Development and validation of a novel stem cell subtype for bladder cancer based on stem genomic profiling

ResearchSquare
Chaozhi TangZhengchun Liu

Abstract

Background Bladder cancer is the fifth most common type of cancer worldwide, with high recurrence and progression rates. Although considerable progress has been made in the treatment of bladder cancer through accurate typing of molecular characteristics, little is known about the various genetic and epigenetic changes that have evolved in stem and progenitor cells. Thus, we developed a novel stem cell typing method to fill this gap. Methods Based on six published genomic data sets, we used 26 stem cell gene sets to classify each data set. Unsupervised and supervised machine learning methods were used to perform the classification. Results We classified BLCA into three subtypes—high stem cell enrichment (SCE_H), medium stem cell enrichment (SCE_M), and low stem cell enrichment (SCE_L)—based on multiple cross-platform data sets. The stability and reliability of the classification were verified. The stemness index obtained from the one-class logistic regression machine learning method showed that the degree of tumor stem cell enrichment was not proportional to the stemness index. Compared with the other subtypes, SCE_H showed the highest degree of cancer stem cell concentration, lowest stemness index, and highest level of immune c...Continue Reading

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