scholarly journals Investigating epithelial‐mesenchymal heterogeneity of tumors and circulating tumor cells with transcriptomic analysis and biophysical modeling

2021 ◽  
Author(s):  
Federico Bocci ◽  
Susmita Mandal ◽  
Tanishq Tejaswi ◽  
Mohit Kumar Jolly
Keyword(s):  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Transcriptomic Analysis ◽  
Biophysical Modeling

scholarly journals Investigating epithelial-mesenchymal heterogeneity of tumors and circulating tumor cells with transcriptomic analysis and biophysical modeling

2020 ◽  
Author(s):  
Federico Bocci ◽  
Susmita Mandal ◽  
Tanishq Tejaswi ◽  
Mohit Kumar Jolly
Keyword(s):  
Cell Migration ◽  
Tumor Cells ◽  
High Throughput ◽  
Primary Tumor ◽  
In Silico ◽  
Cluster Size ◽  
Transcriptomic Analysis ◽  
The Other ◽  
Biophysical Modeling ◽  
Cancer Types

AbstractIntroductionCellular heterogeneity along the Epithelial-Mesenchymal Plasticity (EMP) spectrum is a paramount feature observed in tumors and circulating tumor cells (CTCs). High-throughput techniques now offer unprecedented details on this variability at a singlecell resolution. Yet, there is no current consensus about how EMP in tumors propagates to that in CTCs. To investigate a relationship between EMP associated heterogeneity of tumors and that of CTCs, we integrated transcriptomic analysis and biophysical modeling.MethodsWe apply three EMT (Epithelial-Mesenchymal Transition) scoring metrics to multiple tumor samples and CTC datasets from several cancer types. Moreover, we develop a biophysical model that couples EMT associated phenotypic switching in a primary tumor with cell migration. Finally, we integrate EMT transcriptomic analysis and in silico modeling to evaluate the predictive power of several measurements of tumor aggressiveness, including tumor EMT score, CTC EMT score, fraction of CTC clusters found in circulation, and CTC cluster size distribution.ResultsAnalysis of high-throughput datasets reveals a pronounced heterogeneity without a well-defined relation between EMT traits in tumors and CTCs. Moreover, mathematical modeling predicts different phases where CTCs can be less, equally, or more mesenchymal than primary tumor depending on the dynamics of phenotypic transition and cell migration. Consistently, various datasets of CTC cluster size distribution from different cancer types are fitted onto different regimes of the model. By further constraining the model with experimental measurements of tumor EMT score, CTC EMT score, and fraction of CTC cluster in bloodstream, we show that none of these assays alone can provide sufficient information to predict the other variables.ConclusionsBy integrating analysis of single cell gene expression and in silico modeling, we propose that the relationship between EMT progression in tumors and CTCs can be variable, and in general, predicting one from the other may not be as straightforward as tacitly assumed.

The impact of HER2 phenotype of circulating tumor cells in metastatic breast cancer: a study in 107 patients

2014 ◽  
Vol 74 (S 01) ◽  
Author(s):  
M Wallwiener ◽  
AD Hartkopf ◽  
S Riethdorf ◽  
J Nees ◽  
FA Taran ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Metastatic Breast ◽  
The Impact

EpCAM-independent enrichment approach for isolation of circulating tumor cells (CTCs) in breast cancer

2015 ◽  
Vol 75 (08) ◽  
Author(s):  
H Schneck ◽  
B Gierke ◽  
M Pawlak ◽  
M Templin ◽  
T Fehm ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Cells ◽  
Circulating Tumor Cells
Sign in / Sign up

Export Citation Format

Share Document