MicroRNAs (miRNAs) are an evolutionarily conserved class of small (18-22 nucleotides) noncoding RNAs involved in the regulation of a variety of cellular and developmental processes. MiRNA expression is frequently altered in human cancers compared to normal tissues, potentially contributing to tumorigenesis. Generally, high-throughput profiles of miRNA expression levels are generated using bulk samples, from both normal and cancer tissues. However, cancer tissues are quite heterogeneous and might contain subpopulations critical for tumor development, i.e., cancer stem cells (CSCs) or tumor-initiating cells (TICs) with aberrant stem-like features, such as unlimited self-renewal potential. The isolation of these aberrant subpopulations from solid tumors is a relatively recent achievement, with breast cancer being one of the first solid human cancers in which CSCs have been identified and biologically characterized. Here, we describe a new methodology that can overcome the main challenge in dealing with rare cells such as SCs/CSCs, represented by the paucity of the starting material. Based on previously published protocols, used by both our and other research groups, we used the FACS-sorting approach to isolate mammary normal and cancer stem cells based on the amount of PKH26 fluorescent dye they retained. Depending on the number of SCs/CSCs isolated, we established two different protocols for the reliable and analytically sensitive detection of up to 384 miRNAs using the Taqman Low Density Array (TLDA) platform.
Keywords: FACS-sorting; HT analysis; Mammospheres; Normal and cancer mammary stem cells; PKH26 dye; TLDA platform; miRNAs.
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