Version 1
: Received: 30 July 2024 / Approved: 30 July 2024 / Online: 30 July 2024 (15:56:24 CEST)
How to cite:
Casillas Godínez, C. K.; Orozco Luna, F. D. J.; González Santiago, A. E.; Sánchez Parada, M. G.; Mercado Sesma, A. R.; Jiménez Meza, A. R.; Baptista Rosas, R. C. Using association rules to explore occult patterns in Breast Cancer Mitochondrial Genomes. Preprints2024, 2024072461. https://doi.org/10.20944/preprints202407.2461.v1
Casillas Godínez, C. K.; Orozco Luna, F. D. J.; González Santiago, A. E.; Sánchez Parada, M. G.; Mercado Sesma, A. R.; Jiménez Meza, A. R.; Baptista Rosas, R. C. Using association rules to explore occult patterns in Breast Cancer Mitochondrial Genomes. Preprints 2024, 2024072461. https://doi.org/10.20944/preprints202407.2461.v1
Casillas Godínez, C. K.; Orozco Luna, F. D. J.; González Santiago, A. E.; Sánchez Parada, M. G.; Mercado Sesma, A. R.; Jiménez Meza, A. R.; Baptista Rosas, R. C. Using association rules to explore occult patterns in Breast Cancer Mitochondrial Genomes. Preprints2024, 2024072461. https://doi.org/10.20944/preprints202407.2461.v1
APA Style
Casillas Godínez, C. K., Orozco Luna, F. D. J., González Santiago, A. E., Sánchez Parada, M. G., Mercado Sesma, A. R., Jiménez Meza, A. R., & Baptista Rosas, R. C. (2024). Using association rules to explore occult patterns in Breast Cancer Mitochondrial Genomes. Preprints. https://doi.org/10.20944/preprints202407.2461.v1
Chicago/Turabian Style
Casillas Godínez, C. K., Ana Rosa Jiménez Meza and Raúl C. Baptista Rosas. 2024 "Using association rules to explore occult patterns in Breast Cancer Mitochondrial Genomes" Preprints. https://doi.org/10.20944/preprints202407.2461.v1
Abstract
Single nucleotide polymorphisms in the mitochondrial genome have been investigated in relation to breast cancer. Certain variants could be associated with an increased risk of this malignant disease. These associations underline the importance of mitochondrial function in cancer biology and highlight the potential for mtDNA-based biomarkers and future therapies.
The general objective of this research was to develop a model which is capable of identifying nonlinear patterns in breast cancer mitochondrial sequences. Association rules were used to explore mtDNA variant positions. The analysis included 41 breast cancer patients and 28 control samples. An a priori algorithm identified significant association rules with lift > 1 and confidence > 0.5. A total of 5562 rules for cancer and 157,140 for control sequences were refined after redundancy removal. A total of 150 associations were identified, of which only 78 showed significant support and confidence, while 315 and 1438 positions showed strong associations with breast cancer. Association rules analysis revealed significant patterns, especially in sequences associated with the control region and a specific locus around genes coding for tRNAs and NADH dehydrogenase subunits. However, further research is necessary to establish causality, clinical relevance, and to confirm these findings.
Keywords
Breast cancer; Bioinformatics; Data Science; Pattern Search; Association Rules
Subject
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
