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NF-YA 的可变剪接促进了前列腺癌的侵袭性,代表了一种新的用于患者临床分层的分子标志物。

Alternative splicing of NF-YA promotes prostate cancer aggressiveness and represents a new molecular marker for clinical stratification of patients.

机构信息

Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 213/D, Modena, Italy.

Department of Biosciences, University of Milan, Milan, Italy.

出版信息

J Exp Clin Cancer Res. 2021 Nov 15;40(1):362. doi: 10.1186/s13046-021-02166-4.

Abstract

BACKGROUND

Approaches based on expression signatures of prostate cancer (PCa) have been proposed to predict patient outcomes and response to treatments. The transcription factor NF-Y participates to the progression from benign epithelium to both localized and metastatic PCa and is associated with aggressive transcriptional profile. The gene encoding for NF-YA, the DNA-binding subunit of NF-Y, produces two alternatively spliced transcripts, NF-YAs and NF-YAl. Bioinformatic analyses pointed at NF-YA splicing as a key transcriptional signature to discriminate between different tumor molecular subtypes. In this study, we aimed to determine the pathophysiological role of NF-YA splice variants in PCa and their association with aggressive subtypes.

METHODS

Data on the expression of NF-YA isoforms were extracted from the TCGA (The Cancer Genome Atlas) database of tumor prostate tissues and validated in prostate cell lines. Lentiviral transduction and CRISPR-Cas9 technology allowed the modulation of the expression of NF-YA splice variants in PCa cells. We characterized 3D cell cultures through in vitro assays and RNA-seq profilings. We used the rank-rank hypergeometric overlap approach to identify concordant/discordant gene expression signatures of NF-YAs/NF-YAl-overexpressing cells and human PCa patients. We performed in vivo studies in SHO-SCID mice to determine pathological and molecular phenotypes of NF-YAs/NF-YAl xenograft tumors.

RESULTS

NF-YA depletion affects the tumorigenic potential of PCa cells in vitro and in vivo. Elevated NF-YAs levels are associated to aggressive PCa specimens, defined by Gleason Score and TNM classification. NF-YAl overexpression increases cell motility, while NF-YAs enhances cell proliferation in PCa 3D spheroids and xenograft tumors. The transcriptome of NF-YAs-spheroids has an extensive overlap with localized and metastatic human PCa signatures. According to PCa PAM50 classification, NF-YAs transcript levels are higher in LumB, characterized by poor prognosis compared to LumA and basal subtypes. A significant decrease in NF-YAs/NF-YAl ratio distinguishes PCa circulating tumor cells from cancer cells in metastatic sites, consistently with pro-migratory function of NF-YAl. Stratification of patients based on NF-YAs expression is predictive of clinical outcome.

CONCLUSIONS

Altogether, our results indicate that the modulation of NF-YA isoforms affects prostate pathophysiological processes and contributes to cancer-relevant phenotype, in vitro and in vivo. Evaluation of NF-YA splicing may represent a new molecular strategy for risk assessment of PCa patients.

摘要

背景

基于前列腺癌(PCa)表达特征的方法已被提出用于预测患者的预后和对治疗的反应。转录因子 NF-Y 参与从良性上皮到局部和转移性 PCa 的进展,并与侵袭性转录谱相关。编码 NF-YA 的基因,NF-Y 的 DNA 结合亚基,产生两种选择性剪接的转录本,NF-YAs 和 NF-YAl。生物信息学分析指出 NF-Y 剪接是区分不同肿瘤分子亚型的关键转录特征。在这项研究中,我们旨在确定 NF-YA 剪接变体在 PCa 中的病理生理作用及其与侵袭性亚型的关联。

方法

从肿瘤前列腺组织的 TCGA(癌症基因组图谱)数据库中提取 NF-YA 异构体的表达数据,并在前列腺细胞系中进行验证。慢病毒转导和 CRISPR-Cas9 技术允许在 PCa 细胞中调节 NF-YA 剪接变体的表达。我们通过体外试验和 RNA-seq 分析来描述 3D 细胞培养物。我们使用等级等级超几何重叠方法来识别 NF-YAs/NF-YAl 过表达细胞和人类 PCa 患者的一致/不一致的基因表达特征。我们在 SHO-SCID 小鼠中进行体内研究,以确定 NF-YAs/NF-YAl 异种移植肿瘤的病理和分子表型。

结果

NF-YA 缺失会影响 PCa 细胞的体外和体内致瘤潜力。NF-YAs 水平升高与由 Gleason 评分和 TNM 分类定义的侵袭性 PCa 标本相关。NF-YAl 过表达增加细胞迁移,而 NF-YAs 增强 PCa 3D 球体和异种移植肿瘤中的细胞增殖。NF-YAs-球体的转录组与局部和转移性人类 PCa 特征有广泛的重叠。根据 PCa PAM50 分类,LumB 中 NF-YAs 转录水平较高,与 LumA 和基底亚型相比,预后较差。NF-YAs/NF-YAl 比值的显著降低将 PCa 循环肿瘤细胞与转移部位的癌细胞区分开来,这与 NF-YAl 的促迁移功能一致。基于 NF-YAs 表达的患者分层可预测临床结局。

结论

总之,我们的结果表明,NF-YA 异构体的调节会影响前列腺的生理过程,并有助于体外和体内的癌症相关表型。NF-YA 剪接的评估可能代表 PCa 患者风险评估的新分子策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/738e/8594157/5c4181d73502/13046_2021_2166_Fig1_HTML.jpg

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