Differential expression of cancer-associated fibroblast-related proteins according to molecular subtype and stromal histology in breast cancer

Sung Yeon Park, Hye Min Kim, Ja Seung Koo

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33 Citations (Scopus)

Abstract

The purpose of this study aimed to investigate the clinicopathologic characteristics of breast cancer according to its cancer-associated fibroblast (CAF) phenotype. Immunohistochemistry staining of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 (HER-2), Ki-67, podoplanin, prolyl 4-hydroxylase, fibroblast activation protein alpha (FAPα), S100A4, platelet-derived growth factor receptor alpha (PDGFRα), PDGFRβ, and chondroitin sulfate proteoglycan (NG2) was performed on tissue microarray consisting of 642 breast cancer cases. Samples were categorized into luminal A, luminal B, HER-2, or triple-negative breast cancer (TNBC) according to immunohistochemical results, whereas tumor stroma was classified into desmoplastic, sclerotic, normal-like, or inflammatory type based on histological findings. Expression of CAF-related proteins in the stroma differed depending on breast cancer molecular subtypes. All CAF-related protein expression was high (p < 0.05) in HER-2 type, whereas in luminal A, the expression of FAPα, PDGFα, PDGFβ, and NG2 was low, and in TNBC, the expression of podoplanin, prolyl 4-hydroxylase, and S100A4 was low. In the stromal component, CAF-related protein expression differed according to stromal phenotype (p < 0.001). The desmoplastic type showed high expression of podoplanin, prolyl 4-hydroxylase, S100A4, PDGFRα, and PDGFRβ, whereas the sclerotic type exhibited low expression of FAPα, PDGFα, PDGFβ, and NG2. The inflammatory type had high expression of FAPα and NG2 with low podoplanin, while normal-like type showed low expression of prolyl 4-hydroxylase and S100A4. Our results suggested that differential CAF-related protein expression depended on the molecular subtypes and stromal histologic features of breast cancer, indicating that in the future, this system could potentially use these markers for prognosis prediction and targeted therapy of breast cancer.

Original languageEnglish
Pages (from-to)727-741
Number of pages15
JournalBreast Cancer Research and Treatment
Volume149
Issue number3
DOIs
Publication statusPublished - 2015 Jan 1

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All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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