Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.
Brief Bioinform. 2021 Mar 22;22(2):2151-2160. doi: 10.1093/bib/bbz174.
The progression of cancer is accompanied by the acquisition of stemness features. Many stemness evaluation methods based on transcriptional profiles have been presented to reveal the relationship between stemness and cancer. However, instead of absolute stemness index values-the values with certain range-these methods gave the values without range, which makes them unable to intuitively evaluate the stemness. Besides, these indices were based on the absolute expression values of genes, which were found to be seriously influenced by batch effects and the composition of samples in the dataset. Recently, we have showed that the signatures based on the relative expression orderings (REOs) of gene pairs within a sample were highly robust against these factors, which makes that the REO-based signatures have been stably applied in the evaluations of the continuous scores with certain range. Here, we provided an absolute REO-based stemness index to evaluate the stemness. We found that this stemness index had higher correlation with the culture time of the differentiated stem cells than the previous stemness index. When applied to the cancer and normal tissue samples, the stemness index showed its significant difference between cancers and normal tissues and its ability to reveal the intratumor heterogeneity at stemness level. Importantly, higher stemness index was associated with poorer prognosis and greater oncogenic dedifferentiation reflected by histological grade. All results showed the capability of the REO-based stemness index to assist the assignment of tumor grade and its potential therapeutic and diagnostic implications.
癌症的进展伴随着干性特征的获得。已经提出了许多基于转录谱的干性评估方法来揭示干性与癌症之间的关系。然而，这些方法并没有给出范围值，而是给出了没有范围的数值，这使得它们无法直观地评估干性。此外，这些指数是基于基因的绝对表达值，而这些值受到批次效应和数据集中样本组成的严重影响。最近，我们已经表明，基于样本内基因对相对表达顺序（REO）的特征在很大程度上不受这些因素的影响，这使得基于 REO 的特征能够稳定地应用于具有一定范围的连续评分的评估。在这里，我们提供了一个基于绝对 REO 的干性指数来评估干性。我们发现，与分化干性细胞的培养时间相比，这个干性指数与分化干性细胞的培养时间具有更高的相关性。当应用于癌症和正常组织样本时，干性指数显示出其在癌症和正常组织之间的显著差异，以及其在干性水平上揭示肿瘤内异质性的能力。重要的是，更高的干性指数与较差的预后和更大的肿瘤去分化程度相关，反映在组织学分级上。所有结果均表明，基于 REO 的干性指数能够辅助肿瘤分级，并具有潜在的治疗和诊断意义。
