Who’s Who? Discrimination of Human Breast Cancer Cell Lines by Raman and FTIR Microspectroscopy

Santos, Inês P.; Martins, Clara B.; Carvalho, Luís A. E. Batista de; Marques, M. P. M.; Carvalho, Ana L. M. Batista de

doi:10.3390/cancers14020452

Cited by 15 publications

(14 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As expected, the LA and LB samples have similar spectral profiles, suggesting similar constitution, as they have similar gene expression and biochemical constituents, with higher intensities in virtually all peaks compared to the normal tissue spectrum, but increased peaks of lipids, whereas the TN samples have higher intensities in peaks found approximately at 1100, 1300, and 1440 cm −1 , assigned to proteins (collagen). These results are consistent with the literature of Raman spectroscopy in evaluating molecular subtypes of breast cancer 38–44 . Bi et al 38 differentiated breast cancer cells HER2‐enriched and HER2 nonenriched, obtaining a sensitivity and specificity of 99%, respectively, and showed that HER2‐enriched cells had a higher lipid content due to exacerbated fatty acid and phospholipid synthesis.…”

Section: Discussionsupporting

confidence: 90%

“…These results are consistent with the literature of Raman spectroscopy in evaluating molecular subtypes of breast cancer. [38][39][40][41][42][43][44] Bi et al 38 differentiated breast cancer cells HER2enriched and HER2 nonenriched, obtaining a sensitivity and specificity of 99%, respectively, and showed that HER2-enriched cells had a higher lipid content due to exacerbated fatty acid and phospholipid synthesis. Bendau et al 39 differentiated the collagen molecular characteristics between TN metastatic tumors and nonmetastatic tumors that are ER-positive.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, breast cancer cells showed higher levels of collagen and lipids (peak at 1333 and 1304 cm −1 , respectively). Santos et al 44 applied Raman microspectroscopy and FTIR (Fourier transform infrared) and after analyzing the principal component of the data, they were able to discriminate between TN and non‐TN breast cancer, as well as TNBCMSL (cell‐like mesenchymal trunk) and highly metastatic and little metastatic TNBC BL1 (basal‐like 1) and TNBC BL1 cell lines. A PCA analysis allowed to discriminate between TNBC (MDA‐MB‐231, HCC‐1143 and MDA‐MB‐468) compared to non‐TNBC cell lines (MCF‐7).…”

Section: Discussionmentioning

confidence: 99%

“…Raman spectroscopy is also suitable to unveil the compositional differences between molecular subtypes. Differences in the amount of lipids and proteins, as well as in the amount of nucleic acids, may be able to identify the molecular subtypes as reported in several studies 38–44 …”

Section: Introductionmentioning

confidence: 93%

“…Differences in the amount of lipids and proteins, as well as in the amount of nucleic acids, may be able to identify the molecular subtypes as reported in several studies. [38][39][40][41][42][43][44] The aim of this study was to evaluate the compositonal differences between the molecular subtypes of carcinoma (LA, LB, HER2, and TN) in ex vivo breast tissues versus normal tissues (NT) by means of dispersive Raman spectroscopy compared to anatomopathological (gold standard) and molecular evaluations through IHC, FISH, and other molecular methods. Then, exploratory analysis by means of PCA was used to unveil the spectral differences between the molecular subtypes to correlate these differences with the biochemical components and morphological structures responsible for these cellular alterations.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Diagnosing molecular subtypes of breast cancer by means of Raman spectroscopy

et al. 2022

View full text Add to dashboard Cite

Objectives Raman spectroscopy has been used to discriminate human breast cancer and its different tumor molecular subtypes (luminal A, luminal B, HER2, and triple‐negative) from normal tissue in surgical specimens. Materials and Methods Breast cancer and normal tissue samples from 31 patients were obtained by surgical resection and submitted for histopathology. Before anatomopathological processing, the samples had been submitted to Raman spectroscopy (830 nm, 25 mW excitation laser parameters). In total, 424 Raman spectra were obtained. Principal component analysis (PCA) was used in an exploratory analysis to unveil the compositional differences between the tumors and normal tissues. Discriminant models were developed to distinguish the different cancer subtypes by means of partial least squares (PLS) regression. Results PCA vectors showed spectral features referred to the biochemical constitution of breast tissues, such as lipids, proteins, amino acids, and carotenoids, where lipids were decreased and proteins were increased in breast tumors. Despite the small spectral differences between the different subtypes of tumor and normal tissues, the discriminant model based on PLS was able to discriminate the spectra of the breast tumors from normal tissues with an accuracy of 97.3%, between luminal and nonluminal subtypes with an accuracy of 89.9%, between nontriple‐negative and triple‐negative with an accuracy of 94.7%, and each molecular subtype with an accuracy of 73.0%. Conclusion PCA could reveal the compositional difference between tumors and normal tissues, and PLS could discriminate the Raman spectra of breast tissues regarding the molecular subtypes of cancer, being a useful tool for cancer diagnosis.

show abstract

Section: Discussionsupporting

confidence: 90%