Biology subjects

Tripathi, S.

Publications and source records attributed to Tripathi, S..

70 records · Page 4Linked to original sources

bioRxiv2021

Meta-analysis of orthogonal OMICs data from COVID-19 patients unveils prognostic markers and antiviral factors.

While our battle with the COVID-19 pandemic continues, a multitude of Omics data has been generated from patient samples in various studies, which remains to be translated. We conducted a meta-analysis of published transcriptome and proteome profiles of nasal swab and bronchioalveolar lavage fluid (BALF) samples of COVID-19 patients, to shortlist high confidence upregulated host factors. Subsequently, mRNA overexpression of selected genes was validated in nasal swab/BALF samples from a cohort of COVID-19 positive/negative, symptomatic/asymptomatic individuals. Analysis of these data revealed S100 family genes (S100A6, S100A8, S100A9, and S100P) as prognostic markers of COVID-19 disease. Furthermore, Thioredoxin gene (TXN) was identified as a significant upregulated host factor in our overlap analysis. An FDA-approved drug Auranofin, which inhibits Thioredoxin reduction, was found to mitigate SARS-CoV-2 replication in vitro and in vivo in the hamster challenge model. Overall, this study translates COVID-19 host response Big Data into potential clinical interventions.

microbiology↗

bioRxiv2021

A Mechanistic Modeling Framework Reveals the Key Principles Underlying Tumor Metabolism

While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive heterogeneity with respect to the presentation of the Warburg effect. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. Next, we report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer. Author SummaryTumor cells exhibit heterogeneity and plasticity in their metabolic behavior, relying on distinct nutrients and metabolic pathways, and switching to reliance on different pathways when challenged by an environmental change or a drug. While multiple previous studies have focused on identifying metabolic signatures that can distinguish tumor cells from non-tumorigenic ones, frameworks to analyze the metabolic heterogeneity in tumors have been lacking. Here, we present a mechanistic mathematical model of some of the key metabolic pathways active in tumor cells and analyze the steady state behaviors the model can exhibit. We find that the rate of ATP use by tumor cells can be a key determinant of the metabolic pathway via which tumor cells utilize glucose. We further show that tumor cells can utilize different pathways for satisfying the same metabolic requirements, and explore the implications of such behavior for the response of tumor cells to drugs targeting tumor metabolism. At each step, we discuss how our model predictions fit within the context of experimental observations made across tumor types. The present modeling framework represents an important step towards reconciling the wide array of experimental observations concerning tumor metabolism, and towards a more methodical approach to targeting tumors metabolic vulnerabilities.

cancer biology↗

bioRxiv2020

Structural mimicry confers robustness in the cyanobacterial circadian clock

The histidine kinase SasA enhances robustness of circadian rhythms in the cyanobacterium S. elongatus by temporally controlling expression of the core clock components, kaiB and kaiC. Here we show that SasA also engages directly with KaiB and KaiC proteins to regulate the period and enhance robustness of the reconstituted circadian oscillator in vitro, particularly under limiting concentrations of KaiB. In contrast to its role regulating gene expression, oscillator function does not require SasA kinase activity; rather, SasA uses structural mimicry to cooperatively recruit the rare, fold-switched conformation of KaiB to the KaiC hexamer to form the nighttime repressive complex. Cooperativity gives way to competition with increasing concentrations of SasA to define a dynamic window by which SasA directly modulates clock robustness. One Sentence SummarySasA controls the assembly of clock protein complexes through a balance of cooperative and competitive interactions.

biochemistry↗

bioRxiv2020

Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT

Epithelial-mesenchymal transition (EMT) and its reverse process mesenchymal-epithelial transition (MET) are central to metastatic aggressiveness and therapy resistance in solid tumors. While molecular determinants of both processes have been extensively characterized, the heterogeneity in the response of tumor cells to EMT and MET inducers has come into focus recently, and has been implicated in the failure of anti-cancer therapies. Recent experimental studies have shown that some cells can undergo an irreversible EMT depending on the duration of exposure to EMT-inducing signals. While the irreversibility of MET, or equivalently, resistance to EMT, has not been studied in as much detail, evidence supporting such behavior is slowly emerging. Here, we identify two possible mechanisms that can underlie resistance of cells to undergo EMT: epigenetic feedback in ZEB1/GRHL2 feedback loop and stochastic partitioning of biomolecules during cell division. Identifying the ZEB1/GRHL2 axis as a key determinant of epithelial-mesenchymal plasticity across many cancer types, we use mechanistic mathematical models to show how GRHL2 can be involved in both the abovementioned processes, thus driving an irreversible MET. Our study highlights how an isogenic population may contain subpopulation with varying degrees of susceptibility or resistance to EMT, and proposes a next set of questions for detailed experimental studies characterizing the irreversibility of MET/resistance to EMT.

cancer biology↗

bioRxiv2020

Comparative study of transcriptomics-based scoring metrics for the epithelial-hybrid-mesenchymal spectrum

The Epithelial-mesenchymal transition (EMT) is a cellular process implicated in embryonic development, wound healing, and pathological conditions such as cancer metastasis and fibrosis. Cancer cells undergoing EMT exhibit enhanced aggressive behavior characterized by drug resistance, tumor-initiation potential, and the ability to evade immune system. Recent in silico, in vitro, and in vivo evidence indicates that EMT is not an all-or-none process; instead, cells stably acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes which often can be more aggressive than purely epithelial or mesenchymal cell populations. Thus, the EMT status of cancer cells can prove to be a critical estimate of patient prognosis. Recent attempts have employed different transcriptomics signatures to quantify EMT status in cell lines and patient tumors. However, a comprehensive comparison of these methods, including their accuracy in identifying cells in the hybrid E/M phenotype(s), is lacking. Here, we compare three distinct metrics that score EMT on a continuum, based on the transcriptomics signature of individual samples. Our results demonstrate that these methods exhibit good concordance among themselves in quantifying the extent of EMT in a given sample. Moreover, scoring EMT using any of the three methods discerned that cells undergo varying extents of EMT across tumor types. Separately, our analysis also identified tumor types with maximum variability in terms of EMT and associated an enrichment of hybrid E/M signatures in these samples. Moreover, we also found that the multinomial logistic regression (MLR) based metric was capable of distinguishing between pure individual hybrid E/M vs. mixtures of epithelial (E) and mesenchymal (M) cells. Our results, thus, suggest that while any of the three methods can indicate a generic trend in the EMT status of a given cell, the MLR method has two additional advantages: a) it uses a small number of predictors to calculate the EMT score, and b) it can predict from the transcriptomic signature of a population whether it is comprised of pure hybrid E/M cells at the single-cell level or is instead an ensemble of E and M cell subpopulations.

cancer biology↗

bioRxiv2019

Integration of Multi-level Molecular Scoring for the Interpretation of RAS-Family Genetic Variation

Protein-coding genetic variants are the first considered in most studies and Precision Medicine workflows, but their interpretation is primarily driven by DNA sequence-based analytical tools and annotations. Thus, more specific and mechanistic interpretations should be attainable by integrating DNA-based scores with scores from the protein 3D structure. However, reliable and reproducible standardization of methods that use 3D structure for genomic variation is still lacking. Further, we believe that the current paradigm of aiming to directly predict the pathogenicity of variants skips the critical step of inferring, with precision, molecular mechanisms of dysfunction. Thus, we report herein the development and evaluation of single and composite 3D structure-based scores and their integration with protein and DNA sequence-based scores to better understand not only if a genomic variant alters a protein, but how. We believe this is a critical step for understanding mechanistic changes due to genomic variants, designing functional validation tests, and for improving disease classifications. We applied this approach to the RAS gene family encoding seven distinct proteins and their 935 unique missense variants present somatically in cancer, in rare diseases (termed RASopathies), and in the currently healthy adult population. This knowledge shows that protein structure-based scores are distinct from information available from genomic annotation, that they are useful for interpreting genomic variants, and they should be taken into consideration in future guidelines for genomic data interpretation.\n\nSignificance StatementGenetic information from patients is a powerful data type for understanding individual differences in disease risk and treatment, but most of the genetic variation we observe has no mechanistic interpretation. This lack of interpretation limits the use of genomics data in clinical care. Standard methods for genomics data interpretation take advantage of annotations available for the human reference genome, but they do not consider the 3D protein molecule. We believe that changes to the 3D molecule must be considered, to augment current practice and lead to more precise interpretation. In this work, we present our initial process for systematic multi-level molecular scores, including 3D, to interrogate 935 RAS-family variants that are relevant in both cancer and rare diseases.

genetics↗

bioRxiv2019

Molecular determinants of chaperone interactions on MHC-I for folding and antigen repertoire selection

The interplay between a highly polymorphic set of MHC-I alleles and molecular chaperones shapes the repertoire of peptide antigens displayed on the cell surface for T cell surveillance. Here, we demonstrate that the molecular chaperone TAPBPR associates with a broad range of partially folded MHC-I species inside the cell. Bimolecular fluorescence complementation and deep mutational scanning reveal that TAPBPR recognition is polarized towards one side of the peptide-binding groove, and depends on the formation of a conserved MHC-I disulfide epitope in the 2 domain. Conversely, thermodynamic measurements of TAPBPR binding for a representative set of properly conformed, peptide-loaded molecules suggest a narrower MHC-I specificity range. Using solution NMR, we find that the extent of dynamics at \"hotspot\" surfaces confers TAPBPR recognition of a sparsely populated MHC-I state attained through a global conformational change. Consistently, restriction of MHC-I groove plasticity through the introduction of a disulfide bond between the 1/2 helices abrogates TAPBPR binding, both in solution and on a cellular membrane, while intracellular binding is tolerant of many destabilizing MHC-I substitutions. Our data support parallel TAPBPR functions of i) chaperoning unstable MHC-I molecules at early stages of their folding process, akin to a holdase with broad allele-specificity, and ii) editing the peptide cargo of properly conformed MHC-I molecules en route to the surface, which demonstrates a narrower specificity. Our results suggest that TAPBPR exploits localized structural adaptations, both near and distant to the peptide-binding groove, to selectively recognize discrete conformational states sampled by MHC-I alleles, towards editing Sithe repertoire of displayed antigens.\n\nSignificance StatementThe human population contains thousands of MHC-I alleles, showing a range of dependencies on molecular chaperones for loading of their peptide cargo, which are then displayed on the cell surface for T cell surveillance. Using the chaperone TAPBPR as a model, we combine deep mutagenesis with functional and biophysical data, especially solution NMR, to provide a complete view of the molecular determinants of chaperone recognition. Our data provide significant evidence that localized protein motions define the intrinsic ability of MHC-I molecules to interact with chaperones. The importance of MHC-I dynamics unifies all our findings, with broad recognition of conformationally unstable, nascent MHC-I molecules becoming restricted to a smaller set of MHC-I alleles that retain relevant dynamic motions in their folded state.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC=\"FIGDIR/small/779777v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (66K):\norg.highwire.dtl.DTLVardef@19da2fforg.highwire.dtl.DTLVardef@383607org.highwire.dtl.DTLVardef@63171eorg.highwire.dtl.DTLVardef@182bf14_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDeep mutagenesis identifies a conformational disulfide-linked epitope as the main requirement for association of nascent MHC-I molecules with the TAPBPR chaperone\nC_LIO_LIAnalysis of s-ms timescale conformational dynamics by methyl NMR reveals allele-specific profiles at the TAPBPR interaction surfaces of peptide-loaded MHC-I molecules\nC_LIO_LIs-ms dynamics dictate the specificity of TAPBPR interactions for different MHC-I alleles through the sampling of a minor, \"excited state\" conformation\nC_LIO_LIRestriction of dynamics though an engineered disulfide bond abrogates interactions with TAPBPR, both in solution and on a cellular membrane\nC_LI

immunology↗

bioRxiv2019

Protein dynamics regulate distinct biochemical properties of cryptochromes in mammalian circadian rhythms

Circadian rhythms are generated by a transcription-based feedback loop where CLOCK:BMAL1 drive transcription of their repressors (PER1/2, CRY1/2), which bind to CLOCK:BMAL1 to close the feedback loop with ~24-hour periodicity. Here we identify a key biochemical and structural difference between CRY1 and CRY2 that underlies their differential strengths as transcriptional repressors. While both cryptochromes bind the BMAL1 transactivation domain with similar affinity to sequester it from coactivators, CRY1 is recruited with much higher affinity to the PAS domain core of CLOCK:BMAL1, allowing it to serve as a stronger repressor that lengthens circadian period. We identify a dynamic loop in the secondary pocket that regulates differential binding of cryptochromes to the PAS domain core. Notably, PER2 binding remodels this loop in CRY2 to enhance its affinity for CLOCK:BMAL1, explaining why CRY2 forms an obligate heterodimer with PER2, while CRY1 is capable of repressing CLOCK:BMAL1 both with and without PER2.

biochemistry↗

bioRxiv2019

Casein kinase 1 dynamics underlie the PER2 circadian phosphoswitch

Post-translational control of PERIOD stability by Casein Kinase 1{delta} and {varepsilon} (CK1) plays a key regulatory role in metazoan circadian rhythms. Despite the deep evolutionary conservation of CK1 in eukaryotes, little is known about its regulation and the factors that influence substrate selectivity on functionally antagonistic sites in PERIOD that directly control circadian period. Here we describe a molecular switch involving a highly conserved anion binding site in CK1. This switch controls conformation of the activation loop to define substrate selectivity on mammalian PER2, thereby directly regulating its stability. Integrated experimental and computational studies shed light on the allosteric linkage between two anion binding sites that dynamically regulate kinase activity. We show that period-altering kinase mutations from humans to Drosophila differentially modulate this activation loop switch to elicit predictable changes in PER2 stability, providing a foundation to understand and further manipulate CK1 regulation of circadian rhythms.

biochemistry↗

bioRxiv2019

A Mechanism for Epithelial-Mesenchymal Heterogeneity in a Population of Cancer Cells

Epithelial-mesenchymal heterogeneity, wherein cells within the same tumor can exhibit an epithelial, a mesenchymal, or one or more hybrid epithelial-mesenchymal phenotype(s), has been observed across cancer types and implicated in metastatic aggressiveness. Here, we have used computational modeling to show that this heterogeneity can emerge from the noise in the partitioning of RNAs and proteins among the daughter cells during cancer cell division. Our model captures the population-level behavior of murine prostate cancer cells, the hysteresis in the dynamics of epithelial-mesenchymal plasticity, and how hybrid phenotype-promoting factors alter the phenotypic composition of a population. We further used the model to describe the implications of heterogeneity for therapeutics. By linking the dynamics of an intracellular regulatory circuit to the phenotypic composition of a population, the study contributes towards understanding how non-genetic heterogeneity can be generated and propagated from a small, homogeneous population, and towards therapeutic targeting of cancer cell heterogeneity.

cancer biology↗

bioRxiv2019

The regulatory factor ELF1 triggers a critical wave of transcription in the antiviral response to type I interferon

The transcription of interferon-stimulated genes (ISGs) is classically triggered via activation of the JAK-STAT pathway, and together, ISGs raise a multifaceted antiviral barrier. An increasing body of evidence reports the existence of additional, non-canonical pathways and transcription factors that coordinate ISG expression. Detailed knowledge of how heterogenous mechanisms regulate ISG expression is crucial for the rational design of drugs targeting the type I interferon response. Here, we characterize the first ETS transcription factor family member as a regulator of non-canonical ISG expression: E74-like ETS transcription factor 1 (ELF1). Using high-content microscopy to quantify viral infection over time, we found that ELF1, itself an ISG, inhibits eight diverse RNA and DNA viruses uniquely at multi-cycle replication. ELF1 did not regulate expression of type I or II interferons, and ELF1s antiviral effect was not abolished by the absence of STAT1 or by inhibition of JAK phosphorylation. Accordingly, comparative expression analyses by RNAseq revealed that the ELF1 transcriptional program is distinct from, and delayed with respect to, the immediate interferon response. Finally, knockdown experiments demonstrated that ELF1 is a critical component of the antiviral interferon response in vitro and in vivo. Our findings reveal a previously overlooked mechanism of non-canonical ISG regulation that both amplifies and prolongs the initial interferon response by expressing broadly antiviral restriction factors. AUTHOR SUMMARYOver 60 years after their discovery, we still struggle to understand exactly how interferons inhibit viruses. Our gap in knowledge stems, on one hand, from the sheer number of interferon-stimulated effector genes, of which only few have been characterized in mechanistic detail. On the other hand, our knowledge of interferon-regulated gene transcription is constantly evolving. We know that different regulatory mechanisms greatly influence the quality, magnitude, and timing of interferon-stimulated gene expression, all of which may contribute to the antiviral mechanism of interferons. Deciphering these regulatory mechanisms is indispensable for understanding this critical first line of host defense, and for harnessing the power of interferons in novel antiviral therapies. Here, we report a novel mechanism of interferon-induced gene regulation by an interferon-stimulated gene, which, paradoxically, inhibits viruses in the absence of additional interferon signaling: E74-like ETS transcription factor 1 (ELF1) raises an unusually delayed antiviral program that potently restricts propagation of all viruses tested in our study. Reduced levels of ELF1 significantly diminished interferon-mediated host defenses against influenza A virus in vitro and in vivo, suggesting a critical but previously overlooked role in the type I interferon response. The transcriptional program raised by ELF1 is vast and comprises over 400 potentially antiviral genes, which are almost entirely distinct from those known to be induced by interferon. Taken together, our data provide evidence for a critical secondary wave of antiviral protection that adds both "quality" and "time" to the type I interferon response.

immunology↗

bioRxiv2018

Murine MPDZ-Linked Hydrocephalus is Caused by Hyperpermeability of the Choroid Plexus

Though congenital hydrocephalus is heritable, it has been linked only to eight genes, one of which is MPDZ. Humans and mice that carry a truncated version of MPDZ incur severe hydrocephalus resulting in acute morbidity and lethality. We show by magnetic resonance imaging that contrast-medium penetrates into the brain ventricles of mice carrying a Mpdz loss-of-function mutation, whereas none is detected in the ventricles of normal mice, implying that the permeability of the choroid plexus epithelial cell monolayer is abnormally high. Comparative proteomic analysis of the cerebrospinal fluid of normal and hydrocephalic mice revealed up to a 53-fold increase in protein concentration, suggesting that transcytosis through the choroid plexus epithelial cells of Mpdz KO mice is substantially higher than in normal mice. These conclusions are supported by ultrastructural evidence, and by immunohistochemistry and cytology data. Our results provide a straight-forward and concise explanation for the pathophysiology of Mpdz-linked hydrocephalus.

neuroscience↗

bioRxiv2018

Modern botanical analogue of endangered Yak (Bos mutus) dung from India: Plausible linkage with living and extinct megaherbivores

The study present to document the micro and macrobotanical remain on wild Yak dung to understand the diet, habitat, and ecology in relation to determining possible ecological relationships with extant and extinct megaherbivores. Grasses are the primary diet of the yak as indicated by the abundance of grass pollen and phytoliths, though it is obvious. The other associates non-arboreal and arboreal taxa namely, Cyperacaeae, Rosaceae, Chenopodiaceae, Artemisia, Prunus, and Rhododendron are also important dietary plants for their survival. The observation of plant macrobotanical remains especially the vegetative part and seed of the grasses and Cyperaceae also indicates good agreement with the palynodata. The documented micro and macrobotanical data is indicative of both Alpine meadow and steppe vegetation under cold and dry climate which exactly reflected the current vegetation composition and climate in the region. The recovery of Botryococcus, Arcella, and diatom was marked though in trace values and suggestive of the perennial water system in the region which incorporated through the ingestion of water. Energy dispersive spectroscopy analysis marked that the element contained in dung samples has variation in relation to the summer and winter which might be the availability of the food plants and vegetation. This generated multiproxy data serves as a strong supplementary data for modern pollen and vegetation relationship based on surface soil samples in the region. The recorded multiproxy data could be useful to interpret the coprolites of herbivorous fauna in relation to the palaeodietary and paleoecology in the region and to correlate with other mega herbivores in a global context.

paleontology↗

bioRxiv2017

A deep convolutional neural network approach for astrocyte detection

Astrocytes are involved in brain pathologies such as trauma or stroke, neurodegenerative disorders like Alzheimers and Parkinsons disease, chronic pain, and many others. Determining cell density and timing of morphological and biochemical changes is important for a proper understanding of the role of astrocytes in physiological and pathological conditions. One of the most important of such analyses is astrocytes count within a complex tissue environment in microscopy images. The most widely used approaches for the quantification of microscopy images data are either manual stereological cell counting or semi-automatic segmentation techniques. Detecting astrocytes automatically is a highly challenging computational task, for which we currently lack efficient image analysis tools. In this study, we developed a fast and fully automated software that assesses the number of astrocytes using Deep Convolutional Neural Networks (DCNN). The method highly outperforms state-of-the-art image analysis and machine learning methods and provides detection accuracy and precision comparable to that of human experts. Additionally, the runtime of cell detection is significantly less than other three analyzed computational methods, and it is faster than human observers by orders of magnitude. We applied DCNN-based method to examine the number of astrocytes in different brain regions of rats with opioid-induced hyperalgesia/tolerance (OIH/OIT) as morphine tolerance is believed to activate glial cells in the brain. We observed strong positive correlation between manual cell detection and DCNN-based analysis method for counting astrocytes in the brains of experimental animals.

bioinformatics↗

bioRxiv2017

The standard genetic code facilitates exploration of the space of functional nucleotide sequences

The standard genetic code is well known to be optimized for minimizing the phenotypic effects of single nucleotide substitutions, a property that was likely selected for during the emergence of a universal code. Given the fitness advantage afforded by high standing genetic diversity in a population in a dynamic environment, it is possible that selection to explore a large fraction of the space of functional proteins also occurred. To determine whether selection for such a property played a role during the emergence of the nearly universal genetic code, we investigated the number of functional variants of the Escherichia coli PhoQ protein explored at different time scales under translation using different genetic codes. We found that the standard genetic code is highly optimal for exploring a large fraction of the space of functional PhoQ variants at intermediate time scales as compared to random codes. Environmental changes, in response to which genetic diversity in a population provides a fitness advantage, are likely to have occurred at these intermediate time scales. Our results indicate that the ability of the standard code to explore a large fraction of the space of functional sequence variants arises from a balance between robustness and flexibility and is largely independent of the property of the standard code to minimize the phenotypic effects of mutations. We propose that selection to explore a large fraction of the functional sequence space while minimizing the phenotypic effects of mutations contributed towards the emergence of the standard code as the universal genetic code.

evolutionary biology↗

bioRxiv2017

Analysis of hierarchical organization in gene expression networks reveals underlying principles of collective tumor cell dissemination and metastatic aggressiveness of inflammatory breast cancer

BackgroundClusters of circulating tumor cells (CTCs), despite being rare, may account for more than 95% of metastases. Cells in these clusters do not undergo a complete epithelial-to-mesenchymal transition (EMT) but retain some epithelial traits as compared to individually disseminating tumor cells. Determinants of single cell dissemination versus collective dissemination remain elusive. Inflammatory breast cancer (IBC), a highly aggressive breast cancer subtype that chiefly metastasizes via CTC clusters, is a promising model for studying mechanisms of collective tumor cell dissemination. Previous studies on breast cancer and adult acute myeloid leukemia, motivated by a theory that suggests physical systems with hierarchical organization tend to be more adaptable, have found that the expression of metastasis associated genes is more hierarchically organized in cases of successful metastases.\n\nMethodsWe used the cophenetic correlation coefficient (CCC) to quantify the hierarchical organization in the expression networks of two distinct gene sets, collective dissemination associated genes and IBC associated genes, in cancer cell lines and in tumor samples from breast cancer patients. Hypothesizing that a higher CCC for collective dissemination associated genes and for IBC associated genes would be associated with a more evident epithelial phenotype and with worse outcomes in breast cancer patients, we evaluated the correlation of CCC with different phenotypic groups.\n\nResultsThe CCC of both gene networks, the collective dissemination associated gene network and the IBC associated gene network, was higher in (a) epithelial cell lines as compared to mesenchymal cell lines and (b) tumor samples from IBC patients, as compared to samples from non-IBC breast cancer patients. A higher CCC of both networks was also correlated with a higher rate of metastatic relapse in breast cancer patients. Neither the levels of CDH1 gene expression, nor gene set enrichment analysis could provide similar insights.\n\nConclusionsThese results suggest that retention of some epithelial traits in disseminating tumor cells as IBC progresses promotes successful breast cancer metastasis to distant organs. The CCC provides additional information regarding the organizational complexity of gene expression in comparison to differential gene expression analyses. We have shown that the CCC may be a useful metric for investigating the collective dissemination phenotype and a prognostic factor for IBC.

cancer biology↗