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Open AccessArticle

Omics Integration Analyses Reveal the Early Evolution of Malignancy in Breast Cancer

1
Stem Cell Research Center, Tabriz University of Medical Sciences, Tabriz 5166614756, Iran
2
Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz 5166614756, Iran
3
Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany
4
Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tempa, FL 33612, USA
5
Department of Cancer Physiology, Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA
6
Experimental Medicine and Therapy Research, University of Regensburg, 93053 Regensburg, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work as first authors.
Cancers 2020, 12(6), 1460; https://doi.org/10.3390/cancers12061460
Received: 12 April 2020 / Revised: 29 May 2020 / Accepted: 31 May 2020 / Published: 4 June 2020
The majority of cancer evolution studies involve individual-based approaches that neglect the population dynamics necessary to build a global picture of cancer evolution for each cancer type. Here, we conducted a population-based study in breast cancer to understand the timing of malignancy evolution and its correlation to the genetic evolution of pathological stages. In an omics integrative approach, we integrated gene expression and genomic aberration data for pre-invasive (ductal carcinoma in situ; DCIS, early-stage) and post-invasive (invasive ductal carcinoma; IDC, late-stage) samples and investigated the evolutionary role of further genetic changes in later stages compared to the early ones. We found that single gene alterations (SGAs) and copy-number alterations (CNAs) work together in forward and backward evolution manners to fine-tune the signaling pathways operating in tumors. Analyses of the integrated point mutation and gene expression data showed that (i) our proposed fine-tuning concept is also applicable to metastasis, and (ii) metastases sometimes diverge from the primary tumor at the DCIS stage. Our results indicated that the malignant potency of breast tumors is constant over the pre- and post-invasive pathological stages. Indeed, further genetic alterations in later stages do not establish de novo malignancy routes; however, they serve to fine-tune antecedent signaling pathways. View Full-Text
Keywords: breast cancer; cancer evolution; omics data integration; machine learning; forward and backward evolution breast cancer; cancer evolution; omics data integration; machine learning; forward and backward evolution
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Sarhadi, S.; Salehzadeh-Yazdi, A.; Damaghi, M.; Zarghami, N.; Wolkenhauer, O.; Hosseini, H. Omics Integration Analyses Reveal the Early Evolution of Malignancy in Breast Cancer. Cancers 2020, 12, 1460.

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