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Abstract 2926: Nomination and characterization of TTK for radiosensitization in basal-like breast cancers
Background: Increased rates of locoregional recurrence have been observed in basal-like breast cancer despite the use of radiation therapy (RT), therefore approaches that result in radiosensitization of basal-like breast cancer are critically needed. Studies detailing the poor response of basal-like...
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Published in: | Cancer research (Chicago, Ill.) Ill.), 2019-07, Vol.79 (13_Supplement), p.2926-2926 |
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Main Authors: | , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Background: Increased rates of locoregional recurrence have been observed in basal-like breast cancer despite the use of radiation therapy (RT), therefore approaches that result in radiosensitization of basal-like breast cancer are critically needed. Studies detailing the poor response of basal-like tumors to adjuvant RT underscore the biologic differences and as of yet undefined oncogenic drivers of these particular types of breast cancer.
Methods: 4 independent datasets were used to correlate gene expression with local recurrence (LR) after 3 years. Kaplan-Meier analysis was used to validate the impact of TTK expression on LR. The TCGA and institutional breast cancer dataset were used to determine TTK expression in BC subtypes. TTK RNA and protein levels were measured using qPCR and western blot at baseline and correlated to intrinsic radiosensitivity. Clonogenic survival assays were used to determine the radiosensitization of cell lines after TTK inhibition (TTKi). Mice models were used to assess TTKi in combination with RT in vivo. DNA damage was quantified using γH2AX staining. HR and NHEJ efficiency assays were performed using HR/NHEJ specific reporter systems. HR competency was also assessed using RAD51 foci formation assays.
Results: Ten genes were found to significantly correlate with early LR (≤3 years) across 4 distinct datasets (N=896 pts) (OR of recurrence > 2, p-value |
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ISSN: | 0008-5472 1538-7445 |
DOI: | 10.1158/1538-7445.AM2019-2926 |