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Kashi M, Parastar H. Self-organizing maps for exploration and classification of nuclear magnetic resonance spectra for untargeted metabolomics of breast cancer. J Pharm Biomed Anal 2024; 249:116377. [PMID: 39047464 DOI: 10.1016/j.jpba.2024.116377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/19/2024] [Accepted: 07/20/2024] [Indexed: 07/27/2024]
Abstract
Metabolomics has emerged as a powerful tool for identifying biomarkers of disease, and nuclear magnetic resonance (NMR) spectroscopy allows for the simultaneous detection of a wide range of metabolites. However, due to complex interactions within metabolic networks, metabolites often exhibit high correlation and collinearity. To address this challenge, self-organizing maps (SOMs) of Kohonen maps and counter propagation-artificial neural networks (CP-ANN) were employed in this study to model proton nuclear magnetic resonance spectroscopic (1HNMR) data from control samples and breast cancer (BC) patients. Blood serum samples from a control group (n=24) and BC patients (n=18) were used to extract metabolites using methanol and chloroform solvents in optimum extraction conditions. The 1HNMR data was preprocessed by performing phase, baseline, and shift corrections. Subsequently, the preprocessed data was modeled using Kohonen network as an unsupervised technique and CP-ANN as a supervised technique. In this regard, the model built with CP-ANN successfully distinguished between the two classes with an accuracy of 100 % for both group and sensitivity of 96 % and 100 % for control group and BC patients, respectively. Additionally, CP-ANN algorithm demonstrated predictive capabilities by accurately classifying test samples with 90 % sensitivity, 98 % specificity, and 96 % accuracy for control group and 100 % sensitivity, 90 % specificity, and 96 % accuracy for BC patients. Furthermore, analysis of the resulting topological map revealed 14 significant variables (biomarkers) such as sarcosine, lysine, trehalose, tryptophan, and betaine that effectively differentiated between healthy individuals and BC patients.
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Affiliation(s)
- Maryam Kashi
- Department of Chemistry, Sharif University of Technology, P.O. Box 11155-9516, Tehran, Iran
| | - Hadi Parastar
- Department of Chemistry, Sharif University of Technology, P.O. Box 11155-9516, Tehran, Iran.
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2
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Yamada M, Jinno H, Naruse S, Isono Y, Maeda Y, Sato A, Matsumoto A, Ikeda T, Sugimoto M. Predictive analysis of breast cancer response to neoadjuvant chemotherapy through plasma metabolomics. Breast Cancer Res Treat 2024; 207:393-404. [PMID: 38740665 DOI: 10.1007/s10549-024-07370-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/25/2024] [Indexed: 05/16/2024]
Abstract
PURPOSE Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to neoadjuvant chemotherapy in breast cancer patients utilizing a metabolomic approach. METHODS Plasma samples were obtained from 87 breast cancer patients undergoing neoadjuvant chemotherapy at our facility, collected both before the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles. RESULTS Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second neoadjuvant chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points. CONCLUSION The application of plasma metabolomics, utilizing CE-MS and LC-MS, may serve as a tool for predicting the efficacy of neoadjuvant chemotherapy in breast cancer in the future after all necessary validations have been completed.
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Affiliation(s)
- Miki Yamada
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Hiromitsu Jinno
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan.
| | - Saki Naruse
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Yuka Isono
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Yuka Maeda
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Ayana Sato
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Akiko Matsumoto
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Tatsuhiko Ikeda
- Department of Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi, Tokyo, 173-8606, Japan
| | - Masahiro Sugimoto
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata, 997-0052, Japan
- Institute of Medical Science, Tokyo Medical University, Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan
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3
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Arredondo Eve A, Tunc E, Mehta D, Yoo JY, Yilmaz HE, Emren SV, Akçay FA, Madak Erdogan Z. PFAS and their association with the increased risk of cardiovascular disease in postmenopausal women. Toxicol Sci 2024; 200:312-323. [PMID: 38758093 DOI: 10.1093/toxsci/kfae065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024] Open
Abstract
Cardiovascular diseases (CVDs) are one of the major causes of death globally. In addition to traditional risk factors such as unhealthy lifestyles (smoking, obesity, sedentary) and genetics, common environmental exposures, including persistent environmental contaminants, may also influence CVD risk. Per- and polyfluoroalkyl substances (PFASs) are a class of highly fluorinated chemicals used in household consumer and industrial products known to persist in our environment for years, causing health concerns that are now linked to endocrine disruptions and related outcomes in women, including interference of the cardiovascular and reproductive systems. In postmenopausal women, higher levels of PFAS are observed than in premenopausal women due to the cessation of menstruation, which is crucial for PFAS excretion. Because of these findings, we explored the association between perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorobutanesulfonic acid in postmenopausal women from our previously established CVD study. We used liquid chromatography with tandem mass spectrometry, supported by machine learning approaches, and the detection and quantification of serum metabolites and proteins. Here, we show that PFOS can be a good predictor of coronary artery disease, whereas PFOA can be an intermediate predictor of coronary microvascular disease. We also found that the PFAS levels in our study are significantly associated with inflammation-related proteins. Our findings may provide new insight into the potential mechanisms underlying the PFAS-induced risk of CVDs in this population. This study shows that exposure to PFOA and PFOS is associated with an increased risk of cardiovascular disease in postmenopausal women. PFOS and PFOA levels correlate with amino acids and proteins related to inflammation. These circulating biomarkers contribute to the etiology of CVD and potentially implicate a mechanistic relationship between PFAS exposure and increased risk of cardiovascular events in this population.
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Affiliation(s)
- Alicia Arredondo Eve
- Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Elif Tunc
- Research and Training Hospital, Katip Celebi University, Izmir, 35310, Turkey
| | - Dhruv Mehta
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Jin Young Yoo
- Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Huriye Erbak Yilmaz
- Research and Training Hospital, Katip Celebi University, Izmir, 35310, Turkey
- Izmir Biomedicine and Genome Center, Balcova, Izmir, 35340, Turkey
| | - Sadık Volkan Emren
- Research and Training Hospital, Katip Celebi University, Izmir, 35310, Turkey
| | | | - Zeynep Madak Erdogan
- Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
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4
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Neagu AN, Bruno P, Johnson KR, Ballestas G, Darie CC. Biological Basis of Breast Cancer-Related Disparities in Precision Oncology Era. Int J Mol Sci 2024; 25:4113. [PMID: 38612922 PMCID: PMC11012526 DOI: 10.3390/ijms25074113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 04/14/2024] Open
Abstract
Precision oncology is based on deep knowledge of the molecular profile of tumors, allowing for more accurate and personalized therapy for specific groups of patients who are different in disease susceptibility as well as treatment response. Thus, onco-breastomics is able to discover novel biomarkers that have been found to have racial and ethnic differences, among other types of disparities such as chronological or biological age-, sex/gender- or environmental-related ones. Usually, evidence suggests that breast cancer (BC) disparities are due to ethnicity, aging rate, socioeconomic position, environmental or chemical exposures, psycho-social stressors, comorbidities, Western lifestyle, poverty and rurality, or organizational and health care system factors or access. The aim of this review was to deepen the understanding of BC-related disparities, mainly from a biomedical perspective, which includes genomic-based differences, disparities in breast tumor biology and developmental biology, differences in breast tumors' immune and metabolic landscapes, ecological factors involved in these disparities as well as microbiomics- and metagenomics-based disparities in BC. We can conclude that onco-breastomics, in principle, based on genomics, proteomics, epigenomics, hormonomics, metabolomics and exposomics data, is able to characterize the multiple biological processes and molecular pathways involved in BC disparities, clarifying the differences in incidence, mortality and treatment response for different groups of BC patients.
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Affiliation(s)
- Anca-Narcisa Neagu
- Laboratory of Animal Histology, Faculty of Biology, "Alexandru Ioan Cuza" University of Iași, Carol I bvd. 20A, 700505 Iasi, Romania
| | - Pathea Bruno
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biochemistry, Clarkson University, Potsdam, NY 13699-5810, USA
| | - Kaya R Johnson
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biochemistry, Clarkson University, Potsdam, NY 13699-5810, USA
| | - Gabriella Ballestas
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biochemistry, Clarkson University, Potsdam, NY 13699-5810, USA
| | - Costel C Darie
- Biochemistry & Proteomics Laboratories, Department of Chemistry and Biochemistry, Clarkson University, Potsdam, NY 13699-5810, USA
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Heath H, Mogol AN, Santaliz Casiano A, Zuo Q, Madak-Erdogan Z. Targeting systemic and gut microbial metabolism in ER + breast cancer. Trends Endocrinol Metab 2024; 35:321-330. [PMID: 38220576 DOI: 10.1016/j.tem.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/18/2023] [Accepted: 12/20/2023] [Indexed: 01/16/2024]
Abstract
Estrogen receptor-positive (ER+) breast tumors have a better overall prognosis than ER- tumors; however, there is a sustained risk of recurrence. Mounting evidence indicates that genetic and epigenetic changes associated with resistance impact critical signaling pathways governing cell metabolism. This review delves into recent literature concerning the metabolic pathways regulated in ER+ breast tumors by the availability of nutrients and endocrine therapies and summarizes research on how changes in systemic and gut microbial metabolism can affect ER activity and responsiveness to endocrine therapy. As targeting of metabolic pathways using dietary or pharmacological approaches enters the clinic, we provide an overview of the supporting literature and suggest future directions.
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Affiliation(s)
- Hannah Heath
- Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Ayca Nazli Mogol
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | | | - Qianying Zuo
- Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Zeynep Madak-Erdogan
- Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, IL, USA; Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA; Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
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Schaduangrat N, Homdee N, Shoombuatong W. StackER: a novel SMILES-based stacked approach for the accelerated and efficient discovery of ERα and ERβ antagonists. Sci Rep 2023; 13:22994. [PMID: 38151513 PMCID: PMC10752908 DOI: 10.1038/s41598-023-50393-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 12/29/2023] Open
Abstract
The role of estrogen receptors (ERs) in breast cancer is of great importance in both clinical practice and scientific exploration. However, around 15-30% of those affected do not see benefits from the usual treatments owing to the innate resistance mechanisms, while 30-40% will gain resistance through treatments. In order to address this problem and facilitate community-wide efforts, machine learning (ML)-based approaches are considered one of the most cost-effective and large-scale identification methods. Herein, we propose a new SMILES-based stacked approach, termed StackER, for the accelerated and efficient identification of ERα and ERβ inhibitors. In StackER, we first established an up-to-date dataset consisting of 1,996 and 1,207 compounds for ERα and ERβ, respectively. Using the up-to-date dataset, StackER explored a wide range of different SMILES-based feature descriptors and ML algorithms in order to generate probabilistic features (PFs). Finally, the selected PFs derived from the two-step feature selection strategy were used for the development of an efficient stacked model. Both cross-validation and independent tests showed that StackER surpassed several conventional ML classifiers and the existing method in precisely predicting ERα and ERβ inhibitors. Remarkably, StackER achieved MCC values of 0.829-0.847 and 0.712-0.786 in terms of the cross-validation and independent tests, respectively, which were 5.92-8.29 and 1.59-3.45% higher than the existing method. In addition, StackER was applied to determine useful features for being ERα and ERβ inhibitors and identify FDA-approved drugs as potential ERα inhibitors in efforts to facilitate drug repurposing. This innovative stacked method is anticipated to facilitate community-wide efforts in efficiently narrowing down ER inhibitor screening.
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Affiliation(s)
- Nalini Schaduangrat
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand
| | - Nutta Homdee
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand
| | - Watshara Shoombuatong
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand.
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Yue S, Feng X, Cai Y, Ibrahim SA, Liu Y, Huang W. Regulation of Tumor Apoptosis of Poriae cutis-Derived Lanostane Triterpenes by AKT/PI3K and MAPK Signaling Pathways In Vitro. Nutrients 2023; 15:4360. [PMID: 37892435 PMCID: PMC10610537 DOI: 10.3390/nu15204360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/07/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Poria cocos is traditionally used as both food and medicine. Triterpenoids in Poria cocos have a wide range of pharmacological activities, such as diuretic, sedative and tonic properties. In this study, the anti-tumor activities of poricoic acid A (PAA) and poricoic acid B (PAB), purified by high-speed counter-current chromatography, as well as their mechanisms and signaling pathways, were investigated using a HepG2 cell model. After treatment with PAA and PAB on HepG2 cells, the apoptosis was obviously increased (p < 0.05), and the cell cycle arrested in the G2/M phase. Studies showed that PAA and PAB can also inhibit the occurrence and development of tumor cells by stimulating the generation of ROS in tumor cells and inhibiting tumor migration and invasion. Combined Polymerase Chain Reaction and computer simulation of molecular docking were employed to explore the mechanism of tumor proliferation inhibition by PAA and PAB. By interfering with phosphatidylinositol-3-kinase/protein kinase B, Mitogen-activated protein kinases and p53 signaling pathways; and further affecting the expression of downstream caspases; matrix metalloproteinase family, cyclin-dependent kinase -cyclin, Intercellular adhesion molecules-1, Vascular Cell Adhesion Molecule-1 and Cyclooxygenase -2, may be responsible for their anti-tumor activity. Overall, the results suggested that PAA and PAB induced apoptosis, halted the cell cycle, and inhibited tumor migration and invasion through multi-pathway interactions, which may serve as a potential therapeutic agent against cancer.
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Affiliation(s)
- Shuai Yue
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China;
| | - Xi Feng
- Department of Nutrition, Food Science and Packaging, San Jose State University, San Jose, CA 95192, USA;
| | - Yousheng Cai
- School of Pharmaceutical Sciences, Wuhan University, Wuhan 430071, China;
| | - Salam A. Ibrahim
- Department of Family and Consumer Sciences, North Carolina A&T State University, 171 Carver Hall, Greensboro, NC 27411, USA;
| | - Ying Liu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China;
| | - Wen Huang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China;
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Bel’skaya LV, Gundyrev IA, Solomatin DV. The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review. Curr Issues Mol Biol 2023; 45:7513-7537. [PMID: 37754258 PMCID: PMC10527988 DOI: 10.3390/cimb45090474] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/28/2023] Open
Abstract
This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.
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Affiliation(s)
- Lyudmila V. Bel’skaya
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Ivan A. Gundyrev
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Denis V. Solomatin
- Department of Mathematics and Mathematics Teaching Methods, Omsk State Pedagogical University, 644043 Omsk, Russia;
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