Progress in the clinical detection of heterogeneity in breast cancer

Abstract

Breast cancer is currently the most common form of cancer and the second‐leading cause of death from cancer in women. Though considerable progress has been made in the treatment of breast cancer, the heterogeneity of tumors (both inter‐ and intratumor) remains a considerable diagnostic and prognostic challenge. From clinical observation to genetic mutations, the history of understanding the heterogeneity of breast cancer is lengthy and detailed. Effectively detecting heterogeneity in breast cancer is important during treatment. Various methods of depicting this heterogeneity are now available and include genetic, pathologic, and imaging analysis. These methods allow characterization of the heterogeneity of breast cancer on a genetic level, providing greater insight during the process of establishing an effective therapeutic plan. This study reviews how the understanding of tumor heterogeneity in breast cancer evolved, and further summarizes recent advances in the detection and monitoring of this heterogeneity in patients with breast cancer.

Support vector machine for breast cancer classification using diffusion‐weighted MRI histogram features: Preliminary study

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Overexpression of SYF2 promotes cell proliferation and correlates with poor prognosis in human breast cancer

“…Despite advances in various methods, including genetic, pathologic, and imaging analysis, effective detection and appropriate therapy in breast cancer remains a considerable challenge. In terms of genomic analysis, new techniques’ application and genomic data mining help to develop new targets for therapy and represent the primary future directions of breast cancer treatment [ 17 ]. Further research is needed to understand the molecular basis of BC as to advance in precise diagnosis and effective treatment modalities.…”

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