Biology subjects

Sharma, A.

Publications and source records attributed to Sharma, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Immune-cell depleted diffuse large B-cell lymphomas have reduced expression of MHC class I

Immunotherapy has transformed treatment for many cancers. In the aggressive and genetically heterogeneous diffuse large B-cell lymphoma (DLBCL), CD19 CAR T-cell therapy is highly effective, whereas immune checkpoint blockade has shown limited benefit. Loss of MHC expression is a common mechanism to escape T-cell cytotoxicity, and loss of MHC class I (MHC-I) and II are frequent in DLBCL. We applied imaging mass cytometry to diagnostic biopsies from younger, high-risk DLBCL patients to map the tumor microenvironment (TME) spatial architecture in relation to tumor cell MHC expression, mutational status, transcriptomic and proteomic profiles. Neighborhood analyses identified four TME subtypes: immune-cell depleted and three immune-infiltrated types (mixed, CD4 T cell-rich, CD8 T-cell/macrophage-rich). Depleted cases had shorter overall survival (p = 0.033) and increased expression of proteins involved in DNA replication and proliferation markers compared to infiltrated cases. Tumor cell MHC-I expression was heterogeneous. Cases with low frequency of MHC-I-pos tumor cells were enriched for the depleted TME type. MHC-I-pos tumor cells were surrounded by CD4 and CD8 T cells and M1 macrophages, whereas MHC-I-neg tumor cells were closer to other MHC-I-neg tumor cells. These findings suggest that TME-based classification incorporating tumor cell MHC-I status may improve individualized immunotherapy selection.

cancer biology↗

bioRxiv2026

Functional Contribution of Multienzyme Glucosome Condensates to Cellular Redox Homeostasis in Cancer Cells

Glucosomes are liquid-liquid phase-separated condensates observed in human cells, formed by phosphofructokinase and other rate-determining enzymes in glycolysis and gluconeogenesis. While glucosomes are spatially formed into small-, medium-, and large-sized assemblies in cancer cells, medium-sized glucosomes are functionally characterized to shunt glucose flux to the pentose phosphate pathway (PPP). As the PPP is the primary pathway responsible for maintaining cytosolic NADPH levels during oxidative stress, we hypothesize that medium-sized glucosomes regulate cellular redox homeostasis through the promotion of the PPP. In this work, we started treating Hs578T cells with hydrogen peroxide (H2O2) to evaluate how glucosomes respond to redox perturbation. High-content imaging demonstrated that H2O2 significantly promotes medium-sized glucosomes at both single-cell and population levels. The extracellular acidification rate by Seahorse extracellular flux analysis then corroborated that H2O2 effectively diverts glycolytic flux to the PPP through the upregulation of medium-sized glucosomes. We then investigated the glutathione redox cycle as a potential mechanistic link between medium-sized glucosomes and H2O2 detoxification. Treatment with oxidized glutathione (GSSG), but not reduced glutathione (GSH), markedly increased the population of cells showing medium-sized glucosomes. Moreover, shRNA-mediated knockdown of glutathione reductase, which converts GSSG to GSH at the expense of NADPH, attenuated H2O2-induced glucosome formation in Hs578T cells. Collectively, we demonstrate that glucosome-mediated metabolic reprogramming couples glucose metabolism to the glutathione redox cycle to facilitate H2O2 detoxification, thereby establishing the functional role of glucosomes in cellular redox homeostasis.

cell biology↗

bioRxiv2018

Integration of Molecular Interactome and Targeted Interaction Analysis to Identify a COPD Disease Network Module

The polygenic nature of complex diseases offers potential opportunities to utilize network-based approaches that leverage the comprehensive set of protein-protein interactions (the human interactome) to identify new genes of interest and relevant biological pathways. However, the incompleteness of the current human interactome prevents it from reaching its full potential to extract network-based knowledge from gene discovery efforts, such as genome-wide association studies, for complex diseases like chronic obstructive pulmonary disease (COPD). Here, we provide a framework that integrates the existing human interactome information with new experimental protein-protein interaction data for FAM13A, one of the most highly associated genetic loci to COPD, to find a more comprehensive disease network module. We identified an initial disease network neighborhood by applying a random-walk method. Next, we developed a network-based closeness approach (CAB) that revealed 9 out of 96 FAM13A interacting partners identified by affinity purification assays were significantly close to the initial network neighborhood. Moreover, compared to a similar method (local radiality), the CAB approach predicts low-degree genes as potential candidates. The candidates identified by the network-based closeness approach were combined with the initial network neighborhood to build a comprehensive disease network module (163 genes) that was enriched with genes differentially expressed between controls and COPD subjects in alveolar macrophages, lung tissue, sputum, blood, and bronchial brushing datasets. Overall, we demonstrate an approach to find disease-related network components using new laboratory data to overcome incompleteness of the current interactome.

systems biology↗

bioRxiv2018

Gut microbial features can predict host phenotype response to protein deficiency

Malnutrition remains a major health problem in low and middle income countries. During low protein intake, < 0.67 g/kg/day, there is a loss of nitrogen (N2) balance, due to the unavailability of amino acid for metabolism and unbalanced protein catabolism results. However, there are individuals, who consume the same low protein intake, and preserve N2 balance for unknown reasons. A novel factor, the gut microbiota, may account for these N2 balance differences. To investigate this, we correlated gut microbial profiles with the growth of four murine strains (C57Bl6/J, CD-1, FVB, and NIH-Swiss) on protein deficient (PD) diet. Results show that a PD diet exerts a strain-dependent impact on growth and N2 balance as determined through analysis of urinary urea, ammonia and creatinine excretion. Bacterial alpha diversity was significantly (p < 0.05, FDR) lower across all strains on a PD diet compared to normal chow (NC). Multi-group analyses of the composition of microbiomes (ANCOM) revealed significantly differential microbial signatures between the four strains independent of diet. However, mice on a PD diet demonstrated differential enrichment of bacterial genera including, Allobaculum (C57Bl6/J), Parabacteroides (CD-1), Turicibacter (FVB), and Mucispirillum (NIH-Swiss) relative to NC. Additionally, statistical model fitting revealed that the relative abundance of genera such as Bifidobacterium, Ruminococcus, and Lactobacillus were significantly positively correlated with body weight, while Anaerofustis, Roseburia, and Bilophila were significantly positively correlated with ammonia excretion. Taken together, these results suggest a potential relationship between the specific gut microbiota, N2 balance and animal response to malnutrition.

physiology↗

bioRxiv2018

LRRK2 kinase inhibitors induce a reversible effect in the lungs of non-human primates with no measurable pulmonary deficits

Putative gain-of-function mutations in leucine-rich repeat kinase 2 (LRRK2), resulting in increased kinase activity and cellular toxicity, are a leading genetic cause of Parkinsons disease (PD). Hence, there is strong interest in developing LRRK2 kinase inhibitors as a disease-modifying therapy. Published reports that repeat dosing with two LRRK2 kinase inhibitors (GNE-7915 and GNE-0877) induce histopathological changes in the lung of non-human primates Fuji et al. 2015 (1) raised concerns about potential safety liability of LRRK2 kinase inhibitors. In the present study, we sought to determine whether previously observed effects in the lung: (a) represent on-target pharmacology, but with the potential for margin of safety, (b) are reversible upon drug withdrawal, and (c) are associated with pulmonary function deficits. To this end, we evaluated the histopathological effects, toxicokinetics and target inhibition of three structurally diverse LRRK2 kinase inhibitors, GNE-7915 (30 mg/kg, BID, as a positive control), MLi-2 (15 and 50 mg/kg, QD) and PFE-360 (3 and 6 mg/kg, QD) following 2 weeks of dosing in non-human primates. Subsets of animals dosed with GNE-7915 or MLi-2 were evaluated after 2-week dose-free periods. All three LRRK2 kinase inhibitors induced mild cytoplasmic vacuolation of type II pneumocytes, as reported previously, confirming an on-target effect of these compounds. Interestingly, despite lower doses of both PFE-360 and MLi-2 producing nearly complete inhibition of LRRK2 kinase activity in the brain as assessed by levels of pS935-LRRK2, histopathological changes in lung were absent in animals treated with low-dose PFE-360 and observed only sporadically in the low-dose MLi-2 group. The lung effect was fully reversible at 2 weeks post-dosing of GNE-7915. In a second study of identical dosing with MLi-2 and GNE-7915, no deficits were observed in a battery of translational pulmonary functional tests. In aggregate, these results do not preclude the development of LRRK2 kinase inhibitors for clinical investigation in Parkinsons disease.

pharmacology and toxicology↗

bioRxiv2018

Chicago and Dovetail Hi-C proximity ligation yield chromosome length scaffolds of Ixodes scapularis genome

A high-quality genome sequence is essential for understanding an organism on molecular level. However, the larger genomes with substantial repetitive sequences are challenging to assemble with the sequencing technologies. Hi-C technique is changing the genome architecture landscape by providing links across a variety of length scales, spanning even whole chromosomes. Ixodes scapularis haploid genome is 2.1 gbp and the current assembly consists of 369,495 scaffolds representing 57% of the genome. The fragmented genome poses challenges with functional gene analysis and an improved assembly is needed. We therefore used the Hi C technique to achieve chromosomal level assembly of tick genome. With Chicago and Dovetail Hi C assemblies, we were able to achieve 28 >10Mb sequences that correspond to 28 chromosomes in I. scapularis.

genomics↗

bioRxiv2018

A conserved role of the insulin-like signaling pathway in uric acid pathologies revealed in Drosophila melanogaster

Elevated uric acid (UA) is a key factor for disorders, including gout or kidney stones and result from abrogated expression of Urate Oxidase (Uro) and diet. To understand the genetic pathways influencing UA metabolism we established a Drosophila melanogaster model with elevated UA using Uro knockdown. Reduced Uro expression resulted in the accumulation of UA concretions and diet-dependent shortening of lifespan. Inhibition of insulin-like signaling (ILS) pathway genes reduced UA and concretion load. In humans, SNPs in the ILS genes AKT2 and FOXO3 were associated with UA levels or gout, supporting a conserved role for ILS in modulating UA metabolism. Downstream of the ILS pathway UA pathogenicity was mediated partly by NADPH Oxidase, whose inhibition attenuated the reduced lifespan and concretion accumulation. Thus, genes in the ILS pathway represent potential therapeutic targets for treating UA associated pathologies, including gout and kidney stones.\n\nHighlightsO_LIIn Drosophila high uric acid (UA) levels shorten lifespan and cause UA aggregation\nC_LIO_LIConserved in flies and humans, the ILS pathway associates with UA pathologies\nC_LIO_LIFoxO dampens concretion formation by reducing UA levels and ROS formation\nC_LIO_LIInhibition of NOX alleviates the lifespan attenuation and UA aggregation\nC_LI

pathology↗

bioRxiv2018

Temporal Multiple Kernel Learning (tMKL) model for predicting resting state FC via characterizing fMRI connectivity dynamics

Over the last decade there has been growing interest in understanding the brain activity in the absence of any task or stimulus captured by the resting-state functional magnetic resonance imaging (rsfMRI). These resting state patterns are not static, but exhibit complex spatio-temporal dynamics. In the recent years substantial effort has been put to characterize different FC configurations while brain states makes transitions over time. The dynamics governing this transitions and their relationship with stationary functional connectivity remains elusive. Over the last years a multitude of methods has been proposed to discover and characterize FC dynamics and one of the most accepted method is sliding window approach. Moreover, as these FC configurations are observed to be cyclically repeating in time there was further motivation to use of a generic clustering scheme to identify latent states of dynamics. We discover the underlying lower-dimensional manifold of the temporal structure which is further parameterized as a set of local density distributions, or latent transient states. We propose an innovative method that learns parameters specific to these latent states using a graph-theoretic model (temporal Multiple Kernel Learning, tMKL) and finally predicts the grand average functional connectivity (FC) of the unseen subjects by leveraging a state transition Markov model. tMKL thus learns a mapping between the underlying anatomical network and the temporal structure. Training and testing were done using the rs-fMRI data of 46 healthy participants and the results establish the viability of the proposed solution. Parameters of the model are learned via state-specific optimization formulations and yet the model performs at par or better than state-of-the-art models for predicting the grand average FC. Moreover, the model shows sensitivity towards subject-specific anatomy. The proposed model performs significantly better than the established models of predicting resting state functional connectivity based on whole-brain dynamic mean-field model, single diffusion kernel model and another version of multiple kernel learning model. In summary, We provide a novel solution that does not make strong assumption about underlying data and is generally applicable to resting or task data to learn subject specific state transitions and successful characterization of SC-dFC-FC relationship through an unifying framework.

neuroscience↗

bioRxiv2018

Structural basis for cholesterol transport-like activity of the Hedgehog receptor Patched

Hedgehog protein signals mediate tissue patterning and maintenance via binding to and inactivation of their common receptor Patched, a twelve-transmembrane protein that otherwise would suppress activity of the seven-transmembrane protein, Smoothened. Loss of Patched function, the most common cause of basal cell carcinoma, permits unregulated activation of Smoothened and of the Hedgehog pathway. A cryo-EM structure of the Patched protein reveals striking transmembrane domain similarities to prokaryotic RND transporters. The extracellular domain mediates association of Patched monomers in an unusual dimeric architecture that implies curvature in the associated membrane. A central conduit with cholesterol-like contents courses through the extracellular domain and resembles that used by other RND proteins to transport substrates, suggesting Patched activity in cholesterol transport. Patched expression indeed reduces cholesterol activity in the inner leaflet of the plasma membrane, in a manner antagonized by Hedgehog stimulation and with implications for regulation of Smoothened.

biophysics↗

bioRxiv2018

Regulation of transcription factor SP1 by β-catenin destruction complex modulates Wnt response

The ubiquitous transcription factor Specificity protein 1 (SP1) is heavily modified post-translationally. These modifications are critical for switching its functions and modulation of its transcriptional activity, DNA-binding and stability. However the mechanism governing the stability of SP1 by cellular signaling pathways is not well understood. Here, we provide biochemical and functional evidences that SP1 is an integral part of the Wnt signaling pathway. We identified a phosphodegron motif in SP1 that is specific to mammals. In absence of Wnt signaling, GSK3{beta} kinase mediated phosphorylation and {beta}-TrCP E3 ubiquitin ligase mediated ubiquitination is required to induce SP1 degradation. When Wnt signaling is on, SP1 is stabilized in {beta}-catenin-dependent manner. SP1 directly interacts with {beta}-catenin and Wnt signaling induces the stabilization of SP1 by impeding its interaction with {beta}-TrCP and AXIN1, components of the destruction complex. Wnt signaling suppresses ubiquitination and subsequent proteosomal degradation of SP1. Furthermore, SP1 regulates Wnt-dependent stability of {beta}-catenin and their mutual stabilization is critical for target gene expression, suggesting a feedback mechanism. Upon stabilization SP1 and {beta}-catenin co-occupy the promoters of TCFL2/{beta}-catenin target genes. Collectively, this study uncovers a direct link between SP1 and {beta}-catenin in Wnt signaling pathway.

molecular biology↗

bioRxiv2018

sFlt-1 commutes unfolded protein response into endoplasmic reticulum stress in trophoblast cells in preeclamptic pregnancies

Preeclampsia (PE) and its subtypes (early and late onset) are serious concerns all across the globe affecting about 8% of total pregnancies and accounts for approximately 60,000 deaths annually with a predominance in developing under-developed and countries. The two-stage model in the progression of this disease, deficient spiral artery remodelling and an imbalance between angiogenic (VEGF) and anti-antigenic factor(s) (sFlt-1) are well established facts pertaining to this disease. The presence of increased sFlt-1, high oxidative stress and Endoplasmic reticulum stress (ER stress) have been proposed in preeclamptic pregnancies. Recently, the role of endoplasmic reticulum stress in the onset of the variant forms of PE highlighted a new window to explore further. In our previous studies, we demonstrated that sFlt-1 can induce apoptosis and oxidative stress in trophoblast cells. However the role of sFlt-1, in inducing ER stress is not known so far. In the present study, we for the first time demonstrated significant ER stress in the placental cells (BeWo Cells) (in vitro) when exposed to sera from preeclamptic pregnancies having increased concentration of sFlt-1. The expression of ER stress markers (GRP78, eIF2, XBP1, ATF6 and CHOP) at both transcript and protein levels were compared (between preeclamptic and normotensive non-proteinuric women) at three different time points (8h, 14h and 24hrs), analyzed and found to be significant (p<0.05).\n\nConclusionOur results suggested that sFlt-1, released from placental cells in preeclampsia may be one of the various factors having potential to induce endoplasmic reticulum stress in BeWo cells.

developmental biology↗

bioRxiv2018

Myosin Heavy Chain-embryonic is a crucial regulator of skeletal muscle development and differentiation.

Myosin heavy chains (MyHCs) are contractile proteins that are part of the thick filaments of the functional unit of the skeletal muscle, the sarcomere. In addition to MyHCs that are part of the adult muscle contractile network, two MyHCs - MyHC-embryonic and -perinatal are expressed during muscle development and are only transiently expressed in the adult during regeneration. The functions performed by these MyHCs has been a long-standing question and using a targeted mouse allele, we have characterized the role of MyHC-embryonic. Analysis of loss-of-function mice reveals that lack of MyHC-embryonic leads to mis-regulation of other MyHCs, alterations in fiber size, fiber number and fiber type at neonatal stages. We also find that loss of MyHC-embryonic leads to mis-regulation of genes involved in muscle differentiation. A broad theme from these studies is that loss of MyHC-embryonic has distinct effects on different muscles, possibly reflecting the unique fiber type composition of different muscles. Most significantly, our results indicate that MyHC-embryonic is required during embryonic and fetal myogenesis to regulate myogenic progenitor and myoblast differentiation in a non-cell autonomous manner via Mitogen Activated Protein Kinase (MAPKinase) and Fibroblast Growth Factor (FGF) signaling. Thus, our results signify that MyHC-embryonic is a key regulator of myogenic differentiation during embryonic, fetal and neonatal myogenesis.

developmental biology↗

bioRxiv2018

A simple genetic basis for managing maternally transmitted symbionts

Maternal transmission of intracellular microbes is pivotal in establishing long-term, intimate symbioses. For germline microbes that exert negative reproductive effects on their hosts, selection can theoretically favor the spread of host genes that counteract the microbes harmful effects. Here, we leverage a major difference in bacterial (Wolbachia pipientis) titers between closely-related wasp species with forward genetic, transcriptomic, and cytological approaches to map two quantitative trait loci that suppress bacterial titers via a maternal effect. Fine mapping and knockdown experiments identify the gene Wolbachia density suppressor (Wds), which dominantly suppresses bacterial transmission from mother to embryo. Wds evolved by lineage-specific non-synonymous changes driven by positive selection. Collectively, our findings demonstrate that a genetically simple change arose by Darwinian selection in less than a million years to regulate maternally transmitted bacteria via a dominant, maternal effect gene.

evolutionary biology↗

bioRxiv2017

sFlt-1 (sVEGFR1) induces placental endoplasmic reticulum stress in trophoblast cell: implications for the complications in preeclampsia - an in vitro study

BackgroundThe concentration of sFlt-1, a major anti-angiogenic protein in maternal circulation has been seen to be raised in preeclamptic pregnancies. Endoplasmic reticulum (ER) stress represents one of the three (immunological, oxidative and ER stress) major stresses which placenta undergoes during pregnancies. The present study is designed to investigate the role of sFlt-1 in induction of ER stress in trophoblast cells.\n\nMaterials and MethodsMaternal serum levels of anti-angiogenic protein sFlt-1 and central regulator of unfolded protein response GRP78 was measured using sandwich ELISA. The expression of various ER stress markers (GRP78, eIF2, XBP1, ATF6 and apoptotic protein CHOP) were analyzed depending on various treatments given to the trophoblast cells using Immunofluorescence, western blot and q-RT PCR.\n\nResultsIncreased expression of ER stress markers (GRP78, eIF2, XBP1 ATF6 and apoptotic protein CHOP) was detected in the placental trophoblast cells treated with raised concentration of sFlt-1.\n\nConclusionSignificant upregulated expression of ER stress markers in trophoblast cells exposed with increased concentration of sFlt-1 suggested that it may be one of the anti-angiogenic factors present in maternal sera which not only contributes to oxidative stress but also may cause endoplasmic reticulum stress.

developmental biology↗

bioRxiv2017

Diminished Cortical Thickness is Associated with Impulsive Choice in Adolescence

Adolescence is characterized by both maturation of brain structure and increased risk of negative outcomes from behaviors associated with impulsive decision-making. One important index of impulsive choice is delay discounting (DD), which measures the tendency to prefer smaller rewards available soon over larger rewards delivered after a delay. However, it remains largely unknown how individual differences in structural brain development may be associated with impulsive choice during adolescence. Leveraging a unique large sample of 427 human youths (208 males and 219 females) imaged as part of the Philadelphia Neurodevelopmental Cohort, we examined associations between delay discounting and cortical thickness within structural covariance networks. These structural networks were derived using non-negative matrix factorization, an advanced multivariate technique for dimensionality reduction, and analyzed using generalized additive models with penalized splines to capture both linear and nonlinear developmental effects. We found that impulsive choice, as measured by greater discounting, was most strongly associated with diminished cortical thickness in structural brain networks that encompassed the ventromedial prefrontal cortex, orbitofrontal cortex, temporal pole, and temporoparietal junction. Furthermore, structural brain networks predicted DD above and beyond cognitive performance. Taken together, these results suggest that reduced cortical thickness in regions known to be involved in value-based decision-making is a marker of impulsive choice during the critical period of adolescence.\n\nSIGNIFICANCERisky behaviors during adolescence, such as initiation of substance use or reckless driving, are a major source of morbidity and mortality. In this study, we present evidence from a large sample of youths that diminished cortical thickness in specific structural brain networks is associated with impulsive choice. Notably, the strongest association between impulsive choice and brain structure was seen in regions implicated in value-based decision-making; namely, the ventromedial prefrontal and orbitofrontal cortices. Moving forward, such neuroanatomical markers of impulsivity may aid in the development of personalized interventions targeted to reduce risk of negative outcomes resulting from impulsivity during adolescence.

neuroscience↗

bioRxiv2017

Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates Type 2 Diabetes associated genes

Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p-values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study. We identified variants regulating gene expression (expression quantitative loci, eQTL) of HiCc pathway genes in islet samples. These eQTL genes showed higher levels of differential expression compared to non-eQTL genes in low, medium and high glucose concentrations in rat islets. Among genes with highly significant eQTL evidence, NFATC4 belonged to four HiCc pathways. We asked if the expressions of T2D-associated candidate genes from GWAS and literature are regulated by Nfatc4 in rat islets. Extensive in vitro silencing of Nfatc4 in rat islet cells displayed reduced expression of 16, and increased expression of 4 putative downstream T2D genes. Overall, our approach uncovers the mechanistic connection of NFATC4 with downstream targets including a previously unknown one, TCF7L2, and establishes the HiCc pathways relationship to T2D.

systems biology↗

bioRxiv2017

A systems approach to refine disease taxonomy by integrating phenotypic and molecular networks

The International Classification of Diseases (ICD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy.

bioinformatics↗

bioRxiv2017

Conserved patterns of somatic mutations in human peripheral blood cells

With growing interest in monitoring mutational processes in normal tissues, tumor heterogeneity, and cancer evolution under therapy, the ability to accurately and economically detect ultra-rare mutations is becoming increasingly important. However, this capability has often been compromised by significant sequencing, PCR and DNA preparation error rates. Here, we describe FERMI (Fast Extremely Rare Mutation Identification) - a novel method designed to eliminate majority of these sequencing and library preparation errors in order to significantly improve rare somatic mutation detection. This method leverages barcoded targeting probes to capture and sequence DNA of interest with single copy resolution. The variant calls from the barcoded sequencing data then further filtered in a position-dependent fashion against an adaptive, context-aware null model in order to distinguish true variants. As a proof of principle, we employ FERMI to probe bone marrow biopsies from leukemia patients, and show that rare mutations and clonal evolution can be tracked throughout cancer treatment, including during historically intractable periods like minimum residual disease. Importantly, FERMI is able to accurately detect nascent clonal expansions within leukemias in a manner that may facilitate the early detection and characterization of cancer relapse.

genetics↗