NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence

  1. Mendiburu‐Eliçabe, Marina 12
  2. García‐Sancha, Natalia 12
  3. Corchado‐Cobos, Roberto 12
  4. Martínez‐López, Angélica 45
  5. Chang, Hang 89
  6. Hua Mao, Jian 89
  7. Blanco‐Gómez, Adrián 12
  8. García‐Casas, Ana 45
  9. Castellanos‐Martín, Andrés 12
  10. Salvador, Nélida 45
  11. Jiménez‐Navas, Alejandro 12
  12. Pérez‐Baena, Manuel Jesús 12
  13. Sánchez‐Martín, Manuel Adolfo 1213
  14. Abad‐Hernández, María Del Mar 267
  15. Carmen, Sofía Del 267
  16. Claros‐Ampuero, Juncal 1211
  17. Cruz‐Hernández, Juan Jesús 121112
  18. Rodríguez‐Sánchez, César Augusto 121112
  19. García‐Cenador, María Begoña 23
  20. García‐Criado, Francisco Javier 23
  21. Vicente, Rodrigo Santamaría 10
  22. Castillo‐Lluva, Sonia 45
  23. Pérez‐Losada, Jesús 12
  1. 1 Instituto de Biología Molecular y Celular del Cáncer (IBMCC‐CIC) Universidad de Salamanca/CSIC Salamanca Spain
  2. 2 Biosanitary Research Institute of Salamanca (IBSAL) Salamanca Spain
  3. 3 Departamento de Cirugía Universidad de Salamanca Salamanca Spain
  4. 4 Departamento de Bioquímica y Biología Molecular Facultad de Ciencias Químicas Universidad Complutense Madrid Spain
  5. 5 San Carlos Health Research Institute (IdISSC) Madrid Spain
  6. 6 Departamento de Anatomía Patológica Universidad de Salamanca Salamanca Spain
  7. 7 Servicio de Anatomía Patológica Hospital Universitario de Salamanca Salamanca Spain
  8. 8 Biological Systems and Engineering Division Lawrence Berkeley National Laboratory (LBNL) Berkeley California USA
  9. 9 Berkeley Biomedical Data Science Center Lawrence Berkeley National Laboratory (LBNL) Berkeley California USA
  10. 10 Departamento de Informática y Automática Universidad de Salamanca Salamanca España
  11. 11 Servicio de Oncología Hospital Universitario de Salamanca Salamanca Spain
  12. 12 Departamento de Medicina Universidad de Salamanca Salamanca Spain
  13. 13 Servicio de Transgénesis Plataforma Nucleus Universidad de Salamanca Salamanca Spain
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Revista:
Clinical and Translational Medicine

ISSN: 2001-1326,  2001-1326

Año de publicación: 2024

Volumen: 14

Número: 2

Tipo: Artículo

DOI: 10.1002/CTM2.1554 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Clinical and Translational Medicine

Resumen

BackgroundLuminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment.MethodsWe conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H’s (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels.ResultsWe found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression.ConclusionsThe GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

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