Abstract Types

CRA
Clinical Review Abstract

LBA
Late-Breaking Abstract

TPS
Trials in Progress Abstract

e
Abstracts selected for publication but not presentation at the Annual Meeting

^
Abstracts granted an exception in accordance with ASCO's Conflict of Interest Policy



Meta-analysis of cancer cell lines genomes based on their response to ttfields.

Sub-category:
Genomic and Epigenomic Biomarkers

Category:
Tumor Biology

Meeting:
2013 ASCO Annual Meeting

Abstract No:
e22125

Citation:
J Clin Oncol 31, 2013 (suppl; abstr e22125)

Publication-only abstracts (abstract number preceded by an "e"), published in conjunction with the 2013 Annual Meeting but not presented at the Meeting, can be found online only.

Author(s): Moshe Giladi, Yoram Wasserman, Rosa S. Schneiderman, Yaara Porat, Mijal Munster, Uri Weinberg, Eilon David Kirson, Yoram Palti; NovoCure, Haifa, Israel; Novocure, Haifa, Israel; NovoCure, Lausanne, Switzerland

Abstract Disclosures


Abstract:

Background: Tumor Treating Fields (TTFields) therapy is an established anti-mitotic treatment modality. The inhibitory effect of TTFields was demonstrated in numerous cancer cell lines with some cell lines exhibiting higher treatment sensitivity than others. The goal of the present study is to compare genomic characteristics of cell lines based on their response pattern to TTFields. Methods: Fifteen different human cancerous cell lines were treated using TTFields at their optimal frequency with the same nominal intensity (1.8 V/cm). The distribution of the response to TTFields was found to be bimodal with inhibitions of 30-40% and 50-60% compared to controls. Cell lines were divided into regular and high sensitivity groups according to their response to TTFields. Both groups were characterized based upon the distribution of mutated genes using the Cancer Cell Line Encyclopedia (CCLE) database. Results: Based on the distribution of mutated genes we identified 1 gene with significantly higher probability (P=0.017) to be present in the regular than the high sensitivity group. This gene (NEK3) is a never-in-mitosis (NIMA) related kinase 3 responsible for deacetylation of microtubules. In addition, 2 genes were found with significantly higher probability (P<0.05) to be present in the high- than the regular sensitivity group; ASPH, an aspartate beta-hydroxylase involved in negative regulation of cell proliferation through modulation of calcium homeostasis and TEC, a protein tyrosine kinase involved in immunological signaling pathways. Conclusions: The possible involvement of NEK3 mutations in determining sensitivity to TTFields is interesting in view of the known interference of TTFields with spindle microtubule assembly. ASPH mutations could release cells from negative regulation of proliferation, increasing their replication rate, and thus increasing their sensitivity to TTFields. In order to further test this hypothesis, a comparison of the effect of TTFields needs to be performed on wild type and knockout cell lines for these genes. A comparison of the mutation of these genes in tissue samples from patients whose tumors show high sensitivity to TTFields, may lead to a personalized approach to the use of TTFields clinically.

 

  Other Abstracts in this Sub-Category:

 

1. Use of mutational profiling of metastatic ER+/HER2- breast cancers and the coexistence of KRAS, MET, BRAF, and FGFR3 with PIK3CA mutations.

Meeting: 2013 ASCO Annual Meeting Abstract No: 11003 First Author: D. Fumagalli
Category: Tumor Biology - Genomic and Epigenomic Biomarkers

 

2. Concurrent driver mutations in non-small cell lung cancer (NSCLC) patients (p) on targeted therapy uncovered by comprehensive molecular profiling.

Meeting: 2013 ASCO Annual Meeting Abstract No: 11004 First Author: C. M. Blakely
Category: Tumor Biology - Genomic and Epigenomic Biomarkers

 

3. Amplification of the MET receptor to drive resistance to anti-EGFR therapies in colorectal cancer.

Meeting: 2013 ASCO Annual Meeting Abstract No: 11005 First Author: A. Bardelli
Category: Tumor Biology - Genomic and Epigenomic Biomarkers

 

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