Quantitative distribution of essential elements and non-essential metals in breast cancer tissues by LA-ICP-TOF-MS

Abstract

Breast cancer (BC) is the leading cause of cancer death among women worldwide, making the discovery and quantification of new biomarkers essential for improving diagnostic and preventive strategies to limit dissemination and improve prognosis. Essential trace metals such as Fe, Cu, and Zn may play critical roles in the pathophysiology of both benign and malignant breast tumors. However, due to the high metabolic activity and reduced element selectivity of cancer cells, also non-essential elements may be taken up and may even be implicated with disease progression. This study investigates the spatial distribution and concentrations of both essential and non-essential elements in breast tissues, assessing their potential for diagnostic applications. Laser ablation (LA)-inductively coupled plasma-mass spectrometry (ICP-MS) with a time-of-flight (ToF) mass analyzer (LA-ICP-ToF-MS) was used to inquire the distribution of almost all elements across the periodic table and their abundance in metastatic (n = 11), non-metastatic (n = 7), and healthy (n = 4) breast tissues. Quantification was achieved using gelatine-based standards for external calibration to quantitatively map various elements. Overall, the Fe, Cu, Zn, Sr, and Ba levels were significantly increased in tumor samples with Sr and Ba showing strong correlation, likely due to their similar chemistry. Comparison of calibrated LA-ICP-ToF-MS data with a histologic staining demonstrated the possibility to clearly differentiate between various tissue types and structures in breast tissues such as tumor niche and stroma. The levels of the studied elements were significantly higher in the tumor niche areas compared to the stroma, and for Fe, a significant accumulation was observed in the tumor niche areas from the metastatic patient group relative to the levels found in the same areas of the non-metastatic group.

Keywords: Elemental bioimaging; Elemental quantification; Hyphenated techniques; LA-ICP-MS; Time of flight.

Fig. 1

Graphic representation of k-means clustering for background and irrelevant tissue removal on a non-metastatic sample. A Laser camera image of the analyzed sample with a magnification of the adipose tissue zone. B Quantitative biodistribution of ⁸⁸Sr and histogram. C Quantitative biodistribution of ⁸⁸Sr and histogram after k-means background removal. White arrows 1, 2, and 3 refer to epithelial tissue, glass slide, and adipose tissue, respectively

Fig. 2

A Quantitative distribution for Fe, Cu, Zn, and Sr in the different sample groups. B Box chart of the elemental concentrations found in healthy, non-metastatic, and metastatic tissues. Box charts: * represents statistical significance $(p\le 0.05)$ in Mann–Whitney U test

Fig. 3

A Qualitative elemental distribution (cps) of Sr and Ba in the studied groups (healthy, non-metastatic, metastatic). B Box plots representing the Ba/Sr ratio for each studied group. The Ba signal was normalized using the Sr signal from a gelatine standard of 1.31 µg g^-1. Box plots:* represents statistical significance (p ≤ 0.05) in a Mann–Whitney U test

Fig. 4

Comparison of the tumor niche and stroma distributions in the different sample groups. A Tumor niche and stroma as observed in H&E staining, along with quantitative elemental distributions of Fe, Cu, Zn, and Sr and qualitative distribution of Ba. B Concentration results comparing Fe, Cu, Zn, Sr, and Ba (the latter normalized using a Sr standard) across the different sample groups. Black arrows in the H&E image represent the stroma and red arrows the tumor niche. Box plots: * represents statistical significance (p ≤ 0.05) in a Mann–Whitney U test