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Updated: Jul 10, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Lack of prognostic value of insulin-like growth factor-1 in patients with breast cancer: analysis with tissue
Shyr-Ming Sheen-Chen1, Fong-Fu Chou, Wayne Hsu
1Department of Surgery, Chang Gung Memorial Hospital, Kaohsiung Medical Center, Taiwan, R. O. C. smsheen@yahoo.com
Background:
Recent reports on the risk of prostate, breast, colorectal and lung cancer suggested that high circulating insulin-like growth factor-1 (IGF-1) concentrations are associated with an increased risk of cancer. The power of the tissue microarray (TMA) technique is the ability to perform a series of analyses of thousands of specimens in a parallel fashion with minimal damage to the original blocks.
Materials And Methods:
Archival tissue specimens from 106 patients with primary invasive breast cancer were selected and IGF-1 expression was analyzed by immunohistochemical staining of tissue microarrays. The data regarding primary tumor staging, age, estrogen receptor status, lymph node status, histological grading and TNM staging were also collected.
Results:
There were 2 patients (2%) with grade 1 expression for IGF-1, 39 patients (37%) with grade 2 expression and 65 patients (61%) with grade 3 expression. There was no significant relationship between IGF-1 expression and age (p=0.256), estrogen receptor status (p=0.921), histological grading (p=0.815), primary tumor staging (p=0.455), or TNM staging (p=0.194). No survival difference was noted among the three groups with different IGF-1 expression (p=0.462).
Conclusion:
Immunohistochemical staining of the tissue microarray was convenient and feasible for the analysis of IGF-1 expression in breast cancer, yet its expression did not show any significant correlation with the overall survival rate.
