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放射形态学的复杂性预示着更差的预后,并且与透明细胞肾细胞癌中蛋白酶体成分水平的升高相关。

Complexity in radiological morphology predicts worse prognosis and is associated with an increase in proteasome component levels in clear cell renal cell carcinoma.

作者信息

Kobatake Kohei, Ikeda Kenichiro, Teishima Jun, Sekino Yohei, Babasaki Takashi, Kohada Yuki, Tasaka Ryo, Takemoto Kenshiro, Fukushima Takafumi, Miyamoto Shunsuke, Kitano Hiroyuki, Goto Keisuke, Hieda Keisuke, Hayashi Tetsutaro, Hinata Nobuyuki

机构信息

Department of Urology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.

Department of Urology, Kobe City Hospital Organization Kobe City Medical Center West Hospital, Kobe, Japan.

出版信息

Front Oncol. 2022 Dec 8;12:1039383. doi: 10.3389/fonc.2022.1039383. eCollection 2022.

DOI:10.3389/fonc.2022.1039383
PMID:36568232
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9773190/
Abstract

BACKGROUND

We previously reported preoperative radiological morphology (RM) as an independent predictor for pathological upstaging after partial nephrectomy in patients with T1 renal cell carcinoma (RCC).

PURPOSE

To investigate the prognostic importance of RM in all stages and the molecular characteristics underlying the differences between each type of RM in patients with clear cell RCC (ccRCC).

DESIGN SETTING AND PARTICIPANTS

The Cancer Imaging Archive datasets (TCIA), comprising CT images and RNA-sequencing data, were used (n = 163). Specimens from 63 patients with ccRCC at our institution and their CT images were used. All images were divided into three types according to RM classification.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Relationships with outcome were analyzed using Cox regression analysis and log-rank test.

RESULTS AND LIMITATIONS

The irregular type was a significant independent predictor of worse disease-free survival (odds ratio: 2.22, p = 0.037) compared to round and lobular types in TCIA datasets. The irregular type showed a significant increase in both mRNA and protein expression of proteasome components, PSMB1 and PSMB3. Moreover, high expression of their coding genes shortened the progression-free survival of the patients with ccRCC who received sunitinib or avelumab plus axitinib therapy. The study limitations include the qualitative classification of RM and the need for novel radiomics and texture analysis techniques.

CONCLUSIONS

Investigating RM on pre-treatment CT scans can effectively predict worse prognosis. Increased RM complexity may indirectly predict drug sensitivity increased expression of PSMB1 and PSMB3 in patients with ccRCC. Specific targeting of the ubiquitin-proteasome system might be a novel treatment strategy for ccRCC with increased RM complexity.

PATIENT SUMMARY

The clinical and morphological characteristics of patients with ccRCC vary greatly according to cancer staging. In this study, we built upon our prior findings of the prognostic importance of RM in T1 RCC and expanded it to encompass all stages of RCC, using a series of patients from a Japanese hospital.

摘要

背景

我们之前报道过,术前放射学形态(RM)是T1期肾细胞癌(RCC)患者行部分肾切除术后病理分期升级的独立预测因素。

目的

探讨RM在所有分期中的预后重要性以及透明细胞RCC(ccRCC)患者中各类型RM差异的分子特征。

设计、设置和参与者:使用癌症影像存档数据集(TCIA),包括CT图像和RNA测序数据(n = 163)。使用了我们机构63例ccRCC患者的标本及其CT图像。根据RM分类,将所有图像分为三种类型。

结果测量和统计分析

使用Cox回归分析和对数秩检验分析与预后的关系。

结果和局限性

在TCIA数据集中,与圆形和小叶形相比,不规则形是无病生存期较差的显著独立预测因素(比值比:2.22,p = 0.037)。不规则形显示蛋白酶体成分PSMB1和PSMB3的mRNA和蛋白表达均显著增加。此外,其编码基因的高表达缩短了接受舒尼替尼或阿维鲁单抗加阿昔替尼治疗的ccRCC患者的无进展生存期。研究局限性包括RM的定性分类以及对新型放射组学和纹理分析技术的需求。

结论

在治疗前CT扫描上研究RM可以有效预测较差的预后。RM复杂性增加可能间接预测ccRCC患者对药物的敏感性——PSMB1和PSMB3表达增加。针对泛素-蛋白酶体系统的特异性靶向可能是RM复杂性增加的ccRCC的一种新治疗策略。

患者总结

ccRCC患者的临床和形态学特征根据癌症分期有很大差异。在本研究中,我们基于之前关于RM在T1期RCC中预后重要性的发现,并将其扩展到涵盖RCC的所有分期,使用了一家日本医院的一系列患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/01844c859d57/fonc-12-1039383-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/773ad7d51a87/fonc-12-1039383-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/9cbae6adba07/fonc-12-1039383-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/d55a3f4687ea/fonc-12-1039383-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/6c3472ddb1ed/fonc-12-1039383-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/ef8cc7f89813/fonc-12-1039383-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/01844c859d57/fonc-12-1039383-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/773ad7d51a87/fonc-12-1039383-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/9cbae6adba07/fonc-12-1039383-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/d55a3f4687ea/fonc-12-1039383-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/6c3472ddb1ed/fonc-12-1039383-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7597/9773190/01844c859d57/fonc-12-1039383-g006.jpg

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