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Grant support

This work was supported by grants from the Asociacion Espanola Contra el Cancer (AECC, Hereditary Cancer coordinated group, 2010; AECC Barcelona Ovarian Cancer 2015), the Generalitat de Catalunya (SGR 2014-364 and 2017-449), the Ministerio de Economia y Competitividad (SAF2013-45836-R and SAF2017-87811R), European Regional Development Fund (ERDF/FEDER Una manera de hacer Europa), the Instituto de Salud Carlos III (PIE13/00022-ONCOPROFILE, FIS PI13/01339, PI15/00854, PI16/01898 and RTICC RD12/0036/0008), and Fundacion Mutua Madrilena (AP150932014). A.D-N. is supported by the Department of Education of the Basque Government (PRE-2017-1-0100).

Analysis of institutional authors

Mateo FAuthorStradella, AAuthorTornero EAuthorSoler TAuthorLazaro CAuthorPuente XsAuthorVillanueva AAuthorPujana, MaCorresponding Author

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April 20, 2018
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Tumor xenograft modeling identifies TCF4/ITF2 loss associated with breast cancer chemoresistance.

Publicated to:Disease Models & Mechanisms. 11 (5): - - 2018-05-01 11(5), DOI: 10.1242/dmm.032292

Authors: de Garibay, GR; Mateo, F; Stradella, A; Valdés-Mas, R; Palomero, L; Serra-Musach, J; Puente, DA; Díaz-Navarro, A; Vargas-Parra, G; Tornero, E; Morilla, I; Farré, L; Martinez-Iniesta, M; Herranz, C; McCormack, E; Vidal, A; Petit, A; Soler, T; Lázaro, C; Puent, XS; Villanueva, A; Pujana, MA

Affiliations

Bellvitge Inst Biomed Res IDIBELL, Program Canc Therapeut Resistance ProCURE, Breast Canc & Syst Biol Lab, Oncobell,Catalan Inst Oncol ICO, Barcelona 08908, Catalonia, Spain - Author
CIBERONC, Biomed Res Networking Ctr Canc, Madrid, Spain - Author
IDIBELL, Dept Med Oncol, Oncobell, ICO, Barcelona 08908, Catalonia, Spain - Author
IDIBELL, Oncobell, ICO, Chemoresistance & Predict Factors Lab,ProCURE, Barcelona 08908, Spain - Author
IDIBELL, Oncobell, ICO, Hereditary Canc Programme, Barcelona 08908, Catalonia, Spain - Author
Univ Bergen, Ctr Canc Biomarkers CCBIO, Dept Clin Sci, N-5021 Bergen, Norway - Author
Univ Bergen, Haukeland Univ Hosp, Dept Clin Sci, Haematol Sect, N-5021 Bergen, Norway - Author
Univ Bergen, Haukeland Univ Hosp, Dept Internal Med, Haematol Sect, N-5021 Bergen, Norway - Author
Univ Hosp Bellvitge, Dept Pathol, Oncobell, IDIBELL, Barcelona 08908, Catalonia, Spain - Author
Univ Oviedo, Dept Biochem & Mol Biol, Inst Univ Oncol Principado Asturias, E-33006 Oviedo, Spain - Author
Xenopat SL, Business Bioincubator, Bellvitge Hlth Sci Campus, Barcelona 08908, Catalonia, Spain - Author
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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.© 2018. Published by The Company of Biologists Ltd.

Keywords

Breast cancerCellsChemotherapyCisplatinDihydropyrimidine dehydrogenaseExpressionGenesId proteinsNetworkPatient-derived xenograftPreoperative chemotherapyResistanceSubtypesTcf4TherapyTranscription factorXenograft

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Disease Models & Mechanisms due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2018, it was in position 12/75, thus managing to position itself as a Q1 (Primer Cuartil), in the category Pathology.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 1.95, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-04, the following number of citations:

  • WoS: 12
  • Scopus: 14
  • Europe PMC: 8

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-04:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 26.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 26 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 11.5.
  • The number of mentions on the social network Facebook: 1 (Altmetric).
  • The number of mentions on the social network X (formerly Twitter): 3 (Altmetric).
  • The number of mentions in news outlets: 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Norway.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (de Garibay GR) and Last Author (PUJANA GENESTAR, MIGUEL ANGEL).

the author responsible for correspondence tasks has been PUJANA GENESTAR, MIGUEL ANGEL.