Topological analysis of interaction patterns in cancer-specific gene regulatory network: persistent homology approach
In this study, we investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease. We aim to propose that the quest of understanding cancer takes us beyond pairwise interactions between genes to a higher-order construction. We characterize the most prominent network deviations in the gene interaction patterns between cancer and normal samples that contribute to the complexity of this disease. What we hope is that through understanding these interaction patterns we will notice a deeper structure in the cancer network. This study uncovers the significant deviations that topological features in cancerous cells show from the healthy one, where the last stage of filtration confirms the importance of one-dimensional holes (topological loops) in cancerous cells and two-dimensional holes (topological voids) in healthy cells. In the small threshold region, the drop in the number of connected components of the cancer network, along with the rise in the number of loops and voids, all occurring at some smaller weight values compared to the normal case, reveals the cancerous network tendency to certain pathways.
Highlights
In this study, we investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease
By analyzing the interaction networks from the topological point of view, we aim to uncover prominent insights into cellular gene interaction patterns. To this end, applying the Persistent Homology (PH) technique on the weighted complex networks of the normal and cancerous data sets, we analyze the evolution of the dimension of the k-homology group of the topological space; where these Betti numbers demonstrate the number of k-dimensional topological holes
In this study, according to our results, we propose Topological Data Analysis (TDA) can be employed to associate cancer cell proliferation to numbers and the evolution of topological features, so as to study this disease from the viewpoint of patterns of genes’ interaction in order to confirm how local topological modifications may contribute to global features and propose examining the patterns of interactions as a general and global picture as an alternative to studying single genes and their pairwise interactions
Summary
We investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease. The subsequent cellular phenotype is modulated by a dynamic network of interactions among genes Perturbations in these interactions affect the overall manifestation of genetically driven diseases such as cancer. Responses to driving forces on the structure formation of these networks cause the development of new features and subsequently lead to the identification of unique patterns in the observational data These patterns can arise from non-trivial connections that go beyond classical pairwise interactions, leading to a higher-order c onstruction[16]. These constructions can be described by simplices of different dimensions and can be studied in the framework of Balance Theory and Topological Data Analysis (TDA). Network construction from real data and the result of balance theory analysis of the interaction network
28
- 10.1002/qua.26133
- Dec 17, 2019
- International Journal of Quantum Chemistry
67
- 10.1090/psapm/070/587
- Jan 1, 2012
18
- 10.1002/sim.6157
- Mar 28, 2014
- Statistics in Medicine
34
- 10.1103/physreve.93.042306
- Apr 8, 2016
- Physical Review E
6
- 10.1016/j.chaos.2020.110260
- Sep 7, 2020
- Chaos, Solitons & Fractals
279
- 10.1103/physreve.72.036121
- Sep 21, 2005
- Physical Review E
7461
- 10.1038/ng.2764
- Sep 26, 2013
- Nature Genetics
48
- 10.1103/physreve.95.022314
- Feb 28, 2017
- Physical Review E
14232
- 10.1038/s41598-020-79139-8
- Jan 7, 2021
- Scientific Reports
179
- 10.1103/physrevlett.103.198701
- Nov 4, 2009
- Physical Review Letters
- Research Article
- 10.3390/ncrna8030033
- May 12, 2022
- Non-Coding RNA
Exosomes carry molecules of great biological and clinical interest, such as miRNAs. The contents of exosomes vary between healthy controls and cancer patients. Therefore, miRNAs and other molecules transported in exosomes are considered a potential source of diagnostic and prognostic biomarkers in cancer. Many miRNAs have been detected in recent years. Consequently, a substantial amount of miRNA-related data comparing patients and healthy individuals is available, which contributes to a better understanding of the initiation, development, malignancy, and metastasis of cancer using non-invasive sampling procedures. However, a re-analysis of available ncRNA data is rare. This study used available data about miRNAs in exosomes comparing healthy individuals and cancer patients to identify possible global changes related to the presence of cancer. A robust transcriptomic analysis identified two common miRNAs (miR-495-3p and miR-543) deregulated in five cancer datasets. They had already been implicated in different cancers but not reported in exosomes circulating in blood. The study also examined their target genes and the implications of these genes for functional processes.
- Research Article
29
- 10.1103/physrevlett.128.218101
- May 27, 2022
- Physical Review Letters
Resolution of the intrinsic conflict between the reproduction of single cells and the homeostasis of a multicellular organism is central to animal biology and has direct impact on aging and cancer. Intercellular competition is indispensable in multicellular organisms because it weeds out senescent cells, thereby increasing the organism's fitness and delaying aging. In this Letter, we describe the growth dynamics of multicellular organisms in the presence of intercellular competition and show that the lifespan of organisms can be extended and the onset of cancer can be delayed if cells alternate between competition (a fair strategy) and noncompetitive growth, or cooperation (a losing strategy). This effect recapitulates the weak form of the game-theoretic Parrondo's paradox, whereby strategies that are individually fair or losing achieve a winning outcome when alternated. We show in a population model that periodic and stochastic switching between competitive and cooperative cellular strategies substantially extends the organism lifespan and reduces cancer incidence, which cannot be achieved simply by optimizing the competitive ability of the cells. These results indicate that cells could have evolved to optimally mix competitive and cooperative strategies, and that periodic intercellular competition could potentially be exploited and tuned to delay aging.
- Preprint Article
- 10.1101/2022.11.22.517587
- Nov 24, 2022
ABSTRACTNon-small cell lung cancer (NSCLC), the primary histological form of lung cancer, accounts for about 25% - the highest - of all cancer deaths. As NSCLC is often undetected until symptoms appear in the late stages, it is imperative to discover more effective tumor-associated biomarkers for early diagnosis. Topological data analysis is one of the most powerful methodologies applicable to biological networks. However, current studies fail to consider the biological significance of their quantitative methods and utilize popular scoring metrics without verification, leading to low performance. To extract meaningful insights from genomic data, it is essential to understand the relationship between geometric correlations and biological function mechanisms. Through bioinformatics and network analyses, we propose a novel composite selection index, the C-Index, that best captures significant pathways and interactions in gene networks to identify biomarkers with the highest efficiency and accuracy. Furthermore, we establish a 4-gene biomarker signature that serves as a promising therapeutic target for NSCLC and personalized medicine. We designed a Cascading machine learning model to validate both the C-Index and the biomarkers discovered. The methodology proposed for finding top metrics can be applied to effectively select biomarkers and early diagnose many diseases, revolutionizing the approach to topological network research for all cancers.
- Book Chapter
- 10.1016/b978-0-443-15452-2.00021-2
- Jan 1, 2025
- Mining Biomedical Text, Images and Visual Features for Information Retrieval
Chapter 21 - Persistent homology diagram (PHD) based web service for cancer tagging of mammograms
- Preprint Article
1
- 10.1101/2023.10.04.560910
- Oct 6, 2023
Abstract Glial scar formation represents a fundamental response to central nervous system (CNS) injury. It is mainly characterized by a well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial scar formation have been extensively studied, yet quantitative descriptors of the spatial arrangement of reactive glial cells remain limited. Here, we present a novel approach using point pattern analysis (PPA) and topological data analysis (TDA) to quantify spatial patterns of reactive glial cells after experimental ischemic stroke in mice. We provide open and reproducible tools usingRandJuliato quantify spatial intensity, cell covariance and conditional distribution, cell-to-cell interactions, and short/long-scale arrangement, which collectively disentangle the arrangement patterns of the glial scar. This approach unravels a substantial divergence in the distribution of reactive astrocytes and microglia after injury that conventional analysis methods cannot fully characterize. PPA and TDA are valuable tools for studying the complex spatial arrangement of reactive glia and other nervous cells following CNS injuries and have potential applications for evaluating glial-targeted restorative therapies.
- Research Article
2
- 10.1103/physreve.106.064115
- Dec 12, 2022
- Physical Review E
A well-known class of nonstationary self-similar time series is the fractional Brownian motion (fBm) considered to model ubiquitous stochastic processes in nature. Due to noise and trends superimposed on data and even sample size and irregularity impacts, the well-known computational algorithm to compute the Hurst exponent (H) has encountered superior results. Motivated by this discrepancy, we examine the homology groups of high-dimensional point cloud data (PCD), a subset of the unit D-dimensional cube, constructed from synthetic fBm data as a pipeline to compute the H exponent. We compute topological measures for embedded PCD as a function of the associated Hurst exponent for different embedding dimensions, time delays, and amount of irregularity existing in the dataset in various scales. Our results show that for a regular synthetic fBm, the higher value of the embedding dimension leads to increasing the H dependency of topological measures based on zeroth and first homology groups. To achieve a reliable classification of fBm, we should consider the small value of time delay irrespective of the irregularity presented in the data. More interestingly, the value of the scale for which the PCD to be path connected and the postloopless regime scale are more robust concerning irregularity for distinguishing the fBm signal. Such robustness becomes less for the higher value of the embedding dimension. Finally, the associated Hurst exponents for our topological feature vector for the S&P500 were computed, and the results are consistent with the detrended fluctuation analysis method.
- Research Article
2
- 10.1371/journal.pone.0279089
- Dec 22, 2022
- PLOS ONE
In financial crises, assets see a deep loss of value, and the financial markets experience liquidity shortages. Although they are not uncommon, they may cause by multiple contributing factors which makes them hard to study. To discover features of the financial network, the pairwise interaction of stocks has been considered in many pieces of research, but the existence of the strong correlation between stocks and their collective behavior in crisis made us address higher-order interactions. Hence, in this study, we investigate financial networks by triplet interaction in the framework of balance theory. Due to detecting the contribution of higher-order interactions in understanding the complex behavior of stocks we take the advantage of the order parameter of the higher-order interactions. Looking at real data of the financial market obtained from S&P500 index(SPX) through the lens of balance theory for the quest of network structure in different periods (on and off-crisis) faces us with the existence of a structural difference of networks corresponding to the periods. Addressing two well-known crises the Great regression (2008) and the Covid-19 recession (2020), our results show an ordered structure forms in the on-crisis period in the financial network while stocks behave independently far from a crisis. The formation of the ordered structure of stocks in crisis makes the network more resilient to disorder (thermal fluctuations). The resistance of the ordered structure against applying the disorder measure the crisis strength and determine the temperature at which the network transits. There is a critical temperature, Tc, in the language of statistical mechanics and mean-field approach which above, the ordered structure destroys abruptly and a first-order phase transition occurs. The stronger the crisis, the higher the critical temperature.
- Research Article
5
- 10.1038/s41598-023-35165-w
- May 22, 2023
- Scientific Reports
Non-small cell lung cancer (NSCLC), the primary histological form of lung cancer, accounts for about 25%—the highest—of all cancer deaths. As NSCLC is often undetected until symptoms appear in the late stages, it is imperative to discover more effective tumor-associated biomarkers for early diagnosis. Topological data analysis is one of the most powerful methodologies applicable to biological networks. However, current studies fail to consider the biological significance of their quantitative methods and utilize popular scoring metrics without verification, leading to low performance. To extract meaningful insights from genomic data, it is essential to understand the relationship between geometric correlations and biological function mechanisms. Through bioinformatics and network analyses, we propose a novel composite selection index, the C-Index, that best captures significant pathways and interactions in gene networks to identify biomarkers with the highest efficiency and accuracy. Furthermore, we establish a 4-gene biomarker signature that serves as a promising therapeutic target for NSCLC and personalized medicine. The C-Index and biomarkers discovered were validated with robust machine learning models. The methodology proposed for finding top metrics can be applied to effectively select biomarkers and early diagnose many diseases, revolutionizing the approach to topological network research for all cancers.
- Research Article
2
- 10.1038/s41598-024-69426-z
- Aug 16, 2024
- Scientific Reports
Glial scar formation represents a fundamental response to central nervous system (CNS) injuries. It is mainly characterized by a well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial scar formation have been extensively studied, yet quantitative descriptors of the spatial arrangement of reactive glial cells remain limited. Here, we present a novel approach using point pattern analysis (PPA) and topological data analysis (TDA) to quantify spatial patterns of reactive glial cells after experimental ischemic stroke in mice. We provide open and reproducible tools using R and Julia to quantify spatial intensity, cell covariance and conditional distribution, cell-to-cell interactions, and short/long-scale arrangement, which collectively disentangle the arrangement patterns of the glial scar. This approach unravels a substantial divergence in the distribution of GFAP+ and IBA1+ cells after injury that conventional analysis methods cannot fully characterize. PPA and TDA are valuable tools for studying the complex spatial arrangement of reactive glia and other nervous cells following CNS injuries and have potential applications for evaluating glial-targeted restorative therapies.
- Research Article
2
- 10.1007/s11538-024-01353-6
- Sep 17, 2024
- Bulletin of Mathematical Biology
Topological data analysis (TDA) is an active field of mathematics for quantifying shape in complex data. Standard methods in TDA such as persistent homology (PH) are typically focused on the analysis of data consisting of a single entity (e.g., cells or molecular species). However, state-of-the-art data collection techniques now generate exquisitely detailed multispecies data, prompting a need for methods that can examine and quantify the relations among them. Such heterogeneous data types arise in many contexts, ranging from biomedical imaging, geospatial analysis, to species ecology. Here, we propose two methods for encoding spatial relations among different data types that are based on Dowker complexes and Witness complexes. We apply the methods to synthetic multispecies data of a tumor microenvironment and analyze topological features that capture relations between different cell types, e.g., blood vessels, macrophages, tumor cells, and necrotic cells. We demonstrate that relational topological features can extract biological insight, including the dominant immune cell phenotype (an important predictor of patient prognosis) and the parameter regimes of a data-generating model. The methods provide a quantitative perspective on the relational analysis of multispecies spatial data, overcome the limits of traditional PH, and are readily computable.
- Research Article
18
- 10.1016/j.cels.2020.01.002
- Feb 1, 2020
- Cell Systems
Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations.
- Research Article
56
- 10.1016/s0025-6196(11)61193-2
- Jun 1, 2007
- Mayo Clinic Proceedings
Reading the Tea Leaves: Anticarcinogenic Properties of (-)-Epigallocatechin-3-Gallate
- Research Article
57
- 10.4065/82.6.725
- Jun 1, 2007
- Mayo Clinic Proceedings
Reading the Tea Leaves: Anticarcinogenic Properties of (-)-Epigallocatechin-3-Gallate
- Research Article
1
- 10.1088/2516-1067/ab4a1d
- Oct 11, 2019
- Plasma Research Express
This paper discusses possible mechanisms for the selective effect of weakly ionized nonequilibrium plasma and currents in electrolytes on healthy and cancerous cells in physiological saline in a Petri dish. The interaction with the plasma source leads to a change in osmotic pressure, which affects the electro-mechanical properties of cell membranes in healthy and cancerous cells in different ways. The currents arising in the electrolyte charge the membranes of healthy and cancerous cells to a different potential difference due to the different values of the membranes’ dielectric constants. We hypothesized: 1. The dielectric permeability of cancer cell membranes is lower than that of healthy cells, as is the capacity of a unit of the membrane surface, and therefore, the additional potential difference acquired by the membrane through charging with currents induced in the intercellular electrolyte is greater in cancer cells. This can lead to electroporation of cancer cell membranes, resulting in their apoptosis, but does not affect healthy cells. 2. It is known from the literature that the equilibrium potential differences on the membrane (resting potential) of cancer and healthy cells are noticeably different. Therefore, a change in the potential difference on the membrane due to currents in the extracellular fluid can affect the permeability and transport properties of the membranes. It can also be a reason for the selective effect of the nonequilibrium plasma interaction with healthy and cancerous cells in physiological saline.
- Research Article
- 10.3389/conf.fbioe.2016.01.01121
- Jan 1, 2016
- Frontiers in Bioengineering and Biotechnology
Event Abstract Back to Event Dendritic pro-drug for local and selective treatment of locally advanced breast cancer Nuria Oliva1, Mariana Atilano1, 2*, João Conde1, 3*, Elazer R. Edelman1, 4* and Natalie Artzi1, 5* 1 MIT, IMES, United States 2 IQS, Chemical Engineering, Spain 3 Queen Mary University of London, School of Engineering and Materials Science, United Kingdom 4 BWH, Harvard Medical School, Cardiovascular Division, United States 5 BWH, Harvard Medical School, Department of Medicine, United States Introduction: Systemic neoadjuvant therapy has been established as the preferred therapeutic approach for locally advanced breast cancer, downstaging the disease and preventing mastectomy. However, complications of systemic chemotherapy are devastating. Local therapy would prevent high concentrations of circulating drug and reduce off-target tissue retention. Yet, the means to attain ideal release kinetics and selective uptake remain elusive. We have developed a novel class of biocompatible and biodegradable adhesive materials based on dendrimers and dextrans[1] that can coat the tumor and locally release drugs in a controlled manner. In this work, I have developed and optimized a dendritic pro-drug capable of discerning between healthy and cancer cells. It selectively enters EGFR-overexpressing breast cancer cells through receptor-mediated endocytosis (RME) and releases doxorubicin inside the cells. They will be added to our adhesive hydrogel for local and sustained delivery. Materials and Methods: PAMAM dendrimer generation 5 (Dendritech) was conjugated to EGF-mimicking peptides[2] (Biopolymer Lab, MIT) and also to doxorubicin (Cayman) through a pH-sensitive linker[3]. Cancer cells (MDA-MB-468, ATCC) and healthy mammary epithelial cells (HMEpC, ATCC) were cultured in their recommended media. Cells were treated with 10 uM tagged-dendrimer solutions and uptake was assessed by FACS. Doxorubicin release from the dendrimer was monitored through UV-VIS spectroscopy in PBS (pH 7.4) and acetate buffer (pH 5.5). Cancer and healthy cells were incubated with 10 uM dendritic pro-drug for 48 hours to study cytotoxicity. Results and Discussion: Fluorescence microscopy showed indiscriminate uptake of naked dendrimer independent of cell type (Fig. 1a-b), while dendrimer-peptide uptake was higher in EGFR+ cancer cells than in EGFR- healthy cells (Fig. 1d-e). Blocking of the receptor using an antibody caused abrogation of dendrimer-peptide uptake, but not naked dendrimer (Fig 1c and f). These results were corroborated by FACS (not shown). Taken together, these data prove that our dendrimer conjugates are being uptaken by RME through EGFR, as opposed to diffusion-driven uptake observed for naked dendrimer. Doxorubicin was conjugated to dendrimer-peptide through a cis-aconityl pH-sensitive linker to form the dendritic pro-drug. Incubation of the dendritic pro-drug in PBS (pH 7.4) showed no statistically significant doxorubicin release over 12 hours, while 45% of the drug was released in acetate buffer (pH 5.5) in the first 3 hours (not shown), thus corroborating pH-triggered release. The dendritic pro-drug showed 86% cytotoxicity after 48 hours in cancer cells, while no toxicity was observed in healthy cells (Fig. 1g-k). Conclusions: We have demonstrated that we can successfully develop a dendritic pro-drug that selectively treats EGFR-overexpressing tumors while minimizing side effects in healthy cells surrounding the tumor. The dendritic pro-drug will be incorporated to our adhesive hydrogel and release kinetics and in vivo efficacy will be assessed. Generalization of this platform with peptides targeting other commonly overexpressed growth factor receptors in cancer (FGF2R, VEGFR or PDGFR) will expand the targeting capabilities of our delivery system. We aim to develop a delivery platform capable of treating tumors in a local and selective manner. Marie Curie International Outgoing Fellowship and Funding (FP7-PEOPLE-2013-IOF, Project 626386); Dr. Dong Soo Yun for cryo-TEM assistance at the Peterson Nanotechnology Materials Core Facility; KI MIT Biopolymers Lab; Dr. Glenn Paradis for FACS assistance with Cancer Center Support (FACS core); KI Genomics Core/ MIT BioMicro Center; Timothy E. Cheng for assistance with computation of methods
- Research Article
- 10.1096/fasebj.2021.35.s1.02115
- May 1, 2021
- The FASEB Journal
Significance High platelet counts and advanced stage of ovarian cancer go hand-in-hand in promoting each other in a feed-forward loop that results in blood coagulation and chemotherapy resistance. This results in a high incidence of death due to thrombosis in ovarian cancer patients, and especially in patients with the ovarian clear cell carcinoma histologic type. Objective and Hypothesis We sought to develop an experimental model of the positive interactions between platelets and cancer cells and test the hypothesis that interference with platelet clotting will inhibit this interaction. Approach The effects of platelets on spheroid formation by cancer or healthy epithelial cells were evaluated using a magnetic 3D cancer spheroids assay. The ES2 and MESOV cell lines, which represent clear cell carcinoma and high grade serous histologies, respectively were used for the ovarian cancer cells. Primary human fallopian tube secretory epithelial cell cultures were used to represent healthy cells. The spheroids were imaged and measured using the Optronix GelCount colony counter and evaluated using metabolic viability (MTT) and protein concentration (SRB) assays. The shear-free platelet aggregation assay was performed in the presence of healthy or cancer cells or their conditioned media. Furthermore, we evaluated possible interruption of this feed-forward loop using antiplatelet agents: aspirin—a cyclooxygenase (COX)-1 and -2 inhibitor, celecoxib—a selective COX-2 inhibitor, clopidogrel—an ADP binding inhibitor, dipyridamole—an ADP uptake inhibitor, eptifibatide—a platelet's GP IIb/IIIa inhibitor, and prostacyclin—a platelet aggregation inhibitor. Results Incubation of platelets with cancer spheroids as they are forming decreased the size and density of the spheres in less than 15 minutes of exposure. The MTT assay indicated that condensed spheres were just as live and viable as the spheres that formed in the absence of platelets. Incubation of cancer cells or cancer cells’ conditioned media with platelets caused clumping of platelets in a cancer cells number-dependent manner. Healthy cells’ conditioned media did not cause platelets aggregation. Pre-treating platelets with up to a 1 mM of aspirin, clopidogrel, dipyridamole, and prostacyclin did not prevent cancer cell-induced aggregation, unlike celecoxib, which prevented aggregation at high concentrations, and eptifibatide, which was able to prevent aggregation at low concentrations as 0.1 µM. Conclusions The positive interaction between platelets and cancer cells can be mimicked in co-culture conditions. This interaction appears to involve platelets GPIIb/IIIa binding.
- Research Article
47
- 10.1021/acsami.7b15116
- Nov 1, 2017
- ACS Applied Materials & Interfaces
Despite the early promises of magnetic hyperthermia (MH) as a method for treating cancer, it has been stagnating in the past decade. Some of the reasons for the low effectiveness of superparamagnetic nanoparticles (SPIONs) in MH treatments include (a) low uptake in cancer cells; (b) generation of reactive oxygen species that cause harm to the healthy cells; (c) undeveloped targeting potential; and (d) lack of temperature sensitivity between cancer cells and healthy cells. Here we show that healthy cells, including human mesenchymal stem cells (MSCs) and primary mouse kidney and lung fibroblasts, display an unfavorably increased uptake of SPIONs compared to human brain cancer cells (E297 and U87) and mouse osteosarcomas cells (K7M2). Hydroxyapatite (HAP), the mineral component of our bones, may offer a solution to this unfavorably selective SPION delivery. HAP nanoparticles are commended not only for their exceptional biocompatibility but also for the convenience of their use as an intracellular delivery agent. Here we demonstrate that dispersing SPIONs in HAP using a wet synthesis method could increase the uptake in cancer cells and minimize the risk to healthy cells. Specifically, HAP/SPION nanocomposites retain the superparamagnetic nature of SPIONs, increase the uptake ratio between U87 human brain cancer cells and human MSCs versus their SPION counterparts, reduce migration in a primary brain cancer spheroid model compared to the control, reduce brain cancer cell viability compared to the treatment with SPIONs alone, and retain the viability of healthy human MSCs. A functional synergy between the two components of the nanocomposites was established; as a result, the cancer versus healthy cell (U87/MSC) selectivity in terms of both the uptake and the toxicity was higher for the composite than for SPIONs or HAP alone, allowing it to be damaging to cancer cells and harmless to the healthy ones. The analysis of actin cytoskeleton order at the microscale revealed that healthy MSCs and primary cancer cells after the uptake of SPIONs display reduced and increased anisotropy in their cytoskeletal arrangement, respectively. In contrast, the uptake of SPION/HAP nanocomposites increased the cytoskeletal anisotropy of both the healthy MSCs and the primary cancer cells. In spite of the moderate specific magnetization of HAP/SPION nanohybrids, reaching 15 emu/g for the 28.6 wt % SPION-containing composite, the cancer cell treatment in an alternating magnetic field resulted in an intense hyperthermia effect that increased the temperature by ca. 1 °C per minute of exposure and reduced the cell population treated for 30 min by more than 50%, while leaving the control populations unharmed. These findings on nanocomposites of HAP and SPIONs may open a new avenue for cancer therapies that utilize MH.
- Research Article
20
- 10.1039/d1sc04656j
- Jan 1, 2021
- Chemical Science
It was recently shown that it is possible to exploit the nanoparticle shape to selectively target endocytosis pathways found in cancer and not healthy cells. It is important to understand and compare the endocytosis pathways of nanoparticles in both cancer and healthy cells to restrict the healthy cells from taking up anticancer drugs to help reduce the side effects for patients. Here, the clathrin-mediated endocytosis inhibitor, hydroxychloroquine, and the anticancer drug, doxorubicin, are loaded into the same mesoporous silica nanorods. The use of nanorods was found to restrict the uptake by healthy cells but allowed cancer cells to take up the nanorods via the macropinocytosis pathway. Furthermore, it is shown that the nanorods can selectively deliver doxorubicin to the nucleus of breast cancer cells and to the cytoplasm of pancreatic cancer cells. The dual-drug-loaded nanorods were able to selectively kill the breast cancer cells in the presence of healthy breast cells. This study opens exciting possibilities of targeting cancer cells based on the material shape rather than targeting antibodies.
- Research Article
6
- 10.2174/1574892817666220104094846
- Nov 1, 2022
- Recent Patents on Anti-Cancer Drug Discovery
In most communities, the risk of developing breast cancer is increasing. By affecting the cyclooxygenase 1 and 2 (COX-1 and COX-2) enzymes and actin filaments, acetylsalicylic acid (Aspirin) has been shown to reduce the risk of breast cancer and prevent cell migration in both laboratory and clinical studies. The purpose of this study is to determine the mechanical properties of normal and cancerous breast tissue cells, as well as the short-term effect of aspirin on cancer cells. To this end, the mechanical properties and deformation of three cell types were investigated: healthy MCF-10 breast cells, MCF-7 breast cancer cells, and MCF-7 breast cancer cells treated with a 5 μM aspirin solution. Atomic Force Microscopy (AFM) was used to determine the mechanical properties of the cells. Cell deformation was analyzed in all groups, and Young's modulus was calculated using the Hertz model. According to the obtained data, cancer cells deformed at a rate half that of healthy cells. Nonetheless, when aspirin was used, cancer cells deformed similarly to healthy cells. Additionally, healthy cells' Young's modulus was calculated to be approximately three times that of cancer cells, which was placed closer to that of healthy cells by adding aspirin to Young's modulus. Cell strength appears to have increased due to aspirin's intervention on actin filaments and cytoskeletons, and the mechanical properties of breast cancer cells have become more similar to those of normal cells. The likelihood of cell migration and metastasis decreases as cell strength increases.
- Research Article
- 10.1016/j.ultrasmedbio.2024.12.011
- Jan 1, 2025
- Ultrasound in medicine & biology
Resonance-Induced Therapeutic Technique for Skin Cancer Cells.
- Research Article
- 10.1186/s40168-025-02156-0
- Jul 7, 2025
- Microbiome
BackgroundUnderstanding pairwise bacterial interactions in the human gut is crucial for deciphering the complex networks of bacterial interactions and their contributions to host health. However, there is a lack of large-scale experiments focusing on bacterial interactions within the human gut microbiome.MethodsWe investigated the pairwise interactions of 113 bacterial strains isolated from healthy Chinese volunteers, selected for their high abundance and functional representation of the human gut microbiome. Using mGAM agar plates, a rich medium designed to maintain community structure, we established the “PairInteraX” dataset, which includes 3233 pair combinations of culturable human gut bacteria. This dataset was analyzed to identify interaction patterns and the key factors influencing these patterns.ResultsOur analysis revealed that negative interactions were predominant among the bacteria in the PairInteraX dataset. When combined with in vivo gut metagenome datasets, we noted a diminishing mutualism and an increasing competition as microbial abundances increased; consequently, the maintenance of community diversity requires the participation of various types of interactions, especially the negative interactions. We also identified key factors influencing these interaction patterns including metabolic capacity and motility.ConclusionsThis study provides a comprehensive overview of pairwise bacterial interactions within the human gut microbiome, revealing a dominance of negative interactions. Besides, metabolic capacity and motility were identified as the key factors to influence the pairwise interaction patterns. This large-scale dataset and analysis offer valuable insights for further research on microbial community dynamics and their implications for host health.CQqVLhf9exYcCHQM3rrN7jVideo
- Research Article
27
- 10.1002/adfm.202007880
- May 30, 2021
- Advanced Functional Materials
Macropinocytosis is a consequence of oncogenic alterations of cancer cells while most healthy cells are non‐macropinocytic. It is currently unclear whether macropinocytic cancer cells can be targeted rather than healthy cells, by adjusting the shape and size of nanoparticles. Herein, the endocytosis of two differently shaped nanoparticles; nanorods and nanospheres are compared in cancer and healthy cells. The cells are breast epithelial cancer cells (MCF7) and breast epithelial healthy cells (MCF10A) and pancreas cancer cells (PANC‐1 cells) and non‐tumourogenic patient‐derived cancer‐associated fibroblasts (CAFs). The endocytosis pathway is quantified by a combination of pair correlation microscopy and endocytosis inhibitors. MCF7 cells use clathrin‐mediated endocytosis and macropinocytosis to take up the nanorods while MCF10A cells use predominantly clathrin‐mediated endocytosis. Based on the comparison of endocytic behavior of cancer and healthy cells, MCF7 cells can be induced to take up more nanorods and suppress the metabolism and endocytosis of nanorods in MCF10A cells. The nanorods allow targeting to breast cancer MCF7 cells and pancreas cancer cells over the healthy cells. This study opens exciting possibilities for shape to target the cancer cells over healthy cells, by adjusting nanoparticle shape.
- Research Article
- 10.1016/j.pharma.2025.07.001
- Jul 1, 2025
- Annales pharmaceutiques francaises
Investigation of cytotoxic activity properties of etoxazole towards human cancer and healthy cell lines and molecular docking studies.
- Research Article
21
- 10.1530/vb-21-0008
- Sep 14, 2021
- Vascular Biology
Rho GTPases are small signalling G-proteins that are central regulators of cytoskeleton dynamics, and thereby regulate many cellular processes, including the shape, adhesion and migration of cells. As such, Rho GTPases are also essential for the invasive behaviour of cancer cells, and thus involved in several steps of the metastatic cascade, including the extravasation of cancer cells. Extravasation, the process by which cancer cells leave the circulation by transmigrating through the endothelium that lines capillary walls, is an essential step for metastasis towards distant organs. During extravasation, Rho GTPase signalling networks not only regulate the transmigration of cancer cells but also regulate the interactions between cancer and endothelial cells and are involved in the disruption of the endothelial barrier function, ultimately allowing cancer cells to extravasate into the underlying tissue and potentially form metastases. Thus, targeting Rho GTPase signalling networks in cancer may be an effective approach to inhibit extravasation and metastasis. In this review, the complex process of cancer cell extravasation will be discussed in detail. Additionally, the roles and regulation of Rho GTPase signalling networks during cancer cell extravasation will be discussed, both from a cancer cell and endothelial cell point of view.
- Research Article
2
- 10.3389/fimmu.2023.1219165
- Oct 17, 2023
- Frontiers in Immunology
Chimeric antigen receptor-engineered T cells (CAR-Ts) are investigated in various clinical trials for the treatment of cancer entities beyond hematologic malignancies. A major hurdle is the identification of a target antigen with high expression on the tumor but no expression on healthy cells, since "on-target/off-tumor" cytotoxicity is usually intolerable. Approximately 90% of carcinomas and leukemias are positive for the Thomsen-Friedenreich carbohydrate antigen CD176, which is associated with tumor progression, metastasis and therapy resistance. In contrast, CD176 is not accessible for ligand binding on healthy cells due to prolongation by carbohydrate chains or sialylation. Thus, no "on-target/off-tumor" cytotoxicity and low probability of antigen escape is expected for corresponding CD176-CAR-Ts. Using the anti-CD176 monoclonal antibody (mAb) Nemod-TF2, the presence of CD176 was evaluated on multiple healthy or cancerous tissues and cells. To target CD176, we generated two different 2nd generation CD176-CAR constructs differing in spacer length. Their specificity for CD176 was tested in reporter cells as well as primary CD8+ T cells upon co-cultivation with CD176+ tumor cell lines as models for CD176+ blood and solid cancer entities, as well as after unmasking CD176 on healthy cells by vibrio cholerae neuraminidase (VCN) treatment. Following that, both CD176-CARs were thoroughly examined for their ability to initiate target-specific T-cell signaling and activation, cytokine release, as well as cytotoxicity. Specific expression of CD176 was detected on primary tumor tissues as well as on cell lines from corresponding blood and solid cancer entities. CD176-CARs mediated T-cell signaling (NF-κB activation) and T-cell activation (CD69, CD137 expression) upon recognition of CD176+ cancer cell lines and unmasked CD176, whereby a short spacer enabled superior target recognition. Importantly, they also released effector molecules (e.g. interferon-γ, granzyme B and perforin), mediated cytotoxicity against CD176+ cancer cells, and maintained functionality upon repetitive antigen stimulation. Here, CD176L-CAR-Ts exhibited slightly higher proliferation and mediator-release capacities. Since both CD176-CAR-Ts did not react towards CD176- control cells, their response proved to be target-specific. Genetically engineered CD176-CAR-Ts specifically recognize CD176 which is widely expressed on cancer cells. Since CD176 is masked on most healthy cells, this antigen and the corresponding CAR-Ts represent a promising approach for the treatment of various blood and solid cancers while avoiding "on-target/off-tumor" cytotoxicity.
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