A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

Int J Mol Sci. 2023 Apr 13;24(8):7214. doi: 10.3390/ijms24087214.

Abstract

Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the "omics" clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed "radiomics". Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of "radiology" and "genomics", is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach.

Keywords: breast cancer; genomics; radiogenomics; radiomics.

Publication types

  • Review

MeSH terms

  • Breast Neoplasms* / diagnostic imaging
  • Breast Neoplasms* / genetics
  • Diagnostic Imaging
  • Female
  • Genomics / methods
  • Humans
  • Radiography
  • Radiology* / methods

Grants and funding

This research received no external funding.