Uterine leiomyosarcoma management, outcome, and associated molecular biomarkers: a single institution's experience

子宫平滑肌肉瘤的治疗、预后及相关分子生物标志物:一家机构的经验

阅读:1

Abstract

BACKGROUND: Uterine leiomyosarcoma (ULMS) is an aggressive, rapidly progressive tumor lacking clinical and molecular predictors of outcome. METHODS: ULMS patients (n = 349) were classified by disease status at presentation to MDACC as having intra-abdominal (n = 157) or distant metastatic disease (n = 192). Patient, tumor, treatment, and outcome variables were retrospectively retrieved. Formalin-fixed, paraffin-embedded tumor and control tissues from these patients (n = 109) were assembled in a tissue microarray and evaluated for hormone receptors and markers of angiogenesis, cell-cycle progression and survival. Patient, tumor, and treatment variables were correlatively analyzed. RESULTS: The 5- and 10-year disease-specific survival (DSS) for the cohort was 42 and 27 %, respectively. Patients with primary intra-abdominal tumors had better outcomes than those with recurrent intraperitoneal tumors. Whites had a more favorable prognosis. In patients with intra-abdominal tumors, only mitotic count >10M/10HPF portended poorer prognosis. Patients with pulmonary metastasis had improved outcomes with "curative" metastasectomy. ULMS samples exhibited loss of ER and PR expression, overexpressed Ki-67, and altered p53, Rb, p16, cytoplasmic β-catenin, EGFR, PDGFR-α, PDGFR-β, and AXL levels. Metastatic tumors had increased VEGF, Ki-67, and survivin expression versus localized disease. Survivin and β-catenin expression were associated with intraperitoneal recurrence; high bcl-2 expression predicted longer DSS. CONCLUSIONS: Analysis of both clinicopathologic factors and immunohistochemical biomarkers in ULMS identified several prognostic clinical and molecular factors, suggesting that further study may lead to improved ULMS understanding and treatment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。