Histologic heterogeneity predicts patient prognosis of HER2-positive metastatic breast cancer: A retrospective study based on SEER database

Background: Human epidermal growth factor receptor 2-positive (HER2+) metastatic breast cancer (MBC) is a subtype of breast cancer with a worse prognosis. Little is known about the relationship between histology and prognosis among different distant metastasis sites (DMS). Our aims were to explore the prognostic value of histologic subtypes in different DMS and screen out specific subtypes with particular DMS that need more attention in HER2+ MBC.Methods: HER2+ MBC patient data were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2014. Chi-squared tests were utilized to compare histologic subtypes in four DMS. The logistic regression analyses were used to control confounding factors. The log-rank tests were used to analyze the correlation of histologic subtype with disease-specific survival and overall survival. The survival data was analyzed using Kaplan-Meier methods.Results: A total of 1174 HER2+ MBC patients were involved. First, the distribution of histological subtypes varied across metastatic sites, and the proportions of metastatic sites in different histological subtypes were also different. Furthermore, different histological subtypes within specific DMS showed divergent prognoses, and the different outcomes were shown by distinct DMS for specific histological subtypes. Among them, lobular carcinoma (ILC) subtypes showed the worst prognosis in bone metastasis, and lung metastasis predicted the worst prognosis in infiltration duct and lobular carcinoma (IDC-ILC) subtypes. After further consideration of hormone receptor (HR) status, the IDC-ILC subtype with liver metastasis in HR+/HER2+ MBC patients and the ILC subtype with bone metastasis in HR-/HER2+ MBC patients proved to be noteworthy.Conclusions: Histological subtypes are involved in determining the heterogeneity of HER2+ MBC patient prognosis, which is helpful to guide the prognosis prediction and monitoring of HER2+ breast cancer patients in clinics.