scholarly journals Intratumoral Heterogeneity Promotes Collective Cancer Invasion through NOTCH1 Variation

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3084
Author(s):  
Peter Torab ◽  
Yue Yan ◽  
Mona Ahmed ◽  
Hironobu Yamashita ◽  
Joshua I. Warrick ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Interference ◽  
Computational Model ◽  
Poor Prognosis ◽  
Gene Editing ◽  
Molecular Subtypes ◽  
Intratumoral Heterogeneity ◽  
Molecular Heterogeneity ◽  
Agent Based ◽  
And Control

Cellular and molecular heterogeneity within tumors has long been associated with the progression of cancer to an aggressive phenotype and a poor prognosis. However, how such intratumoral heterogeneity contributes to the invasiveness of cancer is largely unknown. Here, using a tumor bioengineering approach, we investigate the interaction between molecular subtypes within bladder microtumors and the corresponding effects on their invasiveness. Our results reveal heterogeneous microtumors formed by multiple molecular subtypes possess enhanced invasiveness compared to individual cells, even when both cells are not invasive individually. To examine the molecular mechanism of intratumoral heterogeneity mediated invasiveness, live single cell biosensing, RNA interference, and CRISPR-Cas9 gene editing approaches were applied to investigate and control the composition of the microtumors. An agent-based computational model was also developed to evaluate the influence of NOTCH1 variation on DLL4 expression within a microtumor. The data indicate that intratumoral variation in NOTCH1 expression can lead to upregulation of DLL4 expression within the microtumor and enhancement of microtumor invasiveness. Overall, our results reveal a novel mechanism of heterogeneity mediated invasiveness through intratumoral variation of gene expression.

scholarly journals Intratumoral Heterogeneity Promotes Collective Cancer Invasion Through NOTCH1 Variation

2021 ◽  
Author(s):  
Peter Torab ◽  
Yue Yan ◽  
Mona Ahmed ◽  
Hironobu Yamashita ◽  
Joshua Warrick ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Interference ◽  
Poor Prognosis ◽  
Gene Editing ◽  
Multidisciplinary Approach ◽  
Molecular Subtypes ◽  
Intratumoral Heterogeneity ◽  
Molecular Heterogeneity ◽  
Agent Based ◽  
And Control

Cellular and molecular heterogeneity within tumors has long been associated with the progression of cancer to an aggressive phenotype and a poor prognosis. However, how such intratumoral heterogeneity contributes to the invasiveness of cancer is largely unknown. Here, using a multidisciplinary approach, we investigate the interaction between molecular subtypes within bladder microtumors and the corresponding effects on their invasiveness. Our results reveal heterogeneous microtumors formed by multiple molecular subtypes possess enhanced invasiveness compared to individual cells, even when both cells are not invasive individually. To examine the molecular mechanism of intratumoral heterogeneity mediated invasiveness, live single cell biosensing, RNA interference, and CRISPR-Cas9 gene editing approaches were applied to investigate and control the composition of the microtumors. An agent-based computational model was also developed to evaluate the influence of NOTCH1 variation on DLL4 expression within a microtumor. The data indicate that variation in NOTCH1 expression can lead to upregulation of DLL4 expression within the microtumor and enhancement of microtumor invasiveness. Overall, our results reveal a novel mechanism of heterogeneity mediated invasiveness through intratumoral variation of gene expression.

Heterogeneity Within Molecular Subtypes of Breast Cancer

2021 ◽  
Author(s):  
Kevin M. Turner ◽  
Syn Kok Yeo ◽  
Tammy M Holm ◽  
Elizabeth Shaughnessy ◽  
Jun-Lin Guan
Keyword(s):  
Breast Cancer ◽  
Molecular Subtypes ◽  
Tumor Biology ◽  
Treatment Resistance ◽  
Intratumoral Heterogeneity ◽  
Molecular Heterogeneity ◽  
Improve Treatment ◽  
Therapeutic Decisions ◽  
Single Tumor

Breast cancer is the quintessential example of how molecular characterization of tumor biology guides therapeutic decisions. From the discovery of the estrogen receptor to current clinical molecular profiles to evolving single cell analytics, the characterization and compartmentalization of breast cancer into divergent subtypes is clear. However, competing with this divergent model of breast cancer is the recognition of intratumoral heterogeneity, which acknowledges the possibility that multiple different subtypes exist within a single tumor. Intratumoral heterogeneity is driven by both intrinsic effects of the tumor cells themselves as well as extrinsic effects from the surrounding microenvironment. There is emerging evidence that these intratumoral molecular subtypes are not static; rather, plasticity between divergent subtypes is possible. Inter-conversion between seemingly different subtypes within a tumor drives tumor progression, metastases, and treatment resistance. Therapeutic strategies must therefore contend with changing phenotypes in an individual patient's tumor. Identifying targetable drivers of molecular heterogeneity may improve treatment durability and disease progression.

Epigenetically regulated gene expression profiles reveal four molecular subtypes with prognostic and therapeutic implications in colorectal cancer

2020 ◽  
Author(s):  
Xiaokang Wang ◽  
Jinfeng Liu ◽  
Danwen Wang ◽  
Maohui Feng ◽  
Xiongzhi Wu
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Metabolic Activity ◽  
Poor Prognosis ◽  
Molecular Subtypes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Epigenetic Mechanisms ◽  
Regulated Gene Expression ◽  
Marked Proliferation

Abstract Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of colorectal cancer (CRC). Herein, we first demonstrated that the frequencies of the aberrancies of DNA methylation-correlated (METcor) and microRNA (miRNA)-correlated (MIRcor) genes were significantly co-regulated. Next, through integrative clustering of the expression profiles of METcor and MIRcor genes, four molecular subtypes were identified in CRC patients from The Cancer Genome Atlas and then validated in four independent datasets. More importantly, the four subtypes were well characterized and showed distinct clinical and molecular features: (i) S-I: high metabolic activity, sensitive to 5-fluorouracil-based chemotherapy and good prognosis; (ii) S-II: moderate metabolic activity, marked proliferation, frequent KRAS mutation and intermediate prognosis; (iii) S-III: moderate metabolic activity, marked proliferation, promoter DNA hypermethylation, high mutation burden, frequent BRAF and EGFR mutations, moderate levels of epithelial-mesenchymal transition (EMT) and transforming growth factor β (TGFβ) signals, immune-inflamed phenotype, sensitive to cetuximab and death protein-1 inhibitor treatment and relatively poor prognosis and (iv) S-IV: miRNA overexpression, stem/serrated/mesenchymal-like properties, hypoxia, high levels of EMT and TGFβ signals, immune-excluded phenotype and poor prognosis. Overall, this study established a molecular classification based on epigenetically regulated gene expression profiles, thereby providing a better understanding of the epigenetic mechanisms underlying CRC heterogeneity.

scholarly journals High SLC7A11 Expression Is Correlated With Poor Prognosis and Associated With Ferroptosis in Ovarian Cancer 

2021 ◽  
Author(s):  
Mengqi Deng ◽  
Yanqin Zhang ◽  
Xiangyu Chang ◽  
Di Wu ◽  
Chunyu Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Protein Expression ◽  
Differentially Expressed Genes ◽  
Poor Prognosis ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Normal Tissues ◽  
And Control

Abstract The current treatments of ovarian cancer (OC) do not yield satisfactory outcomes. Hence, it is necessary to find new treatment targets for OC. In this study, a comprehensive bioinformatic analysis was conducted to identify differentially expressed genes (DEGs) between OC and control tissues. Five datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by comparing gene expression between OC and control tissues. Module analysis of DEGs was performed on the STRING database and GEPIA. Kaplan Meier plotter and GEPIA database analysis the overall survival. Finally, SLC7A11 was found to be is the hubgene. And we confirm that the protein expression of SLC7A11 was increased in OC tissues. Analysis of a variety of tumor gene databases showed that SLC7A11 gene regulated the processes of OC. The low mutation rate of the gene (which were of amplified type) and high mRNA expression were associated with poor prognosis of OC patients.Using erastin-treated ovarian cancer (OC) cell lines, we examined the relationship between ferroptosis and OC. Results showed that OC tissues contained higher malondialdehyde (MDA) levels than normal tissues. Unlike normal ovarian epithelial cells which are not sensitive to erastin, the OC cell line, ES-2 is very sensitive to erastin. Here, we found that ferrostatin-1 treatment increased levels of reactive oxygen species (ROS), malondialdehyde, and SLC7A11 protein expression. These results provide an important theoretical basis for further studies into the role of SLC7A11, the effective biomarker and potential drug target, in the occurrence and development of OC.

ZIF-C for targeted RNA interference and CRISPR/Cas9 based gene editing in prostate cancer

2020 ◽  
Vol 56 (98) ◽  
pp. 15406-15409
Author(s):  
Arpita Poddar ◽  
Suneela Pyreddy ◽  
Francesco Carraro ◽  
Sudip Dhakal ◽  
Andrea Rassell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Gene Therapy ◽  
Rna Interference ◽  
Green Tea ◽  
Gene Editing ◽  
Metal Organic Frameworks ◽  
Host Gene ◽  
Host Gene Expression ◽  
Metal Organic

Metal–organic-frameworks for gene therapy in prostate cancer – ZIF-C based delivery of RNA interference and CRISPR/Cas9 causes host gene expression knockdown. Coating with a green tea phytochemical enhances uptake and increases cancer cytotoxicity.

Agent-Based Computational Model

2017 ◽  
Author(s):  
Joshua M. Epstein
Keyword(s):  
Computational Model ◽  
Bounded Rationality ◽  
Time Scales ◽  
Spatially Explicit ◽  
Agent Based ◽  
Affective Component ◽  
Elementary Type ◽  
Social Component ◽  
Different Time Scales

This part describes the agent-based and computational model for Agent_Zero and demonstrates its capacity for generative minimalism. It first explains the replicability of the model before offering an interpretation of the model by imagining a guerilla war like Vietnam, Afghanistan, or Iraq, where events transpire on a 2-D population of contiguous yellow patches. Each patch is occupied by a single stationary indigenous agent, which has two possible states: inactive and active. The discussion then turns to Agent_Zero's affective component and an elementary type of bounded rationality, as well as its social component, with particular emphasis on disposition, action, and pseudocode. Computational parables are then presented, including a parable relating to the slaughter of innocents through dispositional contagion. This part also shows how the model can capture three spatially explicit examples in which affect and probability change on different time scales.

GLIOBLASTOMA MULTIFORME: PATHOGENESIS AND MOLECULAR MARKERS

2017 ◽  
Vol 63 (5) ◽  
pp. 695-702
Author(s):  
Oleg Kit ◽  
Dmitriy Vodolazhskiy ◽  
Yelena Frantsiyants ◽  
Svetlana Panina ◽  
E. Rastorguev ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Tumor ◽  
Molecular Markers ◽  
Glioblastoma Multiforme ◽  
Somatic Mutations ◽  
Web Of Science ◽  
Molecular Subtypes ◽  
Regulation Of Gene Expression ◽  
Signal Pathways ◽  
Poorly Differentiated

Glioblastoma multiforme (GBM) is the most common and invasive poorly differentiated brain tumor with nearly 100 % rate of recurrence and unfavorable prognosis. The aim of the present review is to analyze recent studies and experimental results (Scopus, Web of Science, PubMed) concerning somatic mutations in glioblastoma, aberrant regulation of gene expression of signal pathways including EGFR, TGFß, etc. and markers for GBM progression. Particularly the molecular subtypes of glioblastoma and NGS results are considered in this review.

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