Browse
Submit Data
Databases
API
Help

Dataset Information

18 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells.

ABSTRACT: Resistance to anti-estrogen therapy is an unsolved clinical challenge in successfully treating ER+ breast cancer patients. Recent studies have demonstrated the role of non-genetic (i.e. phenotypic) adaptations in tolerating drug treatments; however, the mechanisms and dynamics of such non-genetic adaptation remain elusive. Here, we investigate coupled dynamics of epithelial-mesenchymal transition (EMT) in breast cancer cells and emergence of reversible drug resistance. Our mechanism-based model for underlying regulatory network reveals that these two axes can drive one another, thus enabling non-genetic heterogeneity in a cell population by allowing for six co-existing phenotypes: epithelial-sensitive, mesenchymal-resistant, hybrid E/M-sensitive, hybrid E/M-resistant, mesenchymal-sensitive and epithelial-resistant, with the first two ones being most dominant. Next, in a population dynamics framework, we exemplify the implications of phenotypic plasticity (both drug-induced and intrinsic stochastic switching) and/or non-genetic heterogeneity in promoting population survival in a mixture of sensitive and resistant cells, even in the absence of any cell-cell cooperation. Finally, we propose the potential therapeutic use of mesenchymal-epithelial transition inducers besides canonical anti-estrogen therapy to limit the emergence of reversible drug resistance. Our results offer mechanistic insights into empirical observations on EMT and drug resistance and illustrate how such dynamical insights can be exploited for better therapeutic designs.

SUBMITTER: Sahoo S

PROVIDER: S-EPMC8271219 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Emergence of drug resistance: implications for antiviral control of pandemic influenza.

Project description:Given the danger of an unprecedented spread of the highly pathogenic avian influenza strain H5N1 in humans, and great challenges to the development of an effective influenza vaccine, antiviral drugs will probably play a pivotal role in combating a novel pandemic strain. A critical limitation to the use of these drugs is the evolution of highly transmissible drug-resistant viral mutants. Here, we develop a mathematical model to evaluate the potential impact of an antiviral treatment strategy on the emergence of drug resistance and containment of a pandemic. The results show that elimination of the wild-type strain depends crucially on both the early onset of treatment in indexed cases and population-level treatment. Given the probable delay of 0.5-1 day in seeking healthcare and therefore initiating therapy, the findings indicate that a single strategy of antiviral treatment will be unsuccessful at controlling the spread of disease if the reproduction number of the wild-type strain (R0s) exceeds 1.4. We demonstrate the possible occurrence of a self-sustaining epidemic of resistant strain, in terms of its transmission fitness relative to the wild-type, and the reproduction number R0s. Considering reproduction numbers estimated for the past three pandemics, the findings suggest that an uncontrollable pandemic is likely to occur if resistant viruses with relative transmission fitness above 0.4 emerge. While an antiviral strategy is crucial for containing a pandemic, its effectiveness depends critically on timely and strategic use of drugs.

| S-EPMC2493585 | biostudies-literature

Recurrent Glioblastomas Reveal Molecular Subtypes Associated with Mechanistic Implications of Drug-Resistance.

Project description:Previously, transcriptomic profiling studies have shown distinct molecular subtypes of glioblastomas. It has also been suggested that the recurrence of glioblastomas could be achieved by transcriptomic reprograming of tumors, however, their characteristics are not yet fully understood. Here, to gain the mechanistic insights on the molecular phenotypes of recurrent glioblastomas, gene expression profiling was performed on the 43 cases of glioblastomas including 15 paired primary and recurrent cases. Unsupervised clustering analyses revealed two subtypes of G1 and G2, which were characterized by proliferation and neuron-like gene expression traits, respectively. While the primary tumors were classified as G1 subtype, the recurrent glioblastomas showed two distinct expression types. Compared to paired primary tumors, the recurrent tumors in G1 subtype did not show expression alteration. By contrast, the recurrent tumors in G2 subtype showed expression changes from proliferation type to neuron-like one. We also observed the expression of stemness-related genes in G1 recurrent tumors and the altered expression of DNA-repair genes (i.e., AURK, HOX, MGMT, and MSH6) in the G2 recurrent tumors, which might be responsible for the acquisition of drug resistance mechanism during tumor recurrence in a subtype-specific manner. We suggest that recurrent glioblastomas may choose two different strategies for transcriptomic reprograming to escape the chemotherapeutic treatment during tumor recurrence. Our results might be helpful to determine personalized therapeutic strategy against heterogeneous glioma recurrence.

| S-EPMC4605710 | biostudies-literature

Spatial heterogeneity in drug concentrations can facilitate the emergence of resistance to cancer therapy.

Project description:Acquired resistance is one of the major barriers to successful cancer therapy. The development of resistance is commonly attributed to genetic heterogeneity. However, heterogeneity of drug penetration of the tumor microenvironment both on the microscopic level within solid tumors as well as on the macroscopic level across metastases may also contribute to acquired drug resistance. Here we use mathematical models to investigate the effect of drug heterogeneity on the probability of escape from treatment and the time to resistance. Specifically we address scenarios with sufficiently potent therapies that suppress growth of all preexisting genetic variants in the compartment with the highest possible drug concentration. To study the joint effect of drug heterogeneity, growth rate, and evolution of resistance, we analyze a multi-type stochastic branching process describing growth of cancer cells in multiple compartments with different drug concentrations and limited migration between compartments. We show that resistance is likely to arise first in the sanctuary compartment with poor drug penetrations and from there populate non-sanctuary compartments with high drug concentrations. Moreover, we show that only below a threshold rate of cell migration does spatial heterogeneity accelerate resistance evolution, otherwise deterring drug resistance with excessively high migration rates. Our results provide new insights into understanding why cancers tend to quickly become resistant, and that cell migration and the presence of sanctuary sites with little drug exposure are essential to this end.

| S-EPMC4366398 | biostudies-literature

Antibody-drug conjugates with dual payloads for combating breast tumor heterogeneity and drug resistance.

Project description:Breast tumors generally consist of a diverse population of cells with varying gene expression profiles. Breast tumor heterogeneity is a major factor contributing to drug resistance, recurrence, and metastasis after chemotherapy. Antibody-drug conjugates (ADCs) are emerging chemotherapeutic agents with striking clinical success, including T-DM1 for HER2-positive breast cancer. However, these ADCs often suffer from issues associated with intratumor heterogeneity. Here, we show that homogeneous ADCs containing two distinct payloads are a promising drug class for addressing this clinical challenge. Our conjugates show HER2-specific cell killing potency, desirable pharmacokinetic profiles, minimal inflammatory response, and marginal toxicity at therapeutic doses. Notably, a dual-drug ADC exerts greater treatment effect and survival benefit than does co-administration of two single-drug variants in xenograft mouse models representing intratumor HER2 heterogeneity and elevated drug resistance. Our findings highlight the therapeutic potential of the dual-drug ADC format for treating refractory breast cancer and perhaps other cancers.

| S-EPMC8192907 | biostudies-literature

CircPVT1 promotes ER-positive breast tumorigenesis and drug resistance by targeting ESR1 and MAVS

Project description:The molecular mechanisms underlying estrogen receptor (ER)-positive breast carcinogenesis and endocrine therapy resistance remain incompletely understood. Here, we report that circPVT1, a circular RNA generated from the lncRNA PVT1, is highly expressed in ERα-positive breast cancer cell lines and tumor samples and is functionally important in promoting ERα -positive breast tumorigenesis and endocrine therapy resistance. CircPVT1 acts as a competing endogenous RNA (ceRNA) to sponge miR-181a-2-3p, promoting the expression of ESR1 and downstream ERα-target genes and breast cancer cell growth. Further, circPVT1 directly interacts with MAVS protein to disrupt the RIGI-MAVS complex formation, inhibiting type I interferon (IFN) signaling pathway and anti-tumor immunity. Anti-sense oligonucleotides (ASO) targeting circPVT1 inhibits ERα-positive breast cancer cell and tumor growth, re-sensitizing tamoxifen-resistant ERα-positive breast cancer cells to tamoxifen treatment. Taken together, our data demonstrated that circPVT1 can work through both ceRNA and protein scaffolding mechanisms to promote cancer. Thus, circPVT1 may serve as a diagnostic biomarker and therapeutic target for ERα-positive breast cancer in the clinic.

| S-SCDT-10_15252-EMBJ_2022112408 | biostudies-other

Mass spectrometry captures off-target drug binding and provides mechanistic insights into the human metalloprotease ZMPSTE24.

Project description:Off-target binding of hydrophobic drugs can lead to unwanted side effects, either through specific or non-specific binding to unintended membrane protein targets. However, distinguishing the binding of drugs to membrane proteins from that of detergents, lipids and cofactors is challenging. Here, we use high-resolution mass spectrometry to study the effects of HIV protease inhibitors on the human zinc metalloprotease ZMPSTE24. This intramembrane protease plays a major role in converting prelamin A to mature lamin A. We monitored the proteolysis of farnesylated prelamin A peptide by ZMPSTE24 and unexpectedly found retention of the C-terminal peptide product with the enzyme. We also resolved binding of zinc, lipids and HIV protease inhibitors and showed that drug binding blocked prelamin A peptide cleavage and conferred stability to ZMPSTE24. Our results not only have relevance for the progeria-like side effects of certain HIV protease inhibitor drugs, but also highlight new approaches for documenting off-target drug binding.

| S-EPMC5123592 | biostudies-literature

A systematic in silico mining of the mechanistic implications and therapeutic potentials of estrogen receptor (ER)-α in breast cancer.

Project description:Estrogen receptor (ER)-α has long been a potential target in ER-α-positive breast cancer therapeutics. In this study, we integrated ER-α-related bioinformatic data at different levels to systematically explore the mechanistic and therapeutic implications of ER-α. Firstly, we identified ER-α-interacting proteins and target genes of ER-α-regulating microRNAs (miRNAs), and analyzed their functional gene ontology (GO) annotations of those ER-α-associated proteins. In addition, we predicted ten consensus miRNAs that could target ER-α, and screened candidate traditional Chinese medicine (TCM) compounds that might hit diverse conformations of ER-α ligand binding domain (LBD). These findings may help to uncover the mechanistic implications of ER-α in breast cancer at a systematic level, and provide clues of miRNAs- and small molecule modulators- based strategies for future ER-α-positive breast cancer therapeutics.

| S-EPMC3948898 | biostudies-literature

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures.

Project description:Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

| S-EPMC10542528 | biostudies-literature

Resistance to neoadjuvant chemotherapy in triple-negative breast cancer mediated by a reversible drug-tolerant state.

Project description:Eradicating triple-negative breast cancer (TNBC) resistant to neoadjuvant chemotherapy (NACT) is a critical unmet clinical need. In this study, patient-derived xenograft (PDX) models of treatment-naïve TNBC and serial biopsies from TNBC patients undergoing NACT were used to elucidate mechanisms of chemoresistance in the neoadjuvant setting. Barcode-mediated clonal tracking and genomic sequencing of PDX tumors revealed that residual tumors remaining after treatment with standard frontline chemotherapies, doxorubicin (Adriamycin) combined with cyclophosphamide (AC), maintained the subclonal architecture of untreated tumors, yet their transcriptomes, proteomes, and histologic features were distinct from those of untreated tumors. Once treatment was halted, residual tumors gave rise to AC-sensitive tumors with similar transcriptomes, proteomes, and histological features to those of untreated tumors. Together, these results demonstrated that tumors can adopt a reversible drug-tolerant state that does not involve clonal selection as an AC resistance mechanism. Serial biopsies obtained from patients with TNBC undergoing NACT revealed similar histologic changes and maintenance of stable subclonal architecture, demonstrating that AC-treated PDXs capture molecular features characteristic of human TNBC chemoresistance. Last, pharmacologic inhibition of oxidative phosphorylation using an inhibitor currently in phase 1 clinical development delayed residual tumor regrowth. Thus, AC resistance in treatment-naïve TNBC can be mediated by nonselective mechanisms that confer a reversible chemotherapy-tolerant state with targetable vulnerabilities.

| S-EPMC6541393 | biostudies-literature

CircPVT1 promotes ER-positive breast tumorigenesis and drug resistance by targeting ESR1 and MAVS

Project description:The molecular mechanisms underlying estrogen receptor (ER)-positive breast carcinogenesis and endocrine therapy resistance remain incompletely understood. Here, we reported that circPVT1, a circular RNA generated from lncRNA PVT1, is highly expressed in ERalpha-positive breast cancer cell lines and tumor samples, which is functionally important in promoting ERalpha-positive breast tumorigenesis and endocrine therapy resistance. CircPVT1 acts as a competing endogenous RNA (ceRNA) to sponge miR-181a-2-3p, promoting the expression of ESR1 and downstream ERalpha-target genes and breast cancer cell growth. Meanwhile, circPVT1 directly interacts with MAVS to disrupt the RIGI-MAVS complex formation, inhibiting type I interferon (IFN) signaling pathway and anti-tumor immunity. The dual mechanisms both contribute to ERα-positive breast tumorigenesis. Anti-sense oligonucleotides (ASO) targeting circPVT1 was shown to inhibit ERalpha-positive breast cancer cell and tumor growth, and could re-sensitize tamoxifen-resistant ERalpha-positive breast cancer cells to tamoxifen treatment. Taken together, our data demonstrated that circPVT1 can work through both ceRNA and protein scaffold mechanisms to promote cancer, and in particular, circPVT1 may serve as a diagnosis biomarker and therapeutic target for ERalpha-positive breast cancer in the clinic.

2023-02-06 | GSE220776 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data