scholarly journals Inferred Ancestral Origin of Cancer Cell Lines Associates with Differential Drug Response

2021 ◽  
Vol 22 (18) ◽  
pp. 10135
Author(s):  
Phong B. H. Nguyen ◽  
Alexander J. Ohnmacht ◽  
Samir Sharifli ◽  
Mathew J. Garnett ◽  
Michael P. Menden
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
High Throughput ◽  
Drug Response ◽  
Survival Rates ◽  
Mtor Inhibitors ◽  
Cancer Cell Lines ◽  
Risk Treatment ◽  
Cancer Intervention

Disparities between risk, treatment outcomes and survival rates in cancer patients across the world may be attributed to socioeconomic factors. In addition, the role of ancestry is frequently discussed. In preclinical studies, high-throughput drug screens in cancer cell lines have empowered the identification of clinically relevant molecular biomarkers of drug sensitivity; however, the genetic ancestry from tissue donors has been largely neglected in this setting. In order to address this, here, we show that the inferred ancestry of cancer cell lines is conserved and may impact drug response in patients as a predictive covariate in high-throughput drug screens. We found that there are differential drug responses between European and East Asian ancestries, especially when treated with PI3K/mTOR inhibitors. Our finding emphasizes a new angle in precision medicine, as cancer intervention strategies should consider the germline landscape, thereby reducing the failure rate of clinical trials.

scholarly journals Novel three-dimensional cultures provide insights into thyroid cancer behavior

2020 ◽  
Vol 27 (2) ◽  
pp. 111-121 ◽  
Author(s):  
Mason A Lee ◽  
Kensey N Bergdorf ◽  
Courtney J Phifer ◽  
Caroline Y Jones ◽  
Sonia Y Byon ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
High Throughput ◽  
Drug Response ◽  
3D Culture ◽  
The United States ◽  
Cancer Cell Lines ◽  
Thyroid Cancer Cell ◽  
Thyroid Cancer Cell Lines

Thyroid cancer has the fastest growing incidence of any cancer in the United States, as measured by the number of new cases per year. Despite advances in tissue culture techniques, a robust model for thyroid cancer spheroid culture is yet to be developed. Using eight established thyroid cancer cell lines, we created an efficient and cost-effective 3D culture system that can enhance our understanding of in vivo treatment response. We found that all eight cell lines readily form spheroids in culture with unique morphology, size, and cytoskeletal organization. In addition, we developed a high-throughput workflow that allows for drug screening of spheroids. Using this approach, we found that spheroids from K1 and TPC1 cells demonstrate significant differences in their sensitivities to dabrafenib treatment that closely model expected patient drug response. In addition, K1 spheroids have increased sensitivity to dabrafenib when compared to monolayer K1 cultures. Utilizing traditional 2D cultures of these cell lines, we evaluated the mechanisms of this drug response, showing dramatic and acute changes in their actin cytoskeleton as well as inhibition of migratory behavior in response to dabrafenib treatment. Our study is the first to describe the development of a robust spheroid system from established cultured thyroid cancer cell lines and adaptation to a high-throughput format. We show that combining 3D culture with traditional 2D methods provides a complementary and powerful approach to uncover drug sensitivity and mechanisms of inhibition in thyroid cancer.

Network Propagation Reveals Novel Features Predicting Drug Response of Cancer Cell Lines

2016 ◽  
Vol 11 (2) ◽  
pp. 203-210 ◽  
Author(s):  
Jiguang Wang ◽  
Judith Kribelbauer ◽  
Raul Rabadan
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Drug Response ◽  
Cancer Cell Lines ◽  
Network Propagation

Characterization of FOXF1 as a novel regulator of nodal metastasis in bladder cancer.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 480-480
Author(s):  
Anirban P Mitra ◽  
Andrea Kokorovic ◽  
Tanner Miest ◽  
Vikram M Narayan ◽  
Debasish Sundi ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Differentially Expressed Gene ◽  
Cancer Cell Lines ◽  
Differentially Expressed ◽  
Bladder Cancer Cell ◽  
Primary Tumors ◽  
Orthotopic Xenografts

480 Background: Members of the forkhead transcription factor (FOX) family are important mediators of embryonic development and are known to be altered in a variety of cancers. The functional role of FOXF1 in bladder tumorigenesis and progression has not been clearly characterized thus far. This study investigated the clinical implications of differential FOXF1 expression in bladder cancer, and potential mechanisms by which its alteration can lead to tumor metastasis. Methods: Whole genome expression profiling was performed on paired primary tumors and nodal metastases from a radical cystectomy discovery cohort using Illumina HT12 v3-4 BeadChip arrays to identify FOXF1 as a top differentially expressed gene. Prognostic role of differential FOXF1 expression was validated on two independent cystectomy cohorts. Differential FOXF1 expression was also evaluated in murine orthotopic xenografts. Small interfering RNA was used to knock down FOXF1 in RT112 and UC6 bladder cancer cell lines to develop an in vitro model for assessment of metastatic potential. Next-generation sequencing and hierarchical clustering analysis were used to identify differentially altered genes secondary to FOXF1 knockdown. 186 biologically curated pathways were interrogated with internal validation to elucidate the downstream biologic mechanisms of metastasis. Results: In the discovery cohort, FOXF1 was a top differentially expressed gene with 3.6-fold lower expression in nodal metastases than paired primary tumors (n = 33, p < 0.001). Multivariable analyses in two validation cohorts (total n = 128) indicated that FOXF1 underexpression was associated with worse cancer-specific (p = 0.046) and overall survival (p = 0.006). Murine orthotopic xenografts (n = 13) established from human bladder cancer cell lines (UC3, UC6, UC14) showed FOXF1 underexpression in metastatic deposits compared with primary tumors (p = 0.004). Hierarchical clustering identified 40 differentially expressed genes between FOXF1-knockdown bladder cancer cell lines and their corresponding controls. Biological pathway interrogation showed differential enrichment for genes associated with mitogen-activated protein kinase signaling, focal adhesion and other carcinogenic pathways in FOXF1-knockdown cells compared with controls (normalized enrichment score ≥ 1.3). Conclusions: We identify and characterize FOXF1 as a novel regulatory molecule that potentially drives bladder cancer metastasis. This may be modulated through alterations in intracellular signaling and cellular adhesion. FOXF1 may serve as a prognostic biomarker that can identify patients at impending risk for metastasis who may benefit from more aggressive management.

scholarly journals Transcriptional hallmarks of cancer cell lines reveal an emerging role of branched chain amino acid catabolism

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Ieva Antanavičiūtė ◽  
Valeryia Mikalayeva ◽  
Ieva Ceslevičienė ◽  
Gintarė Milašiūtė ◽  
Vytenis Arvydas Skeberdis ◽  
...  
Keyword(s):  
Amino Acid ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Amino Acid Catabolism ◽  
Hallmarks Of Cancer ◽  
Branched Chain Amino Acid ◽  
Branched Chain

scholarly journals Chemoresistance in H-Ferritin Silenced Cells: The Role of NF-κB

2018 ◽  
Vol 19 (10) ◽  
pp. 2969 ◽  
Author(s):  
Ilenia Aversa ◽  
Roberta Chirillo ◽  
Emanuela Chiarella ◽  
Fabiana Zolea ◽  
Maddalena Di Sanzo ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Nuclear Factor Κb ◽  
Cancer Cell Lines ◽  
Nuclear Accumulation ◽  
Therapeutic Implications ◽  
Ferritin Heavy Chain ◽  
Additional Layer ◽  
Ros Scavenger

Nuclear Factor-κB (NF-κB) is frequently activated in tumor cells contributing to aggressive tumor growth and resistance to chemotherapy. Here we demonstrate that Ferritin Heavy Chain (FHC) protein expression inversely correlates with NF-κB activation in cancer cell lines. In fact, FHC silencing in K562 and SKOV3 cancer cell lines induced p65 nuclear accumulation, whereas FHC overexpression correlated with p65 nuclear depletion in the same cell lines. In FHC-silenced cells, the p65 nuclear accumulation was reverted by treatment with the reactive oxygen species (ROS) scavenger, indicating that NF-κB activation was an indirect effect of FHC on redox metabolism. Finally, FHC knock-down in K562 and SKOV3 cancer cell lines resulted in an improved cell viability following doxorubicin or cisplatin treatment, being counteracted by the transient expression of inhibitory of NF-κB, IκBα. Our results provide an additional layer of information on the complex interplay of FHC with cellular metabolism, and highlight a novel scenario of NF-κB-mediated chemoresistance triggered by the downregulation of FHC with potential therapeutic implications.

scholarly journals Nonlinear mixed-effects models for modeling in vitro drug response data to determine problematic cancer cell lines

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Farnoosh Abbas-Aghababazadeh ◽  
Pengcheng Lu ◽  
Brooke L. Fridley
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Drug Response ◽  
Functional Form ◽  
Cancer Cell Lines ◽  
Mixed Effects ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Models ◽  
Modeling Framework ◽  
Response Data

Abstract Cancer cell lines (CCLs) have been widely used to study of cancer. Recent studies have called into question the reliability of data collected on CCLs. Hence, we set out to determine CCLs that tend to be overly sensitive or resistant to a majority of drugs utilizing a nonlinear mixed-effects (NLME) modeling framework. Using drug response data collected in the Cancer Cell Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC), we determined the optimal functional form for each drug. Then, a NLME model was fit to the drug response data, with the estimated random effects used to determine sensitive or resistant CCLs. Out of the roughly 500 CCLs studies from the CCLE, we found 17 cell lines to be overly sensitive or resistant to the studied drugs. In the GDSC, we found 15 out of the 990 CCLs to be excessively sensitive or resistant. These results can inform researchers in the selection of CCLs to include in drug studies. Additionally, this study illustrates the need for assessing the dose-response functional form and the use of NLME models to achieve more stable estimates of drug response parameters.

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