Abstract:Breast cancer is the most commonly diagnosed cancer type worldwide. Overexpression of human epidermal growth factor receptor 2 (HER2) is an important subtype of breast cancer and results in an increased risk of recurrence and metastasis in patients. At present, immunohistochemistry (IHC) is used to detect the expression of HER2 in breast cancer tissues as the golden standard. However, IHC has some shortcomings, such as large subjective impact, long time consumption, expensive reagents, etc. In this paper, a co… Show more
“… Fig. 5 (A) Schematic of immunohistochemistry analysis of HER2 combined spectroscopic and morphological diagnostic method based on label-free surface-enhanced Raman scattering (SERS) [ 163 ]. Copyright 2023 American Chemical Society .…”
Section: Biomarkers and Strategiesmentioning
confidence: 99%
“…Mo and coworkers developed a strategy for the recognition of HER2 expression in breast cancer tissues using a combined morphological and spectroscopic method via label-free SERS ( Fig. 5 a) [ 163 ]. The approach presented in the study enables not only quantitative detection of HER2 expression but also provides information on the spatial distribution of HER2 in breast tissue.…”
“… Fig. 5 (A) Schematic of immunohistochemistry analysis of HER2 combined spectroscopic and morphological diagnostic method based on label-free surface-enhanced Raman scattering (SERS) [ 163 ]. Copyright 2023 American Chemical Society .…”
Section: Biomarkers and Strategiesmentioning
confidence: 99%
“…Mo and coworkers developed a strategy for the recognition of HER2 expression in breast cancer tissues using a combined morphological and spectroscopic method via label-free SERS ( Fig. 5 a) [ 163 ]. The approach presented in the study enables not only quantitative detection of HER2 expression but also provides information on the spatial distribution of HER2 in breast tissue.…”
“…Indeed, the binding event ampli es the HER2 Raman signal, making easily detectable even the smallest amounts. This combination of selectivity, sensitivity, and molecular speci city renders SERS a breakthrough technique for the detection and quanti cation of membrane biomarkers, particularly HER2 in BC [23,24]. Therefore, while Arti cial Intelligence (AI)-assisted Raman spectroscopy can provide an e cient cell discrimination and identify the speci c metabolic signature of cancer cells, SERS analysis can provide a detailed visualization of the distribution of biomarkers on the cell surface.…”
Section: Introductionmentioning
confidence: 99%
“…The information obtained by Raman spectroscopy and SERS complements each other and enables a synergistic enrichment of the clinical relevance of the collected data. Nonetheless, despite the numerous works carried out, either on classi cation of BC cell lines using Raman spectroscopy [17,18,[25][26][27] or HER2 detection using SERS strategies [24,28], a combined SERS-Raman approach for BC cells analysis and HER2 expression assessment has not been investigated so far.…”
Background
Breast cancer (BC) is a heterogeneous neoplasm characterized by several subtypes. One of the most aggressive with high metastasis rates presents overexpression of the human epidermal growth factor receptor 2 (HER2). A quantitative evaluation of HER2 levels is essential for a correct diagnosis, selection of the most appropriate therapeutic strategy and monitoring the response to therapy.
Results
In this paper, we propose the synergistic use of SERS and Raman technologies for the identification of HER2 expressing cells and its accurate assessment. To this end, we selected SKBR3 and MDA-MB-468 breast cancer cell lines, which have the highest and lowest HER2 expression, respectively, and MCF10A, a non-tumorigenic cell line from normal breast epithelium for comparison.
The combined approach provides a quantitative estimate of HER2 expression and visualization of its distribution on the membrane at single cell level, clearly identifying cancer cells. Moreover, it provides a more comprehensive picture of the investigated cells disclosing a metabolic signature represented by an elevated content of proteins and aromatic amino acids.
We further support these data by silencing the HER2 gene in SKBR3 cells, using the RNA interference technology, generating stable clones further analyzed with the same combined methodology. Significant changes in HER2 expression are detected at single cell level before and after HER2 silencing and the HER2 status correlates with variations of fatty acids and downstream signalling molecule contents in the context of the general metabolic rewiring occurring in cancer cells. Specifically, HER2 silencing does reduce the growth ability but not the lipid metabolism that, instead, increases, suggesting that higher fatty acids biosynthesis and metabolism can occur independently of the proliferating potential tied to HER2 overexpression.
Conclusions
Our results clearly demonstrate the efficacy of the combined SERS and Raman approach to definitely pose a correct diagnosis, further supported by the data obtained by the HER2 gene silencing. Furthermore, they pave the way to a new approach to monitor the efficacy of pharmacologic treatments with the aim to tailor personalized therapies and optimize patients’ outcome.
“…Indeed, the binding event amplifies the HER2 Raman signal, making it easily detectable even in the smallest amounts. This combination of selectivity, sensitivity, and molecular specificity renders SERS a breakthrough technique for the detection and quantification of membrane biomarkers, particularly HER2 in BC [ 25 , 26 ].…”
Background
Breast cancer (BC) is a heterogeneous neoplasm characterized by several subtypes. One of the most aggressive with high metastasis rates presents overexpression of the human epidermal growth factor receptor 2 (HER2). A quantitative evaluation of HER2 levels is essential for a correct diagnosis, selection of the most appropriate therapeutic strategy and monitoring the response to therapy.
Results
In this paper, we propose the synergistic use of SERS and Raman technologies for the identification of HER2 expressing cells and its accurate assessment. To this end, we selected SKBR3 and MDA-MB-468 breast cancer cell lines, which have the highest and lowest HER2 expression, respectively, and MCF10A, a non-tumorigenic cell line from normal breast epithelium for comparison. The combined approach provides a quantitative estimate of HER2 expression and visualization of its distribution on the membrane at single cell level, clearly identifying cancer cells. Moreover, it provides a more comprehensive picture of the investigated cells disclosing a metabolic signature represented by an elevated content of proteins and aromatic amino acids. We further support these data by silencing the HER2 gene in SKBR3 cells, using the RNA interference technology, generating stable clones further analysed with the same combined methodology. Significant changes in HER2 expression are detected at single cell level before and after HER2 silencing and the HER2 status correlates with variations of fatty acids and downstream signalling molecule contents in the context of the general metabolic rewiring occurring in cancer cells. Specifically, HER2 silencing does reduce the growth ability but not the lipid metabolism that, instead, increases, suggesting that higher fatty acids biosynthesis and metabolism can occur independently of the proliferating potential tied to HER2 overexpression.
Conclusions
Our results clearly demonstrate the efficacy of the combined SERS and Raman approach to definitely pose a correct diagnosis, further supported by the data obtained by the HER2 gene silencing. Furthermore, they pave the way to a new approach to monitor the efficacy of pharmacologic treatments with the aim to tailor personalized therapies and optimize patients’ outcome.
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