Consensus gene modules strategy identifies candidate blood-based biomarkers for primary Sjögren's disease.

Primary Sjögren disease (pSD) is an autoimmune disease characterized by lymphoid infiltration of exocrine glands leading to dryness of the mucosal surfaces and by the production of autoantibodies. The pathophysiology of pSD remains elusive and no treatment with demonstrated efficacy is available yet. To better understand the biology underlying pSD heterogeneity, we aimed at identifying Consensus gene Modules (CMs) that summarize the high-dimensional transcriptomic data of whole blood samples in pSD patients. We performed unsupervised gene classification on four data sets and identified thirteen CMs. We annotated and interpreted each of these CMs as corresponding to cell type abundances or biological functions by using gene set enrichment analyses and transcriptomic profiles of sorted blood cell subsets. Correlation with independently measured cell type abundances by flow cytometry confirmed these annotations. We used these CMs to reconcile previously proposed patient stratifications of pSD. Importantly, we showed that the expression of modules representing lymphocytes and erythrocytes before treatment initiation is associated with response to hydroxychloroquine and leflunomide combination therapy in a clinical trial. These consensus modules will help the identification and translation of blood-based predictive biomarkers for the treatment of pSD.

Survival factor NFIL3 restricts FOXO-induced gene expression in cancer.

Depending on the circumstance, FOXO (Forkhead O) (FOXO1, FOXO3, and FOXO4) transcription factors activate the expression of markedly different sets of genes to produce different phenotypic effects. For example, distinct FOXO-regulated transcriptional programs stimulate cell death or enhance organism life span. To gain insight into how FOXOs select specific genes for regulation, we performed a screen for genes that modify FOXO activation of TRAIL, a death receptor ligand capable of inducing extrinsic apoptosis. We discovered that the bZIP transcriptional repressor NFIL3 (nuclear factor interleukin 3-regulated) hindered FOXO transcription factor access to chromatin at the TRAIL promoter by binding to nearby DNA and recruiting histone deacetylase-2 (HDAC2) to reduce histone acetylation. In the same manner, NFIL3 repressed expression of certain FOXO targets--e.g., FAS, GADD45α (growth arrest and DNA damage-inducible, α), and GADD45ß--but not others. NFIL3, which we found to be overexpressed in different cancers, supported tumor cell survival largely through repression of TRAIL and antagonized hydrogen peroxide-induced cell death. Moreover, its expression in cancer was associated with lower patient survival. Therefore, NFIL3 alters cancer cell behavior and FOXO function by acting on chromatin to restrict the menu of FOXO target genes. Targeting of NFIL3 could be of therapeutic benefit for cancer patients.

Structure-based prediction of protein-protein interactions on a genome-wide scale.

The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. Much of our present knowledge derives from high-throughput techniques such as the yeast two-hybrid assay and affinity purification, as well as from manual curation of experiments on individual systems. A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein-protein interactions (PPIs). Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages. Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence. Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human. Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins.

rCGH: a comprehensive array-based genomic profile platform for precision medicine.

UNLABELLED: We present rCGH, a comprehensive array-based comparative genomic hybridization analysis workflow, integrating computational improvements and functionalities specifically designed for precision medicine. rCGH supports the major microarray platforms, ensures a full traceability and facilitates profiles interpretation and decision-making through sharable interactive visualizations. AVAILABILITY AND IMPLEMENTATION: The rCGH R package is available on bioconductor (under Artistic-2.0). The aCGH-viewer is available at https://fredcommo.shinyapps.io/aCGH_viewer, and the application implementation is freely available for installation at https://github.com/fredcommo/aCGH_viewer CONTACT: frederic.commo@gustaveroussy.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutational Profile of Metastatic Breast Cancers: A Retrospective Analysis.

BACKGROUND: Major advances have been achieved in the characterization of early breast cancer (eBC) genomic profiles. Metastatic breast cancer (mBC) is associated with poor outcomes, yet limited information is available on the genomic profile of this disease. This study aims to decipher mutational profiles of mBC using next-generation sequencing. METHODS AND FINDINGS: Whole-exome sequencing was performed on 216 tumor-blood pairs from mBC patients who underwent a biopsy in the context of the SAFIR01, SAFIR02, SHIVA, or Molecular Screening for Cancer Treatment Optimization (MOSCATO) prospective trials. Mutational profiles from 772 primary breast tumors from The Cancer Genome Atlas (TCGA) were used as a reference for comparing primary and mBC mutational profiles. Twelve genes (TP53, PIK3CA, GATA3, ESR1, MAP3K1, CDH1, AKT1, MAP2K4, RB1, PTEN, CBFB, and CDKN2A) were identified as significantly mutated in mBC (false discovery rate [FDR] < 0.1). Eight genes (ESR1, FSIP2, FRAS1, OSBPL3, EDC4, PALB2, IGFN1, and AGRN) were more frequently mutated in mBC as compared to eBC (FDR < 0.01). ESR1 was identified both as a driver and as a metastatic gene (n = 22, odds ratio = 29, 95% CI [9-155], p = 1.2e-12) and also presented with focal amplification (n = 9) for a total of 31 mBCs with either ESR1 mutation or amplification, including 27 hormone receptor positive (HR+) and HER2 negative (HER2-) mBCs (19%). HR+/HER2- mBC presented a high prevalence of mutations on genes located on the mechanistic target of rapamycin (mTOR) pathway (TSC1 and TSC2) as compared to HR+/HER2- eBC (respectively 6% and 0.7%, p = 0.0004). Other actionable genes were more frequently mutated in HR+ mBC, including ERBB4 (n = 8), NOTCH3 (n = 7), and ALK (n = 7). Analysis of mutational signatures revealed a significant increase in APOBEC-mediated mutagenesis in HR+/HER2- metastatic tumors as compared to primary TCGA samples (p < 2e-16). The main limitations of this study include the absence of bone metastases and the size of the cohort, which might not have allowed the identification of rare mutations and their effect on survival. CONCLUSIONS: This work reports the results of the analysis of the first large-scale study on mutation profiles of mBC. This study revealed genomic alterations and mutational signatures involved in the resistance to therapies, including actionable mutations.

Whole exome sequencing of rare aggressive breast cancer histologies.

Little is known about mutational landscape of rare breast cancer (BC) subtypes. The aim of the study was to apply next generation sequencing to three different subtypes of rare BCs in order to identify new genes related to cancer progression. We performed whole exome and targeted sequencing of 29 micropapillary, 23 metaplastic, and 27 pleomorphic lobular BCs. Micropapillary BCs exhibit a profile comparable to common BCs: PIK3CA, TP53, GATA3, and MAP2K4 were the most frequently mutated genes. Metaplastic BCs presented a high frequency of TP53 (78 %) and PIK3CA (48 %) mutations and were recurrently mutated on KDM6A (13 %), a gene involved in histone demethylation. Pleomorphic lobular carcinoma exhibited high mutation rate of PIK3CA (30 %), TP53 (22 %), and CDH1 (41 %) and also presented mutations in PYGM, a gene involved in glycogen metabolism, in 8 out of 27 samples (30 %). Further analyses of publicly available datasets showed that PYGM is dramatically underexpressed in common cancers as compared to normal tissues and that low expression in tumors is correlated with poor relapse-free survival. Immunohistochemical staining on formalin-fixed paraffin-embedded tissues available in our cohort of patients confirmed higher PYGM expression in normal breast tissue compared to equivalent tumoral zone. Next generation sequencing methods applied on rare cancer subtypes can serve as a useful tool in order to uncover new potential therapeutic targets. Sequencing of pleomorphic lobular carcinoma identified a high rate of alterations in PYGM. These findings emphasize the role of glycogen metabolism in cancer progression.

Interrogation of a context-specific transcription factor network identifies novel regulators of pluripotency.

The predominant view of pluripotency regulation proposes a stable ground state with coordinated expression of key transcription factors (TFs) that prohibit differentiation. Another perspective suggests a more complexly regulated state involving competition between multiple lineage-specifying TFs that define pluripotency. These contrasting views were developed from extensive analyses of TFs in pluripotent cells in vitro. An experimentally validated, genome-wide repertoire of the regulatory interactions that control pluripotency within the in vivo cellular contexts is yet to be developed. To address this limitation, we assembled a TF interactome of adult human male germ cell tumors (GCTs) using the Algorithm for the Accurate Reconstruction of Cellular Pathways (ARACNe) to analyze gene expression profiles of 141 tumors comprising pluripotent and differentiated subsets. The network (GCT(Net)) comprised 1,305 TFs, and its ingenuity pathway analysis identified pluripotency and embryonal development as the top functional pathways. We experimentally validated GCT(Net) by functional (silencing) and biochemical (ChIP-seq) analysis of the core pluripotency regulatory TFs POU5F1, NANOG, and SOX2 in relation to their targets predicted by ARACNe. To define the extent of the in vivo pluripotency network in this system, we ranked all TFs in the GCT(Net) according to sharing of ARACNe-predicted targets with those of POU5F1 and NANOG using an odds-ratio analysis method. To validate this network, we silenced the top 10 TFs in the network in H9 embryonic stem cells. Silencing of each led to downregulation of pluripotency and induction of lineage; 7 of the 10 TFs were identified as pluripotency regulators for the first time.

ETV4 promotes metastasis in response to activation of PI3-kinase and Ras signaling in a mouse model of advanced prostate cancer.

Combinatorial activation of PI3-kinase and RAS signaling occurs frequently in advanced prostate cancer and is associated with adverse patient outcome. We now report that the oncogenic Ets variant 4 (Etv4) promotes prostate cancer metastasis in response to coactivation of PI3-kinase and Ras signaling pathways in a genetically engineered mouse model of highly penetrant, metastatic prostate cancer. Using an inducible Cre driver to simultaneously inactivate Pten while activating oncogenic Kras and a fluorescent reporter allele in the prostate epithelium, we performed lineage tracing in vivo to define the temporal and spatial occurrence of prostate tumors, disseminated tumor cells, and metastases. These analyses revealed that though disseminated tumors cells arise early following the initial occurrence of prostate tumors, there is a significant temporal lag in metastasis, which is temporally coincident with the up-regulation of Etv4 expression in primary tumors. Functional studies showed that knockdown of Etv4 in a metastatic cell line derived from the mouse model abrogates the metastatic phenotype but does not affect tumor growth. Notably, expression and activation of ETV4, but not other oncogenic ETS genes, is correlated with activation of both PI3-kinase and Ras signaling in human prostate tumors and metastases. Our findings indicate that ETV4 promotes metastasis in prostate tumors that have activation of PI3-kinase and Ras signaling, and therefore, ETV4 represents a potential target of therapeutic intervention for metastatic prostate cancer.

Practical guidelines for the comprehensive analysis of ChIP-seq data.

Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.

MeCP2 regulates ethanol sensitivity and intake.

We have investigated the expression of chromatin-regulating genes in the prefrontal cortex and in the shell subdivision of the nucleus accumbens during protracted withdrawal in mice with increased ethanol drinking after chronic intermittent ethanol (CIE) vapor exposure and in mice with a history of non-dependent drinking. We observed that the methyl-CpG binding protein 2 (MeCP2) was one of the few chromatin-regulating genes to be differentially regulated by a history of dependence. As MeCP2 has the potential of acting as a broad gene regulator, we investigated sensitivity to ethanol and ethanol drinking in MeCP2(308/) (Y) mice, which harbor a truncated MeCP2 allele but have a milder phenotype than MeCP2 null mice. We observed that MeCP2(308/) (Y) mice were more sensitive to ethanol's stimulatory and sedative effects than wild-type (WT) mice, drank less ethanol in a limited access 2 bottle choice paradigm and did not show increased drinking after induction of dependence with exposure to CIE vapors. Alcohol metabolism did not differ in MeCP2(308/) (Y) and WT mice. Additionally, MeCP2(308/) (Y) mice did not differ from WT mice in ethanol preference in a 24-hour paradigm nor in their intake of graded solutions of saccharin or quinine, suggesting that the MeCP2(308/) (Y) mutation did not alter taste function. Lastly, using the Gene Set Enrichment Analysis algorithm, we found a significant overlap in the genes regulated by alcohol and by MeCP2. Together, these results suggest that MeCP2 contributes to the regulation of ethanol sensitivity and drinking.

Transforming drug discovery with a high-throughput AI-powered platform: A 5-year experience with Patrimony.

High-throughput computational platforms are being established to accelerate drug discovery. Servier launched the Patrimony platform to harness computational sciences and artificial intelligence (AI) to integrate massive multimodal data from internal and external sources. Patrimony has enabled researchers to prioritize therapeutic targets based on a deep understanding of the pathophysiology of immuno-inflammatory diseases. Herein, we share our experience regarding main challenges and critical success factors faced when industrializing the platform and broadening its applications to neurological diseases. We emphasize the importance of integrating such platforms in an end-to-end drug discovery process and engaging human experts early on to ensure a transforming impact.

Characterization of CD4+ and CD8+ T cells responses in the mixed lymphocyte reaction by flow cytometry and single cell RNA sequencing.

Background: The Mixed Lymphocyte Reaction (MLR) consists in the allogeneic co-culture of monocytes derived dendritic cells (MoDCs) with T cells from another donor. This in vitro assay is largely used for the assessment of immunotherapy compounds. Nevertheless, the phenotypic changes associated with lymphocyte responsiveness under MLR have never been thoroughly evaluated. Methods: Here, we used multiplex cytokine and chemokine assays, multiparametric flow cytometry and single cell RNA sequencing to deeply characterize T cells activation and function in the context of CD4+- and CD8+-specific MLR kinetics. Results: We showed that CD4+ and CD8+ T cells in MLR share common classical markers of response such as polyfunctionality, increased proliferation and CD25 expression but differ in their kinetics and amplitude of activation as well as their patterns of cytokines secretion and immune checkpoints expression. The analysis of immunoreactive Ki-67+CD25+ T cells identified PBK, LRR1 and MYO1G as new potential markers of MLR response. Using cell-cell communication network inference and pathway analysis on single cell RNA sequencing data, we also highlighted key components of the immunological synapse occurring between T cells and the stimulatory MoDCs together with downstream signaling pathways involved in CD4+ and CD8+ T cells activation. Conclusion: These results provide a deep understanding of the kinetics of the MLR assay for CD4+ or CD8+ T cells and may allow to better characterize compounds impacting MLR and eventually identify new strategies for immunotherapy in cancer.

Uterine perforation by a cystoperitoneal shunt, an unusual cause of recurrent vaginal discharge.

BACKGROUND: We describe the first reported case of uterine perforation by a cystoperitoneal shunt. The mechanism of this unusual complication is unclear. CASE: A 17-year-old patient had a cystoperitoneal shunt for a porencephalic cyst. She presented with recurrent watery vaginal discharge. A pelvic ultrasound examination showed that the uterus had been perforated by the distal tip of the shunt. The cystoperitoneal shunt was converted to a ventriculo-atrial shunt, and the vaginal discharge subsequently resolved. CONCLUSION: The appearance of light and clear vaginal discharge in a patient with a cystoperitoneal shunt raises the possibility of uterine perforation. This can be confirmed by ultrasound and analysis of the discharge. Removal of the shunt leads to spontaneous closure of the uterine defect.

Escalated (Dependent) Oxycodone Self-Administration Is Associated with Cognitive Impairment and Transcriptional Evidence of Neurodegeneration in Human Immunodeficiency Virus (HIV) Transgenic Rats.

Substance use disorder is associated with accelerated disease progression in people with human immunodeficiency virus (HIV; PWH). Problem opioid use, including high-dose opioid therapy, prescription drug misuse, and opioid abuse, is high and increasing in the PWH population. Oxycodone is a broadly prescribed opioid in both the general population and PWH. Here, we allowed HIV transgenic (Tg) rats and wildtype (WT) littermates to intravenously self-administer oxycodone under short-access (ShA) conditions, which led to moderate, stable, "recreational"-like levels of drug intake, or under long-access (LgA) conditions, which led to escalated (dependent) drug intake. HIV Tg rats with histories of oxycodone self-administration under LgA conditions exhibited significant impairment in memory performance in the novel object recognition (NOR) paradigm. RNA-sequencing expression profiling of the medial prefrontal cortex (mPFC) in HIV Tg rats that self-administered oxycodone under ShA conditions exhibited greater transcriptional evidence of inflammation than WT rats that self-administered oxycodone under the same conditions. HIV Tg rats that self-administered oxycodone under LgA conditions exhibited transcriptional evidence of an increase in neuronal injury and neurodegeneration compared with WT rats under the same conditions. Gene expression analysis indicated that glucocorticoid-dependent adaptations contributed to the gene expression effects of oxycodone self-administration. Overall, the present results indicate that a history of opioid intake promotes neuroinflammation and glucocorticoid dysregulation, and excessive opioid intake is associated with neurotoxicity and cognitive impairment in HIV Tg rats.

Industrializing AI-powered drug discovery: lessons learned from the Patrimony computing platform.

INTRODUCTION: As a mid-size international pharmaceutical company, we initiated 4 years ago the launch of a dedicated high-throughput computing platform supporting drug discovery. The platform named 'Patrimony' was built up on the initial predicate to capitalize on our proprietary data while leveraging public data sources in order to foster a Computational Precision Medicine approach with the power of artificial intelligence. AREAS COVERED: Specifically, Patrimony is designed to identify novel therapeutic target candidates. With several successful use cases in immuno-inflammatory diseases, and current ongoing extension to applications to oncology and neurology, we document how this industrial computational platform has had a transformational impact on our R&D, making it more competitive, as well time and cost effective through a model-based educated selection of therapeutic targets and drug candidates. EXPERT OPINION: We report our achievements, but also our challenges in implementing data access and governance processes, building up hardware and user interfaces, and acculturing scientists to use predictive models to inform decisions.

A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers.

Assembly of a transcriptional and post-translational molecular interaction network in B cells, the human B-cell interactome (HBCI), reveals a hierarchical, transcriptional control module, where MYB and FOXM1 act as synergistic master regulators of proliferation in the germinal center (GC). Eighty percent of genes jointly regulated by these transcription factors are activated in the GC, including those encoding proteins in a complex regulating DNA pre-replication, replication, and mitosis. These results indicate that the HBCI analysis can be used for the identification of determinants of major human cell phenotypes and provides a paradigm of general applicability to normal and pathologic tissues.

Central nervous system (CNS) transcriptomic correlates of human immunodeficiency virus (HIV) brain RNA load in HIV-infected individuals.

To generate new mechanistic hypotheses on the pathogenesis and disease progression of neuroHIV and identify novel therapeutic targets to improve neuropsychological function in people with HIV, we investigated host genes and pathway dysregulations associated with brain HIV RNA load in gene expression profiles of the frontal cortex, basal ganglia, and white matter of HIV+ patients. Pathway analyses showed that host genes correlated with HIV expression in all three brain regions were predominantly related to inflammation, neurodegeneration, and bioenergetics. HIV RNA load directly correlated particularly with inflammation genesets representative of cytokine signaling, and this was more prominent in white matter and the basal ganglia. Increases in interferon signaling were correlated with high brain HIV RNA load in the basal ganglia and the white matter although not in the frontal cortex. Brain HIV RNA load was inversely correlated with genesets that are indicative of neuronal and synaptic genes, particularly in the cortex, indicative of synaptic injury and neurodegeneration. Brain HIV RNA load was inversely correlated with genesets that are representative of oxidative phosphorylation, electron transfer, and the tricarboxylic acid cycle in all three brain regions. Mitochondrial dysfunction has been implicated in the toxicity of some antiretrovirals, and these results indicate that mitochondrial dysfunction is also associated with productive HIV infection. Genes and pathways correlated with brain HIV RNA load suggest potential therapeutic targets to ameliorate neuropsychological functioning in people living with HIV.

Increases in compulsivity, inflammation, and neural injury in HIV transgenic rats with escalated methamphetamine self-administration under extended-access conditions.

The abuse of stimulants, such as methamphetamine (METH), is associated with treatment non-compliance, a greater risk of viral transmission, and the more rapid clinical progression of immunological and central nervous system human immunodeficiency virus (HIV) disease. The behavioral effects of METH in the setting of HIV remain largely uncharacterized. We used a state-of-the-art paradigm of the escalation of voluntary intravenous drug self-administration in HIV transgenic (Tg) and wildtype rats. The rats were first allowed to self-administer METH under short-access (ShA) conditions, which is characterized by a nondependent and more "recreational" pattern of METH use, and then allowed to self-administer METH under long-access (LgA) conditions, which leads to compulsive (dependent) METH intake. HIV Tg and wildtype rats self-administered equal amounts of METH under ShA conditions. HIV Tg rats self-administered METH under LgA conditions following a 4-week enforced abstinence period to model the intermittent pattern of stimulant abuse in humans. These HIV Tg rats developed greater motivation to self-administer METH and self-administered larger amounts of METH. Impairments in function of the medial prefrontal cortex (mPFC) contribute to compulsive drug and alcohol intake. Gene expression profiling of the mPFC in HIV Tg rats with a history of escalated METH self-administration under LgA conditions showed transcriptional evidence of increased inflammation, greater neural injury, and impaired aerobic glucose metabolism than wildtype rats that self-administered METH under LgA conditions. The detrimental effects of the interaction between neuroHIV and escalated METH intake on the mPFC are likely key factors in the greater vulnerability to excessive drug intake in the setting of HIV.

An Accessible and Unique Insight into Metastasis Mutational Content Through Whole-exome Sequencing of Circulating Tumor Cells in Metastatic Prostate Cancer.

BACKGROUND: Genomic analysis of circulating tumor cells (CTCs) could provide a unique and accessible representation of tumor diversity but remains hindered by technical challenges associated with CTC rarity and heterogeneity. OBJECTIVE: To evaluate CTCs as surrogate samples for genomic analyses in metastatic castration-resistant prostate cancer (mCRPC). DESIGN, SETTING, AND PARTICIPANTS: Three isolation strategies (filter laser-capture microdissection, self-seeding microwell chips, and fluorescence-activated cell sorting) were developed to capture CTCs with various epithelial and mesenchymal phenotypes and isolate them at the single-cell level. Whole-genome amplification (WGA) and WGA quality control were performed on 179 CTC samples, matched metastasis biopsies, and negative controls from 11 patients. All patients but one were pretreated with enzalutamide or abiraterone. Whole-exome sequencing (WES) of 34 CTC samples, metastasis biopsies, and negative controls were performed for seven patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: WES of CTCs was rigorously qualified in terms of percentage coverage at 10× depth, allelic dropout, and uncovered regions. Shared somatic mutations between CTCs and matched metastasis biopsies were identified. A customized approach based on determination of mutation rates for CTC samples was developed for identification of CTC-exclusive mutations. RESULTS AND LIMITATIONS: Shared mutations were mostly detected in epithelial CTCs and were recurrent. For two patients for whom a deeper analysis was performed, a few CTCs were sufficient to represent half to one-third of the mutations in the matched metastasis biopsy. CTC-exclusive mutations were identified in both epithelial and nonepithelial CTCs and affected cytoskeleton, invasion, DNA repair, and cancer-driver genes. Some 41% of CTC-exclusive mutations had a predicted deleterious impact on protein function. Phylogenic relationships between CTCs with distinct phenotypes were evidenced. CONCLUSIONS: CTCs can provide unique insight into metastasis mutational diversity and reveal undiagnosed genomic aberrations in matched metastasis biopsies. PATIENT SUMMARY: Our results demonstrate the clinical potential of circulating tumor cells to provide insight into metastatic events that could be critical to target using precision medicine.