Suppr超能文献

整合复发性体细胞突变与临床结局:1049 例透明细胞肾细胞癌患者的汇总分析。

Integration of Recurrent Somatic Mutations with Clinical Outcomes: A Pooled Analysis of 1049 Patients with Clear Cell Renal Cell Carcinoma.

机构信息

Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

出版信息

Eur Urol Focus. 2017 Oct;3(4-5):421-427. doi: 10.1016/j.euf.2016.06.015. Epub 2016 Jul 16.

Abstract

BACKGROUND

Analyses of associations between clinicopathologic outcomes and recurrent somatic mutations in clear cell renal cell carcinoma (ccRCC) have been limited to individual cohorts.

OBJECTIVE

To define clinicopathologic associations between specific mutations and ccRCC disease characteristics.

DESIGN, SETTING, AND PARTICIPANTS: DNA sequencing data were pooled from three collaborative genomic cohorts (n=754) and our institutional database (n=295). All patients had clinical data and identification of somatic mutations from their primary tumors.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Analysis of gene mutations for associations with maximal tumor size (linear regression) and pathologic stage (logistic regression). Cancer-specific survival (CSS) and recurrence-free survival (RFS) were calculated using competing risks methods. Analyses were adjusted for cohort site, and results were adjusted for multiple testing (q value). Relevant genes were used in multivariable models that included confounding variables and the validated Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score.

RESULTS AND LIMITATIONS

Association with tumor size was found for mutations in BAP1 (q=0.013). No mutations were found to be associated with stage after adjusted analysis. Mutations in BAP1 (q=0.004) and TP53 (q=0.001) were associated with decreased CSS in a multivariable model; only TP53 (q=0.005) remained significant when SSIGN score was included. SETD2 mutations (q=0.047) were associated with decreased RFS in multivariable models, including models with SSIGN score.

CONCLUSIONS

In >1000 patients with ccRCC, pooled analysis and multivariable modeling demonstrated that three mutated genes have statistically significant associations with poor clinical outcomes. This included the more commonly mutated BAP1 and SETD2 and the less frequently mutated TP53. After adjustment for clinical confounders, mutations of TP53 and SETD2 were associated with decreased CSS and RFS, respectively.

PATIENT SUMMARY

Using rigorous statistical methods, this study affirmed that certain mutations in clear cell renal cell carcinoma may portend inferior survival and an increased risk of recurrence.

摘要

背景

分析透明细胞肾细胞癌(ccRCC)临床病理结局与复发性体细胞突变之间的关系,仅限于单个队列。

目的

定义特定突变与 ccRCC 疾病特征之间的临床病理关联。

设计、设置和参与者:从三个合作基因组队列(n=754)和我们的机构数据库(n=295)中汇集 DNA 测序数据。所有患者均具有来自其原发肿瘤的临床数据和体细胞突变识别。

测量和统计分析

对与最大肿瘤大小(线性回归)和病理分期(逻辑回归)相关的基因突变进行分析。使用竞争风险方法计算癌症特异性生存率(CSS)和无复发生存率(RFS)。分析调整了队列地点,结果针对多次检验(q 值)进行了调整。在包括混杂变量和验证后的 Mayo 临床分期、大小、分级和坏死(SSIGN)评分的多变量模型中使用了相关基因。

结果和局限性

在 BAP1 突变中发现与肿瘤大小相关(q=0.013)。经过调整分析,未发现与分期相关的突变。在多变量模型中,BAP1(q=0.004)和 TP53(q=0.001)突变与 CSS 降低相关;当包括 SSIGN 评分时,只有 TP53(q=0.005)仍然显著。SET2 突变(q=0.047)与多变量模型中的 RFS 降低相关,包括包含 SSIGN 评分的模型。

结论

在 >1000 例 ccRCC 患者中,汇总分析和多变量模型表明,三个突变基因与不良临床结局具有统计学显著关联。这包括更常见的 BAP1 和 SETD2 以及不太常见的 TP53。在调整临床混杂因素后,TP53 和 SETD2 的突变与 CSS 和 RFS 降低分别相关。

患者总结

使用严格的统计方法,本研究证实透明细胞肾细胞癌中的某些突变可能预示着生存率降低和复发风险增加。

相似文献

引用本文的文献

7
The evolving management of small renal masses.小肾肿瘤的不断演变的治疗策略。
Nat Rev Urol. 2024 Jul;21(7):406-421. doi: 10.1038/s41585-023-00848-6. Epub 2024 Feb 16.

本文引用的文献

1
Genomic characterization of sarcomatoid transformation in clear cell renal cell carcinoma.透明细胞肾细胞癌中肉瘤样转化的基因组特征
Proc Natl Acad Sci U S A. 2016 Feb 23;113(8):2170-5. doi: 10.1073/pnas.1525735113. Epub 2016 Feb 10.
5
The Global Burden of Cancer 2013.《2013 年全球癌症负担》。
JAMA Oncol. 2015 Jul;1(4):505-27. doi: 10.1001/jamaoncol.2015.0735.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验