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High fibroblast growth factor 19 (FGF19) expression predicts worse prognosis in invasive ductal carcinoma of breast

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Tumor Biology

Abstract

Metabolic diseases like diabetes and obesity are major risk factors for breast cancer. Aberrant expression of metabolic effectors such as fibroblast growth factor 19 (FGF19) could be therefore associated with the disease. The expression of FGF19 was examined in 193 archival breast tumor samples by immunohistochemistry and evaluated semi-quantitatively by determining the staining index and correlating it with clinicopathological parameters using Fisher's exact test. The correlation between FGF19 expression and 5-year disease-specific survival rate was determined using the univariate Kaplan–Meier analysis. The prognostic value of FGF19 expression was evaluated using the multivariate Cox regression analysis. Of the 193 tumors analyzed, 40 % were classified with low FGF19 expression, whereas 60 % were categorized as tumors with high FGF19 expression. There was a highly significant correlation between high FGF19 expression and patients' age (p = 0.008) as well as 5-year disease-specific survival (p = 0.001). However, FGF19 expression did not show any significant correlations with other clinicopathological parameters, including hormonal status, tumor grade, tumor size, or lymph node status. Univariate Kaplan–Meier log rank analysis showed that patients with high FGF19 expression exhibited a significantly shorter disease-specific 5-year survival (p = 0.007). This effect was exacerbated by lymph node metastasis (p = 0.001), negative estrogen receptor (ER) status (p = 0.002), or old age (p = 0.013). Multivariate analysis showed that high FGF19 expression could be an independent prognostic marker of disease-specific survival in breast cancer patients (p = 0.030). Quantification of FGF19 expression appears to provide valuable prognostic information in breast cancer, particularly in older patients with lymph node metastasis and negative ER status.

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Acknowledgments

The authors would like thank the Ministry of Higher Education (MOHE) and King Abdulaziz City for Science and Technology (KACST) for their financial support to this research (ARP-29-292). The authors also would like to thank Samira Dini, Basmat Abdullah, Noha Abozaid, and Saher Al-Hakami from CEGMR laboratory and Muneeb Ashoor and Kifah Abunar from Al-Jeel Company, the exclusive representative of Ventana in KSA, for their highly significant technical assistance.

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None.

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Authors and Affiliations

  1. Center of Excellence in Genomic Medicine Research, King Abdulaziz University, P.O. Box 80216, Jeddah, 21589, Kingdom of Saudi Arabia

    Abdelbaset Buhmeida, Ashraf Dallol, Mamdooh A. Gari, Muhammad M. Abu-Elmagd, Adeel G. Chaudhary, Adel M. Abuzenadah & Mohammed H. Al-Qahtani

  2. KACST Technology Innovation Center in Personalized Medicine, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Ashraf Dallol & Adel M. Abuzenadah

  3. Department of Surgery, Faculty of Medicine, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Adnan Merdad & Fatima Al-Thubaity

  4. Department of Pathology, Faculty of Medicine, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Jaudah Al-Maghrabi

  5. Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Mamdooh A. Gari, Adeel G. Chaudhary, Adel M. Abuzenadah & Mohammed H. Al-Qahtani

  6. King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Taoufik Nedjadi

  7. Department of Oncology, National Cancer Institute, Sabratha, Libya

    Eramah Ermiah

  8. Zoology Department, Faculty of Science, Minia University, Minia, Egypt

    Muhammad M. Abu-Elmagd

Authors
  1. Abdelbaset Buhmeida
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  2. Ashraf Dallol
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  3. Adnan Merdad
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  4. Jaudah Al-Maghrabi
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  5. Mamdooh A. Gari
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  6. Muhammad M. Abu-Elmagd
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  7. Adeel G. Chaudhary
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  8. Adel M. Abuzenadah
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  9. Taoufik Nedjadi
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  11. Fatima Al-Thubaity
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  12. Mohammed H. Al-Qahtani
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Correspondence to Ashraf Dallol.

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Buhmeida, A., Dallol, A., Merdad, A. et al. High fibroblast growth factor 19 (FGF19) expression predicts worse prognosis in invasive ductal carcinoma of breast. Tumor Biol. 35, 2817–2824 (2014). https://doi.org/10.1007/s13277-013-1374-y

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  • DOI: https://doi.org/10.1007/s13277-013-1374-y

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