Breast Cancer Metabolomics Using NMR

Metabolic Profiling of Breast Cancer Cell Lines: Unique and Shared Metabolites

Breast Cancer (BrCa) exhibits a high phenotypic heterogeneity, leading to the emergence of aggressive clones and the development of drug resistance. Considering the BrCa heterogeneity and that metabolic reprogramming is a cancer hallmark, we selected seven BrCa cell lines with diverse subtypes to provide their comprehensive metabolome characterization: five lines commonly used (SK-Br-3, T-47D, MCF-7, MDA-MB-436, and MDA-MB-231), and two patient-derived xenografts (Hbcx39 and Hbcx9). We characterized their endometabolomes using 1H-NMR spectroscopy. We found distinct metabolite profiles, with certain metabolites being common but differentially accumulated across the selected BrCa cell lines. High levels of glycine, lactate, glutamate, and formate, metabolites known to promote invasion and metastasis, were detected in all BrCa cells. In our experiment setting were identified unique metabolites to specific cell lines: xanthine and 2-oxoglutarate in SK-Br-3, 2-oxobutyrate in T-47D, cystathionine and glucose-1-phosphate in MCF-7, NAD+ in MDA-MB-436, isocitrate in MDA-MB-231, and NADP+ in Hbcx9. The unique and enriched metabolites enabled us to identify the metabolic pathways modulated in a cell-line-specific manner, which may represent potential candidate targets for therapeutic intervention. We believe this study may contribute to the functional characterization of BrCa cells and assist in selecting appropriate cell lines for drug-response studies.

1H-NMR-based urine metabolomics of prostate cancer and benign prostatic hyperplasia

Background

Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are prevalent conditions affecting a significant portion of the male population, particularly with advancing age. Traditional diagnostic methods, such as digital rectal examination (DRE) and prostate-specific antigen (PSA) tests, have limitations in specificity and sensitivity, leading to potential overdiagnosis and unnecessary biopsies.

Significance

This study explores the effectiveness of 1H NMR urine metabolomics in distinguishing PCa from BPH and in differentiating various PCa grades, presenting a non-invasive diagnostic alternative with the potential to enhance early detection and patient-specific treatment strategies.

Results

The study demonstrated the capability of 1H NMR urine metabolomics in detecting distinct metabolic profiles between PCa and BPH, as well as among different Gleason grade groups. Notably, this method surpassed the PSA test in distinguishing PCa from BPH. Untargeted metabolomics analysis also revealed several metabolites with varying relative concentrations between PCa and BPH cases, suggesting potential biomarkers for these conditions.

The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis

The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.

Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism

A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for illustrating physiological and molecular processes changes before anatomical manifestations on conventional MR imaging. Among these, in vivo proton (1H) MR spectroscopy (MRS) is widely used for differentiating breast malignancy from benign diseases by measuring elevated choline-containing compounds. Further, the use of hyperpolarized 13C and 31P MRS enhanced the understanding of glucose and phospholipid metabolism. The metabolic profiling of an array of biological specimens (intact tissues, tissue extracts, and various biofluids such as blood, urine, nipple aspirates, and fine needle aspirates) can also be investigated through in vitro high-resolution NMR spectroscopy and high-resolution magic angle spectroscopy (HRMAS). Such studies can provide information on more metabolites than what is seen by in vivo MRS, thus providing a deeper insight into cancer biology and metabolism. The analysis of a large number of NMR spectral data sets through multivariate statistical methods classified the tumor sub-types. It showed enormous potential in the development of new therapeutic approaches. Recently, multiparametric MRI approaches were found to be helpful in elucidating the pathophysiology of cancer by quantifying structural, vasculature, diffusion, perfusion, and metabolic abnormalities in vivo. This review focuses on the applications of NMR, MRS, and MRI methods in understanding breast cancer biology and in the diagnosis and therapeutic monitoring of breast cancer.

MR spectroscopy in breast cancer metabolomics

Breast cancer poses a significant health care challenge worldwide requiring early detection and effective treatment strategies for better patient outcome. A deeper understanding of the breast cancer biology and metabolism may help developing better diagnostic and therapeutic approaches. Metabolomic studies give a comprehensive analysis of small molecule metabolites present in human tissues in vivo. The changes in the level of these metabolites provide information on the complex mechanism of the development of the disease and its progression. Metabolomic approach using analytical techniques such as magnetic resonance spectroscopy (MRS) has evolved as an important tool for identifying clinically relevant metabolic biomarkers. The metabolic characterization of breast lesions using in-vivo MRS has shown that malignant breast tissues contain elevated levels of choline containing compounds (tCho), suggesting rapid proliferation of cancer cells and alterations in membrane metabolism. Also, tCho has been identified as one of the important biomarkers that help to enhance the diagnostic accuracy of dynamic contrast enhanced magnetic resonance imaging and also for monitoring treatment response. Further, metabolome of malignant tissues can be studied using ex vivo and in vitro MRS at high magnetic fields. This provided the advantage of detection of a large number of compounds that facilitated more comprehensive insight into the altered metabolic pathways associated with the cancer development and progression and also in identification of several metabolites as potential biomarkers. This article briefly reviews the role of MRS based metabolic profiling in the discovery of biomarkers and understanding of the altered metabolism in breast cancer.

Is Elevated Choline on Magnetic Resonance Spectroscopy a Reliable Marker of Breast Lesion Malignancy?

Background

Contemporary magnetic resonance imaging (MRI) of the breast represents a powerful diagnostic modality for cancer detection, with excellent sensitivity and high specificity. Magnetic resonance spectroscopy (MRS) is being explored as an additional tool for improving specificity in breast cancer detection, using multiparametric MRI. The aim of this study was to examine the possibility of 1H-MRS to discriminate malignant from benign breast lesions, using elevated choline (Cho) peak as an imaging biomarker.

Methods

A total of 60 patients were included in this prospective study: 30 with malignant (average age, 55.2 years; average lesion size, 35 mm) and 30 with benign breast lesions (average age, 44.8 years; average lesion size, 20 mm), who underwent multiparametric MRI with multivoxel 3D ¹H-MRS on a 1.5-T scanner in a 3-year period. Three patients with benign breast lesions were excluded from the study. All lesions were histologically verified. Peaks identified on ¹H-MRS were lipid (0.9, 2.3, 2.8, and 5.2 ppm), choline (3.2 ppm), and water peaks (4.7 ppm). Sensitivity and specificity, as well as positive and negative predictive values, were defined using ROC curves. Cohen's Kappa test of inter-test reliability was performed [testing the agreement between ¹H-MRS and histologic finding, and ¹H-MRS and MR mammography (MRM)].

Results

Choline peak was elevated in 24/30 malignant lesions and in 20/27 benign breast lesions. The sensitivity of ¹H-MRS was 0.8, specificity was 0.741, positive predictive value was 0.774, and negative predictive value was 0.769. Area under ROC was 0.77 (CI 0.640-0.871). Inter-test reliability between ¹H-MRS and histologic finding was 0.543 (moderate agreement) and that between ¹H-MRS and MRM was 0.573 (moderate agreement). False-negative findings were most frequently observed in invasive lobular cancers, while false-positive findings were most frequently observed in adenoid fibroadenomas.

Conclusion

Although elevation of the choline peak has a good sensitivity and specificity in breast cancer detection, both are significantly lower than those of multiparametric MRM. Inclusion of spectra located on tumor margins as well as analysis of lipid peaks could aid both sensitivity and specificity. An important ratio of false-positive and false-negative findings in specific types of breast lesions (lobular cancer and adenoid fibroadenoma) suggests interpreting these lesions with a caveat.

Abnormalities in metabolic pathways in celiac disease investigated by the metabolic profiling of small intestinal mucosa, blood plasma and urine by NMR spectroscopy

Celiac disease (CeD) is an autoimmune enteropathy caused by gluten intake in genetically predisposed individuals. We investigated the metabolism of CeD by metabolic profiling of intestinal mucosa, blood plasma and urine using NMR spectroscopy and multivariate analysis. The metabolic profile of the small intestinal mucosa was compared between patients with CeD (n = 64) and disease controls (DCs, n = 30). The blood plasma and urinary metabolomes of CeD patients were compared with healthy controls (HCs, n = 39). Twelve metabolites (proline (Pro), arginine (Arg), glycine (Gly), histidine (His), glutamate (Glu), aspartate, tryptophan (Trp), fumarate, formate, succinate (Succ), glycerophosphocholine (GPC) and allantoin (Alln)) of intestinal mucosa differentiated CeD from controls. The metabolome of blood plasma with 18 metabolites (Pro, Arg, Gly, alanine, Glu, glutamine, glucose (Glc), lactate (Lac), acetate (Ace), acetoacetate (AcAc), β-hydroxybutyrate (β-OHB), pyruvate (Pyr), Succ, citrate (Cit), choline (Cho), creatine (Cr), phosphocreatine (PCr) and creatinine) and 9 metabolites of urine (Pro, Trp, β-OHB, Pyr, Succ, N-methylnicotinamide (NMN), aminohippurate (AHA), indoxyl sulfate (IS) and Alln) distinguished CeD from HCs. Our data demonstrated changes in nine metabolic pathways. The altered metabolites were associated with increased oxidative stress (Alln), impaired healing and repair mechanisms (Pro, Arg), compromised anti-inflammatory and cytoprotective processes (Gly, His, NMN), altered energy metabolism (Glc, Lac, β-OHB, Ace, AcAc, Pyr, Succ, Cit, Cho, Cr and PCr), impaired membrane metabolism (GPC and Cho) and intestinal dysbiosis (AHA and IS). An orthogonal partial least square discriminant analysis model provided clear differentiation between patients with CeD and controls in all three specimens. A classification model built by combining the distinguishing metabolites of blood plasma and urine samples gave an AUC of 0.99 with 97.7% sensitivity, 93.3% specificity and a predictive accuracy of 95.1%, which was higher than for the models built separately using small intestinal mucosa, blood plasma and urine. In conclusion, a panel of metabolic biomarkers in intestinal biopsies, plasma and urine samples has potential to differentiate CeD from controls and may complement traditional tests to improve the diagnosis of CeD.

Novel Antiproliferative Biphenyl Nicotinamide: NMR Metabolomic Study of its Effect on the MCF-7 Cell in Comparison with Cisplatin and Vinblastine

A 1H-NMR-based metabolomic study was performed on MCF-7 cell lines treated with a novel nicotinamide derivative (DT-8) in comparison with two drugs characterized by a well-established mechanism of action, namely the DNA-metalating drug cisplatin (cis-diamminedichloridoplatinum(II), CDDP) and the antimitotic drug vinblastine (vinblastine, VIN). The effects of the three compounds, each one at the concentration corresponding to the IC50 value, were investigated, with respect to the controls (K), by the 1H-NMR of cells lysates and multivariate analysis (MVA) of the spectroscopic data. Relevant differences were found in the metabolic profiles of the different treatments with respect to the controls. A large overlap of the metabolic profiles in DT-8 vs. K and VIN vs. K suggests a similar biological response and mechanism of action, significantly diverse with respect to CDDP. On the other hand, DT8 seems to act by disorganizing the mitotic spindle and ultimately blocking the cell division, through a mechanism implying methionine depletion and/or S-adenosylmethionine (SAM) limitation.