Biology subjects

Tran, T.

Publications and source records attributed to Tran, T..

At least 91 records · Page 5Linked to original sources

bioRxiv2020

Direct RNA sequencing and early evolution of SARS-CoV-2

Fundamental aspects of SARS-CoV-2 biology remain to be described, having the potential to provide insight to the response effort for this high-priority pathogen. Here we describe the first native RNA sequence of SARS-CoV-2, detailing the coronaviral transcriptome and epitranscriptome, and share these data publicly. A data-driven inference of viral genetic features and evolutionary rate is also made. The rapid sharing of sequence information throughout the SARS-CoV-2 pandemic represents an inflection point for public health and genomic epidemiology, providing early insights into the biology and evolution of this emerging pathogen.

microbiology↗

bioRxiv2020

Control of tissue development by cell cycle dependent transcriptional filtering

Cell cycle duration changes dramatically during development, starting out fast to generate cells quickly and slowing down over time as the organism matures. The cell cycle can also act as a transcriptional filter to control the expression of long genes which are partially transcribed in short cycles. Using mathematical simulations of cell proliferation, we identify an emergent property, that this filter can act as a tuning knob to control cell fate, cell diversity and the number and proportion of different cell types in a tissue. Our predictions are supported by comparison to single-cell RNA-seq data captured over embryonic development. Evolutionary genome analysis shows that fast developing organisms have a narrow genomic distribution of gene lengths while slower developers have an expanded number of long genes. Our results support the idea that cell cycle dynamics may be important across multicellular animals for controlling gene expression and cell fate.

developmental biology↗

bioRxiv2019

Local nucleosome dynamics and eviction following a double-strand break are reversible by NHEJ-mediated repair in the absence of DNA replication

Although the molecular events required for the repair of double-strand breaks (DSB) have been well characterized, the role of epigenetic processes in the recognition and repair of DSBs has only been investigated at low resolution. We rapidly and synchronously induced a site-specific DSB in Saccharomyces cerevisiae upstream of the PHO5 locus, which has well-positioned nucleosomes. Utilizing MNase-seq epigenome mapping we interrogated the order of chromatin changes that occur immediately following a DSB by generating a base-pair resolution map of the chromatin landscape. In wild type cells, the first nucleosome left of the break was rapidly evicted. The eviction of this flanking nucleosome was dynamic and proceeded through an early intermediate chromatin structure where the nucleosome was repositioned in the adjacent linker DNA. Other nucleosomes bordering both sides of the break were also shifted away from the break; however, their loss was more gradual. These local changes preceded a broader loss of chromatin organization and nucleosome eviction that was marked by increased MNase sensitivity in the regions [~]8 kb on each side of the break. While the broad loss of chromatin organization was dependent on the end-processing complex, Mre11-Rad50-Xrs2 (MRX), the early remodeling and repositioning of the nucleosome adjacent to the break was independent of the MRX and YKU70/80 complexes. We also examined the temporal dynamics of NHEJ-mediated repair in a G1-arrested population, where 5 to 3 end-resection of DSB ends is blocked. Concomitant with DSB repair, we observed the re-deposition and precise re-positioning of nucleosomes at the originally-occupied positions. This re-establishment of the pre-lesion chromatin landscape suggests that a DNA replication-independent mechanism exists in G1 cells to preserve epigenome organization following DSB repair.

genomics↗

bioRxiv2019

Methylthioadenosine is Not Dramatically Elevated in MTAP-Homozygous Deleted Primary Glioblastomas

In BriefThe co-deletion of MTAP in the CDKN2A locus is a frequent event in diverse cancers including glioblastoma. Recent publications report that significant accumulations of the MTAP substrate, methylthioadenosine (MTA), can sensitize MTAP-deleted cancer cells to novel inhibitors of PRMT5 and MAT2A for targeted therapy against tumors with this particular genetic alteration. In this work, using comprehensive metabolomic profiling, we show that MTA is primarily secreted, resulting in exceedingly high levels of extracellular MTA in vitro. We further show that primary human glioblastoma tumors minimally accumulate MTA in vivo, which is likely explained by the metabolism of MTA by MTAP-competent stromal cells. Together, these data challenge whether the metabolic conditions required for therapies to exploit vulnerabilities associated MTAP deletions are present in primary human tumors, questioning their translational efficacy in the clinic.\n\nHighlightsO_LIMethylthioadenosine (MTA) is elevated in MTAP-deleted cancer cells in vitro, which provides a selective vulnerability to PRMT5 and MAT2A inhibitors\nC_LIO_LIAccumulation of MTA in MTAP-deleted cancer cells is predominately extracellular, suggesting active secretion of MTA.\nC_LIO_LIMTAP-deleted primary human glioblastoma tumors show minimal intratumoral elevations of MTA, which is likely explained by secretion and metabolism by MTAP-competent stromal cells.\nC_LI\n\nSUMMARYHomozygous deletion of the CDK2NA locus frequently results in co-deletion of methylthioadenosine phosphorylase (MTAP) in many fatal cancers such as glioblastoma multiforme (GBM), resulting in elevations of the substrate metabolite, methylthioadenosine (MTA). To capitalize on such accumulations, therapeutic targeting of protein arginine methyltransferase 5 (PRMT5) and methionine adenosyl transferase (MAT2A) are ongoing. While extensively corroborated in vitro, the clinical efficacy of these strategies ultimately relies on equally significant accumulations of MTA in human tumors. Here, we show that in vitro accumulation of MTA is a predominately extracellular phenomenon, indicating secretion of MTA from MTAP-deleted cells. In primary human GBMs, we find that MTA levels are not significantly higher in MTAP-deleted compared to MTAP-intact tumors or normal brain tissue. Together, these findings highlight the metabolic discrepancies between in vitro models and primary human tumors and should thus be carefully considered in the development of the precision therapies targeting MTAP-homozygous deleted GBM.

cancer biology↗

bioRxiv2019

Deep in the Bowel: Highly Interpretable Neural Encoder-Decoder Networks Predict Gut Metabolites from Gut Microbiome

Technological advances in next-generation sequencing (NGS) and chromatographic assays [e.g., liquid chromatography mass spectrometry (LC-MS)] have made it possible to identify thousands of microbe and metabolite species, and to measure their relative abundance. In this paper, we propose a sparse neural encoder-decoder network to predict metabolite abundances from microbe abundances. Using paired data from a cohort of inflammatory bowel disease (IBD) patients, we show that our neural encoder-decoder model outperforms linear univariate and multivariate methods in terms of accuracy, sparsity, and stability. Importantly, we show that our neural encoder-decoder model is not simply a black box designed to maximize predictive accuracy. Rather, the networks hidden layer (i.e., the latent space, comprised only of sparsely weighted microbe counts) actually captures key microbe-metabolite relationships that are themselves clinically meaningful. Although this hidden layer is learned without any knowledge of the patients diagnosis, we show that the learned latent features are structured in a way that predicts IBD and treatment status with high accuracy. By imposing a non-negative weights constraint, the network becomes a directed graph where each downstream node is interpretable as the additive combination of the upstream nodes. Here, the middle layer comprises distinct microbe-metabolite axes that relate key microbial biomarkers with metabolite biomarkers. By pre-processing the microbiome and metabolome data using compositional data analysis methods, we ensure that our proposed multi-omics workflow will generalize to any pair of -omics data. To the best of our knowledge, this work is the first application of neural encoder-decoders for the interpretable integration of multi-omics biological data.

bioinformatics↗

bioRxiv2019

Alcohol increases aggression in flies

Alcohol-induced aggression is a destructive and widespread phenomenon, but we understand very little about the mechanisms that produce this behavior. We found that two different alcohol exposures potentiate aggression in male flies. (1) A pharmacologically relevant dose of alcohol increases aggression and decreases a goal-directed behavior in male flies. (2) In addition, the odor of alcohol itself enhances intermale aggression by potentiating olfactory signaling by cis-vaccenyl acetate (cVa), a volatile male pheromone. Characterizing these behaviors in the genetically tractable fruit fly can lead to a better understanding of the molecular correlates that regulate alcohol-induced aggression in humans and provide insights into an ethologically relevant behavior.\n\nOne Sentence SummaryWe identified two pathways through which alcohol stimulates intermale aggression in flies; one acts by potentiating a male olfactory pheromone while the other is mediated by the systemic effects of alcohol.

ecology↗

bioRxiv2019

A predicted deleterious allele of the essential meiosis gene MND1, present in ~3% of East Asians, does not disrupt reproduction in mice.

Infertility is a major health problem affecting ~15% of couples worldwide. Except for cases involving readily-detectable chromosome aberrations, confident identification of a causative genetic defect is problematic. Despite the advent of genome sequencing for diagnostic purposes, the preponderance of segregating genetic variants complicates identification of culprit genetic alleles or mutations. Many algorithms have been developed to predict the effects of \"variants of unknown significance\" (VUS), typically SNPs (single nucleotide polymorphisms), but these predictions are not sufficiently accurate for clinical action. As part of a project to identify population variants that impact fertility, we have been generating CRISPR-Cas9 edited mouse models of suspect SNPs in genes that are known to be required for fertility in mice. Here, we present data on a non-synonymous (amino acid altering) SNP (rs140107488) in the meiosis gene Mnd1, which is predicted bioinformatically to be deleterious to protein function. We report that when modeled in mice, this allele (MND1K85M), which is present allele frequency of ~3% in East Asians, has no discernable effect upon fertility, fecundity, or gametogenesis, although it may cause sex skewing of progeny from homozygous males. In sum, this appears to be a benign allele that can be eliminated or de-prioritized in clinical genomic analyses of infertility patients.

genetics↗

bioRxiv2019

Lactic Acid Containing Polymers Produced in Engineered Sinorhizobium meliloti and Pseudomonas putida

This study demonstrates that novel polymer production can be achieved by introducing pTAM, a broad-host-range plasmid expressing codon-optimized genes encoding Clostridium propionicum propionate CoA transferase (PctCp) and a modified Pseudomonas sp. MBEL 6-19 polyhydroxyalkanoate (PHA) synthase 1 (PhaC1Ps6-19), into phaC mutant strains of the native polymer producers Sinorhizobium meliloti and Pseudomonas putida. Both phenotypic analysis and gas chromatography analysis indicated the synthesis and accumulation of biopolymers in S. meliloti and P. putida strains. Expression in S. meliloti resulted in the production of PLA homopolymer up to 3.2% dried cell weight (DCW). The quaterpolymer P(3HB-co-LA-co-3HHx-co-3HO) was produced by expression in P. putida. The P. putida phaC mutant strain produced this type of polymer the most efficiently with polymer content of 42% DCW when cultured in defined media with the addition of sodium octanoate, while the greatest LA fraction (4% mol) was achieved in the same strain cultured in LB with the addition of lactic acid. This is the first report, to our knowledge, of the production of a range of different biopolymers using the same plasmid-based system in different backgrounds. In addition, it is the first time that the novel polymer (P(3HB-co-LA-co-3HHx-co-3HO)), has been reported being produced in bacteria.

microbiology↗

bioRxiv2019

Reduced Cognitive Performance in Aged Rats Correlates with Increased Excitation/Inhibition Ratio in the Dentate Gyrus in Response to Lateral Entorhinal Input

Aging often impairs cognitive functions associated with the medial temporal lobe (MTL). Anatomical studies identified the layer II pyramidal cells of the lateral entorhinal cortex (LEC) as one of the most vulnerable elements within the MTL. These cells provide a major excitatory input to the dentate gyrus hippocampal subfield by synapsing onto granule cells and onto local inhibitory interneurons, and a fraction of these contacts are lost in aged individuals with impaired learning. Using optogenetics we evaluated the functional status of the remaining inputs in an outbred rat model of aging that distinguishes between learning impaired and learning unimpaired individuals. We found that aging affects the pre- and postsynaptic strength of the LEC inputs onto granule cells. However, the magnitude these changes was similar in impaired and un-impaired rats. In contrast, the recruitment of inhibition by LEC activation was selectively reduced in the aged impaired subjects. These findings are consistent with the notion that the preservation of an adequate balance of excitation and inhibition is crucial for maintain proficient memory performance during aging.

neuroscience↗

bioRxiv2019

Restoration of Susceptibility to Amikacin by 8-Hydroxyquinoline Analogs Complexed to Zinc

Gram-negative pathogens resistant to amikacin and other aminoglycosides of clinical relevance usually harbor the 6-N-acetyltransferase type Ib [AAC(6)-Ib], an enzyme that catalyzes inactivation of the antibiotic by acetylation using acetyl-CoA as donor substrate. Inhibition of the acetylating reaction could be a way to induce phenotypic conversion to susceptibility in these bacteria. We have previously observed that Zn+2 acts as an inhibitor of the enzymatic acetylation of aminoglycosides by AAC(6)-Ib, and in complex with ionophores it effectively reduced the levels of resistance in cellulo. We compared the activity of 8-hydroxyquinoline, three halogenated derivatives, and 5-[N-Methyl-N-Propargylaminomethyl]-8-Hydroxyquinoline in complex with Zn+2 to inhibit growth of amikacin-resistant Acinetobacter baumannii in the presence of the antibiotic. Two of the compounds, clioquinol (5-chloro-7-iodo-8-hydroxyquinoline) and 5,7-diiodo-8-hydroxyquinoline, showed robust inhibition of growth of the two A. baumannii clinical isolates that produce AAC(6)-Ib. However, none of the combinations had any activity on another amikacin-resistant A. baumannii strain that possesses a different, still unknown mechanism of resistance. Time-kill assays showed that the combination of clioquinol or 5,7-diiodo-8-hydroxyquinoline with Zn+2 and amikacin was bactericidal. Addition of 8-hydroxyquinoline, clioquinol, or 5,7-diiodo-8-hydroxyquinoline, alone or in combination with Zn+2, and amikacin to HEK293 cells did not result in significant toxicity. These results indicate that ionophores in complex with Zn+2 could be developed into potent adjuvants to be used in combination with aminoglycosides to treat Gram-negative pathogens in which resistance is mediated by AAC(6)-Ib and most probably other related aminoglycoside modifying enzymes.

microbiology↗

bioRxiv2019

DeepTRIAGE: Interpretable and Individualised BiomarkerScores using Attention Mechanism for the Classification of Breast Cancer Sub-types

MotivationBreast cancer is a collection of multiple tissue pathologies, each with a distinct molecular signature that correlates with patient prognosis and response to therapy. Accurately differentiating between breast cancer sub-types is an important part of clinical decision-making. Already, this problem has been addressed using machine learning methods that separate tissue samples into distinct groups. However, there remains unexplained heterogeneity within the established sub-types that cannot be resolved by the commonly used classification algorithms. In this paper, we propose a novel deep learning architecture, called DeepTRIAGE (Deep learning for the TRactable Individualised Analysis of Gene Expression), which not only classifies cancer sub-types with comparable accuracy, but simultaneously assigns each patient their own set of interpretable and individualised biomarker scores. These personalised scores describe how important each feature is in the classification of each patient, and can be analysed post-hoc to generate new hypotheses about intra-class heterogeneity. ResultsWe apply the DeepTRIAGE framework to classify the gene expression signatures of luminal A and luminal B breast cancer sub-types, and illustrate its use for genes and gene set (i.e., GO and KEGG) features. Using DeepTRIAGE, we find that the GINS1 gene and the kinetochore organisation GO term are the most important features for luminal sub-type classification. Through classification, DeepTRIAGE simultaneously reveals heterogeneity within the luminal A biomarker scores that significantly associate with tumour stage, placing all luminal samples along a continuum of severity. Availability and implementationThe proposed model is implemented in Python using Py-Torch framework. The analysis is done in Python and R. All Methods and models are freely available from https://github.com/adham/BiomarkerAttend.

biophysics↗

bioRxiv2019

Personalized Annotation-based Networks (PAN) for the Prediction of Breast Cancer Relapse

The classification of clinical samples based on gene expression data is an important part of precision medicine. However, it has proved difficult to accurately predict survival outcomes and treatment responses for cancer patients. In this manuscript, we show how transforming gene expression data into a set of personalized (sample-specific) networks can allow us to harness existing graph-based methods to improve classifier performance. Existing approaches to personalized gene networks all have the limitation that they depend on other samples in the data and must get re-computed whenever a new sample is introduced. Here, we propose a novel method, called Personalized Annotation-based Networks (PAN), that avoids this limitation by using curated annotation databases to transform gene expression data into a graph. These databases organize genes into overlapping gene sets, called annotations, that we use to build a network where nodes represent functional terms and edges represent the similarity between them. Unlike competing methods, PANs are calculated for each sample independent of the population, making it a more efficient way to obtain single-sample networks. Using three breast cancer datasets as a case study (METABRIC and a super-set of GEO studies), we show that PAN classifiers not only predict cancer relapse better than gene features alone, but also outperform PPI and population-level graph-based classifiers. This work demonstrates the practical advantages of graph-based classification for high-dimensional genomic data, while offering a new approach to making sample-specific networks. Supplementary informationThe codes and data are available at https://github.com/thinng/PAN. ContactThuc.Le@unisa.edu.au

bioinformatics↗

bioRxiv2019

Hera-T: an efficient and accurate approach for quantifying gene abundances from 10X-Chromium data with high rates of non-exonic reads.

An important but rarely discussed phenomenon in single cell data generated by the 10X-Chromium protocol is that the fraction of non-exonic reads is very high. This number usually exceeds 30% of the total reads. Without aligning them to a complete genome reference, non-exonic reads can be erroneously aligned to the transcriptome reference with higher error rates. To tackle this problem, Cell Ranger chooses to firstly align reads against the whole genome, and at a later step, uses a genome annotation to select reads that align to the transcriptome. Despite its high running time and large memory consumption, Cell Ranger remains the most widely used tool to quantify 10XGenomics single cell RNA-Seq data for its accuracy. In this work, we introduce Hera-T, a fast and accurate tool for estimating gene abundances in single cell data generated by the 10X-Chromium protocol. By devising a new strategy for aligning reads to both transcriptome and genome references, Hera-T reduces both running time and memory consumption from 10 to 100 folds while giving similar results compared to Cell Rangers. Hera-T also addresses some difficult splicing alignment scenarios that Cell Ranger fails to address, and therefore, obtains better accuracy compared to Cell Ranger. Excluding the reads in those scenarios, Hera-T and Cell Ranger results have correlation scores > 0.99. For a single-cell data set with 49 million of reads, Cell Ranger took 3 hours (179 minutes) while Hera-T took 1.75 minutes; for another single-cell data set with 784 millions of reads, Cell Ranger took about 25 hours while Hera-T took 32 minutes. For those data sets, Cell Ranger completely used all 32 GB of memory while Hera-T consumed at most 8 GB. Hera-T package is available for download at: https://bioturing.com/product/hera-t

bioinformatics↗

bioRxiv2018

A revisit of RSEM generative model and its EM algorithm for quantifying transcript abundances.

RSEM has been mainly known for its accuracy in transcript abundance quantification. However, its quantification time is extremely high compared to that of recent quantification tools. In this paper, we revised the RSEMs EM algorithm. In particular, we derived accurate M-step updates to eliminate incorrect heuristic updates in RSEM. We also implement some optimizations that reduce the quantification time about a hundred times while still have better accuracy compared to RSEM. In particular, we noticed that different parameters have different convergence rates, therefore we identified and removed early converged parameters to significantly reduce the model complexity in further iterations, and we also use SQUAREM method to further speed up the convergence rate. We implemented these revisions in a packaged named Hera-EM, with source code available at: https://github.com/bioturing/hera/tree/master/hera-EM

bioinformatics↗

bioRxiv2018

Covalent Aurora A regulation by the metabolic integrator coenzyme A

Aurora A is a cell cycle protein kinase implicated in multiple human cancers, and several Aurora A-specific kinase inhibitors have progressed into clinical trials. In this study, we report structural and cellular analysis of a novel biochemical mode of Aurora A inhibition, which occurs through reversible covalent interaction with the universal metabolic integrator coenzyme A (CoA). Mechanistically, the CoA 3-phospho ADP moiety interacts with Thr 217, an Aurora A selectivity filter, which permits the formation of an unprecedented covalent bond with Cys 290 in the kinase activation segment, lying some 15 [A] away. CoA modification (CoAlation) of endogenous Aurora A is rapidly induced by oxidative stresses at Cys 290 in human cells, and microinjection of CoA into mouse embryos perturbs meitoic spindle formation and chromosome alignment. Aurora A regulation by CoA reveals how targeting of Aurora A might be accomplished in the future by development of a double-anchored covalent inhibitor.

biochemistry↗

bioRxiv2018

Critical Limb Ischemia Induces Remodeling of Skeletal Muscle Motor Unit and Myonuclear- and Mitochondrial-Domains

Critical limb ischemia, the most severe form of peripheral artery disease, leads to extensive damage and alterations in skeletal muscle homeostasis. Although recent developments towards revascularization therapies have been introduced, there has been limited research into treatments for ischemic myopathy. To elucidate the regenerative mechanism of the muscle stem cell and its niche components in response to ischemic insults, we explored interactions between the vasculature, motor neuron, muscle fiber, and the muscle stem cell. We first investigated changes in the neuromuscular junction and motor neuron innervation following a surgical hindlimb ischemia model of critical limb ischemia in mice. Along with previous findings that support remodeling of the neuromuscular junction, we report that ischemic injury also causes significant alterations to the myofiber through a muscle stem cell-mediated increase of myonuclei number per fiber, a concomitant decrease in myonuclear domain size, and an increase in relative mitochondrial content per myonucleus. These results indicate that as a regenerative response to critical limb ischemia, myofibers exhibit myonuclear expansion to allow enhanced transcriptional support and an increase in mitochondrial content for bioenergetic need of the energy-demanding tissue regeneration.

physiology↗

bioRxiv2018

Repression of Transcription Factor AP-2 Alpha by Peroxisome Proliferator Activated Receptor Gamma Reveals a Novel Transcriptional Circuit in basal-squamous Bladder Cancer

The discovery of bladder cancer transcriptional subtypes provides an opportunity to identify high risk patients, and tailor disease management. Recent studies suggest tumor heterogeneity contributes to \"plasticity\" of molecular subtype during progression and following treatment. Nonetheless, the transcriptional drivers of the aggressive basal-squamous subtype remain unidentified. As PPAR{gamma} has been repeatedly implicated in the luminal subtype of bladder cancer, we hypothesized inactivation of this transcriptional master regulator during progression results in increased expression of basal-squamous specific transcription factors (TFs) which act to drive aggressive behavior. We initiated a pharmacologic and RNA-seq-based screen to identify PPAR{gamma}-repressed, basal-squamous specific TFs. Hierarchical clustering of RNA-seq data following treatment of a panel of human bladder cancer cell lines with a PPAR{gamma} agonist identified a number of TFs regulated by PPAR{gamma} activation, several of which are implicated in urothelial and squamous differentiation. One PPAR{gamma}-repressed TF implicated in squamous differentiation identified is Transcription Factor Activating Protein 2 alpha (TFAP2A). We show TFAP2A and its paralog TFAP2C are overexpressed in basal-squamous bladder cancer and in squamous areas of cystectomy samples, and that overexpression is associated with increased lymph node metastasis and distant recurrence, respectively. Biochemical analysis confirmed the ability of PPAR{gamma} activation to repress TFAP2A, while PPAR{gamma} antagonist studies indicate the requirement of a functional receptor. In vivo tissue recombination studies show TFAP2A and TFAP2C promote tumor growth in line with the aggressive nature of basal-squamous bladder cancer. Our findings suggest PPAR{gamma} inactivation, as well as TFAP2A and TFAP2C overexpression cooperate with other TFs to promote the basal-squamous transition.

cancer biology↗

bioRxiv2018

Eradication of ENO1-deleted Glioblastoma through Collateral Lethality

Inhibiting glycolysis remains an aspirational approach for the treatment of cancer. We recently demonstrated that SF2312, a natural product phosphonate antibiotic, is a potent inhibitor of the glycolytic enzyme Enolase with potential utility for the collateral lethality-based treatment of Enolase-deficient glioblastoma (GBM). However, phosphonates are anionic at physiological pH, limiting cell and tissue permeability. Here, we show that addition of pivaloyloxymethyl (POM) groups to SF2312 (POMSF) dramatically increases potency, leading to inhibition of glycolysis and killing of ENO1-deleted glioma cells in the low nM range. But the utility of POMSF in vivo is dose-limited by severe hemolytic anemia. A derivative, POMHEX, shows equipotency to POMSF without inducing hemolytic anemia. POMHEX can eradicate intracranial orthotopic ENO1-deleted tumors, despite sub-optimal pharmacokinetic properties. Taken together, our data provide in vivo proof-of-principal for collateral lethality in precision oncology and showcase POMHEX as a useful molecule for the study of glycolysis in cancer metabolism.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC=\"FIGDIR/small/331538_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@1b78ebcorg.highwire.dtl.DTLVardef@1fc0ccforg.highwire.dtl.DTLVardef@ad268corg.highwire.dtl.DTLVardef@1bdee32_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗