The role of radiogenomics in the diagnosis of breast cancer: a systematic review

Abstract

Background

One of the most common cancers diagnosed worldwide is breast cancer (BC), which is the leading cause of cancer death among women. The radiogenomics method is more accurate for managing and inhibiting this disease, which takes individual diagnosis on genes, environments, and lifestyles of each person. The present study aims to highlight the current state-of-the-art, the current role and limitations, and future directions of radiogenomics in breast cancer.

Method

This systematic review article was searched from databases such as Embase, PubMed, Web of Science, Google Scholar, Scopus, and Cochrane Library without any date or language limitations of databases. Searches were performed using Boolean OR and AND operators between the main terms and keywords of particular topic of the subject under investigation. All retrospective, prospective, cohort, and pilot studies were included, which were provided with more details about the topic. Articles such as letter to the editor, review, and short communications were excluded because of lack of information, discussions, or use of radiogenomics method on other cancers. For quality assessment of articles, STROBE checklist was used.

Result

For the systematic review, 18 articles were approved after assessing the full text of selected articles. In this review, 3614 patients with BC of selected articles were evaluated, and all radiogenomics were associated with more power in classification, differential diagnosis, and prognosis of BC. Among the various modalities to predict genomic indicators and molecular subtypes, DCE-MRI has the higher performance and finally the highest amount of AUC value (0.956) belonged to PI3K gene.

Conclusion

This review shows that radiogenomics can help with the diagnosis and treatment of breast cancer in patients. It has shown that recognizing and specifying radiogenomic phenotypes in the genomic signatures can be helpful in treatment and diagnosis of disease. The molecular methods used in these articles are limited to miRNAs expression, gene expression, Ki67 proliferation index, next-generation RNA sequencing, whole RNA sequencing, and molecular histopathology that can be completed in future studies by other methods such as exosomal miRNAs, specific proteins expression, DNA repair capacity, and other biomarkers that have prognostic and predictive value for cancer treatment response. Studies with control group and large sample size for evaluation of radiogenomics in diagnosis and treatment recommended.