Surprisal analysis characterizes the free energy time course of cancer cells undergoing epithelial-to-mesenchymal transition

Kinetic Trajectories of Glucose Uptake in Single Cancer Cells Reveal a Drug-Induced Cell-State Change Within Hours of Drug Treatment

The development of drug resistance is a nearly universal phenomenon in patients with glioblastoma multiforme (GBM) brain tumors. Upon treatment, GBM cancer cells may initially undergo a drug-induced cell-state change to a drug-tolerant, slow-cycling state. The kinetics of that process are not well understood, in part due to the heterogeneity of GBM tumors and tumor models, which can confound the interpretation of kinetic data. Here, we resolve drug-adaptation kinetics in a patient-derived in vitro GBM tumor model characterized by the epithelial growth factor receptor (EGFR) variant(v)III oncogene treated with an EGFR inhibitor. We use radiolabeled 18F-fluorodeoxyglucose (FDG) to monitor the glucose uptake trajectories of single GBM cancer cells over a 12 h period of drug treatment. Autocorrelation analysis of the single-cell glucose uptake trajectories reveals evidence of a drug-induced cell-state change from a high- to low-glycolytic phenotype after 5-7 h of drug treatment. Information theoretic analysis of a bulk transcriptome kinetic series of the GBM tumor model delineated the underlying molecular mechanisms driving the cellular state change, including a shift from a stem-like mesenchymal state to a more differentiated, slow-cycling astrocyte-like state. Our results demonstrate that complex drug-induced cancer cell-state changes of cancer cells can be captured via measurements of single cell metabolic trajectories and reveal the extremely facile nature of drug adaptation.

Epithelial-mesenchymal plasticity in cancer: signaling pathways and therapeutic targets

Currently, cancer is still a leading cause of human death globally. Tumor deterioration comprises multiple events including metastasis, therapeutic resistance and immune evasion, all of which are tightly related to the phenotypic plasticity especially epithelial-mesenchymal plasticity (EMP). Tumor cells with EMP are manifest in three states as epithelial-mesenchymal transition (EMT), partial EMT, and mesenchymal-epithelial transition, which orchestrate the phenotypic switch and heterogeneity of tumor cells via transcriptional regulation and a series of signaling pathways, including transforming growth factor-β, Wnt/β-catenin, and Notch. However, due to the complicated nature of EMP, the diverse process of EMP is still not fully understood. In this review, we systematically conclude the biological background, regulating mechanisms of EMP as well as the role of EMP in therapy response. We also summarize a range of small molecule inhibitors, immune-related therapeutic approaches, and combination therapies that have been developed to target EMP for the outstanding role of EMP-driven tumor deterioration. Additionally, we explore the potential technique for EMP-based tumor mechanistic investigation and therapeutic research, which may burst vigorous prospects. Overall, we elucidate the multifaceted aspects of EMP in tumor progression and suggest a promising direction of cancer treatment based on targeting EMP.

The essence of phase transitions in condensed matter by an information theoretic approach

Our information theoretic considerations suggest that the essence of phase transitions in condensed matter is the change in entropy as reflected in the change in the number of isomers between two phases. The explicit number of isomers as a function of size is computed using a graph theoretic approach that is compared to a direct count for smaller systems. This allows us to apply a common approach to both nanosystems and their macroscopic limit. The entropy increases very rapidly with size with the results that replacing the actual distribution over size by an average is not an accurate approximation. That the phase transition is a sharp function of the temperature is due to the high heat capacity of both the solid and liquid phases. The difference in entropy at the transition is related to the Trouton-Richards considerations. The finite width of the boundary between two phases of a finite system is related to the inherent uncertainty product that is derived from the maximum entropy formalism and that is a result of the fluctuations about equilibrium. As the system size increases, the boundary becomes sharper and one recovers the usual thermodynamic description.

SCA: recovering single-cell heterogeneity through information-based dimensionality reduction

Dimensionality reduction summarizes the complex transcriptomic landscape of single-cell datasets for downstream analyses. Current approaches favor large cellular populations defined by many genes, at the expense of smaller and more subtly defined populations. Here, we present surprisal component analysis (SCA), a technique that newly leverages the information-theoretic notion of surprisal for dimensionality reduction to promote more meaningful signal extraction. For example, SCA uncovers clinically important cytotoxic T-cell subpopulations that are indistinguishable using existing pipelines. We also demonstrate that SCA substantially improves downstream imputation. SCA's efficient information-theoretic paradigm has broad applications to the study of complex biological tissues in health and disease.

Fame through surprise: How fame-seeking mass shooters diversify their attacks

Mass shootings are becoming more frequent in the United States, as we routinely learn from the media about attempts that have been prevented or tragedies that destroyed entire communities. To date, there has been limited understanding of the modus operandi of mass shooters, especially those who seek fame through their attacks. Here, we explore whether the attacks of these fame-seeking mass shooters were more surprising than those of others and clarify the link between fame and surprise in mass shootings. We assembled a dataset of 189 mass shootings from 1966 to 2021, integrating data from multiple sources. We categorized the incidents in terms of the targeted population and shooting location. We measured "surprisal" (often known as "Shannon information content") with respect to these features, and we scored fame from Wikipedia traffic data-a commonly used metric of fame. Surprisal was significantly higher for fame-seeking mass shooters than non-fame-seeking ones. We also registered a significant positive correlation between fame and surprisal controlling for the number of casualties and injured victims. Not only do we uncover a link between fame-seeking behavior and surprise in the attacks but also we demonstrate an association between the fame of a mass shooting and its surprise.

Roles of TGF-β in cancer hallmarks and emerging onco-therapeutic design

Transforming growth factor-beta (TGF-β) is a double-edged sword in cancer treatment because of its pivotal yet complex and roles played during cancer initiation/development. Current anti-cancer strategies involving TGF-β largely view TGF-β as an onco-therapeutic target that not only substantially hinders its full utilisation for cancer control, but also considerably restricts innovations in this field. Thereby, how to take advantages of therapeutically favourable properties of TGF-β for cancer management represents an interesting and less investigated problem. Here, by categorising cancer hallmarks into four critical transition events and one enabling characteristic controlling cancer initiation and progression, and delineating TGF-β complexities according to these cancer traits, we identify the suppressive role of TGF-β in tumour initiation and early-stage progression and its promotive functionalities in cancer metastasis as well as other cancer hallmarks. We also propose the feasibility and possible scenarios of combining cold atmospheric plasma (CAP) with onco-therapeutics utilising TGF-β for cancer control given the intrinsic properties of CAP against cancer hallmarks.

Visualizing physiological parameters in cells and tissues using genetically encoded indicators for metabolites

The study of metabolism is undergoing a renaissance. Since the year 2002, over 50 genetically-encoded fluorescent indicators (GEFIs) have been introduced, capable of monitoring metabolites with high spatial/temporal resolution using fluorescence microscopy. Indicators are fusion proteins that change their fluorescence upon binding a specific metabolite. There are indicators for sugars, monocarboxylates, Krebs cycle intermediates, amino acids, cofactors, and energy nucleotides. They permit monitoring relative levels, concentrations, and fluxes in living systems. At a minimum they report relative levels and, in some cases, absolute concentrations may be obtained by performing ad hoc calibration protocols. Proper data collection, processing, and interpretation are critical to take full advantage of these new tools. This review offers a survey of the metabolic indicators that have been validated in mammalian systems. Minimally invasive, these indicators have been instrumental for the purposes of confirmation, rebuttal and discovery. We envision that this powerful technology will foster metabolic physiology.

The Role of SMAD4 Inactivation in Epithelial-Mesenchymal Plasticity of Pancreatic Ductal Adenocarcinoma: The Missing Link?

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) is currently one of the deadliest cancers. Despite the progress that has been made in the research of patient care and the understanding of pancreatic cancer, the survival rate remains mediocre. SMAD4, a tumor-suppressor gene, is specifically inactivated in 50–55% of pancreatic cancers. The role of SMAD4 protein loss in PDAC remains controversial, but seems to be associated with worse overall survival and metastasis. Here, we review the function of SMAD4 inactivation in the context of a specific biological process called epithelial–mesenchymal transition, as it has been increasingly associated with tumor formation, metastasis and resistance to therapy. By improving our understanding of these molecular mechanisms, we hope to find new targets for therapy and improve the care of patients with PDAC.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) presents a five-year survival rate of 10% and its incidence increases over the years. It is, therefore, essential to improve our understanding of the molecular mechanisms that promote metastasis and chemoresistance in PDAC, which are the main causes of death in these patients. SMAD4 is inactivated in 50% of PDACs and its loss has been associated with worse overall survival and metastasis, although some controversy still exists. SMAD4 is the central signal transducer of the transforming growth factor-beta (TGF-beta) pathway, which is notably known to play a role in epithelial–mesenchymal transition (EMT). EMT is a biological process where epithelial cells lose their characteristics to acquire a spindle-cell phenotype and increased motility. EMT has been increasingly studied due to its potential implication in metastasis and therapy resistance. Recently, it has been suggested that cells undergo EMT transition through intermediary states, which is referred to as epithelial–mesenchymal plasticity (EMP). The intermediary states are characterized by enhanced aggressiveness and more efficient metastasis. Therefore, this review aims to summarize and analyze the current knowledge on SMAD4 loss in patients with PDAC and to investigate its potential role in EMP in order to better understand its function in PDAC carcinogenesis.

Transcriptional census of epithelial-mesenchymal plasticity in cancer

Epithelial-mesenchymal plasticity (EMP) contributes to tumor progression, promoting therapy resistance and immune cell evasion. Definitive molecular features of this plasticity have largely remained elusive due to the limited scale of most studies. Leveraging single-cell RNA sequencing data from 266 tumors spanning eight different cancer types, we identify expression patterns associated with intratumoral EMP. Integrative analysis of these programs confirmed a high degree of diversity among tumors. These diverse programs are associated with combinations of various common regulatory mechanisms initiated from cues within the tumor microenvironment. We show that inferring regulatory features can inform effective therapeutics to restrict EMP.

A Theoretical Approach to Coupling the Epithelial-Mesenchymal Transition (EMT) to Extracellular Matrix (ECM) Stiffness via LOXL2

Simple Summary

Epithelial-mesenchymal transition (EMT) is a key process in cancer progression through which cells weaken their cell-cell adhesion and gain mobility and invasive traits. Besides chemical signaling, recent studies have established the connection of EMT to mechanical microenvironment, such as the stiffness of extracellular matrix (ECM). LOXL2 is representative of a family of enzymes that promotes fiber cross-linking in ECM. With increased cross-linking comes increased stiffness, which induces EMT that can, in turn, elevate LOXL2 levels. As such, a positive feedback loop among EMT, LOXL2, and ECM stiffness can be formed. We built a mathematical model on a core biochemical reaction network featuring this feedback loop, and showed how strongly it drives EMT. We also illustrated mechanistically how cross-linking connects with stiffness, using a mechanical model of collagen (a major component of ECM). Using this theoretical framework, we demonstrated the heterogeneity of LOXL2/stiffness and its implications on migrating cancer cells that could seed metastasis, the growth of secondary malignant tumors. This framework can inspire experimental studies of more fine-grained mechanotransduction and biomechanical heterogeneity in cancers.

Abstract

The epithelial-mesenchymal transition (EMT) plays a critical role in cancer progression, being responsible in many cases for the onset of the metastatic cascade and being integral in the ability of cells to resist drug treatment. Most studies of EMT focus on its induction via chemical signals such as TGF-β or Notch ligands, but it has become increasingly clear that biomechanical features of the microenvironment such as extracellular matrix (ECM) stiffness can be equally important. Here, we introduce a coupled feedback loop connecting stiffness to the EMT transcription factor ZEB1, which acts via increasing the secretion of LOXL2 that leads to increased cross-linking of collagen fibers in the ECM. This increased cross-linking can effectively increase ECM stiffness and increase ZEB1 levels, thus setting a positive feedback loop between ZEB1 and ECM stiffness. To investigate the impact of this non-cell-autonomous effect, we introduce a computational approach capable of connecting LOXL2 concentration to increased stiffness and thereby to higher ZEB1 levels. Our results indicate that this positive feedback loop, once activated, can effectively lock the cells in a mesenchymal state. The spatial-temporal heterogeneity of the LOXL2 concentration and thus the mechanical stiffness also has direct implications for migrating cells that attempt to escape the primary tumor.

Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19

We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.

Raman-guided subcellular pharmaco-metabolomics for metastatic melanoma cells

Non-invasively probing metabolites within single live cells is highly desired but challenging. Here we utilize Raman spectro-microscopy for spatial mapping of metabolites within single cells, with the specific goal of identifying druggable metabolic susceptibilities from a series of patient-derived melanoma cell lines. Each cell line represents a different characteristic level of cancer cell de-differentiation. First, with Raman spectroscopy, followed by stimulated Raman scattering (SRS) microscopy and transcriptomics analysis, we identify the fatty acid synthesis pathway as a druggable susceptibility for differentiated melanocytic cells. We then utilize hyperspectral-SRS imaging of intracellular lipid droplets to identify a previously unknown susceptibility of lipid mono-unsaturation within de-differentiated mesenchymal cells with innate resistance to BRAF inhibition. Drugging this target leads to cellular apoptosis accompanied by the formation of phase-separated intracellular membrane domains. The integration of subcellular Raman spectro-microscopy with lipidomics and transcriptomics suggests possible lipid regulatory mechanisms underlying this pharmacological treatment. Our method should provide a general approach in spatially-resolved single cell metabolomics studies.

Single-cell metabolomics can offer deep insights into the metabolic reprogramming that accompanies disease states. Here, the authors use Raman spectro-microscopy for non-invasive metabolite analysis and identification of druggable metabolic susceptibilities in single live melanoma cells.

TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation

The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA.

Thermodynamic energetics underlying genomic instability and whole-genome doubling in cancer

Genomic instability contributes to tumorigenesis through the amplification and deletion of cancer driver genes. DNA copy number (CN) profiling of ensembles of tumors allows a thermodynamic analysis of the profile for each tumor. The free energy of the distribution of CNs is found to be a monotonically increasing function of the average chromosomal ploidy. The dependence is universal across several cancer types. Surprisal analysis distinguishes two main known subgroups: tumors with cells that have or have not undergone whole-genome duplication (WGD). The analysis uncovers that CN states having a narrower distribution are energetically more favorable toward the WGD transition. Surprisal analysis also determines the deviations from a fully stable-state distribution. These deviations reflect constraints imposed by tumor fitness selection pressures. The results point to CN changes that are more common in high-ploidy tumors and thus support altered selection pressures upon WGD.

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia

Temporal dynamics of gene expression inform cellular and molecular perturbations associated with disease development and evolution. Given the complexity of high-dimensional temporal genomic data, an analytic framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Here we model temporal dynamics of the transcriptome of peripheral blood mononuclear cells in a two-dimensional state-space representing states of health and leukemia using time-sequential bulk RNA-seq data from a murine model of acute myeloid leukemia (AML). The state-transition model identified critical points that accurately predict AML development and identifies stepwise transcriptomic perturbations that drive leukemia progression. The geometry of the transcriptome state-space provided a biological interpretation of gene dynamics, aligned gene signals that are not synchronized in time across mice, and allowed quantification of gene and pathway contributions to leukemia development. Our state-transition model synthesizes information from multiple cell types in the peripheral blood and identifies critical points in the transition from health to leukemia to guide interpretation of changes in the transcriptome as a whole to predict disease progression. SIGNIFICANCE: These findings apply the theory of state transitions to model the initiation and development of acute myeloid leukemia, identifying transcriptomic perturbations that accurately predict time to disease development.See related commentary by Kuijjer, p. 3072 GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/15/3157/F1.large.jpg.

Multiomic Immunophenotyping of COVID-19 Patients Reveals Early Infection Trajectories

Host immune responses play central roles in controlling SARS-CoV2 infection, yet remain incompletely characterized and understood. Here, we present a comprehensive immune response map spanning 454 proteins and 847 metabolites in plasma integrated with single-cell multi-omic assays of PBMCs in which whole transcriptome, 192 surface proteins, and T and B cell receptor sequence were co-analyzed within the context of clinical measures from 50 COVID19 patient samples. Our study reveals novel cellular subpopulations, such as proliferative exhausted CD8 ⁺ and CD4 ⁺ T cells, and cytotoxic CD4 ⁺ T cells, that may be features of severe COVID-19 infection. We condensed over 1 million immune features into a single immune response axis that independently aligns with many clinical features and is also strongly associated with disease severity. Our study represents an important resource towards understanding the heterogeneous immune responses of COVID-19 patients and may provide key information for informing therapeutic development.

TGFβ-induced metabolic reprogramming during epithelial-to-mesenchymal transition in cancer

Metastasis is the most frequent cause of death in cancer patients. Epithelial-to-mesenchymal transition (EMT) is the process in which cells lose epithelial integrity and become motile, a critical step for cancer cell invasion, drug resistance and immune evasion. The transforming growth factor-β (TGFβ) signaling pathway is a major driver of EMT. Increasing evidence demonstrates that metabolic reprogramming is a hallmark of cancer and extensive metabolic changes are observed during EMT. The aim of this review is to summarize and interconnect recent findings that illustrate how changes in glycolysis, mitochondrial, lipid and choline metabolism coincide and functionally contribute to TGFβ-induced EMT. We describe TGFβ signaling is involved in stimulating both glycolysis and mitochondrial respiration. Interestingly, the subsequent metabolic consequences for the redox state and lipid metabolism in cancer cells are found to be in favor of EMT as well. Combined we illustrate that a better understanding of the mechanistic links between TGFβ signaling, cancer metabolism and EMT holds promising strategies for cancer therapy, some of which are already actively being explored in the clinic.

Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge for understanding biological changes ranging from cellular differentiation to epigenetic responses of diseased cells upon drugging. We integrate experiments and theory to determine the trajectories that single BRAFV600E mutant melanoma cancer cells take between drug-naive and drug-tolerant states. Although single-cell omics tools can yield snapshots of the cell-state landscape, the determination of individual cell trajectories through that space can be confounded by stochastic cell-state switching. We assayed for a panel of signaling, phenotypic, and metabolic regulators at points across 5 days of drug treatment to uncover a cell-state landscape with two paths connecting drug-naive and drug-tolerant states. The trajectory a given cell takes depends upon the drug-naive level of a lineage-restricted transcription factor. Each trajectory exhibits unique druggable susceptibilities, thus updating the paradigm of adaptive resistance development in an isogenic cell population.

Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance

Phenotypic plasticity is associated with non-genetic drug tolerance in several cancers. Such plasticity can arise from chromatin remodeling, transcriptomic reprogramming, and/or protein signaling rewiring, and is characterized as a cell state transition in response to molecular or physical perturbations. This, in turn, can confound interpretations of drug responses and resistance development. Using BRAF-mutant melanoma cell lines as the prototype, we report on a joint theoretical and experimental investigation of the cell-state transition dynamics associated with BRAF inhibitor drug tolerance. Thermodynamically motivated surprisal analysis of transcriptome data was used to treat the cell population as an entropy maximizing system under the influence of time-dependent constraints. This permits the extraction of an epigenetic potential landscape for drug-induced phenotypic evolution. Single-cell flow cytometry data of the same system were modeled with a modified Fokker-Planck-type kinetic model. The two approaches yield a consistent picture that accounts for the phenotypic heterogeneity observed over the course of drug tolerance development. The results reveal that, in certain plastic cancers, the population heterogeneity and evolution of cell phenotypes may be understood by accounting for the competing interactions of the epigenetic potential landscape and state-dependent cell proliferation. Accounting for such competition permits accurate, experimentally verifiable predictions that can potentially guide the design of effective treatment strategies.

Cancer cells exhibit varied degrees of phenotypic heterogeneity. These phenotypes, each of them with unique molecular and functional profiles, display dynamic interconversion in response to drug perturbations, and can evolve to form new drug-tolerant phenotypes. Such phenotypic plasticity, in turn, renders tumor cells extremely difficult to treat. To get a quantitative biophysical understanding of the origins of the phenotypic equilibrium and evolution associated with drug tolerance development in highly plastic patient-derived melanoma cells, we employed joint experimental and computational approaches, using either bulk or single cell measurements as input, to interrogate the epigenetic landscape of the phenotypic evolution. We found that the observed phenotypic equilibria were established via competition between state-dependent net proliferation rates and landscape potential. The results reveal how the tumor cells maintain a phenotypic heterogeneity that facilitates appropriate responses to external cues. They implicate that, in certain phenotypically plastic tumor cells, drug targeting the driver oncogenes may not have sustained efficacy unless the phenotypic plasticity of the tumor is co-targeted.

Vitamin D inhibits the epithelial-mesenchymal transition by a negative feedback regulation of TGF-β activity

Vitamin D and TGF-β exert opposite effects on epithelial-mesenchymal EMT transition. Here we report a novel mechanism of action of TGF-β that promotes the counteracting activity of vitamin D; in two models of human epithelial-mesenchymal EMT transition we demonstrated for the first time that TGF-β strongly induced the expression of vitamin D receptor (VDR) and that 1,25(OH)₂D₃ was able to contrast the TGF-β-driven EMT transition by transcriptional modulation. In human bronchial epithelial cells the effects of TGF-β on EMT transition markers (E-Cadherin expression and cell motility) were reversed by pre-treatment and co-treatment with 1,25(OH)₂D_3, but not when the hormone was given later. Silencing experiments demonstrated that the inhibition of TGF-β activity was VDR-dependent. 1,25(OH)₂D₃ abrogated the mitochondrial stimulation triggered by TGF-β. In fact we showed that 1,25(OH)₂D₃ repressed the transcriptional induction of respiratory complex, limited the enhanced mitochondrial membrane potential and restrained the increased levels of mitochondrial ATP; 1,25(OH)₂D₃ also decreased the production of reactive oxygen species promoted by TGF-β. Overall, our study suggests that the overexpression and activity of VDR may be a regulatory response to TGF-β signaling that could be exploited in clinical protocols, unraveling the therapeutic potentiality of 1,25(OH)₂D₃ in the prevention of cancer metastasis.

Intermediate cell states in epithelial-to-mesenchymal transition

The transition of epithelial cells into a mesenchymal state (epithelial-to-mesenchymal transition or EMT) is a highly dynamic process implicated in various biological processes. During EMT, cells do not necessarily exist in 'pure' epithelial or mesenchymal states. There are cells with mixed (or hybrid) features of the two, which are termed as the intermediate cell states (ICSs). While the exact functions of ICS remain elusive, together with EMT it appears to play important roles in embryogenesis, tissue development, and pathological processes such as cancer metastasis. Recent single cell experiments and advanced mathematical modeling have improved our capability in identifying ICS and provided a better understanding of ICS in development and disease. Here, we review the recent findings related to the ICS in/or EMT and highlight the challenges in the identification and functional characterization of ICS.

CtBP promotes metastasis of breast cancer through repressing cholesterol and activating TGF-β signaling

Metastasis is the process through which the primary cancer cells spread beyond the primary tumor and disseminate to other organs. Most cancer patients die of metastatic disease. EMT is proposed to be the initial event associated with cancer metastasis and how it occurred is still a mystery. CtBP is known as a co-repressor abundantly expressed in many types of cancer and regulates genes involved in cancer initiation, progression, and metastasis. We found that CtBP regulates intracellular cholesterol homeostasis in breast cancer cells by forming a complex with ZEB1 and transcriptionally repressing SREBF2 expression. Importantly, CtBP repression of intracellular cholesterol abundance leads to increased EMT and cell migration. The reason is that cholesterol negatively regulates the stability of TGF-β receptors on the cell membrane. Interestingly, TGF-β is also capable of reducing intracellular cholesterol relying on the increased recruitment of ZEB1 and CtBP complex to SREBF2 promoter. Thus, we propose a feedback loop formed by CtBP, cholesterol, and TGF-β signaling pathway, through which TGF-β triggers the cascade that mobilizes the cancer cells for metastasis. Consistently, the intravenous injection of breast cancer cells with ectopically CtBP expression show increased lung metastasis depending on the reduction of intracellular cholesterol. Finally, we analyzed the public breast cancer datasets and found that CtBP expression negatively correlates with SREBF2 and HMGCR expressions. High expression of CtBP and low expression of SREBF2 and HMGCR significantly correlates with high EMT of the primary tumors.

Hybrid epithelial/mesenchymal phenotypes promote metastasis and therapy resistance across carcinomas

Cancer metastasis and therapy resistance are the major unsolved clinical challenges, and account for nearly all cancer-related deaths. Both metastasis and therapy resistance are fueled by epithelial plasticity, the reversible phenotypic transitions between epithelial and mesenchymal phenotypes, including epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET). EMT and MET have been largely considered as binary processes, where cells detach from the primary tumor as individual units with many, if not all, traits of a mesenchymal cell (EMT) and then convert back to being epithelial (MET). However, recent studies have demonstrated that cells can metastasize in ways alternative to traditional EMT paradigm; for example, they can detach as clusters, and/or occupy one or more stable hybrid epithelial/mesenchymal (E/M) phenotypes that can be the end point of a transition. Such hybrid E/M cells can integrate various epithelial and mesenchymal traits and markers, facilitating collective cell migration. Furthermore, these hybrid E/M cells may possess higher tumor-initiation and metastatic potential as compared to cells on either end of the EMT spectrum. Here, we review in silico, in vitro, in vivo and clinical evidence for the existence of one or more hybrid E/M phenotype(s) in multiple carcinomas, and discuss their implications in tumor-initiation, tumor relapse, therapy resistance, and metastasis. Together, these studies drive the emerging notion that cells in a hybrid E/M phenotype may occupy 'metastatic sweet spot' in multiple subtypes of carcinomas, and pathways linked to this (these) hybrid E/M state(s) may be relevant as prognostic biomarkers as well as a promising therapeutic targets.

Addressing the Challenge of Molecular Change: An Interim Report

Invited by the editorial committee of the Annual Review of Physical Chemistry to "contribute my autobiography," I present it here, as I understand the term. It is about my parents, my mentors, my coworkers, and my friends in learning and the scientific problems that we tried to address. Courtesy of the editorial assistance of Annual Reviews, some of the science is in the figure captions and sidebars. I am by no means done: I am currently trying to fuse the quantitative rigor of physical chemistry with systems biology while also dealing with a post-Born-Oppenheimer regime in electronic dynamics and am attempting to instruct molecules to perform advanced logic.

Nonequilibrium internal energy distributions during dissociation

In this work, we propose a model for nonequilibrium vibrational and rotational energy distributions in nitrogen using surprisal analysis. The model is constructed by using data from direct molecular simulations (DMSs) of rapidly heated nitrogen gas using an ab initio potential energy surface (PES). The surprisal-based model is able to capture the overpopulation of high internal energy levels during the excitation phase and also the depletion of high internal energy levels during the quasi-steady-state (QSS) dissociation phase. Due to strong coupling between internal energy and dissociation chemistry, such non-Boltzmann effects can influence the overall dissociation rate in the gas. Conditions representative of the flow behind strong shockwaves, relevant to hypersonic flight, are analyzed. The surprisal-based model captures important molecular-level nonequilibrium physics, yet the simple functional form leads to a continuum-level expression that now accounts for the underlying energy distributions and their coupling to dissociation.

Single cell proteomics in biomedicine: High-dimensional data acquisition, visualization, and analysis

New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions.

Complex Determinants of Epithelial: Mesenchymal Phenotypic Plasticity in Ovarian Cancer

Unlike most epithelial malignancies which metastasize hematogenously, metastasis of epithelial ovarian cancer (EOC) occurs primarily via transcoelomic dissemination, characterized by exfoliation of cells from the primary tumor, avoidance of detachment-induced cell death (anoikis), movement throughout the peritoneal cavity as individual cells and multi-cellular aggregates (MCAs), adhesion to and disruption of the mesothelial lining of the peritoneum, and submesothelial matrix anchoring and proliferation to generate widely disseminated metastases. This exceptional microenvironment is highly permissive for phenotypic plasticity, enabling mesenchymal-to-epithelial (MET) and epithelial-to-mesenchymal (EMT) transitions. In this review, we summarize current knowledge on EOC heterogeneity in an EMT context, outline major regulators of EMT in ovarian cancer, address controversies in EMT and EOC chemoresistance, and highlight computational modeling approaches toward understanding EMT/MET in EOC.

EMT and MET: necessary or permissive for metastasis?

Epithelial‐to‐mesenchymal transition (EMT) and its reverse mesenchymal‐to‐epithelial transition (MET) have been suggested to play crucial roles in metastatic dissemination of carcinomas. These phenotypic transitions between states are not binary. Instead, carcinoma cells often exhibit a spectrum of epithelial/mesenchymal phenotype(s). While epithelial/mesenchymal plasticity has been observed preclinically and clinically, whether any of these phenotypic transitions are indispensable for metastatic outgrowth remains an unanswered question. Here, we focus on epithelial/mesenchymal plasticity in metastatic dissemination and propose alternative mechanisms for successful dissemination and metastases beyond the traditional EMT/MET view. We highlight multiple hypotheses that can help reconcile conflicting observations, and outline the next set of key questions that can offer valuable insights into mechanisms of metastasis in multiple tumor models.

Integrin-β4 identifies cancer stem cell-enriched populations of partially mesenchymal carcinoma cells

Neoplastic cells within individual carcinomas often exhibit considerable phenotypic heterogeneity in their epithelial versus mesenchymal-like cell states. Because carcinoma cells with mesenchymal features are often more resistant to therapy and may serve as a source of relapse, we sought to determine whether such cells could be further stratified into functionally distinct subtypes. Indeed, we find that a basal epithelial marker, integrin-β4 (ITGB4), can be used to enable stratification of mesenchymal-like triple-negative breast cancer (TNBC) cells that differ from one another in their relative tumorigenic abilities. Notably, we demonstrate that ITGB4⁺ cancer stem cell (CSC)-enriched mesenchymal cells reside in an intermediate epithelial/mesenchymal phenotypic state. Among patients with TNBC who received chemotherapy, elevated ITGB4 expression was associated with a worse 5-year probability of relapse-free survival. Mechanistically, we find that the ZEB1 (zinc finger E-box binding homeobox 1) transcription factor activity in highly mesenchymal SUM159 TNBC cells can repress expression of the epithelial transcription factor TAp63α (tumor protein 63 isoform 1), a protein that promotes ITGB4 expression. In addition, we demonstrate that ZEB1 and ITGB4 are important in modulating the histopathological phenotypes of tumors derived from mesenchymal TNBC cells. Hence, mesenchymal carcinoma cell populations are internally heterogeneous, and ITGB4 is a mechanistically driven prognostic biomarker that can be used to identify the more aggressive subtypes of mesenchymal carcinoma cells in TNBC. The ability to rapidly isolate and mechanistically interrogate the CSC-enriched, partially mesenchymal carcinoma cells should further enable identification of novel therapeutic opportunities to improve the prognosis for high-risk patients with TNBC.

EMT: 2016

The significant parallels between cell plasticity during embryonic development and carcinoma progression have helped us understand the importance of the epithelial-mesenchymal transition (EMT) in human disease. Our expanding knowledge of EMT has led to a clarification of the EMT program as a set of multiple and dynamic transitional states between the epithelial and mesenchymal phenotypes, as opposed to a process involving a single binary decision. EMT and its intermediate states have recently been identified as crucial drivers of organ fibrosis and tumor progression, although there is some need for caution when interpreting its contribution to metastatic colonization. Here, we discuss the current state-of-the-art and latest findings regarding the concept of cellular plasticity and heterogeneity in EMT. We raise some of the questions pending and identify the challenges faced in this fast-moving field.

Imaging Adenosine Triphosphate (ATP)

Adenosine triphosphate (ATP) is a universal mediator of metabolism and signaling across unicellular and multicellular species. There is a fundamental interdependence between the dynamics of ATP and the physiology that occurs inside and outside the cell. Characterizing and understanding ATP dynamics provide valuable mechanistic insight into processes that range from neurotransmission to the chemotaxis of immune cells. Therefore, we require the methodology to interrogate both temporal and spatial components of ATP dynamics from the subcellular to the organismal levels in live specimens. Over the last several decades, a number of molecular probes that are specific to ATP have been developed. These probes have been combined with imaging approaches, particularly optical microscopy, to enable qualitative and quantitative detection of this critical molecule. In this review, we survey current examples of technologies available for visualizing ATP in living cells, and identify areas where new tools and approaches are needed to expand our capabilities.

Mechanisms of TGFβ-Induced Epithelial-Mesenchymal Transition

Transitory phenotypic changes such as the epithelial–mesenchymal transition (EMT) help embryonic cells to generate migratory descendants that populate new sites and establish the distinct tissues in the developing embryo. The mesenchymal descendants of diverse epithelia also participate in the wound healing response of adult tissues, and facilitate the progression of cancer. EMT can be induced by several extracellular cues in the microenvironment of a given epithelial tissue. One such cue, transforming growth factor β (TGFβ), prominently induces EMT via a group of specific transcription factors. The potency of TGFβ is partly based on its ability to perform two parallel molecular functions, i.e. to induce the expression of growth factors, cytokines and chemokines, which sequentially and in a complementary manner help to establish and maintain the EMT, and to mediate signaling crosstalk with other developmental signaling pathways, thus promoting changes in cell differentiation. The molecules that are activated by TGFβ signaling or act as cooperating partners of this pathway are impossible to exhaust within a single coherent and contemporary report. Here, we present selected examples to illustrate the key principles of the circuits that control EMT under the influence of TGFβ.

Tubular atrophy in the pathogenesis of chronic kidney disease progression

The longstanding focus in chronic kidney disease (CKD) research has been on the glomerulus, which is sensible because this is where glomerular filtration occurs, and a large proportion of progressive CKD is associated with significant glomerular pathology. However, it has been known for decades that tubular atrophy is also a hallmark of CKD and that it is superior to glomerular pathology as a predictor of glomerular filtration rate decline in CKD. Nevertheless, there are vastly fewer studies that investigate the causes of tubular atrophy, and fewer still that identify potential therapeutic targets. The purpose of this review is to discuss plausible mechanisms of tubular atrophy, including tubular epithelial cell apoptosis, cell senescence, peritubular capillary rarefaction and downstream tubule ischemia, oxidative stress, atubular glomeruli, epithelial-to-mesenchymal transition, interstitial inflammation, lipotoxicity and Na(+)/H(+) exchanger-1 inactivation. Once a a better understanding of tubular atrophy (and interstitial fibrosis) pathophysiology has been obtained, it might then be possible to consider tandem glomerular and tubular therapeutic strategies, in a manner similar to cancer chemotherapy regimens, which employ multiple drugs to simultaneously target different mechanistic pathways.

Statistical thermodynamics of transcription profiles in normal development and tumorigeneses in cohorts of patients

Experimental biology is providing the distribution of numerous different biological molecules inside cells and in body fluids of patients. Statistical methods of analysis have very successfully examined these rather large databases. We seek to use a thermodynamic analysis to provide a physical understanding and quantitative characterization of human cancers and other pathologies within a molecule-centered approach. The key technical development is the introduction of a Lagrangian. By imposing constraints the minimal value of the Lagrangian defines a thermodynamically stable state of the cellular system. The minimization also allows using experimental data measured at a number of different conditions to evaluate the steady-state distribution of biomolecules such as messenger RNAs. Thereby the number of effectively accessible quantum states of biomolecules is determined from the experimentally measured expression levels. With the increased resolution provided by the minimization of the Lagrangian one can differentiate between normal and diseased patients and further between disease subtypes. Each such refinement corresponds to imposing an additional constraint of biological origin. The constraints are the unbalanced ongoing biological processes in the system. MicroRNA expression level data for control and diseased lung cancer patients are analyzed as an example.

The cancer cell 'energy grid': TGF-β1 signaling coordinates metabolism for migration

Cancer cells have an increased reliance on lipogenesis, which is required for uncontrolled cell division. We recently reported transcriptional and functional 'reprogramming' of the cellular energy grid, allowing cancer cells to divert metabolism from biosynthesis to bioenergetic pathways and thus supplying enhanced mobility during epithelial-mesenchymal transition (EMT) induced by transforming growth factor β (TGF-β1) (Fig. 1).

Dynamic Sialylation in Transforming Growth Factor-β (TGF-β)-induced Epithelial to Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a fundamental process in embryonic development and organ formation. Aberrant regulation of EMT often leads to tumor progression. Changes in cell surface sialylation have recently been implicated in mediating EMT. Herein we report the visualization of dynamic changes of sialylation and glycoproteomic analysis of newly synthesized sialylated proteins in EMT by metabolic labeling of sialylated glycans with azides, followed by click labeling with fluorophores or affinity tags. We discovered that sialylation was down-regulated during EMT but then reverted and up-regulated in the mesenchymal state after EMT, accompanied by mRNA expression level changes of genes involved in the sialic acid biosynthesis. Quantitative proteomic analysis identified a list of sialylated proteins whose biosynthesis was dynamically regulated during EMT. Sialylation of cell surface adherent receptor integrin β4 was found to be down-regulated, which may regulate integrin functions during EMT. Furthermore, a global sialylation inhibitor was used to probe the functional role of sialylation during EMT. We found that inhibition of sialylation promoted EMT. Taken together, our findings suggest the important role of sialylation in regulating EMT and imply its possible function in related pathophysiological events, such as cancer metastasis.