Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance.
Dis Model Mech
; 11(5)2018 05 18.
Article
em En
| MEDLINE
| ID: mdl-29666142
ABSTRACT
Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs), we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2) is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA) supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
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Resistencia a Medicamentos Antineoplásicos
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Fator de Transcrição 4
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
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Animals
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Female
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Humans
Idioma:
En
Revista:
Dis Model Mech
Assunto da revista:
MEDICINA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Espanha