Hypoxia has been shown to increase the aggressiveness and severity of tumor progression. Along with chronic and acute hypoxic regions, solid tumors contain regions of cycling hypoxia (also called ...intermittent hypoxia or IH). Cyclic hypoxia is mimicked
and
by periodic exposure to cycles of hypoxia and reoxygenation (H-R cycles). Compared to chronic hypoxia, cyclic hypoxia has been shown to augment various hallmarks of cancer to a greater extent: angiogenesis, immune evasion, metastasis, survival etc. Cycling hypoxia has also been shown to be the major contributing factor in increasing the risk of cancer in obstructive sleep apnea (OSA) patients. Here, we first compare and contrast the effects of acute, chronic and intermittent hypoxia in terms of molecular pathways activated and the cellular processes affected. We highlight the underlying complexity of these differential effects and emphasize the need to investigate various combinations of factors impacting cellular adaptation to hypoxia: total duration of hypoxia, concentration of oxygen (O
), and the presence of and frequency of H-R cycles. Finally, we summarize the effects of cycling hypoxia on various hallmarks of cancer highlighting their dependence on the abovementioned factors. We conclude with a call for an integrative and rigorous analysis of the effects of varying extents and durations of hypoxia on cells, including tools such as mechanism-based mathematical modelling and microfluidic setups.
Epithelial-mesenchymal transition (EMT) is a cellular biological process involved in migration of primary cancer cells to secondary sites facilitating metastasis. Besides, EMT also confers properties ...such as stemness, drug resistance and immune evasion which can aid a successful colonization at the distant site. EMT is not a binary process; recent evidence suggests that cells in partial EMT or hybrid E/M phenotype(s) can have enhanced stemness and drug resistance as compared to those undergoing a complete EMT. Moreover, partial EMT enables collective migration of cells as clusters of circulating tumor cells or emboli, further endorsing that cells in hybrid E/M phenotypes may be the ‘fittest’ for metastasis. Here, we review mechanisms and implications of hybrid E/M phenotypes, including their reported association with hypoxia. Hypoxia-driven activation of HIF-1α can drive EMT. In addition, cyclic hypoxia, as compared to acute or chronic hypoxia, shows the highest levels of active HIF-1α and can augment cancer aggressiveness to a greater extent, including enriching for a partial EMT phenotype. We also discuss how metastasis is influenced by hypoxia, partial EMT and collective cell migration, and call for a better understanding of interconnections among these mechanisms. We discuss the known regulators of hypoxia, hybrid EMT and collective cell migration and highlight the gaps which needs to be filled for connecting these three axes which will increase our understanding of dynamics of metastasis and help control it more effectively.
Display omitted
Cancer Stem Cell Plasticity - A Deadly Deal Thankamony, Archana P; Saxena, Kritika; Murali, Reshma ...
Frontiers in molecular biosciences,
04/2020, Volume:
7
Journal Article
Peer reviewed
Open access
Intratumoral heterogeneity is a major ongoing challenge in the effective therapeutic targeting of cancer. Accumulating evidence suggests that a fraction of cells within a tumor termed Cancer Stem ...Cells (CSCs) are primarily responsible for this diversity resulting in therapeutic resistance and metastasis. Adding to this complexity, recent studies have shown that there can be different subpopulations of CSCs with varying biochemical and biophysical traits resulting in varied dissemination and drug-resistance potential. Moreover, cancer cells can exhibit a high level of plasticity or the ability to dynamically switch between CSC and non-CSC states or among different subsets of CSCs. In addition, CSCs also display extensive metabolic plasticity. The molecular mechanisms underlying these different interconnected axes of plasticity has been under extensive investigation and the trans-differentiation process of Epithelial to Mesenchymal transition (EMT) has been identified as a major contributing factor. Besides genetic and epigenetic factors, CSC plasticity is also shaped by non-cell-autonomous effects such as the tumor microenvironment (TME). In this review, we discuss the latest developments in decoding mechanisms and implications of CSC plasticity in tumor progression at biochemical and biophysical levels, and the latest
approaches being taken for characterizing cancer cell plasticity. These efforts can help improve existing therapeutic approaches by taking into consideration the contribution of cellular plasticity/heterogeneity in enabling drug resistance.
Despite identical genetic constitution, a cancer cell population can exhibit phenotypic variations termed as non-genetic/non-mutational heterogeneity. Such heterogeneity – a ubiquitous nature of ...biological systems – has been implicated in metastasis, therapy resistance and tumour relapse. Here, we review the evidence for existence, sources and implications of non-genetic heterogeneity in multiple cancer types. Stochasticity/noise in transcription, protein conformation and/or external microenvironment can underlie such heterogeneity. Moreover, the existence of multiple possible cell states (phenotypes) as a consequence of the emergent dynamics of gene regulatory networks may enable reversible cell-state transitions (phenotypic plasticity) that can facilitate adaptive drug resistance and higher metastatic fitness. Finally, we highlight how computational and mathematical models can drive a better understanding of non-genetic heterogeneity and how a systems-level approach integrating mathematical modeling and
in vitro
/
in vivo
experiments can map the diverse phenotypic repertoire and identify therapeutic vulnerabilities of an otherwise clonal cell population.
Automation of emerging smart distribution grids is required to operate the grid efficiently and swiftly. This study draws a vision on grid automation with agent‐based cyber‐physical system ...integration to provide a truly distributed architecture. Furthermore, this study introduces a notion of self‐organising smart distribution grid that promotes the grid capability to heal and organise itself in the best‐suited topology without the intervention of a central operator. The proposed architecture comprises the system of bus agents (BAs) that emulate the given grid. This emulation is used by BAs to comprehend the grid conditions, switch location and compute their representative bus voltage and partial loss and to estimate the best organisation of the BAs as well as the grid. This study details the behavioural designing of BA that incorporates the functioning above. The proposed architecture also uses an event trigger approach to initiate grid organisation, which is showcased by case studies on IEEE 33 bus system. The results showcase the efficiency of the concept regarding solution accuracy with distributed computations; computational efficiency during contingencies; architecture performance under communication latency; and fault‐tolerant characteristics of the proposed architecture.
Traditional expansion planning models reflect usage-based practices and do not consider the complete utilisation of existing resources. This problem arises due to non-inclusion of price-based ...incentives provided to the consumers who incur additional network reinforcement or expansion cost. The paper proposes a generation and transmission expansion planning framework that includes price-based incentives to define the future nodal load growth. The framework implements long-run incremental cost (LRIC)-based pricing signals for economically distributed demand to minimise consumer usage charges as well as network investment. Peak demand conditions by consumers are further minimised by the time-of-use-based demand response mechanism. The combined effects of price-based response and demand response are reflected in the future demand which serves as the basis for combined generation and transmission expansion planning. The case studies highlight the drawbacks of the conventional approaches which does not maximise the utilisation of existing grid resources while the proposed framework results in delayed investment strategies as a collective effort of the users and planner to optimise grid resources and the cost of assessing the electricity.
Centralized grid operations are now facing data storage and computation complexities more than ever. These are further compounded by communication saturation and related issues. These have instigated ...the transition towards distributed computing paradigm. This paper proposes a novel agent-based distributed (node-node) state estimation that overcomes the complexities of centralized operations. The proposed methodology sketches distributed constraint satisfaction algorithm that enables an agent to estimate its local representative bus's state only by local computation and asynchronous message exchange with connected neighboring agents. The case studies demonstrate the performance, efficacy and solution accuracy of the proposed methodology by comparing it with centralized and distributed algorithms.
Feature extraction for fault detection and classification using Symbolic Dynamic Filtering (SDF) is explored in this paper. It provides an edge over existing methodologies by compressing voluminous ...waveform data into probability histograms which describe signature features of the faults. A SDF is constructed based on the knowledge of symbolic encoding and finite state automata to generate signature histogram patterns from different fault categories. These histogram patterns are used for training various pattern classifiers to build the fault classification model. The simulation results on a test distribution network showcase the model accuracy for fault prediction with k-nearest neighbour (kNN) and support vector machines.
PDF
