scholarly journals A pseudotemporal causality approach to identifying miRNA–mRNA interactions during biological processes

2020 ◽  
Author(s):  
Andres M Cifuentes-Bernal ◽  
Vu Vh Pham ◽  
Xiaomei Li ◽  
Lin Liu ◽  
Jiuyong Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Progression ◽  
Cancer Metastasis ◽  
Biological Process ◽  
Supplementary Information ◽  
Biological Processes ◽  
Mesenchymal Transition ◽  
Novel Approach ◽  
Static Information ◽  
Temporal Aspect

Abstract Motivation microRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA–mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using ‘pseudotime’ concept have inspired us to develop a pseudotime-based method to infer the miRNA–mRNA relationships characterizing a biological process by taking into account the temporal aspect of the process. Results We have developed a novel approach, called pseudotime causality, to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition, a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA–mRNA interactions in both single cell and bulk data. The results suggest that utilizing the pseudotemporal information from the data helps reveal the gene regulation in a biological process much better than using the static information. Availability and implementation R scripts and datasets can be found at https://github.com/AndresMCB/PTC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A Pseudo-Temporal Causality Approach to Identifying miRNA-mRNA Interactions During Biological Processes

2020 ◽  
Author(s):  
Andres M. Cifuentes-Bernal ◽  
Vu VH Pham ◽  
Xiaomei Li ◽  
Lin Liu ◽  
Jiuyong Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Progression ◽  
Cancer Metastasis ◽  
Biological Process ◽  
Biological Processes ◽  
Mesenchymal Transition ◽  
Novel Approach ◽  
Static Information ◽  
Temporal Aspect ◽  
Cell Trajectories

AbstractMotivationmicroRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA-mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using “pseudo-time” concept have inspired us to develop a pseudo-time based method to infer the miRNA-mRNA relationships characterising a biological process by taking into account the temporal aspect of the process.ResultsWe have developed a novel approach, called pseudo-time causality (PTC), to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition (EMT), a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA-mRNA interactions in both single cell and bulk data. The results suggest that utilising the pseudo-temporal information from the data helps reveal the gene regulation in a biological process much better than using the static information.AvailabilityR scripts and datasets can be found at https://github.com/AndresMCB/PTC

scholarly journals Single Cell Hydrodynamic Stretching and Microsieve Filtration Reveal Genetic, Phenotypic and Treatment-Related Links to Cellular Deformability

Micromachines ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 486
Author(s):  
Fenfang Li ◽  
Igor Cima ◽  
Jess Honganh Vo ◽  
Min-Han Tan ◽  
Claus Dieter Ohl
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Cancer Progression ◽  
Cancer Metastasis ◽  
Extensional Flow ◽  
Colorectal Cancer Cell Line ◽  
Mesenchymal Transition ◽  
Cellular Models ◽  
Cellular Deformability

Deformability is shown to correlate with the invasiveness and metastasis of cancer cells. Recent studies suggest epithelial-to-mesenchymal transition (EMT) might enable cancer metastasis. However, the correlation of EMT with cancer cell deformability has not been well elucidated. Cellular deformability could also help evaluate the drug response of cancer cells. Here, we combine hydrodynamic stretching and microsieve filtration to study cellular deformability in several cellular models. Hydrodynamic stretching uses extensional flow to rapidly quantify cellular deformability and size with high throughput at the single cell level. Microsieve filtration can rapidly estimate relative deformability in cellular populations. We show that colorectal cancer cell line RKO with the mesenchymal-like feature is more flexible than the epithelial-like HCT116. In another model, the breast epithelial cells MCF10A with deletion of the TP53 gene are also significantly more deformable compared to their isogenic wildtype counterpart, indicating a potential genetic link to cellular deformability. We also find that the drug docetaxel leads to an increase in the size of A549 lung cancer cells. The ability to associate mechanical properties of cancer cells with their phenotypes and genetics using single cell hydrodynamic stretching or the microsieve may help to deepen our understanding of the basic properties of cancer progression.

Galectin-3: A factotum in carcinogenesis bestowing an archery for prevention

Tumor Biology ◽  
2021 ◽  
Vol 43 (1) ◽  
pp. 77-96
Author(s):  
T. Jeethy Ram ◽  
Asha Lekshmi ◽  
Thara Somanathan ◽  
K. Sujathan
Keyword(s):  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Cancer Metastasis ◽  
Epithelial Mesenchymal Transition ◽  
Therapy Resistance ◽  
Cellular Level ◽  
Clinical Samples ◽  
Innovative Strategy ◽  
Mesenchymal Transition ◽  
Galectin 3

Cancer metastasis and therapy resistance are the foremost hurdles in oncology at the moment. This review aims to pinpoint the functional aspects of a unique multifaceted glycosylated molecule in both intracellular and extracellular compartments of a cell namely galectin-3 along with its metastatic potential in different types of cancer. All materials reviewed here were collected through the search engines PubMed, Scopus, and Google scholar. Among the 15 galectins identified, the chimeric gal-3 plays an indispensable role in the differentiation, transformation, and multi-step process of tumor metastasis. It has been implicated in the molecular mechanisms that allow the cancer cells to survive in the intravascular milieu and promote tumor cell extravasation, ultimately leading to metastasis. Gal-3 has also been found to have a pivotal role in immune surveillance and pro-angiogenesis and several studies have pointed out the importance of gal-3 in establishing a resistant phenotype, particularly through the epithelial-mesenchymal transition process. Additionally, some recent findings suggest the use of gal-3 inhibitors in overcoming therapeutic resistance. All these reports suggest that the deregulation of these specific lectins at the cellular level could inhibit cancer progression and metastasis. A more systematic study of glycosylation in clinical samples along with the development of selective gal-3 antagonists inhibiting the activity of these molecules at the cellular level offers an innovative strategy for primary cancer prevention.

scholarly journals Cooperation of Cancer Stem Cell Properties and Epithelial-Mesenchymal Transition in the Establishment of Breast Cancer Metastasis

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Tetsu Hayashida ◽  
Hiromitsu Jinno ◽  
Yuko Kitagawa ◽  
Masaki Kitajima
Keyword(s):  
Breast Cancer ◽  
Stem Cell ◽  
Cancer Stem Cell ◽  
Cancer Progression ◽  
Cancer Metastasis ◽  
Epithelial Mesenchymal Transition ◽  
Metastatic Tumor ◽  
Breast Cancer Metastasis ◽  
Cell Junctions ◽  
Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a multistep process in which cells acquire molecular alterations such as loss of cell-cell junctions and restructuring of the cytoskeleton. There is an increasing understanding that this process may promote breast cancer progression through promotion of invasive and metastatic tumor growth. Recent observations imply that there may be a cross-talk between EMT and cancer stem cell properties, leading to enhanced tumorigenicity and the capacity to generate heterogeneous tumor cell populations. Here, we review the experimental and clinical evidence for the involvement of EMT in cancer stem cell theory, focusing on the common characteristics of this phenomenon.

scholarly journals Characterizing Intercellular Communication of Pan-Cancer Reveals SPP1+ Tumor-Associated Macrophage Expanded in Hypoxia and Promoting Cancer Malignancy Through Single-Cell RNA-Seq Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Jinfen Wei ◽  
Zixi Chen ◽  
Meiling Hu ◽  
Ziqing He ◽  
Dawei Jiang ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Cancer Progression ◽  
Epithelial Mesenchymal Transition ◽  
Single Cells ◽  
Matrix Remodeling ◽  
Rna Seq ◽  
Mesenchymal Transition ◽  
Tumor Associated Macrophage ◽  
Cancer Types

Hypoxia is a characteristic of tumor microenvironment (TME) and is a major contributor to tumor progression. Yet, subtype identification of tumor-associated non-malignant cells at single-cell resolution and how they influence cancer progression under hypoxia TME remain largely unexplored. Here, we used RNA-seq data of 424,194 single cells from 108 patients to identify the subtypes of cancer cells, stromal cells, and immune cells; to evaluate their hypoxia score; and also to uncover potential interaction signals between these cells in vivo across six cancer types. We identified SPP1+ tumor-associated macrophage (TAM) subpopulation potentially enhanced epithelial–mesenchymal transition (EMT) by interaction with cancer cells through paracrine pattern. We prioritized SPP1 as a TAM-secreted factor to act on cancer cells and found a significant enhanced migration phenotype and invasion ability in A549 lung cancer cells induced by recombinant protein SPP1. Besides, prognostic analysis indicated that a higher expression of SPP1 was found to be related to worse clinical outcome in six cancer types. SPP1 expression was higher in hypoxia-high macrophages based on single-cell data, which was further validated by an in vitro experiment that SPP1 was upregulated in macrophages under hypoxia-cultured compared with normoxic conditions. Additionally, a differential analysis demonstrated that hypoxia potentially influences extracellular matrix remodeling, glycolysis, and interleukin-10 signal activation in various cancer types. Our work illuminates the clearer underlying mechanism in the intricate interaction between different cell subtypes within hypoxia TME and proposes the guidelines for the development of therapeutic targets specifically for patients with high proportion of SPP1+ TAMs in hypoxic lesions.

scholarly journals PKM2 Is the Target of a Multi-Herb-Combined Decoction During the Inhibition of Gastric Cancer Progression

2021 ◽  
Vol 11 ◽  
Author(s):  
Qingmin Sun ◽  
Mengyun Yuan ◽  
Hongxing Wang ◽  
Xingxing Zhang ◽  
Ruijuan Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Progression ◽  
Cancer Metastasis ◽  
Nuclear Translocation ◽  
Aerobic Glycolysis ◽  
Metabolic Reprogramming ◽  
Migration And Invasion ◽  
Dependent Manner ◽  
Gastric Cancer Cells ◽  
Mesenchymal Transition

Gastric cancer is the third leading cause of cancer death worldwide. Traditional Chinese medicine (TCM) is increasingly extensively applied as a complementary therapy for gastric cancer (GC) in China, which shows unique advantages in preventing gastric cancer metastasis. Previous study indicates modified Jian-pi-yang-zheng (mJPYZ) decoction inhibit the progression of gastric cancer by regulating tumor-associated macrophages (TAM). However, it is unclear whether mJPYZ can affect metabolic reprogramming of gastric cancer cells. Here, we showed that mJPYZ effectively attenuated GC cells proliferation, migration and invasion. Meantime, mJPYZ reduced the aerobic glycolysis level of GC cells in vivo and in vitro by regulating the expression and nuclear translocation of PKM2. Overexpression of PKM2 that could reverse the inhibitory effect of mJPYZ, migration and epithelial to mesenchymal transition (EMT). Our results showed PKM2/HIF-1α signaling was the key metabolic regulator of mJPYZ in GC cells. In summary, our present study suggested that abnormal PKM2 is required for maintaining the malignant phenotype of GC cells. The TCM decoction mJPYZ inhibited GC cells growth and EMT by reducing of glycolysis in PKM2 dependent manner. This evidence expanded our understanding of the anti-tumor mechanism of mJPYZ and further indicated mJPYZ a potential anti-tumor agent for GC patients.Chemical Compounds Studied in this ArticleRutin (PubChem CID: 5280805); Lobetyolin (PubChem CID: 53486204); Calycosin-7-glucoside (PubChem CID: 71571502); Formononetin (PubChem CID: 5280378); Calycosin (PubChem CID: 5280448); Ononin (PubChem CID: 442813); P-Coumaric Acid (PubChem CID: 637542).

scholarly journals Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Loukia G. Karacosta ◽  
Benedict Anchang ◽  
Nikolaos Ignatiadis ◽  
Samuel C. Kimmey ◽  
Jalen A. Benson ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Single Cell ◽  
Cancer Progression ◽  
Time Course ◽  
Epithelial Mesenchymal Transition ◽  
Clinical Samples ◽  
Neural Net ◽  
Mesenchymal Transition ◽  
Phenotypic Profile

AbstractElucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies.

scholarly journals Galectin-3 as a Potential Target to Prevent Cancer Metastasis

2015 ◽  
Vol 9 ◽  
pp. CMO.S29462 ◽  
Author(s):  
Hafiz Ahmed ◽  
Dina M. M. Alsadek
Keyword(s):  
Cancer Progression ◽  
Growth Regulation ◽  
Cancer Metastasis ◽  
Carbohydrate Binding ◽  
Biological Processes ◽  
Binding Properties ◽  
Galectin 3 ◽  
Carbohydrate Ligands ◽  
Lectin Family ◽  
Binding Lectin

Interactions between two cells or between cell and extracellular matrix mediated by protein–carbohydrate interactions play pivotal roles in modulating various biological processes such as growth regulation, immune function, cancer metastasis, and apoptosis. Galectin-3, a member of the β-galactoside-binding lectin family, is involved in fibrosis as well as cancer progression and metastasis, but the detailed mechanisms of its functions remain elusive. This review discusses its structure, carbohydrate-binding properties, and involvement in various aspects of tumorigenesis and some potential carbohydrate ligands that are currently investigated to block galectin-3 activity.

scholarly journals GPseudoRank: a permutation sampler for single cell orderings

2017 ◽  
Author(s):  
Magdalena E Strauß ◽  
John E Reid ◽  
Lorenz Wernisch
Keyword(s):  
Single Cell ◽  
Microarray Data ◽  
Network Inference ◽  
Biological Process ◽  
Supplementary Information ◽  
Established Method ◽  
Data Set ◽  
Point Estimates ◽  
Biological Development ◽  
Selection Of

AbstractMotivationA number of pseudotime methods have provided point estimates of the ordering of cells for scRNA-seq data. A still limited number of methods also model the uncertainty of the pseudotime estimate. However, there is still a need for a method to sample from complicated and multi-modal distributions of orders, and to estimate changes in the amount of the uncertainty of the order during the course of a biological development, as this can support the selection of suitable cells for the clustering of genes or for network inference.ResultsIn an application to a microarray data set our proposed method, GPseudoRank, identifies two modes of the distribution, each of them corresponding to point estimates of orders obtained by a different established method. In an application to scRNA-seq data we demonstrate the potential of GPseudoRank to identify phases of lower and higher pseudotime uncertainty during a biological process. GPseudoRank also correctly identifies cells precocious in their antiviral response.Availability and implementationOur method is available on github: https://github.com/magStra/GPseudoRank.Contactmagdalena.strauss@mrc-bsu.cam.ac.ukSupplementary informationSupplementary materials are available.

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