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Dis Model Mech. 2018 May 18;11(5). pii: dmm032292. doi: 10.1242/dmm.032292.

Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance.

Author information

1
Breast Cancer and Systems Biology Laboratory, Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.
2
Department of Medical Oncology, ICO, Oncobell, IDIBELL, L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.
3
Department of Biochemistry and Molecular Biology, Instituto Universitario de Oncología del Principado de Asturias, Universidad de Oviedo, Oviedo 33006, Spain.
4
Hereditary Cancer Programme, ICO, Oncobell, IDIBELL, L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.
5
Chemoresistance and Predictive Factors Laboratory, ProCURE, ICO, Oncobell, IDIBELL, L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.
6
Departments of Clinical Science and Internal Medicine, Haematology Section, Haukeland University Hospital, and Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen 5021, Norway.
7
Department of Pathology, University Hospital of Bellvitge, Oncobell, IDIBELL, L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.
8
Biomedical Research Networking Centre of Cancer, CIBERONC, Spain.
9
Xenopat S.L., Business Bioincubator, Bellvitge Health Science Campus, L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.
10
Breast Cancer and Systems Biology Laboratory, Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain mapujana@iconcologia.net.

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.

KEYWORDS:

Breast cancer; Chemotherapy; Patient-derived xenograft; Resistance; TCF4; Transcription factor; Xenograft

PMID:
29666142
PMCID:
PMC5992609
DOI:
10.1242/dmm.032292
[Indexed for MEDLINE]
Free PMC Article

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