Identification of transcriptomic patterns specific to different types of lung adenocarcinomas comparing EGFR, KRAS, and ALK fusion oncogenic driver molecular alterations
Objective. Lung cancer remains the principal cause of cancer death globally. Targeted therapies have been developed due to a better knowledge of cancer biology and the identification of oncogenic driver alterations that are therapeutically targetable. The main objective is to identify unique transcr...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/154229 |
| Acceso en línea: | https://hdl.handle.net/10609/154229 |
| Access Level: | acceso abierto |
| Palabra clave: | lung adenocarcinoma oncogenic drivers transcriptional analyses adenocarcinoma de pulmón conductores oncogénicos análisis transcripcionales Bioinformatics -- TFM Bioinformàtica -- TFM |
| Sumario: | Objective. Lung cancer remains the principal cause of cancer death globally. Targeted therapies have been developed due to a better knowledge of cancer biology and the identification of oncogenic driver alterations that are therapeutically targetable. The main objective is to identify unique transcriptomic patterns that distinguish the three molecular subtypes of EGFR, KRAS, and ALK fusion oncogenic drivers in lung adenocarcinomas (LUAD). This is carried out by identifying differentially expressed genes (DEGs) through pairwise comparisons of these three molecular subtypes. Methods: The total of 158 patients selected from the Gene Expression Omnibus DataSet GSE31210 were stage I–II LUAD. Specifically, 127 had EGFR mutation, 20 had KRAS mutation, and 11 had EML4-ALK fusion. The Platform was Affymetrix Human Genome U133 Plus 2.0 Array. The bioinformatics tools used were R version 4.4.2, Bioconductor (version ‘3.20’), and RStudio 2025.05.0+496. The biological significance of DEGs was analyzed through a gene enrichment analysis. Results: KRAS-mutated tumors showed probably an "immune-activated" microenvironment characterized by higher levels of immune activity compared to the other two types. The mitotic checkpoint's response to errors in chromosome attachment was probably increased in KRAS versus ALK, producing a longer delay at prometaphase. KRAS-mutated tumors showed probably more mitotic errors and dysregulations of the cell cycle than the other two types. Conclusion: The differences in the immune microenvironment have clinical implications, as KRAS-mutated tumors generally are more responsive to immunotherapy than the other two types. The differences in cell cycle control could have clinical implications for how these tumors respond to certain chemotherapies. |
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