Identification of the miRNA Profile Associated with Epithelial Mesenchymal Transition and the Generation of Cancer Stem Cells in a Lung Cancer Model

Lung cancer is a highly aggressive tumor that frequently leads to metastasis, resulting in one of the highest annual mortality rates worldwide. In 2022, this neoplasm accounted for 1,817,469 deaths globally, according to the World Health Organization (WHO). Despite advancements in cancer treatment, metastasis remains the primary cause of death associated with malignant tumors, with approximately 90% of patients succumbing to it. Although extensive research has focused on understanding the mechanisms underlying tumor cell invasion, our knowledge of the molecular signaling pathways driving metastasis is still limited, hindering the development of effective targeted therapies.Metastasis requires tumor cells to undergo alterations that allow them to acquire motility and invasiveness. To achieve this, tumor cells activate the epithelial to mesenchymal transition (EMT) program, and a subset of these cells can further undergo dedifferentiation to generate cancer stem cells (CSCs), which play a critical role in metastasis and resistance to conventional therapies. Evidence suggests that changes in gene regulation and the expression of non coding RNAs, such as microRNAs (miRNAs), contribute to EMT and CSC formation. However, the specific miRNAs involved in these processes in lung cancer remain poorly understood.Based on this, our research aimed to identify the miRNAs potentially responsible for EMT and CSC generation. To accomplish this, we induced EMT in two lung cancer cell lines (A549 and NCI H1975) using dCas9 technology to activate the transcription factor Twist, generating a population with a mesenchymal phenotype. This population was subsequently cultured for several days to obtain CSCs, which were selected and isolated using the well established CSC marker CD133. RNA extraction and small RNA sequencing (small RNA seq) were performed on the fourth cell populations (epithelial phenotype without any treatment, epithelial cells infected with CopGFP lentiviral particles as a transduction control, mesenchymal phenotype, and CSCs). Based on these data, bioinformatics analyses were conducted to identify differentially expressed miRNAs across adherent epithelial cells, mesenchymal cells, and CSCs. We identified 33 miRNAs that were overexpressed and 19 miRNAs that were downregulated in the CSC population