Expression data from glioblastoma tissue. Expression data from glioblastoma tissue

Glioblastomas are among the most lethal cancers; however, recent advances in survival have increased the need for better prognostic markers. microRNAs (miRNAs) hold great prognostic potential being deregulated in glioblastomas and highly stable in stored tissue specimens. Moreover, miRNAs control multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included retrospectively; patients were comparable on all clinical aspects except overall survival enabling patients to be categorized as short-term or long-term survivors based on median survival. A miRNome screening was employed, and a prognostic profile was developed using leave-one-out cross-validation. We found that expression patterns of miRNAs; particularly the four miRNAs: hsa-miR-107_st, hsa-miR-548x_st, hsa-miR-3125_st and hsa-miR-331-3p_st could determine short- and long-term survival with a predicted accuracy of 78%. Heatmap dendrograms dichotomized glioblastomas into prognostic subgroups with a significant association to survival in univariate (HR 8.50; 95% CI 3.06-23.62; p<0.001) and multivariate analysis (HR 9.84; 95% CI 2.93-33.06; p<0.001). Similar tendency was seen in The Cancer Genome Atlas (TCGA) using a 2-miRNA signature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available in TCGA. In TCGA, patients with O6-methylguanine-DNA-methyltransferase (MGMT) unmethylated tumors and low miR sum score had the shortest survival. Adjusting for age and MGMT status, low miR sum score was associated with a poorer prognosis (HR 0.66; 95% CI 0.45-0.97; p=0.033). A Kyoto Encyclopedia of Genes and Genomes analysis predicted the identified miRNAs to regulate genes involved in cell cycle regulation and survival. In conclusion, the biology of miRNAs is complex, but the identified 4-miRNA expression pattern could comprise promising biomarkers in glioblastoma stratifying patients into short- and long-term survivors. Overall design: miRNA expression data from primary glioblastoma tissue; 40 patient samples were analyzed. One sample was omitted from further analysis due to low intensity on the chip (Patient ID 10). Another sample (Patient ID 21) had a mutation in isocitrate dehydrogenase 1 and was therefore omitted from further analysis due to potential confounding.

胶质母细胞瘤（Glioblastomas）是致死性最高的癌症类型之一；近年来患者生存期有所延长，因此对更优质的预后标志物的需求愈发迫切。微小RNA（miRNAs）在胶质母细胞瘤中存在表达失调，且在储存的组织标本中稳定性极佳，具备极高的预后评估潜力。此外，微小RNA可调控大量基因，代表了一层额外的基因调控机制，其预后价值可能优于单基因标志物。本研究旨在筛选出一种新型微小RNA特征，以实现将患者划分为不同预后亚组的目标。

本研究回顾性纳入了40例胶质母细胞瘤患者的样本；所有患者在临床特征上均具有可比性，仅总生存期存在差异，据此可依据中位生存期将患者划分为短期生存组与长期生存组。研究采用了微小RNA组（miRNome）筛选策略，并通过留一交叉验证法（leave-one-out cross-validation）构建了预后特征模型。

研究发现，特定微小RNA的表达模式——尤其是hsa-miR-107_st、hsa-miR-548x_st、hsa-miR-3125_st及hsa-miR-331-3p_st这4种微小RNA——可准确区分患者的短期与长期生存状态，预测准确率达78%。通过热图聚类树（Heatmap dendrograms）可将胶质母细胞瘤样本划分为不同预后亚组，该分组与患者生存期显著相关：单因素分析中风险比（HR）为8.50，95%置信区间（CI）为3.06~23.62，p<0.001；多因素分析中HR为9.84，95%CI为2.93~33.06，p<0.001。

在癌症基因组图谱（TCGA）数据集内，利用miR-107与miR-331这两种可获取的微小RNA构建的双微小RNA特征（miR总和评分）也观察到了相似趋势。在TCGA队列中，O6-甲基鸟嘌呤-DNA-甲基转移酶（MGMT）未甲基化且miR总和评分较低的患者生存期最短。在校正年龄与MGMT状态后，低miR总和评分仍与较差的预后显著相关（HR=0.66，95%CI=0.45~0.97，p=0.033）。

京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes）分析预测，本研究筛选出的微小RNA可调控参与细胞周期调控与细胞存活过程的基因。

综上，微小RNA的生物学功能极为复杂，但本研究鉴定出的4种微小RNA表达特征有望成为胶质母细胞瘤的潜在生物标志物，实现对患者短期与长期生存状态的分层。

本研究的整体实验设计：分析了原代胶质母细胞瘤组织的微小RNA表达数据，共纳入40例患者样本。其中1例因芯片信号强度过低被排除后续分析（患者ID：10），另1例因存在异柠檬酸脱氢酶1（isocitrate dehydrogenase 1）突变，可能存在混杂因素，故同样排除后续分析（患者ID：21）。