Construction and validation of prognosis and treatment outcome models based on plasma membrane tension characteristics in bladder cancer.

IF 2.4 3区 生物学 Q2 MULTIDISCIPLINARY SCIENCES PeerJ Pub Date : 2025-01-06 eCollection Date: 2025-01-01 DOI:10.7717/peerj.18816
Zhipeng Wang, Sheng Li, Fuchun Zheng, Situ Xiong, Lei Zhang, Liangwei Wan, Chen Wang, Xiaoqiang Liu, Jun Deng
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Abstract

Background: Plasma membrane tension-related genes (MTRGs) are known to play a crucial role in tumor progression by influencing cell migration and adhesion. However, their specific mechanisms in bladder cancer (BLCA) remain unclear.

Methods: Transcriptomic, clinical and mutation data from BLCA patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Clusters associated with MTRGs were identified by consensus unsupervised cluster analysis. The genes of different clusters were analyzed by GO and KEGG gene enrichment analysis. Differentially expressed genes (DEGs) were screened from different clusters. Consensus cluster analysis of prognostic DEGs was performed to identify gene subtypes. Patients were then randomly divided into training and validation groups, and MTRG scores were constructed by logistic minimum absolute contraction and selection operator (LASSO) and Cox regression analysis. We assessed changes in clinical outcomes and immune-related factors between different patient groups. The single-cell RNA sequencing (scRNA-seq) dataset for BLCA was collected and analyzed from the Tumor Immune Single-cell Hub (TISCH) database. Biological functions were investigated using a series of experiments including quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), wound healing, transwell, etc.

Results: Our MTRG score is based on eight genes (HTRA1, GOLT1A, DCBLD2, UGT1A1, FOSL1, DSC2, IGFBP3 and TAC3). Higher scores were characterized by lower cancer stem cell (CSC) indices, as well as higher tumor microenvironment (TME) stromal and immune scores, suggesting that high scores were associated with poorer prognosis. In addition, some drugs such as cisplatin, paclitaxel, doxorubicin, and docetaxel exhibited lower IC50 values in the high MTRG score group. Functional experiments have demonstrated that downregulation of DCBLD2 affects tumor cell migration, but not proliferation.

Conclusions: Our study sheds light on the prognostic significance of MTRGs within the TME and their correlation with immune infiltration patterns, ultimately impacting patient survival in BLCA. Notably, our findings highlight DCBLD2 as a promising candidate for targeted therapeutic interventions in the clinical management of BLCA.

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基于膀胱癌质膜张力特征的预后和治疗结果模型的构建与验证。
背景:已知质膜张力相关基因(MTRGs)通过影响细胞迁移和粘附在肿瘤进展中起关键作用。然而,它们在膀胱癌(BLCA)中的具体机制尚不清楚。方法:从The Cancer Genome Atlas (TCGA)和Gene Expression Omnibus (GEO)数据库中收集BLCA患者的转录组学、临床和突变数据。通过一致的无监督聚类分析确定与mtrg相关的聚类。对不同簇的基因进行GO和KEGG基因富集分析。从不同簇中筛选差异表达基因(DEGs)。对预后deg进行一致聚类分析以确定基因亚型。将患者随机分为训练组和验证组,采用logistic最小绝对收缩和选择算子(LASSO)和Cox回归分析构建MTRG评分。我们评估了不同患者组之间临床结果和免疫相关因素的变化。从肿瘤免疫单细胞中心(Tumor Immune single-cell Hub, TISCH)数据库中收集并分析BLCA的单细胞RNA测序(scRNA-seq)数据集。结果:MTRG评分基于8个基因(HTRA1、GOLT1A、DCBLD2、UGT1A1、FOSL1、DSC2、IGFBP3和TAC3)。评分越高,肿瘤干细胞(CSC)指数越低,肿瘤微环境(TME)基质和免疫评分越高,提示评分越高预后越差。此外,一些药物如顺铂、紫杉醇、阿霉素、多西紫杉醇在MTRG高评分组的IC50值较低。功能实验表明,下调DCBLD2影响肿瘤细胞迁移,但不影响增殖。结论:我们的研究揭示了TME内MTRGs的预后意义及其与免疫浸润模式的相关性,最终影响BLCA患者的生存。值得注意的是,我们的研究结果突出了DCBLD2作为BLCA临床管理中靶向治疗干预的有希望的候选者。
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来源期刊
PeerJ
PeerJ MULTIDISCIPLINARY SCIENCES-
CiteScore
4.70
自引率
3.70%
发文量
1665
审稿时长
10 weeks
期刊介绍: PeerJ is an open access peer-reviewed scientific journal covering research in the biological and medical sciences. At PeerJ, authors take out a lifetime publication plan (for as little as $99) which allows them to publish articles in the journal for free, forever. PeerJ has 5 Nobel Prize Winners on the Board; they have won several industry and media awards; and they are widely recognized as being one of the most interesting recent developments in academic publishing.
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