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用于早期识别透明细胞肾细胞癌预后不良的17基因表达特征

A 17-Gene Expression Signature for Early Identification of Poor Prognosis in Clear Cell Renal Cell Carcinoma.

作者信息

Bassanelli Maria, Borro Marina, Roberto Michela, Giannarelli Diana, Giacinti Silvana, Di Martino Simona, Ceribelli Anna, Russo Andrea, Aschelter Annamaria, Scarpino Stefania, Montori Andrea, Pescarmona Edoardo, Tomao Silverio, Simmaco Maurizio, Cognetti Francesco, Milella Michele, Marchetti Paolo

机构信息

Department of Medical and Surgical Sciences and Translational Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00100 Rome, Italy.

(DIMA) Department of Neurosciences, Mental Health and Sensory Organs, Sapienza University of Rome, 00187 Rome, Italy.

出版信息

Cancers (Basel). 2021 Dec 30;14(1):178. doi: 10.3390/cancers14010178.

Abstract

UNLABELLED

The Identification of reliable Biomarkers able to predict the outcome after nephrectomy of patients with clear cell renal cell carcinoma (ccRCC) is an unmet need. The gene expression analysis in tumor tissues represents a promising tool for better stratification of ccRCC subtypes and patients' evaluation.

METHODS

In our study we retrospectively analyzed using Next-Generation expression analysis (NanoString), the expression of a gene panel in tumor tissue from 46 consecutive patients treated with nephrectomy for non-metastatic ccRCC at two Italian Oncological Centres. Significant differences in expression levels of selected genes was sought. Additionally, we performed a univariate and a multivariate analysis on overall survival according to Cox regression model.

RESULTS

A 17-gene expression signature of patients with a recurrence-free survival (RFS) < 1 year (unfavorable genomic signature (UGS)) and of patients with a RFS > 5 years (favorable genomic signature (FGS)) was identified and resulted in being significantly correlated with overall survival of the patients included in this analysis (HR 51.37, < 0.0001).

CONCLUSIONS

The identified Genomic Signatures may serve as potential biomarkers for prognosis prediction of non-metastatic RCC and could drive both follow-up and treatment personalization in RCC management.

摘要

未标注

确定能够预测透明细胞肾细胞癌(ccRCC)患者肾切除术后预后的可靠生物标志物是一项尚未满足的需求。肿瘤组织中的基因表达分析是对ccRCC亚型进行更好分层和评估患者的一种有前景的工具。

方法

在我们的研究中,我们使用下一代表达分析(NanoString)对来自两个意大利肿瘤中心的46例接受肾切除术治疗的非转移性ccRCC连续患者的肿瘤组织中的一组基因表达进行了回顾性分析。寻找所选基因表达水平的显著差异。此外,我们根据Cox回归模型对总生存期进行了单变量和多变量分析。

结果

确定了无复发生存期(RFS)<1年的患者(不良基因组特征(UGS))和RFS>5年的患者(良好基因组特征(FGS))的17基因表达特征,并且该特征与本分析中纳入患者的总生存期显著相关(HR 51.37,<0.0001)。

结论

所确定的基因组特征可作为非转移性RCC预后预测的潜在生物标志物,并可推动RCC管理中的随访和治疗个性化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ac5/8750239/07fe025de3b2/cancers-14-00178-g001.jpg

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