| Title: | Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds |
| Author(s): | Woollam M; Wang L; Grocki P; Liu S; Siegel AP; Kalra M; Goodpaster JV; Yokota H; Agarwal M; |
| Address: | "Department of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA. Integrated Nanosystems Development Institute, Indiana University-Purdue University, Indianapolis, IN 46202, USA. Department of Biomedical Engineering, Indiana University-Purdue University, Indianapolis, IN 46202, USA. Hematology and Oncology, Ball Memorial Hospital, Indiana University Health, Muncie, IN 47303, USA. Biomechanics and Biomaterials Research Center, Indiana University-Purdue University, Indianapolis, IN 46202, USA. Department of Mechanical & Energy Engineering, Indiana University-Purdue University, Indianapolis, IN 46202, USA" |
| ISSN/ISBN: | 2072-6694 (Print) 2072-6694 (Electronic) 2072-6694 (Linking) |
| Abstract: | "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 (R(2) = 0.71 and adjusted R(2) = 0.63). VOC biomarkers identified by these analyses were associated with metabolic pathways relevant to breast cancer" |
| Keywords: | breast cancer biomarkers gas chromatography (GC) headspace solid phase microextraction (HS-SPME) linear discriminant analysis (LDA) mass spectrometry (MS) principal component analysis (PCA) principal component regression (PCR) volatile organic compounds (; |
| Notes: | "PubMed-not-MEDLINEWoollam, Mark Wang, Luqi Grocki, Paul Liu, Shengzhi Siegel, Amanda P Kalra, Maitri Goodpaster, John V Yokota, Hiroki Agarwal, Mangilal eng Switzerland 2021/04/04 Cancers (Basel). 2021 Mar 23; 13(6):1462. doi: 10.3390/cancers13061462" |
