Suppr超能文献

使用计算机模拟转化方法研究高Gleason评分及局限性/局部进展性前列腺癌患者的独特生物学特征

Unique Biological Characteristics of Patients with High Gleason Score and Localized/Locally Advanced Prostate Cancer Using an In Silico Translational Approach.

作者信息

Miyachi Shiori, Oshi Masanori, Sasaki Takeshi, Endo Itaru, Makiyama Kazuhide, Inoue Takahiro

机构信息

Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu 514-8507, Mie, Japan.

Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Kanagawa, Japan.

出版信息

Curr Oncol. 2025 Jul 18;32(7):409. doi: 10.3390/curroncol32070409.

Abstract

Gleason score (GS) is one of the best predictors of prostate cancer (PCa) aggressiveness; however, its biological features need to be elucidated. This study aimed to explore the biological characteristics of localized/locally advanced PCa stratified using in silico GS analysis. Biological features were analyzed using gene set variation analysis and the xCell algorithm with mRNA expression in two independent public databases: The Cancer Genome Atlas (TCGA) ( = 493; radical prostatectomy cohort) and GSE116918 ( = 248; radiation therapy cohort). GS levels were positively correlated with the activity levels of cell proliferation-related gene sets, including E2F targets, the G2M checkpoint, the mitotic spindle, and MYC targets v1 and v2 in both cohorts. Furthermore, GS levels were positively associated with the activity levels of immune-related gene sets and infiltrating fractions of immune cells, including CD4+ memory T cells, dendritic cells, M1 macrophages, and Th2 cells, in both cohorts. Notably, GS levels were positively associated with the score levels of homologous recombination defects, intratumor heterogeneity, fraction genome alteration, neoantigens, and mutation rates in the TCGA cohort. In conclusion, PCa with high GS levels was associated with cancer cell proliferation, immune cell infiltration, and high mutation rates, which may reflect worse clinical outcomes.

摘要

Gleason评分(GS)是前列腺癌(PCa)侵袭性的最佳预测指标之一;然而,其生物学特征仍需阐明。本研究旨在通过计算机模拟GS分析,探索局限性/局部进展性PCa分层后的生物学特征。在两个独立的公共数据库中,使用基因集变异分析和xCell算法,结合mRNA表达来分析生物学特征:癌症基因组图谱(TCGA)(n = 493;根治性前列腺切除术队列)和GSE116918(n = 248;放射治疗队列)。在两个队列中,GS水平均与细胞增殖相关基因集的活性水平呈正相关,这些基因集包括E2F靶点、G2M检查点、有丝分裂纺锤体以及MYC靶点v1和v2。此外,在两个队列中,GS水平均与免疫相关基因集的活性水平以及免疫细胞的浸润分数呈正相关,这些免疫细胞包括CD4 + 记忆T细胞、树突状细胞、M1巨噬细胞和Th2细胞。值得注意的是,在TCGA队列中,GS水平与同源重组缺陷、肿瘤内异质性、基因组改变分数、新抗原和突变率的评分水平呈正相关。总之,高GS水平的PCa与癌细胞增殖、免疫细胞浸润和高突变率相关,这可能反映出更差的临床结局。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00aa/12294092/1df873546b2b/curroncol-32-00409-g001.jpg

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