scholarly journals Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors

2013 ◽  
Vol 14 (4) ◽  
pp. R37 ◽  
Author(s):  
Pedro Casado ◽  
Maria P Alcolea ◽  
Francesco Iorio ◽  
Juan-Carlos Rodríguez-Prados ◽  
Bart Vanhaesebroeck ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Kinase Inhibitors ◽  
Cancer Cell Lines ◽  
Tumor Type ◽  
Hematological Cancer

scholarly journals Synthesis of Novel Tryptamine Derivatives and Their Biological Activity as Antitumor Agents

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 683
Author(s):  
Giorgia Simonetti ◽  
Carla Boga ◽  
Joseph Durante ◽  
Gabriele Micheletti ◽  
Dario Telese ◽  
...  
Keyword(s):  
Biological Activity ◽  
Cell Lines ◽  
Cancer Cell ◽  
Solid Tumor ◽  
Antitumor Agents ◽  
Cancer Cell Lines ◽  
Hematological Cancer ◽  
Selective Effect ◽  
Ht29 Cells ◽  
High Level

We synthesized five novel tryptamine derivatives characterized by the presence of an azelayl chain or of a 1,1,1-trichloroethyl group, in turn connected to another heterocyclic scaffold. The combination of tryptamin-, 1,1,1-trichloroethyl- and 2-aminopyrimidinyl- moieties produced compound 9 identified as the most active compound in hematological cancer cell lines (IC50 = 0.57–65.32 μM). Moreover, keeping constant the presence of the tryptaminic scaffold and binding it to the azelayl moiety, the compounds maintain biological activity. Compound 13 is still active against hematological cancer cell lines and shows a selective effect only on HT29 cells (IC50 = 0.006 µM) among solid tumor models. Compound 14 loses activity on all leukemic lines, while showing a high level of toxicity on all solid tumor lines tested (IC50 0.0015–0.469 µM).

scholarly journals Predicting tumor response to drugs based on gene-expression biomarkers of sensitivity learned from cancer cell lines

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yuanyuan Li ◽  
David M. Umbach ◽  
Juno M. Krahn ◽  
Igor Shats ◽  
Xiaoling Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Predictive Models ◽  
Drug Sensitivity ◽  
Human Cancer ◽  
Cancer Cell Lines ◽  
The Cancer Genome Atlas ◽  
Differential Sensitivity ◽  
Tumor Type

Abstract Background Human cancer cell line profiling and drug sensitivity studies provide valuable information about the therapeutic potential of drugs and their possible mechanisms of action. The goal of those studies is to translate the findings from in vitro studies of cancer cell lines into in vivo therapeutic relevance and, eventually, patients’ care. Tremendous progress has been made. Results In this work, we built predictive models for 453 drugs using data on gene expression and drug sensitivity (IC50) from cancer cell lines. We identified many known drug-gene interactions and uncovered several potentially novel drug-gene associations. Importantly, we further applied these predictive models to ~ 17,000 bulk RNA-seq samples from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database to predict drug sensitivity for both normal and tumor tissues. We created a web site for users to visualize and download our predicted data (https://manticore.niehs.nih.gov/cancerRxTissue). Using trametinib as an example, we showed that our approach can faithfully recapitulate the known tumor specificity of the drug. Conclusions We demonstrated that our approach can predict drugs that 1) are tumor-type specific; 2) elicit higher sensitivity from tumor compared to corresponding normal tissue; 3) elicit differential sensitivity across breast cancer subtypes. If validated, our prediction could have relevance for preclinical drug testing and in phase I clinical design.

Synthesis and antiproliferative and c-Src kinase inhibitory activities of cinnamoyl- and pyranochromen-2-one derivatives

2013 ◽  
Vol 91 (8) ◽  
pp. 741-754 ◽  
Author(s):  
Karam Chand ◽  
Amir Nasrolahi Shirazi ◽  
Preeti Yadav ◽  
Rakesh K. Tiwari ◽  
Meena Kumari ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Anticancer Agents ◽  
Kinase Inhibitors ◽  
Human Cancer ◽  
Src Kinase ◽  
Cancer Cell Lines ◽  
Ovarian Adenocarcinoma ◽  
Human Cancer Cell Lines ◽  
Mcf 7

A series of 6- and 8-cinnamoylchromen-2-one and dihydropyranochromen-2-one derivatives were synthesized and their antiproliferative activities were evaluated against three human cancer cell lines, i.e., ovarian adenocarcinoma (SK-OV-3), leukemia (CCRF-CEM), and breast carcinoma (MCF-7). In general, 8-cinnamoylchromen-2-one derivatives were found to have higher antiproliferative activity against the cancer cells when compared with 6-cinnamoyl analogues. Among all of the hybrid chromen-2-one − chalcone/flavanone compounds, a 7-hydroxy-8-cinnamoylchromen-2-one derivative 35 was found to be consistently active against all the cancer cell lines and inhibited the cell proliferation of SK-OV-3, CCRF-CEM, and MCF-7 by 63%, 50%, and 43%, respectively, at a concentration of 50 μmol/L after 72 h of incubation. This compound also exhibited the highest Src kinase inhibition (IC50 = 14.5 μmol/L). Structure−activity relationship studies provided insights for designing the next generation of chromen-2-one − chalcone hybrid prototypes and the development of new leads as anticancer agents and (or) Src kinase inhibitors.

scholarly journals Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines

PLoS ONE ◽  
2013 ◽  
Vol 8 (3) ◽  
pp. e59503 ◽  
Author(s):  
Zsófia Pénzváltó ◽  
Bálint Tegze ◽  
A. Marcell Szász ◽  
Zsófia Sztupinszki ◽  
István Likó ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Cell Lines ◽  
Cancer Cell ◽  
Kinase Inhibitors ◽  
Cancer Cell Lines ◽  
Resistance Mechanisms ◽  
Ras Pathway

scholarly journals Transcriptional fidelity enhances cancer cell line selection in pediatric cancers

2021 ◽  
Author(s):  
Cuyler Luck ◽  
Katharine Yu ◽  
Ross A Okimoto ◽  
Marina Sirota
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Molecular Subtype ◽  
Unmet Need ◽  
Cancer Cell Lines ◽  
Tumor Type ◽  
Pediatric Cancers ◽  
Public Data ◽  
Tumor Types

Multi-omic technologies have allowed for comprehensive profiling of patient-derived tumor samples and the cell lines that are intended to model them. Yet, our understanding of how cancer cell lines reflect native pediatric cancers in the age of molecular subclassification remains unclear and represents a clinical unmet need. Here we use Treehouse public data to provide an RNA-seq driven analysis of 799 cancer cell lines, focusing on how well they correlate to 1,655 pediatric tumor samples spanning 12 tumor types. For each tumor type we present a ranked list of the most representative cell lines based on correlation of their transcriptomic profiles to those of the tumor. We found that most (8/12) tumor types best correlated to a cell line of the closest matched disease type. We furthermore showed that inferred molecular subtype differences in medulloblastoma significantly impacted correlation between medulloblastoma tumor samples and cell lines. Our results are available as an interactive web application to help researchers select cancer cell lines that more faithfully recapitulate pediatric cancer.

Abstract 3795: Novel and selective MELK kinase inhibitors active in breast cancer cell lines

2016 ◽  
Author(s):  
Patrizia Carpinelli ◽  
Marisa Montemartini ◽  
Nadia Amboldi ◽  
Dario Ballinari ◽  
Sabrina Cribioli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Kinase Inhibitors ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines
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