Suppr超能文献

高表达的 MLANA 在头颈部鳞状细胞癌患者的血浆中作为肿瘤进展的预测指标。

High expression of MLANA in the plasma of patients with head and neck squamous cell carcinoma as a predictor of tumor progression.

机构信息

Biological Science Department, Campus Diadema, Universidade Federal de São Paulo, Diadema, São Paulo, Brazil.

Cancer Therapeutics Research Laboratory, National Cancer Centre, Singapore.

出版信息

Head Neck. 2019 May;41(5):1199-1205. doi: 10.1002/hed.25510. Epub 2019 Feb 25.

Abstract

BACKGROUND

There is a paucity of plasma-based biomarkers that predict outcome in patients with head and neck squamous cell carcinoma (HNSCC) treated with chemoradiation therapy (CRT). Here, we evaluate the prognostic potential of plasma Melanoma-Antigen Recognized by T-cells 1 (MLANA) in this setting.

METHODS

MLANA expression in HNSCC lines were evaluated by reverse transcription polymerase chain reaction, whereas plasma levels were quantified using ELISA in 48 patients with locally advanced HNSCC undergoing a phase 2 trial with CRT.

RESULTS

MLANA is expressed at variable levels in a panel of HNSCC lines. In plasma, levels were elevated in patients with tumor relapse compared to those without (P < .004); 73.9% of the patients expressing high plasma MLANA levels progressed with recurrent disease (P = .020). Multivariate analysis showed that plasma MLANA levels and tumor resectability were independent prognostic factors for progression free survival.

CONCLUSION

Plasma MLANA expression appears to be an effective noninvasive biomarker for outcomes in patients treated with CRT, and could potentially guide therapeutic decisions in this context.

摘要

背景

目前用于预测头颈部鳞状细胞癌(HNSCC)患者接受放化疗(CRT)后结局的基于血浆的生物标志物较少。在此,我们评估了黑素瘤抗原识别 T 细胞 1(MLANA)在该环境中的预后潜力。

方法

通过逆转录聚合酶链反应评估 HNSCC 细胞系中的 MLANA 表达,并用 ELISA 定量检测 48 例接受 CRT 治疗的局部晚期 HNSCC 患者的血浆水平。

结果

MLANA 在一组 HNSCC 细胞系中以不同水平表达。与无肿瘤复发的患者相比,肿瘤复发患者的血浆水平升高(P<0.004);表达高水平血浆 MLANA 的患者中有 73.9%出现复发性疾病进展(P=0.020)。多因素分析显示,血浆 MLANA 水平和肿瘤可切除性是无进展生存期的独立预后因素。

结论

血浆 MLANA 表达似乎是 CRT 治疗患者结局的有效无创生物标志物,并且可能在这种情况下指导治疗决策。

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