants identified in 179 human genomes.

Short insertions and deletions (indels) are the second most abundant form of human genetic variation, but our understanding of their origins and functional effects lags behind that of other types of variants. Using population-scale sequencing, we have identified a high-quality set of 1.6 million indels from 179 individuals representing three diverse human populations. We show that rates of indel mutagenesis are highly heterogeneous, with 43%-48% of indels occurring in 4.03% of the genome, whereas in the remaining 96% their prevalence is 16 times lower than SNPs. Polymerase slippage can explain upwards of three-fourths of all indels, with the remainder being mostly simple deletions in complex sequence. However, insertions do occur and are significantly associated with pseudo-palindromic sequence features compatible with the fork stalling and template switching (FoSTeS) mechanism more commonly associated with large structural variations. We introduce a quantitative model of polymerase slippage, which enables us to identify indel-hypermutagenic protein-coding genes, some of which are associated with recurrent mutations leading to disease. Accounting for mutational rate heterogeneity due to sequence context, we find that indels across functional sequence are generally subject to stronger purifying selection than SNPs. We find that indel length modulates selection strength, and that indels affecting multiple functionally constrained nucleotides undergo stronger purifying selection. We further find that indels are enriched in associations with gene expression and find evidence for a contribution of nonsense-mediated decay. Finally, we show that indels can be integrated in existing genome-wide association studies (GWAS); although we do not find direct evidence that potentially causal protein-coding indels are enriched with associations to known disease-associated SNPs, our findings suggest that the causal variant underlying some of these associations may be indels.

Segmenting the human genome based on states of neutral genetic divergence.

Many studies have demonstrated that divergence levels generated by different mutation types vary and covary across the human genome. To improve our still-incomplete understanding of the mechanistic basis of this phenomenon, we analyze several mutation types simultaneously, anchoring their variation to specific regions of the genome. Using hidden Markov models on insertion, deletion, nucleotide substitution, and microsatellite divergence estimates inferred from human-orangutan alignments of neutrally evolving genomic sequences, we segment the human genome into regions corresponding to different divergence states--each uniquely characterized by specific combinations of divergence levels. We then parsed the mutagenic contributions of various biochemical processes associating divergence states with a broad range of genomic landscape features. We find that high divergence states inhabit guanine- and cytosine (GC)-rich, highly recombining subtelomeric regions; low divergence states cover inner parts of autosomes; chromosome X forms its own state with lowest divergence; and a state of elevated microsatellite mutability is interspersed across the genome. These general trends are mirrored in human diversity data from the 1000 Genomes Project, and departures from them highlight the evolutionary history of primate chromosomes. We also find that genes and noncoding functional marks [annotations from the Encyclopedia of DNA Elements (ENCODE)] are concentrated in high divergence states. Our results provide a powerful tool for biomedical data analysis: segmentations can be used to screen personal genome variants--including those associated with cancer and other diseases--and to improve computational predictions of noncoding functional elements.

Development and validation of the JAX Cancer Treatment Profile™ for detection of clinically actionable mutations in solid tumors.

BACKGROUND: The continued development of targeted therapeutics for cancer treatment has required the concomitant development of more expansive methods for the molecular profiling of the patient's tumor. We describe the validation of the JAX Cancer Treatment Profile™ (JAX-CTP™), a next generation sequencing (NGS)-based molecular diagnostic assay that detects actionable mutations in solid tumors to inform the selection of targeted therapeutics for cancer treatment. METHODS: NGS libraries are generated from DNA extracted from formalin fixed paraffin embedded tumors. Using hybrid capture, the genes of interest are enriched and sequenced on the Illumina HiSeq 2500 or MiSeq sequencers followed by variant detection and functional and clinical annotation for the generation of a clinical report. RESULTS: The JAX-CTP™ detects actionable variants, in the form of single nucleotide variations and small insertions and deletions (≤50 bp) in 190 genes in specimens with a neoplastic cell content of ≥10%. The JAX-CTP™ is also validated for the detection of clinically actionable gene amplifications. CONCLUSIONS: There is a lack of consensus in the molecular diagnostics field on the best method for the validation of NGS-based assays in oncology, thus the importance of communicating methods, as contained in this report. The growing number of targeted therapeutics and the complexity of the tumor genome necessitate continued development and refinement of advanced assays for tumor profiling to enable precision cancer treatment.

A Panel-Based Mutational Signature of Mismatch Repair Deficiency is Associated With Durable Response to Pembrolizumab in Metastatic Castration-Resistant Prostate Cancer.

INTRODUCTION/BACKGROUND: Immune checkpoint inhibitors (ICIs) have limited efficacy in prostate cancer (PCa). Better biomarkers are needed to predict responses to ICIs. We sought to demonstrate that a panel-based mutational signature identifies mismatch repair (MMR) deficient (MMRd) PCa and is a biomarker of response to pembrolizumab. PATIENTS AND METHODS: Clinico-genomic data was obtained for 2664 patients with PCa sequenced at Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering (MSK). Clinical outcomes were collected for patients with metastatic castration-resistant PCa (mCRPC) treated with pembrolizumab at DFCI. SigMA was used to characterize tumors as MMRd or MMR proficient (MMRp). The concordance between MMRd with microsatellite instability (MSI-H) was assessed. Radiographic progression-free survival (rPFS) and overall survival (OS) were collected for patients treated with pembrolizumab. Event-time distributions were estimated using Kaplan-Meier methodology. RESULTS: Across both cohorts, 100% (DFCI: 12/12; MSK: 43/43) of MSI-H tumors were MMRd. However, 14% (2/14) and 9.1% (6/66) of MMRd tumors in the DFCI and MSK cohorts respectively were microsatellite stable (MSS), and 26% (17/66) were MSI-indeterminate in the MSK cohort. Among patients treated with pembrolizumab, those with MMRd (n = 5) versus MMRp (n = 14) mCRPC experienced markedly improved rPFS (HR = 0.088, 95% CI: 0.011-0.70; P = .0064) and OS (HR = 0.11, 95% CI: 0.014-0.80; P = .010) from start of treatment. Four patients with MMRd experienced remissions of >= 2.5 years. CONCLUSION: SigMA detects additional cases of MMRd as compared to MSI testing in PCa and identifies patients likely to experience durable response to pembrolizumab.

Windshield splatter analysis with the Galaxy metagenomic pipeline.

How many species inhabit our immediate surroundings? A straightforward collection technique suitable for answering this question is known to anyone who has ever driven a car at highway speeds. The windshield of a moving vehicle is subjected to numerous insect strikes and can be used as a collection device for representative sampling. Unfortunately the analysis of biological material collected in that manner, as with most metagenomic studies, proves to be rather demanding due to the large number of required tools and considerable computational infrastructure. In this study, we use organic matter collected by a moving vehicle to design and test a comprehensive pipeline for phylogenetic profiling of metagenomic samples that includes all steps from processing and quality control of data generated by next-generation sequencing technologies to statistical analyses and data visualization. To the best of our knowledge, this is also the first publication that features a live online supplement providing access to exact analyses and workflows used in the article.

RNA-Seq for the detection of gene fusions in solid tumors: development and validation of the JAX FusionSeq™ 2.0 assay.

Whole transcriptome sequencing (RNA-Seq) has gained prominence for the detection of fusions in solid tumors. Here, we describe the development and validation of an in-house RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, in formalin-fixed paraffin-embedded (FFPE) specimens, using seventy tumor samples with varying fusion status. Conditions were optimized for RNA input of 50 ng, shown to be adequate to call known fusions at as low as 20% neoplastic content. Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. Performance analysis of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility. This clinically developed and validated RNA-Seq-based approach for fusion detection in FPPE samples was shown to be on par if not superior to off-the-shelf commercially offered assays. With gene fusions implicated in a variety of cancer types, offering high-quality, low-cost molecular testing services for FFPE specimens will serve to best benefit the patient and the advancement of precision medicine in molecular oncology. KEY MESSAGES: A custom RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. The assay can be performed with low RNA input and neoplastic content. Performance characteristics of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility.

Genomic and biological study of fusion genes as resistance mechanisms to EGFR inhibitors.

The clinical significance of gene fusions detected by DNA-based next generation sequencing remains unclear as resistance mechanisms to EGFR tyrosine kinase inhibitors in EGFR mutant non-small cell lung cancer. By studying EGFR inhibitor-resistant patients treated with a combination of an EGFR inhibitor and a drug targeting the putative resistance-causing fusion oncogene, we identify patients who benefit and those who do not from this treatment approach. Through evaluation including RNA-seq of potential drug resistance-imparting fusion oncogenes in 504 patients with EGFR mutant lung cancer, we identify only a minority of them as functional, potentially capable of imparting EGFR inhibitor resistance. We further functionally validate fusion oncogenes in vitro using CRISPR-based editing of EGFR mutant cell lines and use these models to identify known and unknown drug resistance mechanisms to combination therapies. Collectively, our results partially reveal the complex nature of fusion oncogenes as potential drug resistance mechanisms and highlight approaches that can be undertaken to determine their functional significance.

Ancestry-driven recalibration of tumor mutational burden and disparate clinical outcomes in response to immune checkpoint inhibitors.

The immune checkpoint inhibitor (ICI) pembrolizumab is US FDA approved for treatment of solid tumors with high tumor mutational burden (TMB-high; ≥10 variants/Mb). However, the extent to which TMB-high generalizes as an accurate biomarker in diverse patient populations is largely unknown. Using two clinical cohorts, we investigated the interplay between genetic ancestry, TMB, and tumor-only versus tumor-normal paired sequencing in solid tumors. TMB estimates from tumor-only panels substantially overclassified individuals into the clinically important TMB-high group due to germline contamination, and this bias was particularly pronounced in patients with Asian/African ancestry. Among patients with non-small cell lung cancer treated with ICIs, those misclassified as TMB-high from tumor-only panels did not associate with improved outcomes. TMB-high was significantly associated with improved outcomes only in European ancestries and merits validation in non-European ancestry populations. Ancestry-aware tumor-only TMB calibration and ancestry-diverse biomarker studies are critical to ensure that existing disparities are not exacerbated in precision medicine.

Astrocyte Support for Oligodendrocyte Differentiation can be Conveyed via Extracellular Vesicles but Diminishes with Age.

The aging brain is associated with significant changes in physiology that alter the tissue microenvironment of the central nervous system (CNS). In the aged CNS, increased demyelination has been associated with astrocyte hypertrophy and aging has been implicated as a basis for these pathological changes. Aging tissues accumulate chronic cellular stress, which can lead to the development of a pro-inflammatory phenotype that can be associated with cellular senescence. Herein, we provide evidence that astrocytes aged in culture develop a spontaneous pro-inflammatory and senescence-like phenotype. We found that extracellular vesicles (EVs) from young astrocyte were sufficient to convey support for oligodendrocyte differentiation while this support was lost by EVs from aged astrocytes. Importantly, the negative influence of culture age on astrocytes, and their cognate EVs, could be countered by treatment with rapamycin. Comparative proteomic analysis of EVs from young and aged astrocytes revealed peptide repertoires unique to each age. Taken together, these findings provide new information on the contribution of EVs as potent mediators by which astrocytes can extert changing influence in either the disease or aged brain.

Mutation Yield of a Custom 212-Gene Next-Generation Sequencing Panel for Solid Tumors: Clinical Experience of the First 260 Cases Tested Using the JAX ActionSeq™ Assay.

OBJECTIVE: The study aimed to retrospectively evaluate the positive yield rate of a custom 212-gene next-generation sequencing (NGS) panel, the JAX ActionSeq™ assay, used in molecular profiling of solid tumors for precision medicine. METHODS: We evaluated 261 cases tested over a 24-month period including cancers across 24 primary tissue types and report on the mutation yield in these cases. RESULTS: Thirty-three of the 261 cases (13%) had no detectable clinically significant variants. In the remaining 228 cases (87%), we identified 550 clinically significant variants in 88 of the 212 genes, with four of fewer clinically significant variants being detected in 62 of 88 genes (70%). TP53 had the highest number of variants (125), followed by APC (47), KRAS (47), ARID1A (20), PIK3CA (20) and EGFR (18). There were 38 tier I and 512 tier II variants, with two genes having only a tier I variant, seven genes having both a tier I and tier II variant, and 79 genes having at least one tier II variant. Overall, the ActionSeq™ assay detected clinically significant variants in 42% of the genes included in the panel (88/212), 68% of which (60/88) were detected in more than one tumor type. CONCLUSIONS: This study demonstrates that of the genes with documented involvement in cancer, only a limited number are currently clinically significant from a therapeutic, diagnostic and/or prognostic perspective.

Technical and Regulatory Considerations for Taking Liquid Biopsy to the Clinic: Validation of the JAX PlasmaMonitorTM Assay.

The standard of care in oncology has been genomic profiling of tumor tissue biopsies for the treatment and management of disease, which can prove to be quite challenging in terms of cost, invasiveness of procedure, and potential risk for the patient. As the number of available drugs in oncology continues to increase, so too does the demand for technologies and testing applications that can identify genomic alterations targetable by these new therapies. Liquid biopsies that use a blood draw from the diseased patient may offset the many disadvantages of the invasive procedure. However, as with any new technology or finding in the clinical field, the clinical utility of an analytical test such as that of the liquid biopsy has to be established. Here, we review the clinical testing space for liquid biopsy offerings and elucidate the technical and regulatory considerations to develop such an assay, using our recently validated PlasmaMonitorTM test.

Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines.

BACKGROUND: Patient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison. RESULTS: We report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA). CONCLUSIONS: The analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows .