Discrimination of breast cancer from benign tumours using Raman spectroscopy

PLoS One. 2019 Feb 14;14(2):e0212376. doi: 10.1371/journal.pone.0212376. eCollection 2019.

Abstract

Breast cancer is the most common cancer among women worldwide, with an estimated 1.7 million cases and 522,000 deaths in 2012. Breast cancer is diagnosed by histopathological examination of breast biopsy material but this is subjective and relies on morphological changes in the tissue. Raman spectroscopy uses incident radiation to induce vibrations in the molecules of a sample and the scattered radiation can be used to characterise the sample. This technique is rapid and non-destructive and is sensitive to subtle biochemical changes occurring at the molecular level. This allows spectral variations corresponding to disease onset to be detected. The aim of this work was to use Raman spectroscopy to discriminate between benign lesions (fibrocystic, fibroadenoma, intraductal papilloma) and cancer (invasive ductal carcinoma and lobular carcinoma) using formalin fixed paraffin preserved (FFPP) tissue. Haematoxylin and Eosin stained sections from the patient biopsies were marked by a pathologist. Raman maps were recorded from parallel unstained tissue sections. Immunohistochemical staining for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2/neu) was performed on a further set of parallel sections. Both benign and cancer cases were positive for ER while only the cancer cases were positive for HER2. Significant spectral differences were observed between the benign and cancer cases and the benign cases could be differentiated from the cancer cases with good sensitivity and specificity. This study has shown the potential of Raman spectroscopy as an aid to histopathological diagnosis of breast cancer, in particular in the discrimination between benign and malignant tumours.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast / metabolism
  • Breast / pathology*
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / metabolism
  • Breast Neoplasms / pathology*
  • Discriminant Analysis
  • Female
  • Humans
  • Hyperplasia
  • Principal Component Analysis
  • Receptor, ErbB-2 / metabolism
  • Receptors, Estrogen / metabolism
  • Sensitivity and Specificity
  • Spectrum Analysis, Raman / methods*
  • Support Vector Machine

Substances

  • Receptors, Estrogen
  • ERBB2 protein, human
  • Receptor, ErbB-2

Grants and funding

This article was made possible by a NPRP Award [7 - 1267 - 3 – 328] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.