Biology subjects

Tu, X.

Publications and source records attributed to Tu, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Serial KinderMiner (SKiM) Discovers and Annotates Biomedical Knowledge Using Co-Occurrence and Transformer Models

BackgroundThe PubMed database contains more than 34 million articles; consequently, it is becoming increasingly difficult for a biomedical researcher to keep up-to-date with different knowledge domains. Computationally efficient and interpretable tools are needed to help researchers find and understand associations between biomedical concepts. The goal of literature-based discovery (LBD) is to connect concepts in isolated literature domains that would normally go undiscovered. This usually takes the form of an A-B-C relationship, where A and C terms are linked through a B term intermediate. Here we describe Serial KinderMiner (SKiM), an LBD algorithm for finding statistically significant links between an A term and one or more C terms through some B term intermediate(s). The development of SKiM is motivated by the the observation that there are only a few LBD tools that provide a functional web interface, and that the available tools are limited in one or more of the following ways: 1) they identify a relationship but not the type of relationship, 2) they do not allow the user to provide their own lists of B or C terms, hindering flexibility, 3) they do not allow for querying thousands of C terms (which is crucial if, for instance, the user wants to query connections between a disease and the thousands of available drugs), or 4) they are specific for a particular biomedical domain (such as cancer). We provide an open-source tool and web interface that improves on all of these issues. ResultsWe demonstrate SKiMs ability to discover useful A-B-C linkages in three control experiments: classic LBD discoveries, drug repurposing, and finding associations related to cancer. Furthermore, we supplement SKiM with a knowledge graph built with transformer machine-learning models to aid in interpreting the relationships between terms found by SKiM. Finally, we provide a simple and intuitive open-source web interface (https://skim.morgridge.org) with comprehensive lists of drugs, diseases, phenotypes, and symptoms so that anyone can easily perform SKiM searches. ConclusionsSKiM is a simple algorithm that can perform LBD searches to discover relationships between arbitrary user-defined concepts. SKiM is generalized for any domain, can perform searches with many thousands of C term concepts, and moves beyond the simple identification of an existence of a relationship; many relationships are given relationship type labels from our knowledge graph.

bioinformatics↗

bioRxiv2023

SMARCAD1 and TOPBP1 contribute to heterochromatin maintenance at the transition from the 2C-like to the pluripotent state

Chromocenters are established after the 2-cell (2C) stage during mouse embryonic development, but the factors that mediate chromocenter formation remain largely unknown. To identify regulators of 2C heterochromatin establishment, we generated an inducible system to convert embryonic stem cells (ESCs) to 2C-like cells. This conversion is marked by a global reorganization and dispersion of H3K9me3-heterochromatin foci, which are then reversibly formed upon re-entry into pluripotency. By profiling the chromatin-bound proteome (chromatome) through genome capture of ESCs transitioning to 2C-like cells, we uncover chromatin regulators involved in de novo heterochromatin formation. We identified TOPBP1 and investigated its binding partner SMARCAD1. SMARCAD1 and TOPBP1 associate with H3K9me3-heterochromatin in ESCs. Interestingly, the nuclear localization of SMARCAD1 is lost in 2C-like cells. SMARCAD1 or TOPBP1 depletion in mouse embryos leads to developmental arrest, reduction of H3K9me3, and remodeling of heterochromatin foci. Collectively, our findings contribute to comprehending the maintenance of chromocenters during early development.

developmental biology↗

bioRxiv2022

Transcriptomic landscape and potential therapeutic targets for human testicular aging revealed by single-cell RNA sequencing

BackgroundTesticular aging is known to cause male age-related fertility decline and hypogonadism, but the underlying molecular mechanisms remain unclear. MethodsWe survey the single-cell transcriptomic landscape of testes from young and old men and examine age-related changes in germline and somatic niche cells. ResultsIn-depth evaluation of the gene expression dynamics of germline cells reveals that disturbance of base-excision repair pathway is a major feature of aging spermatogonial stem cells (SSCs), suggesting that defective DNA repair of SSCs may serve as a potential driver for increased de novo germline mutations with age. Further analysis of aging-associated transcriptional changes shows that stress-related changes and apoptotic signaling pathway accumulate in aged somatic cells. We identify age-related impairment of redox homeostasis in aged Leydig cells and find that pharmacological treatment with antioxidants alleviate this cellular dysfunction of Leydig cells and promote testosterone production. Lastly, our results reveal that decreased pleiotrophin (PTN) signaling is a contributing factor for testicular aging. ConclusionsThese findings provide a comprehensive understanding of the cell-type-specific mechanisms underlying human testicular aging at a single-cell resolution, and suggest potential therapeutic targets that may be leveraged to address age-related male fertility decline and hypogonadism. FundingThis work was supported by the National Key Research and Development Program of China (2018YFA0107200, 2018YFA0801404), the National Natural Science Foundation of China (32130046, 82171564, 82101669, 81871110, 81971759), the Key Research and Development Program of Guangdong Province (2019B020234001), the Natural Science Foundation of Guangdong Province, China (2022A1515010371), the Major Project of Medical Science and Technology Development Research Center of National Health Planning Commission, China (HDSL202001000), the Open Project of NHC Key Laboratory of Male Reproduction and Genetics (Family Planning Research Institute of Guangdong Province) (KF202001), the Guangdong Province Regional Joint Fund-Youth Fund Project (2021A1515110921), the China Postdoctoral Science Foundation (2021M703736).

developmental biology↗

bioRxiv2022

Measurement of Cervical Neuronal Activity during Stress Challenge Using Novel Flexible Adhesive Surface Electrodes

This study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with a novel electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this novel electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new novel technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the novel electrode measurements, neural activity was classified in two ways: 1) pre-to-post CPT, and 2) during a timed respiratory challenge. Unique to this work: 1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and 2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states.

physiology↗

bioRxiv2021

A combinatorial indexing strategy for epigenomic profiling of plant single cells

Understanding how cis-regulatory elements facilitate gene expression is a key question in biology. Recent advances in single-cell genomics have led to the discovery of cell-specific chromatin landscapes that underlie transcription programs. However, the high equipment and reagent costs of commercial systems limit their applications for many laboratories. In this study, we profiled the Arabidopsis root single-cell epigenome using a combinatorial index and dual PCR barcode strategy without the need of any specialized equipment. We generated chromatin accessibility profiles for 13,576 Arabidopsis thaliana root nuclei with an average of 12,784 unique Tn5 integrations per cell and 85% of the Tn5 insertions localizing to discrete accessible chromatin regions. Comparison with data generated from a commercial microfluidic platform revealed that our method is capable of unbiased identification of cell type-specific chromatin accessibility with improved throughput, quality, and efficiency. We anticipate that by removing cost, instrument, and other technical obstacles, this combinatorial indexing method will be a valuable tool for routine investigation of single-cell epigenomes and usher new insight into plant growth, development and their interactions with the environment.

genomics↗

bioRxiv2021

Dual regulation of spine-specific and synapse-to-nucleus signaling by PKCδ during plasticity

The activity-dependent plasticity of synapses is believed to be the cellular basis of learning. These synaptic changes are mediated through the coordination of local biochemical reactions in synapses and changes in gene transcription in the nucleus to modulate neuronal circuits and behavior. The protein kinase C (PKC) family of isozymes has long been established as critical for synaptic plasticity. However, due to a lack of suitable isozyme-specific tools, the role of the novel subfamily of PKC isozymes is largely unknown. Here, through the development of FLIM-FRET activity sensors, we investigate novel PKC isozymes in synaptic plasticity in mouse CA1 pyramidal neurons. We find that PKC{delta} is activated downstream of TrkB and that the spatiotemporal nature of its activation depends on the plasticity stimulation. In response to single spine plasticity, PKC{delta} is activated primarily in the stimulated spine and is required for local expression of plasticity. However, in response to multi-spine stimulation, a long-lasting and spreading activation of PKC{delta} scales with the number of spines stimulated and, by regulating CREB activity, couples spine plasticity to transcription in the nucleus. Thus, PKC{delta} plays a dual functional role in facilitating synaptic plasticity.

neuroscience↗

bioRxiv2021

Molecular basis for PICS-mediated piRNA biogenesis and cell division

By incorporating two mutually exclusive factors, PID-1 and TOST-1, C. elegans PICS complex plays important roles in piRNA biogenesis, chromosome segregation and cell division, respectively. We firstly mapped the interaction network between PICS subunits. By solving the several complex structures, including those of TOFU-6/PICS-1, ERH-2/PICS-1, and ERH-2/TOST-1, we uncover the mechanisms underlying the interactions between PICS subunits. Our biochemical experiment demonstrates that PICS exists as an octamer consisting of two copies of each subunits. Combining structural analyses with mutagenesis experiments, we identified residues of PICS subunits that are critical for maintaining intact PICS complex in vitro. Furthermore, using genetics, cell biology and imaging experiments, we found that those mutants impairing the in vitro interaction network within PICS, also lead to abnormal dysfunction PICS in vivo, including mislocalization of PICS, and reduced levels of piRNAs or abnormal chromosome segregation and cell division. Therefore, our work provides structural insights into understanding the PICS-mediated piRNA biogenesis and cell division.

molecular biology↗

bioRxiv2021

Local autocrine signaling of IGF1 synthesized and released by CA1 pyramidal neurons regulates plasticity of dendritic spines

Insulin-like growth factor 1 (IGF1) regulates hippocampal plasticity, learning, and memory. While circulating, liver-derived IGF1 is known to play an essential role in hippocampal function and plasticity, IGF1 is also synthesized in multiple brain regions, including the hippocampus. However, little is known about the role of hippocampus-derived IGF1 in synaptic plasticity, the type of cells that may provide relevant IGF1, and the spatiotemporal dynamics of IGF1 signaling. Here, using a new FRET sensor for IGF1 signaling, we show that IGF1 in the hippocampus is primarily synthesized in CA1 pyramidal neurons and released in an activity-dependent manner in mice. The local IGF1 release from dendritic spines triggers local autocrine IGF1 receptor activation on the same spine, regulating structural and electrophysiological plasticity of the activated spine. Thus, our study demonstrates a novel mechanism underlying synaptic plasticity by the synthesis and autocrine signaling of IGF1 specific to CA1 pyramidal neurons.

neuroscience↗

bioRxiv2021

AAV-mediated gene therapy produces fertile offspring in the Lhcgr-deficient mouse model of Leydig cell failure

Leydig cell failure (LCF) caused by gene mutation results in testosterone deficiency and infertility. Serum testosterone levels can be recovered via testosterone replacement; however, established therapies have shown limited success in restoring fertility. Here, we used a luteinizing hormone/choriogonadotrophin receptor (Lhcgr)-deficient mouse model of genetic LCF to investigate the feasibility of gene therapy for restoring testosterone production and fertility. We screened several adeno-associated virus (AAV) serotypes and identified AAV8 as an efficient vector to drive exogenous Lhcgr expression in progenitor Leydig cells through interstitial injection. We observed considerable testosterone recovery and Leydig cell maturation after AAV8-Lhcgr treatment in pubertal Lhcgr-/- mice. This gene therapy substantially recovered sexual development, partially restored spermatogenesis and effectively produced fertile offspring. Furthermore, these favorable effects could be reproduced in adult Lhcgr-/- mice. Our proof-of-concept experiments in this mouse model demonstrate that AAV-mediated gene therapy may represent a promising therapeutic approach for patients with genetic LCF.

developmental biology↗

bioRxiv2021

Characterization of novel regulatory modules controlling leaf angle in maize

Leaf angle is an important agronomic trait determining maize planting density and light penetration into the canopy, and contributes significantly to the yield gain in modern maize hybrids. However, little is known about its molecular mechanism beyond the Liguless1 (LG1) and Liguless2 (LG2) genes. In this study, we found that transcription factor ZmBEH1 is targeted by ZmLG2 and regulates the leaf angle formation by influencing the sclerenchyma cells layers on the adaxial side. ZmBEH1 can interact with transcription factor ZmBZR1, whose expression is directly activated by ZmLG1. Both ZmBEH1 and ZmBZR1 bind to the promoter of ZmSCL28, the third transcription factors that influences the leaf angle. Our study demonstrates novel regulatory modules controlling leaf angle, and provides new gene editing targets for creating optimal maize architecture suitable for dense-planting.

plant biology↗

bioRxiv2020

Associations between Early Midlife Lifestyle Behaviors, Young Adult Cognitive Reserve and Advanced Predicted Brain Age in Late Midlife

ImportanceBoth cognitive reserve and modifiable lifestyle behaviors are associated with dementia risk. The effect of early lifestyle behaviors and cognitive reserve on late midlife brain aging could inform early identification and risk reduction of future dementia. ObjectiveDetermine associations of young adult cognitive reserve, early midlife lifestyle behaviors, and the reserve-by-lifestyle interaction on late midlife brain age. Examine the relationship between mild cognitive impairment (MCI) and brain age. DesignParticipants were from the nationally representative Vietnam Era Twin Study of Aging (VETSA). Cognitive reserve was assessed at median age 20 years (IQR=1.38) with the Armed Forces Qualification Test (AFQT). Lifestyle behaviors (smoking, alcohol consumption, and social engagement) were assessed at median age 41 (IQR=5.00). Structural brain imaging conducted at median age 69 (IQR=4.74) was used to construct predicted brain age difference scores (PBAD=chronological age minus predicted brain age) and MCI was ascertained. SettingIn-person cognitive testing (ages 20 and 69); mailed survey (age 41); structural MRI, MCI diagnosis at University of California, San Diego (age 69). Participants431 community-dwelling men. ExposuresAFQT; self-reported health and lifestyle behaviors. Main outcomes and measuresPBAD scores; MCI. ResultsIn fully adjusted mixed linear models, age 20 cognitive reserve and the age 41 lifestyle composite were associated with age 69 PBAD [t (104)=2.62, p=0.01, 95%CI 0.874, 6.285; t (104)=3.37, p=0.001, 95%CI 0.583, 2.249 respectively] as was the reserve-by-lifestyle interaction [t (104) = -2.29, p=0.02, 95%CI -2.330, -0.167]. Unfavorable lifestyle predicted more advanced brain age, but only for those with lower young adult cognitive reserve. The MCI group had more advanced brain age (F (2,130) = 3.13; p=0.05). Conclusions and relevanceFavorable lifestyle behaviors promoted resistance to accelerated brain aging 3 decades later for those with lower young adult cognitive reserve. High reserve appeared to be protective regardless of lifestyle. The association with MCI suggests that advanced PBAD scores reflect poorer brain integrity, although it is unclear if PBAD is related to Alzheimers dementia specifically. Lower cognitive reserve increases risk for dementia, but early lifestyle modification may promote healthier brain aging and dementia risk reduction, particularly in those with lower reserve. Study TypeCohort Study Key PointsO_ST_ABSQuestionC_ST_ABSDo modifiable lifestyle behaviors in early midlife predict later accelerated brain aging and is that association moderated by cognitive reserve? FindingsA lifestyle composite of smoking, alcohol consumption and social engagement at age 41 was associated with estimated brain age in late midlife. There was a significant moderation effect whereby more unfavorable lifestyle behaviors predicted more advanced brain aging, but only in those with low-to-moderate cognitive reserve. MeaningFavorable lifestyle behaviors appear to be protective for brain integrity especially among those with lower cognitive reserve. Early midlife efforts at prevention could be prioritized among those with lower cognitive reserve.

neuroscience↗

bioRxiv2020

Physical and mental health characteristics of adults with subjective cognitive decline: A study of 3,407 people aged 18-81 years from an MTurk-based U.S. national sample

Subjective cognitive decline (SCD), or internal feelings of reduced mental capacity, is of increasing interest in the scientific, clinical, and lay community. Much of the extant literature is focused on SCD as a risk factor for Alzheimers disease in older adults, while less attention has been paid to non-cognitive health correlates of SCD across adulthood. Consequently, we investigated physical and mental health correlates of SCD in younger, middle-aged, and older adults. We recruited 3,407 U.S. residents through Amazons Mechanical Turk, an online labor market. Participants completed a 90-item self-report survey questionnaire assessing sociodemographic characteristics, physical health, sleep, depression, anxiety, loneliness, wisdom, self-efficacy, and happiness. Overall, 493/1930 (25.5%) of younger adults (18-49) and 278/1032 (26.9%) of older adults (50 or older) endorsed the SCD item. Multivariate analysis of variance and follow-up t-tests revealed worse physical and mental health characteristics in people endorsing SCD compared to those who did not, with effect sizes primarily in the medium to large range. Additionally, age did not moderate relationships between SCD and physical and mental health. Results suggest that SCD is associated with a diverse set of negative health characteristics such as poor sleep and high body mass index, and lower levels of positive factors including happiness and wisdom. Effect sizes of psychological correlates of SCD were as large as (or larger than) those of physical correlates, indicating that mental health and affective symptoms may be critical to consider when evaluating SCD. Overall, findings from this large, national U.S. sample suggest the presence of relationships between SCD and multiple psychological and perceived health factors; our results also show that SCD may be highly prevalent in both younger and older adults, suggesting that it be assessed across the adult lifespan.

neuroscience↗

bioRxiv2020

Decoding the regulatory architecture of the maize leaf

The transcription regulatory network underlying essential and complex functionalities inside a eukaryotic cell is defined by the combinatorial actions of transcription factors (TFs). However, TF binding studies in plants are too few in number to produce a general picture of this complex regulatory netowrk. Here, we used ChIP-seq to determine the binding profiles of 104 TF expressed in the maize leaf. With this large dataset, we could reconstruct a transcription regulatory network that covers over 77% of the expressed genes, and reveal its scale-free topology and functional modularity like a real-world network. We found that TF binding occurs in clusters covering [~]2% of the genome, and shows enrichment for sequence variations associated with eQTLs and GWAS hits of complex agronomic traits. Machine-learning analyses were used to identify TF sequence preferences, and showed that co-binding is key for TF specificity. The trained models were used to predict and compare the regulatory networks in other species and showed that the core network is evolutionarily conserved. This study provided an extensive description of the architecture, organizing principle and evolution of the transcription regulatory network inside the plant leaf.

molecular biology↗

bioRxiv2019

Rac1 is a downstream effector of PKCα in structural synaptic plasticity

Structural and functional plasticity of dendritic spines is the basis of animal learning. The calcium-dependent protein kinase C isoform, PKC, has been suggested to be critical for this actin-dependent plasticity. However, mechanisms linking PKC and structural plasticity of spines are unknown. Here, we examine the spatiotemporal activation of actin regulators, including small GTPases Rac1, Cdc42 and Ras, in the presence or absence of PKC during single-spine structural plasticity. Removal of PKC expression in the postsynapse attenuated Rac1 activation during structural plasticity without affecting Ras or Cdc42 activity. Moreover, disruption of a PDZ binding domain within PKC led to impaired Rac1 activation and deficits in structural spine remodeling. These results demonstrate that PKC positively regulates the activation of Rac1 during structural plasticity.

neuroscience↗

bioRxiv2019

Using Machine Learning and Gene Nonhomology Features to Predict Gene Ontology

Advances in genome sequencing and annotation have eased the difficulty of identifying new gene sequences. Predicting the functions of these newly identified genes remains challenging. Genes descended from a common ancestral sequence are likely to have common functions. As a result homology is widely used for gene function prediction. This means functional annotation errors also propagate from one species to another. Several approaches based on machine learning classification algorithms were evaluated for their ability to accurately predict gene function from non-homology gene features. Among the eight supervised classification algorithms evaluated, random forest-based prediction consistently provided the most accurate gene function prediction. Non-homology-based functional annotation provides complementary strengths to homology-based annotation, with higher average performance in Biological Process GO terms, the domain where homology-based functional annotation performs the worst, and weaker performance in Molecular Function GO terms, the domain where the accuracy of homology-based functional annotation is highest. Non-homology-based functional annotation based on machine learning may ultimately prove useful both as a method to assign predicted functions to orphan genes which lack functionally characterized homologs, and to identify and correct functional annotation errors which were propagated through homology-based functional annotations.

bioinformatics↗

bioRxiv2019

Expectation pooling: An effective and interpretable pooling method for predicting DNA-protein binding

MotivationConvolutional neural networks (CNNs) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. While previous studies have built a connection between CNNs and probabilistic models, simple models of CNNs cannot achieve sufficient accuracy on this problem. Recently, some methods of neural networks have increased performance using complex neural networks whose results cannot be directly interpreted. However, it is difficult to combine probabilistic models and CNNs effectively to improve DNA-protein binding predictions.\n\nResultsIn this paper, we present a novel global pooling method: expectation pooling for predicting DNA-protein binding. Our pooling method stems naturally from the EM algorithm, and its benefits can be interpreted both statistically and via deep learning theory. Through experiments, we demonstrate that our pooling method improves the prediction performance DNA-protein binding. Our interpretable pooling method combines probabilistic ideas with global pooling by taking the expectations of inputs without increasing the number of parameters. We also analyze the hyperparameters in our method and propose optional structures to help fit different datasets. We explore how to effectively utilize these novel pooling methods and show that combining statistical methods with deep learning is highly beneficial, which is promising and meaningful for future studies in this field.\n\nContactdengmh@pku.edu.cn, gaog@mail.cbi.pku.edu.cn\n\nSupplementary informationAll code is public in https://github.com/gao-lab/ePooling

bioinformatics↗

bioRxiv2019

Tissue-specific Hi-C analyses of rice, foxtail millet and maize suggest non-canonical function of plant chromatin domains

Chromatins are not randomly packaged in the nucleus and their organization plays important roles in transcription regulation. Using in situ Hi-C, we have compared the 3D chromatin architectures of rice mesophyll and endosperm, foxtail millet bundle sheath and mesophyll, and maize bundle sheath, mesophyll and endosperm tissues. We have also profiled their DNA methylation, open chromatin, histone modification and gene expression to investigate whether chromatin structural dynamics are associated with epigenome features changes. We found that plant global A/B compartment partitions are stable across tissues, while local A/B compartment has tissue-specific dynamic that is associated with differential gene expression. Plant domains are largely stable across tissues, while rare domain border changes are often associated with gene activation. Genes inside plant domains are not conserved across species, and lack significant co-expression behavior unlike those in mammalian cells. When comparing synteny gene pairs, we found those maize genes involved in gene island chromatin loops have shorter genomic distances in smaller genomes without gene island loops such as rice and foxtail millet, suggesting that they have conserved functions. Our study revealed that the 3D configuration of the plant chromatin is also complex and dynamic with unique features that need to be further examined.

genomics↗

bioRxiv2018

Multi-Center Study of Resectable Lung Lesions by Ultra-Deep Sequencing of Targeted Genes in Plasma Cell-Free DNA to Assess Nodule Malignancy and Detect Lung Cancers

BACKGROUNDEarly detection of lung cancer to allow curative treatment remains challenging. Cell-free circulating tumor DNA (ctDNA) analysis may aid in malignancy assessment and early cancer diagnosis of lung nodules found in screening imagery.\n\nMETHODSThe multi-center clinical study enrolled 192 patients with operable occupying lung diseases. Plasma ctDNA, white blood cell genomic DNA (gDNA) and tumor tissue gDNA of each patient were analyzed by ultra-deep sequencing to an average of 35,000X of the coding regions of 65 lung cancer-related genes.\n\nRESULTSThe cohort consists of a quarter of benign lung diseases and three quarters of cancer patients with all histopathology subtypes. 64% of the cancer patients is at Stage I. Gene mutations detection in tissue gDNA and plasma ctDNA results in a sensitivity of 91% and specificity of 88%. When ctDNA assay was used as the test, the sensitivity was 69% and specificity 96%. As for the lung cancer patients, the assay detected 63%, 83%, 94% and 100%, for Stage I, II, III and IV, respectively. In a linear discriminant analysis, combination of ctDNA, patient age and a panel of serum biomarkers boosted the overall sensitivity to 80% at a specificity of 99%. 29 out of the 65 genes harbored mutations in the lung cancer patients with the largest number found in TP53 (30% plasma and 62% tumor tissue samples) and EGFR (20% and 40%, respectively).\n\nCONCLUSIONPlasma ctDNA was analyzed in lung nodule assessment and early cancer detection while an algorithm combining clinical information enhanced the test performance.

clinical trials↗