Abstract

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.

Highlights

  • Modern cancer biology, which is expanding rapidly in the light of omics approaches, has validated many aspects of Darwinian somatic evolution in cancer progression [1]

  • ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) Are Indistinguishable Based on Gene Expression Profiles

  • We hypothesized that DCIS can be distinguished from IDC based on molecular features

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Summary

Introduction

Modern cancer biology, which is expanding rapidly in the light of omics approaches, has validated many aspects of Darwinian somatic evolution in cancer progression [1]. Such evolutionary logic influences our thinking and actions [2]. There are still some unknowns in the cancer evolution field, and innovative ideas and approaches are needed. It is not clear how the progress of tumor staging could be correlated to clinical outcomes.

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