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Singh, A.

Publications and source records attributed to Singh, A..

At least 559 records · Page 31Linked to original sources

Stochastic dynamics of consumer-resource interactions

The interaction between a consumer (such as, a predator or a parasitoid) and a resource (such as, a prey or a host) forms an integral motif in ecological food webs, and has been modeled since the early 20th century starting from the seminal work of Lotka and Volterra. While the Lotka-Volterra predator-prey model predicts a neutrally stable equilibrium with oscillating population densities, a density-dependent predator attack rate is known to stabilize the equilibrium. Here, we consider a stochastic formulation of the Lotka-Volterra model where the preys reproduction rate is a random process, and the predators attack rate depends on both the prey and predator population densities. Analysis shows that increasing the sensitivity of the attack rate to the prey density attenuates the magnitude of stochastic fluctuations in the population densities. In contrast, these fluctuations vary non-monotonically with the sensitivity of the attack rate to the predator density with an optimal level of sensitivity minimizing the magnitude of fluctuations. Interestingly, our systematic study of the predator-prey correlations reveals distinct signatures depending on the form of the density-dependent attack rate. In summary, stochastic dynamics of nonlinear Lotka-Volterra models can be harnessed to infer density-dependent mechanisms regulating consumer-resource interactions. Moreover, these mechanisms can have contrasting consequences on population fluctuations, with predator-dependent attack rates amplifying stochasticity, while prey-dependent attack rates countering to buffer fluctuations.

ecology↗

H3K27me3 mediated KRT14 upregulation promotes TNBC peritoneal metastasis

Triple Negative Breast Cancer (TNBC) is known to have poor prognosis and adverse clinical outcome among all breast cancer subtypes due to the absence of available targeted therapy for it. Emerging literature indicates that epigenetic reprogramming is now appreciated as a driving force for TNBC pathophysiology. High expression of epigenetic modulator EZH2 (Enhancer of zeste homolog 2) has been shown to correlate with TNBC poor prognosis but the contribution of EZH2 catalytic (H3K27me3) versus non-catalytic EZH2 (NC-EZH2) function in TNBC growth and progression remains elusive. In the process of dissecting the impact of H3K27me3 versus NC-EZH2 function in TNBC pathogenesis, we reveal that selective hyperactivation of H3K27me3 over NC-EZH2 not only promotes TNBC metastasis but also alters the metastatic landscape of TNBC. Using extensive in- vivo live animal imaging, we present conclusive evidence that peritoneal metastasis, particularly splenic metastasis of TNBC is governed by H3K27me3. Transcriptome analyses of hyperactive H3K27me3 cells lead us to discover Cytokeratin-14 (KRT14) as a new target of H3K27me3. Unlike classical H3K27me3 mediated suppression of gene expression, here; we observe that H3K27me3 enhances KRT14 transcription by attenuating the binding of transcriptional repressor Sp1 to its promoter. Further, loss of KRT14 significantly reduces TNBC migration, invasion and splenic metastasis. Finally, genetic ablation of EZH2 or pharmacological inhibition of EZH2 catalytic function by FDA approved drug tazemetostat (EPZ6438) robustly inhibits TNBC peritoneal metastasis. Altogether, our preclinical findings posit a rational insight for the clinical development of H3K27me3 inhibitor like tazemetostat as a targeted therapy against TNBC.

cancer biology↗

AhNGE : A Database for Arachis hypogaea Nodule Developmental Gene Expression

Symbiotic nitrogen fixation (SNF) inside root-nodules is a primary and sustainable source of soil nitrogen. Understanding nodule development and metabolism in crop legumes may lead to more effective SNF in agriculture. Peanut (Arachis hypogaea) is an economically important allotetraploid legume with non-canonical nodule developmental features. Recent genome sequencing of peanut has opened the possibility of making peanut a model for studying atypical nodule development. To help the community of nodule biologists, we have developed a database called AhNGE (Arachis hypogaea Nodule Developmental Gene Expression: http://nipgr.ac.in/AhNGE/index.php). AhNGE contains RNAseq data from six data points of nodule development in A. hypogagea cv. Tifrunner. This data represents a dynamic view of gene expression during peanut nodule development. Research in model legumes has generated a huge knowledgebase in the last twenty years. To streamline comparative genomics among legumes, we performed ortholog analysis among four legumes (Cicer, Glycine, Lotus, and Medicago) and one non-legume (Arabidopsis). This will facilitate the integration of existing knowledge in nodule development with the Arachis transcriptome. The available data can be retrieved using a single or batch query or searching using gene ID, from above mentioned five species. The output displays the gene expression pattern in graphical as well as tabular form, along with further options to download the sequence data. The database is linked with PeanutBase, the main genomic resource of peanut. Additionally, the expression level of different splicing variants can be retrieved from the database. In summary, AhNGE serves as an important resource for the scientific community working on nodule development.

bioinformatics↗

Management of altered metabolic activity in Drosophila model of Huntington's disease by curcumin

Huntingtons disease (HD) is a devastating polyglutamine (polyQ) disorder characterized by extensive neurodegeneration and metabolic abnormalities at systemic, cellular and intracellular levels. Metabolic alterations in HD manifest as abnormal body weight, dysregulated biomolecule levels, impaired adipocyte functions and defective energy state which exacerbate disease progression and pose acute threat to the health of challenged individuals in form of insulin resistance, cardiovascular disease and energy crisis. To colossally mitigate disease symptoms, we tested the efficacy of curcumin in Drosophila model of HD. Curcumin is bioactive component of turmeric (Curcuma longa Linn), well-known for its ability to modulate metabolic activities. We found that curcumin effectively managed abnormal body weight, dysregulated lipid content and carbohydrate level in HD flies. In addition, curcumin administration lowered elevated reactive-oxygen-species (ROS) levels in adult adipose tissue of diseased flies, and improved survival and locomotor function in HD flies at advanced disease stage. Altogether, these findings clearly suggest that curcumin efficiently attenuates metabolic derangements in HD flies and can prove beneficial in alleviating the complexities associated with HD. Phytochemicals like curcumin that can regulate multiple targets in complex diseases like HD, with least side-effects and maximum benefits, provide a better hope for the treatment of terminally-ill HD patients.

neuroscience↗

MicroRNA775 and target Galactosyltransferase (GALT9) module regulates recovery from submergence induced senescence by modulating SAGs in Arabidopsis thaliana

Submergence induced hypoxic condition is one of the abiotic stresses which negatively affects the plant growth and development, and causes early onset of senescence. Hypoxic conditions ateres the expression of a number of non-coding microRNAs (miRNAs), besides protein-coding genes. However, the molecular function of stress-induced miRNA in submergence induced physiological or developmental changes and recovery remains to be understood. The expression of miR775 is highly induced under hypoxic stress conditions. Here, we show that miR775 is a potential post-transcriptional regulator number of targets, including Galactosyltransferase (GALT9). The expression of miR775 and target GALT9 was significantly induced and reduced respectively at 24 hours of submergence. The overexpression of miR775 (miR775-Oe) confers enhanced recovery from submergence stress and reduced accumulation of ROS, in contrast to wild type and endogenous target mimic of miR775 (MIM775) Arabidopsis plants. We observed a similar recovery phenotype in case of target galt9 mutant plants, indicating the role of miR775-GALT9 module in recovery from submergence. Further, we showed that the expression of SENESCENCE ASSOCIATED GENES (SAGs), such as SAG12, SAG29, and ORE1. was increased in MIM775 and reduced in miR775-Oe and galt9 plants. Thus, our results suggest that miR775-GALT9 module plays a crucial role in the recovery from submergence by modulating the expression of SAGs through differential accumulation of ROS.

plant biology↗

microRNA775 targets a β-(1,3)-galactosyltransferase to regulate growth and development in Arabidopsis thaliana

MicroRNAs are critical regulators of gene expression in plants and other organisms, and are involved in regulating plethora of developmental processes. Evolutionarily, miRNAs can be ancient and conserved across species or recently evolved and young, which are not conserved across diverse plant groups. miR775 is a non-conserved miRNA identified only in Arabidopsis thaliana. Here, we investigated the functional significance of miR775 in A. thaliana and observed that miR775 targets a probable {beta}-(1,3)-galactosyltransferase gene at post transcriptional level. Phenotypic analysis of miR775 over-expression lines and the target mutant suggested miR775 regulates rosette size by elongating petiole length and increasing leaf area. Further, the expression of miR775 was found to be up-regulated in response to UV-B and hypoxia. Our results also suggest that miR775 regulated {beta}-(1,3)-galactosyltransferase may involve in regulating the {beta}-(1,3)-galactan content of arabinogalactans. Collectively, our findings establish a role of miR775 in regulating growth and development in A. thaliana. HighlightsO_LIThe role of an uncharacterized microRNA, miR775 has been explored C_LIO_LImiR775 targets a probable {beta}-(1,3)-galactosyltransferase involved in complex carbohydrate biosynthesis C_LIO_LImiR775 regulates rosette size in A. thaliana and may play role under UV light and hypoxia C_LI

plant biology↗

Abolished miR158 activity leads to 21-nucleotide tertiary phasiRNA biogenesis that targets NHX2 in Arabidopsis thaliana

Small RNAs including microRNAs (miRNAs) are short 20-24-nucleotide non-coding RNAs. They are key regulators of gene expression in plants and other organisms. Some small RNAs, mostly 22-nucleotide long trigger biogenesis of secondary small interfering RNAs (siRNAs). Those siRNAs having distinctive phased configuration are known as phased siRNAs (phasiRNAs) and act either in cis or trans enhancing silencing cascade. Here, we report natural variants of MIR158 having deletions or insertions led to negligible or reduced expression of miR158. The deletion/insertion events affected processing of primary transcript of miR158 to precursor and to mature miR158. We show that miR158 targets a pseudo-pentatricopeptide gene and its abolished activity led to 21-nucleotide tertiary phasiRNA generation from its target. The biogenesis of these phasiRNAS is triggered by TAS2 derived two siRNAs. Accordingly, small RNA analyses of these natural variants, mutants and over-expression lines of MIR158 or its target exhibited enhanced or reduced phasiRNA biogenesis. Finally, we functionally validated the highest expressed tertiary phasiRNA that targets NHX2 thereby regulating transpiration and stomatal conductance. Overall, we deciphered a new module of small RNA network, miRNA-TAS-siRNA-pseudogene-tertiary phasiRNA-NHX2, suggesting an additional layer of gene regulation and larger role of pseudogene in plants.

plant biology↗

Profiling acetogenic community dynamics in anaerobic digesters - comparative analyses using next-generation sequencing and T-RFLP

Acetogens play a key role in anaerobic degradation of organic material and in maintaining biogas process efficiency. Profiling this community and its temporal changes can help evaluate process stability and function, especially under disturbance/stress conditions, and avoid complete process failure. The formyltetrahydrofolate synthetase (FTHFS) gene can be used as a marker for acetogenic community profiling in diverse environments. In this study, we developed a new high-throughput FTHFS gene sequencing method for acetogenic community profiling and compared it with conventional T-RFLP of the FTHFS gene, 16S rRNA gene-based profiling of the whole bacterial community, and indirect analysis via 16S rRNA profiling of the FTHFS gene-harbouring community. Analyses and method comparisons were made using samples from two laboratory-scale biogas processes, one operated under stable control and one exposed to controlled overloading disturbance. Comparative analysis revealed satisfactory detection of the bacterial community and its changes for all methods, but with some differences in resolution and taxonomic identification. FTHFS gene sequencing was found to be the most suitable and reliable method to study acetogenic communities. These results pave the way for community profiling in various biogas processes and in other environments where the dynamics of acetogenic bacteria have not been well studied. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/427894v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@14ac78org.highwire.dtl.DTLVardef@1472ea3org.highwire.dtl.DTLVardef@46fc19org.highwire.dtl.DTLVardef@50ce7a_HPS_FORMAT_FIGEXP M_FIG C_FIG ONE SENTENCE SUMMARYOur high-throughput FTHFS gene AmpSeq method for barcoded samples and unsupervised analysis with AcetoScan accurately reveals temporal dynamics of acetogenic community structure in anaerobic digesters.

microbiology↗

Prioritizing and characterizing functionally relevant genes across human tissues

Knowledge of genes that are critical to a tissues function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model - FUGUE - combining transcriptional and network features, to predict tissue-relevant genes across 30 human tissues. FUGUE achieves an average cross-validation auROC of 0.86 and auPRC of 0.50 (expected 0.09). In three independent datasets, FUGUE accurately distinguishes tissue or cell type-specific genes, significantly outperforming the conventional metric based on tissue-specific expression alone. Comparison of tissue-relevant transcription factors across tissue recapitulate their developmental relationships. Interestingly, the tissue-relevant genes cluster on the genome within topologically associated domains and furthermore, are highly enriched for differentially expressed genes in the corresponding cancer type. We provide the prioritized gene lists in 30 human tissues and an open-source software to prioritize genes in a novel context given multi-sample transcriptomic data.

systems biology↗

A transcriptionally distinct subpopulation of healthy acinar cells exhibit features of pancreatic progenitors and PDAC

Pancreatic ductal adenocarcinoma (PDAC) tumors can originate either from acinar or ductal cells in the adult pancreas. We re-analyze multiple pancreas and PDAC single-cell RNA-seq datasets and find a subset of non-malignant acinar cells, which we refer to as acinar edge (AE) cells, whose transcriptomes highly diverge from a typical acinar cell in each dataset. Genes up-regulated among AE cells are enriched for transcriptomic signatures of pancreatic progenitors, acinar dedifferentiation, and several oncogenic programs. AE-upregulated genes are up-regulated in human PDAC tumors, and consistently, their promoters are hypo-methylated. High expression of these genes is associated with poor patient survival. The fraction of AE-like cells increases with age in healthy pancreatic tissue, which is not explained by clonal mutations, thus pointing to a non-genetic source of variation. We also find edge-like states in lung and liver tissues, suggesting that sub-populations of healthy cells across tissues can exist in pre-malignant states.

genomics↗

Population dynamics of multi-host communities attacked by a common parasitoid

We model population dynamics of two host species attacked by a common parasitoid using a discrete-time formalism that captures their population densities from year to year. It is well known starting from the seminal work of Nicholson and Bailey that a constant parasitoid attack rate leads to an unstable host-parasitoid interaction. However, a Type III functional response, where the parasitoid attack rate accelerates with increasing host density stabilizes the population dynamics. We first consider a scenario where both host species are attacked by a parasitoid with the same Type III functional response. Our results show that sufficient fast acceleration of the parasitoid attack rate stabilizes the population dynamics of all three species. For two symmetric host species, the extent of acceleration needed to stabilize the three-species equilibrium is exactly the same as that needed for a single host-parasitoid interaction. However, asymmetry can lead to scenarios where the removal of a host species from a stable interaction destabilizes the interaction between the remaining host species and the parasitoid. Next, we consider a situation where one of the host species is attacked at a constant rate (i.e., Type I functional response), and the other species is attacked via a Type III functional response. We identify parameter regimes where a Type III functional response to just one of the host species stabilizes the three species interaction. In summary, our results show that a generalist parasitoid with a Type III functional response to one or many host species can play a key role in stabilizing population dynamics of host-parasitoid communities in apparent competition.

ecology↗

Testing the efficacy of hyperspectral (AVIRIS-NG), multispectral (Sentinel-2) and radar (Sentinel-1) remote sensing images to detect native and invasive non-native trees

Invasive alien species (IAS) threaten tropical grasslands and native biodiversity and impact ecosystem service delivery, ecosystem function, and associated human livelihoods. Tropical grasslands have been dramatically and disproportionately lost to invasion by trees. The invasion continues to move rapidly into the remaining fragmented grasslands impacting various native grassland-dependent species and water streamflow in tropical montane habitats. The Shola Sky Islands of the Western Ghats host a mosaic of native grasslands and forests; of which the grasslands have been lost to exotic tree invasion (Acacias, Eucalyptus and Pines) since the 1950s. The invasion intensities, however, differ between these species wherein Acacia mearnsii and Pinus patula are highly invasive in contrast to Eucalyptus globulus. These disparities necessitate distinguishing these species for effective grassland restoration. Further, these invasive alien trees are highly intermixed with native species, thus requiring high discrimination abilities to native species apart from the non-native species. Here we assess the accuracy of various satellite and airborne remote sensing sensors and machine learning classification algorithms to identify the spatial extent of native habitats and invasive trees. Specifically, we test Sentinel-1 SAR and Sentinel-2 multispectral data and assess high spatial and spectral resolution AVIRIS-NG imagery identifying invasive species across this landscape. Sensor combinations thus include hyperspectral, multispectral and radar data and present tradeoffs in associated costs and ease of procurement. Classification methods tested include Support Vector Machine (SVM), Classification and Regression Trees (CART) and Random Forest (RF) algorithms implemented on the Google Earth Engine platform. Results indicate that AVIRIS-NG data in combination with SVM recover the highest classification skill (Overall -98%, Kappa-0.98); while CART and RF yielded < 90% accuracy. Fused Sentinel-1 and Sentinel-2 produce 91% accuracy, while Sentinel-2 alone yielded 91% accuracy with RF and SVM classification; but only with higher coverage of ground control points. AVIRIS-NG imagery was able to accurately (97%) demarcate the Acacia invasion front while Sentinel-1 and Sentinel-2 data failed. Our results suggest that Sentinel-2 images could be useful for detecting the native and non-native forests with more ground truth points, but hyperspectral data (AVIRIS-NG) permits distinguishing, native and non-native tree species and recent invasions with high precision using limited ground truth points. We suspect that large areas will have to be mapped and assessed in the coming years by conservation managers, NGOs to plan restoration, or to assess the success of restoration activities, and several data procurement and analysis steps may have to be simplified.

ecology↗

Fluctuations in population densities inform stability mechanisms in host-parasitoid interactions

Population dynamics of host-parasitoid interactions has been traditionally studied using a discrete-time formalism starting from the classical work of Nicholson and Bailey. It is well known that differences in parasitism risk among individual hosts can stabilize the otherwise unstable equilibrium of the Nicholson-Bailey model. Here, we consider a stochastic formulation of these discrete-time models, where the host reproduction is a random variable that varies from year to year and drives fluctuations in population densities. Interestingly, our analysis reveals that there exists an optimal level of heterogeneity in parasitism risk that minimizes the extent of fluctuations in the host population density. Intuitively, low variation in parasitism risk drives large fluctuations in the host population density as the system is on the edge of stability. In contrast, high variation in parasitism risk makes the host equilibrium sensitive to the host reproduction rate, also leading to large fluctuations in the population density. Further results show that the correlation between the adult host and parasitoid densities is high for the same year, and gradually decays to zero as one considers cross-species correlations across different years. We next consider an alternative mechanism of stabilizing host-parasitoid population dynamics based on a Type III functional response, where the parasitoid attack rate accelerates with increasing host density. Intriguingly, this nonlinear functional response makes qualitatively different correlation signatures than those seen with heterogeneity in parasitism risk. In particular, a Type III functional response leads to uncorrelated adult and parasitoid densities in the same year, but high cross-species correlation across successive years. In summary, these results argue that the cross-correlation function between population densities contains signatures for uncovering mechanisms that stabilize consumer-resource population dynamics.

ecology↗

Glycolysis downregulation is a hallmark of HIV-1 latency and sensitizes infected cells to oxidative stress

HIV-1 infects lymphoid and myeloid cells, which can harbor a latent proviral reservoir responsible for maintaining lifelong infection. Glycolytic metabolism has been identified as a determinant of susceptibility to HIV-1 infection, but its role in the development and maintenance of HIV-1 latency has not been elucidated. By combining transcriptomic, proteomic and metabolomic analysis, we here show that transition to latent HIV-1 infection downregulates glycolysis, while viral reactivation by conventional stimuli reverts this effect. Decreased glycolytic output in latently infected cells is associated with downregulation of NAD+/NADH. Consequently, infected cells rely on the parallel pentose phosphate pathway and its main product, the antioxidant NADPH, fueling antioxidant pathways maintaining HIV-1 latency. Of note, blocking NADPH downstream effectors, thioredoxin and glutathione, favors HIV-1 reactivation from latency in lymphoid and myeloid cellular models. This provides a "shock and kill effect" decreasing proviral DNA in cells from people-living-with-HIV/AIDS. Overall, our data show that downmodulation of glycolysis is a metabolic signature of HIV-1 latency that can be exploited to target latently infected cells with eradication strategies.

immunology↗

Cell size distribution of lineage data: analytic results and parameter inference

Recent advances in single-cell technologies have enabled time-resolved measurements of the cell size over several cell cycles. This data encodes information on how cells correct size aberrations so that they do not grow abnormally large or small. Here we formulate a piecewise deterministic Markov model describing the evolution of the cell size over many generations, for all three cell size homeostasis strategies (timer, sizer, and adder). The model is solved to obtain an analytical expression for the non-Gaussian cell size distribution in a cell lineage; the theory is used to understand how the shape of the distribution is influenced by the parameters controlling the dynamics of the cell cycle and by the choice of cell tracking protocol. The theoretical cell size distribution is found to provide an excellent match to the experimental cell size distribution of E. coli lineage data collected under various growth conditions.

systems biology↗

Generalized conditions for coexistence of competing parasitoids on a shared host

Motivated by the univoltine life histories of insects residing in the temperate-regions of the world, there is a rich tradition of modeling arthropod host-parasitoid interactions using a discrete-time formalism. We introduce a general class of discrete-time models for capturing the population dynamics of two competing parasitoid species that attack the same vulnerable stage of the host species. These models are characterized by two density-dependent functions: an escape response defined by the fraction of hosts escaping parasitism; and a competition response defined by the fraction of parasitized hosts that develop into adult parasitoids of either species. Model analysis reveals remarkably simple stability conditions for the coexistence of competing parasitoids. More specifically, coexistence occurs, if and only if, the adult host density increases with host reproduction rate, and the log sensitivity of the competition response is less than half. The latter condition implies that any increase in the adult parasitoid density will result in a sufficiently slow increase in the fraction of parasitized hosts that develop into parasitoids of that type. We next consider a model motivated by differences in parasitism risk among individual hosts with risk from the two parasitoid species assumed to be independently distributed as per a Gamma distribution. In such models, the heterogeneity in host risk to each parasitoid is quantified by the corresponding Coefficient of Variation (CV). Our results show that parasitoid coexistence occurs for sufficiently large reproduction rate, if and only if, the sum of the inverse of the two CV squares is less than one. This result generalizes the "CV greater than one" rule that defined the stability for a single parasitoid-host system to a multi parasitoid-host community.

ecology↗

Role of periodic forcing on the stochastic dynamics of a biomolecular clock

Biomolecular clocks produce sustained oscillations in mRNA/protein copy numbers that are subject to inherent copy-number fluctuations with important implications for proper cellular timekeeping. These random fluctuations embedded within periodic variations in copy numbers make the quantification of noise particularly challenging in stochastic gene oscillatory systems, unlike other non-oscillatory circuits. Motivated by diurnal cycles driving circadian clocks, we investigate the noise properties in the well-known Goodwin oscillator in the presence and absence of a periodic driving signal. We use two approaches to compute the noise as a function of time: (i) solving the moment dynamics derived from the linear noise approximation (LNA) assuming fluctuations are small relative to the mean and (ii) analyzing trajectories obtained from exact stochastic simulations of the Goodwin oscillator. Our results demonstrate that the LNA can predict the noise behavior quite accurately when the system shows damped oscillations or in the presence of external periodic forcing. However, the LNA could be misleading in the case of sustained oscillations without an external signal due to the propagation of large noise. Finally, we study the effect of random bursting of gene products on the clock stochastic dynamics. Our analysis reveals that the burst of mRNAs enhances the noise in the copy number regardless of the presence of external forcing, although the extent of fluctuations becomes less due to the forcing.

systems biology↗

VGLL1-directed TEAD activation drives endocrine therapy resistance in estrogen receptor positive breast cancer

Resistance to endocrine therapies (ET) is common in estrogen receptor (ER) positive breast cancer and most relapsed patients die with ET-resistant disease. While genetic mutations provide explanations for some relapsed patients1, mechanisms of resistance remain undefined in many cases. Drug-induced epigenetic reprogramming provides possible routes to resistance2. By analysing histone H3 lysine 27 acetylation (H3K27ac) profiles in models of ET resistance, we discovered that selective ER down-regulators (SERDs) such as fulvestrant promote epigenetic activation of VGLL1, a co-activator for TEAD transcription factors. We show that VGLL1, acting via TEADs, promotes expression of genes that drive growth of fulvestrant-resistant breast cancer cells. Pharmacological disruption of VGLL1/TEAD4 interaction inhibits VGLL1/TEAD transcriptional programmes to block growth of the resistant cells and prevents growth. Among the VGLL1/TEAD-regulated genes, we identify EGFR, whereby VGLL1-directed EGFR upregulation sensitises fulvestrant-resistant breast cancer cells to EGFR inhibitors. Taken together, our findings identify VGLL1 as a transcriptional driver in ET resistance and advance new therapeutic possibilities for relapsed ER+ breast cancer patients.

cancer biology↗