Suppr超能文献

皮肤鳞状细胞癌的预后标准。

Prognostic criteria for squamous cell cancer of the skin.

机构信息

Department of Surgery, University of Arizona College of Medicine, Tucson, Arizona 85723, USA.

出版信息

J Surg Res. 2010 Mar;159(1):509-16. doi: 10.1016/j.jss.2008.12.008. Epub 2009 Jan 1.

Abstract

BACKGROUND

Non-well-differentiated cutaneous squamous cell carcinomas may display a more aggressive behavior. It is important to better define prognostic criteria for these tumors.

METHODS

This was a retrospective case-control analysis of a squamous cell carcinoma database. Patients with non-well-differentiated and well-differentiated tumors were matched based on site of tumor, age, and immunocompromised status. Comparisons included demographics, histology, immunohistochemical protein expressions (Ki-67, p53, E-cadherin, cyclin D1), and clinical outcomes.

RESULTS

Demographic features were similar between cases (n=30) and controls (n=30). Non-well-differentiated tumors were larger (1.8 cm versus 1.3 cm, P=0.08), deeper (0.81 cm versus 0.32 cm, P<0.0001), and had greater recurrence (P=0.003). Non-well-differentiated tumors showed increased proliferation rate, Ki-67 index (77% versus 61%, P=0.001); no significant difference in activity of p53, E-cadherin, and cyclin D1 between the two groups.

CONCLUSIONS

Tumor differentiation and depth are important pathologic and prognostic criteria for cutaneous squamous cell carcinoma. Immunohistochemistry helps describe patterns of biomarker protein expression and may exemplify aggressive subtypes.

摘要

背景

非典型分化的皮肤鳞状细胞癌可能表现出更具侵袭性的行为。因此,更好地定义这些肿瘤的预后标准非常重要。

方法

这是一项对鳞状细胞癌数据库的回顾性病例对照分析。非典型分化和典型分化的肿瘤患者根据肿瘤部位、年龄和免疫功能低下状态进行匹配。比较包括人口统计学、组织学、免疫组织化学蛋白表达(Ki-67、p53、E-钙黏蛋白、细胞周期蛋白 D1)和临床结果。

结果

病例组(n=30)和对照组(n=30)的人口统计学特征相似。非典型分化的肿瘤更大(1.8 厘米对 1.3 厘米,P=0.08),更深(0.81 厘米对 0.32 厘米,P<0.0001),复发率更高(P=0.003)。非典型分化的肿瘤增殖率、Ki-67 指数较高(77%对 61%,P=0.001);两组之间 p53、E-钙黏蛋白和细胞周期蛋白 D1 的活性无显著差异。

结论

肿瘤分化和深度是皮肤鳞状细胞癌的重要病理和预后标准。免疫组织化学有助于描述生物标志物蛋白表达模式,并可能代表侵袭性亚型。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验