Next Article in Journal
Applications of Melanin and Melanin-Like Nanoparticles in Cancer Therapy: A Review of Recent Advances
Next Article in Special Issue
Somatic Mutation Profiling in the Liquid Biopsy and Clinical Analysis of Hereditary and Familial Pancreatic Cancer Cases Reveals KRAS Negativity and a Longer Overall Survival
Previous Article in Journal
Three-Dimensional Radiological Assessment of Ablative Margins in Hepatocellular Carcinoma: Pilot Study of Overlay Fused CT/MRI Imaging with Automatic Registration
Previous Article in Special Issue
Serum Exosomes and Their miRNA Load—A Potential Biomarker of Lung Cancer
Open AccessArticle

Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds

1
Department of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA
2
Integrated Nanosystems Development Institute, Indiana University-Purdue University, Indianapolis, IN 46202, USA
3
Department of Biomedical Engineering, Indiana University-Purdue University, Indianapolis, IN 46202, USA
4
Hematology and Oncology, Ball Memorial Hospital, Indiana University Health, Muncie, IN 47303, USA
5
Biomechanics and Biomaterials Research Center, Indiana University-Purdue University, Indianapolis, IN 46202, USA
6
Department of Mechanical & Energy Engineering, Indiana University-Purdue University, Indianapolis, IN 46202, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Fabrizio Bianchi
Cancers 2021, 13(6), 1462; https://doi.org/10.3390/cancers13061462
Received: 3 February 2021 / Revised: 15 March 2021 / Accepted: 17 March 2021 / Published: 23 March 2021
(This article belongs to the Special Issue Cancer Biomarkers in Body Fluids)
Volatile organic compounds (VOCs) in urine have been shown to be potential biomarkers for breast cancer. However, how urinary VOCs change upon the course of tumor progression has never been studied. The aim of our study was to identify changes in VOC profiles corresponding to mammary tumor (triple negative cells) presence and progression in mice models of induced breast cancer. Urine samples were collected from mice prior to tumor injection and from days 2–19 after. VOC models constructed by linear discriminant analysis had high ability to distinguish tumor-bearing mice from control and determine the week of urine collection after tumor injection. Principal component regression analysis demonstrated that VOCs could predict the number of days since tumor injection. VOCs identified from these analyses correspond to metabolic pathways dysregulated by breast cancer and previous biomarker investigations. It is anticipated that these findings can be translated into human research for early detection of breast cancer recurrence.
Previous studies have shown that volatile organic compounds (VOCs) are potential biomarkers of breast cancer. An unanswered question is how urinary VOCs change over time as tumors progress. To explore this, BALB/c mice were injected with 4T1.2 triple negative murine tumor cells in the tibia. This typically causes tumor progression and osteolysis in 1–2 weeks. Samples were collected prior to tumor injection and from days 2–19. Samples were analyzed by headspace solid phase microextraction coupled to gas chromatography–mass spectrometry. Univariate analysis identified VOCs that were biomarkers for breast cancer; some of these varied significantly over time and others did not. Principal component analysis was used to distinguish Cancer (all Weeks) from Control and Cancer Week 1 from Cancer Week 3 with over 90% accuracy. Forward feature selection and linear discriminant analysis identified a unique panel that could identify tumor presence with 94% accuracy and distinguish progression (Cancer Week 1 from Cancer Week 3) with 97% accuracy. Principal component regression analysis also demonstrated that a VOC panel could predict number of days since tumor injection (R2 = 0.71 and adjusted R2 = 0.63). VOC biomarkers identified by these analyses were associated with metabolic pathways relevant to breast cancer. View Full-Text
Keywords: volatile organic compounds (VOCs); gas chromatography (GC); mass spectrometry (MS); headspace solid phase microextraction (HS-SPME); breast cancer biomarkers; principal component analysis (PCA); linear discriminant analysis (LDA); principal component regression (PCR) volatile organic compounds (VOCs); gas chromatography (GC); mass spectrometry (MS); headspace solid phase microextraction (HS-SPME); breast cancer biomarkers; principal component analysis (PCA); linear discriminant analysis (LDA); principal component regression (PCR)
Show Figures

Graphical abstract

MDPI and ACS Style

Woollam, M.; Wang, L.; Grocki, P.; Liu, S.; Siegel, A.P.; Kalra, M.; Goodpaster, J.V.; Yokota, H.; Agarwal, M. Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds. Cancers 2021, 13, 1462. https://doi.org/10.3390/cancers13061462

AMA Style

Woollam M, Wang L, Grocki P, Liu S, Siegel AP, Kalra M, Goodpaster JV, Yokota H, Agarwal M. Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds. Cancers. 2021; 13(6):1462. https://doi.org/10.3390/cancers13061462

Chicago/Turabian Style

Woollam, Mark; Wang, Luqi; Grocki, Paul; Liu, Shengzhi; Siegel, Amanda P.; Kalra, Maitri; Goodpaster, John V.; Yokota, Hiroki; Agarwal, Mangilal. 2021. "Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds" Cancers 13, no. 6: 1462. https://doi.org/10.3390/cancers13061462

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop