Lessons learned from the intrinsic subtypes of breast cancer in the quest for precision therapy  

Oleh:

Norum, J.H. ; Andersen, K. ; Sorlie, T.

Jenis: Article from Article - diterbitkan di jurnal ilmiah internasional
Dalam koleksi: BJS: British Journal of Surgery vol. 101 no. 08 (Jul. 2014), page 925-938.
Topik: breast cancer; kanker payudara; treatment; breast tumours; sel kanker; molecular classification
Fulltext: bjs9562.pdf (506.84KB)

Ketersediaan

Perpustakaan FK Nomor Panggil: B15.K Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Background Wide variability in breast cancer, between patients and within each individual neoplasm, adds confounding complexity to the treatment of the disease. In clinical practice, hormone receptor status has been used to classify breast tumours and to guide treatment. Modern classification systems should take the wide tumour heterogeneity into account to improve patient outcome. Methods This article reviews the identification of the intrinsic molecular subtypes of breast cancer, their prognostic and therapeutic implications, and the impact of tumour heterogeneity on cancer progression and treatment. The possibility of functionally addressing tumour-specific characteristics in in vivo models to inform decisions for precision therapies is also discussed. Results Despite the robust breast tumour classification system provided by gene expression profiling, heterogeneity is also evident within these molecular portraits. A complicating factor in breast cancer classification is the process of selective clonality within developing neoplasms. Phenotypically and functionally distinct clones representing the intratumour heterogeneity might confuse molecular classification. Molecular portraits of the heterogeneous primary tumour might not necessarily reflect the subclone of cancer cells that causes the disease to relapse. Studies of reciprocal relationships between cancer cell subpopulations within developing tumours are therefore needed, and are possible only in genetically engineered mouse models or patient-derived xenograft models, in which the treatment-induced selection pressure on individual cell clones can be mimicked. Conclusion In the future, more refined classifications, based on integration of information at several molecular levels, are required to improve treatment guidelines. Large-scale translational research efforts paved the way for identification of the intrinsic subtypes, and are still fundamental for ensuring future progress in cancer care.

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