Biological processes associated with breast cancer subtypes: A meta-analysis study
-
Published:2023-11-20
Issue:3
Volume:4
Page:11-27
-
ISSN:2753-9148
-
Container-title:Systematic Literature Review and Meta-Analysis Journal
-
language:
-
Short-container-title:Sys Lit Rev & Meta-Anl J
Author:
El Aboudi Najia,Ouardi Faissal,Ababou Mouna,Laraqui Abdelilah,Mguil Malika,Elbiad Oubaida,Badaoui Bouabid
Abstract
This study delves into the modular mechanisms underlying various breast cancer subtypes, including Basal-like, HER2, Luminal A, Luminal B, Normal-like, and the differences between Luminal A and B. Through microarrays meta-analyses, the research identifies potential biomarkers for these subtypes by comparing each with the normal state, revealing 408, 429, 531, 346, 113, and 1085 differentially expressed genes associated with Basal-like, HER2, Luminal A, Luminal B, Normal-like, and Luminal A vs Luminal B, respectively. Significant enrichment of top GO terms like 'nuclear-transcribed mRNA catabolic process nonsense-mediated decay', 'SRP-dependent cotranslational protein targeting to membrane', 'translational initiation', 'rRNA processing', and 'viral transcription and response to corticosteroid' was observed in different breast cancer subtypes. Specifically, in the comparison between Luminal A and B cancers, 'tumor necrosis factor-mediated signaling' was the most enriched pathway. The most differentially expressed genes in this comparison were 'TOP2A, AURKA, RRM2, CDK1, and MDA2L1' (up-regulated), and 'LTF and MYBPC1' (down-regulated). These insights could be pivotal in developing new clinical-genomic models and identifying novel therapeutic strategies for specific molecular subgroups of breast cancer. The present study aims to investigate the modular mechanisms underlying different breast cancer subtypes and identifies potential biomarkers for Basal-like subtype (Normal vs Basal-like), HER2 subtype (Normal vs HER2), Luminal A subtype (Normal vs Luminal A), Luminal B subtype (Normal vs Luminal B), Normal-like subtype (Normal vs Normal-like) and between Luminal A and B (Luminal A vs Luminal B) using microarrays meta-analyses. 408, 429, 531, 346, 113, and 1085 differentially expressed genes were associated with Basal-like, HER2, Luminal A, Luminal B, Normal-like subtypes, and ‘Luminal A vs Luminal B’, respectively. Top GO terms significantly enriched for different breast cancer subtypes include ‘nuclear-transcribed mRNA catabolic process nonsense-mediated decay’, ‘SRP-dependent cotranslational protein targeting to membrane’, ‘translational initiation’, ‘rRNA processing’, and ‘viral transcription and response to corticosteroid’. The comparison between Luminal A and B cancers found that ‘tumor necrosis factor-mediated signaling’ was the most enriched pathway and the most differentially expressed genes included ‘sTOP2A, AURKA, RRM2, CDK1 and MDA2L1 (up-regulated)’ and ‘LTF and MYBPC1 (down-regulated)’. These findings may contribute to defining new clinical-genomic models and identifying new therapeutic strategies in the specific molecular subgroups.
Publisher
The Association of Professional Researchers and Academicians
Reference32 articles.
1. Alexa, A., & Rahnenführer, J. (2009). Gene set enrichment analysis with topGO. Bioconductor Improv, 27, 1-26. 2. Balkwill, F. (2009). Tumor necrosis factor and cancer. Nature Reviews Cancer, 9(5), 361-371. https://doi.org/10.1038/nrc2628 3. Collins, F. S., & Varmus, H. (2015). A new initiative on precision medicine. New England Journal of Medicine, 372(9), 793-795. https://doi.org/10.1056/NEJMp1500523 4. Creighton, C. J. (2012). The molecular profile of luminal B breast cancer. Biologics, 6, 289-297. https://doi.org/10.2147/BTT.S29923 5. Dowsett, M., Nielsen, T. O., A’Hern, R., Bartlett, J., Coombes, R. C., Cuzick, J., Ellis, M., Henry, N. L., Hugh, J. C., Lively, T., McShane, L., Paik, S., Penault-Llorca, F., Prudkin, L., Regan, M., Salter, J., Sotiriou, C., Smith, I. E., Viale, G., Zujewski, J. A., & Hayes, D. F. (2011). International Ki-67 in Breast Cancer Working Group. Journal of the National Cancer Institute, 103(22), 1656-1664. https://doi.org/10.1093/jnci/djr393
|
|