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Browsing by Author "Wang, Luqi"
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Item Attraction and Compaction of Migratory Breast Cancer Cells by Bone Matrix Proteins through Tumor-Osteocyte Interactions(Nature Publishing Group, 2018-04-03) Chen, Andy; Wang, Luqi; Liu, Shengzhi; Wang, Yue; Liu, Yunlong; Wang, Mu; Nakshatri, Harikrishna; Li, Bai-Yan; Yokota, Hiroki; Biomedical Engineering, School of Engineering and TechnologyBone is a frequent site of metastasis from breast cancer. To understand the potential role of osteocytes in bone metastasis, we investigated tumor-osteocyte interactions using two cell lines derived from the MDA-MB-231 breast cancer cells, primary breast cancer cells, and MLO-A5/MLO-Y4 osteocyte cells. When three-dimensional (3D) tumor spheroids were grown with osteocyte spheroids, tumor spheroids fused with osteocyte spheroids and shrank. This size reduction was also observed when tumor spheroids were exposed to conditioned medium isolated from osteocyte cells. Mass spectrometry-based analysis predicted that several bone matrix proteins (e.g., collagen, biglycan) in conditioned medium could be responsible for tumor shrinkage. The osteocyte-driven shrinkage was mimicked by type I collagen, the most abundant organic component in bone, but not by hydroxyapatite, a major inorganic component in bone. RNA and protein expression analysis revealed that tumor-osteocyte interactions downregulated Snail, a transcription factor involved in epithelial-to-mesenchymal transition (EMT). An agarose bead assay showed that bone matrix proteins act as a tumor attractant. Collectively, the study herein demonstrates that osteocytes attract and compact migratory breast cancer cells through bone matrix proteins, suppress tumor migration, by Snail downregulation, and promote subsequent metastatic colonization.Item Chemometric Analysis of Urinary Volatile Organic Compounds to Monitor the Efficacy of Pitavastatin Treatments on Mammary Tumor Progression over Time(MDPI, 2022-07) Grocki, Paul; Woollam, Mark; Wang, Luqi; Liu, Shengzhi; Kalra, Maitri; Siegel, Amanda P.; Li, Bai-Yan; Yokota, Hiroki; Agarwal, Mangilal; Chemistry and Chemical Biology, School of ScienceVolatile organic compounds (VOCs) in urine are potential biomarkers of breast cancer. Previously, our group has investigated breast cancer through analysis of VOCs in mouse urine and identified a panel of VOCs with the ability to monitor tumor progression. However, an unanswered question is whether VOCs can be exploited similarly to monitor the efficacy of antitumor treatments over time. Herein, subsets of tumor-bearing mice were treated with pitavastatin at high (8 mg/kg) and low (4 mg/kg) concentrations, and urine was analyzed through solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Previous investigations using X-ray and micro-CT analysis indicated pitavastatin administered at 8 mg/kg had a protective effect against mammary tumors, whereas 4 mg/kg treatments did not inhibit tumor-induced damage. VOCs from mice treated with pitavastatin were compared to the previously analyzed healthy controls and tumor-bearing mice using chemometric analyses, which revealed that mice treated with pitavastatin at high concentrations were significantly different than tumor-bearing untreated mice in the direction of healthy controls. Mice treated with low concentrations demonstrated significant differences relative to healthy controls and were reflective of tumor-bearing untreated mice. These results show that urinary VOCs can accurately and noninvasively predict the efficacy of pitavastatin treatments over time.Item Effects of a checkpoint kinase inhibitor, AZD7762, on tumor suppression and bone remodeling(Spandidos Publications, 2018-09) Wang, Luqi; Wang, Yue; Chen, Andy; Jalali, Aydin; Liu, Shengzhi; Guo, Yunxia; Na, Sungsoo; Nakshatri, Harikrishna; Li, Bai-Yan; Yokota, Hiroki; Biomedical Engineering, School of Engineering and TechnologyChemotherapy for suppressing tumor growth and metastasis tends to induce various effects on other organs. Using AZD7762, an inhibitor of checkpoint kinase (Chk) 1 and 2, the present study examined its effect on mammary tumor cells in addition to bone cells (osteoclasts, osteoblasts and osteocytes), using monolayer cell cultures and three-dimensional (3D) cell spheroids. The results revealed that AZD7762 blocked the proliferation of 4T1.2 mammary tumor cells and suppressed the development of RAW264.7 pre-osteoclast cells by downregulating nuclear factor of activated T cells cytoplasmic 1. AZD7762 also promoted the mineralization of MC3T3 osteoblast-like cells and 3D bio-printed bone constructs of MLO-A5 osteocyte spheroids. While a Chk1 inhibitor, PD407824, suppressed the proliferation of tumor cells and the differentiation of pre-osteoclasts, its effect on gene expression in osteoblasts was markedly different compared with AZD7762. Western blotting indicated that the stimulating effect of AZD7762 on osteoblast development was associated with the inhibition of Chk2 and the downregulation of cellular tumor antigen p53. The results of the present study indicated that in addition to acting as a tumor suppressor, AZD7762 may prevent bone loss by inhibiting osteoclastogenesis and stimulating osteoblast mineralization.Item Pitavastatin slows tumor progression and alters urine-derived volatile organic compounds through the mevalonate pathway(Wiley, 2019-10-04) Wang, Luqi; Wang, Yue; Chen, Andy; Teli, Meghana; Kondo, Rika; Jalali, Aydin; Fan, Yao; Liu, Shengzhi; Zhao, Xinyu; Siegel, Amanda; Minami, Kazumasa; Agarwal, Mangilal; Li, Bai-Yan; Yokota, Hiroki; Biomedical Engineering, School of Engineering and TechnologyBone is a frequent site of metastasis from breast cancer, and a desirable drug could suppress tumor growth as well as metastasis-linked bone loss. Currently, no drug is able to cure breast cancer–associated bone metastasis. In this study, we focused on statins that are known to inhibit cholesterol production and act as antitumor agents. After an initial potency screening of 7 U.S. Food and Drug Administration–approved statins, we examined pitavastatin as a drug candidate for inhibiting tumor and tumor-induced bone loss. In vitro analysis revealed that pitavastatin acted as an inhibitor of tumor progression by altering stress to the endoplasmic reticulum, down-regulating peroxisome proliferator–activated receptor γ, and reducing Snail and matrix metalloproteinase 9. In bone homeostasis, it blocked osteoclast development by suppressing transcription factors c-Fos and JunB, but stimulated osteoblast mineralization by regulating bone morphogenetic protein 2 and p53. In a mouse model, pitavastatin presented a dual role in tumor inhibition in the mammary fat pad, as well as in bone protection in the osteolytic tibia. In mass spectrometry–based analysis, volatile organic compounds (VOCs) that were linked to lipid metabolism and cholesterol synthesis were elevated in mice from the tumor-grown placebo group. Notably, pitavastatin-treated mice reduced specific VOCs that are linked to lipid metabolites in the mevalonate pathway. Collectively, the results lay a foundation for further investigation of pitavastatin’s therapeutic efficacy in tumor-induced bone loss, as well as VOC-based diagnosis of tumor progression and treatment efficacy.—Wang, L., Wang, Y., Chen, A., Teli, M., Kondo, R., Jalali, A., Fan, Y., Liu, S., Zhao, X., Siegel, A., Minami, K., Agarwal, M., Li, B.-Y., Yokota, H. Pitavastatin slows tumor progression and alters urine-derived volatile organic compounds through the mevalonate pathway.Item Reduction in Migratory Phenotype in a Metastasized Breast Cancer Cell Line via Downregulation of S100A4 and GRM3(Springer Nature, 2017-06-14) Chen, Andy; Wang, Luqi; Li, Bai-Yan; Sherman, Jesse; Ryu, Jong E.; Hamamura, Kazunori; Liu, Yunlong; Nakshatri, Harikrishna; Yokota, Hiroki; Biomedical Engineering, School of Engineering and TechnologyTo investigate phenotypic and genotypic alterations before and after bone metastasis, we conducted genome-wide mRNA profiling and DNA exon sequencing of two cell lines (TMD and BMD) derived from a mouse xenograft model. TMD cells were harvested from the mammary fat pad after transfecting MDA-MB-231 breast cancer cells, while BMD cells were isolated from the metastasized bone. Compared to BMD cells, TMD cells exhibited higher cellular motility. In contrast, BMD cells formed a spheroid with a smoother and more circular surface when co-cultured with osteoblasts. In characterizing mRNA expression using principal component analysis, S100 calcium-binding protein A4 (S100A4) was aligned to a principal axis associated with metastasis. Partial silencing of S100A4 suppressed migratory capabilities of TMD cells, while Paclitaxel decreased the S100A4 level and reduced TMD's cellular motility. DNA mutation analysis revealed that the glutamate metabotropic receptor 3 (GRM3) gene gained a premature stop codon in BMD cells, and silencing GRM3 in TMD cells altered their spheroid shape closer to that of BMD cells. Collectively, this study demonstrates that metastasized cells are less migratory due in part to the post-metastatic downregulation of S100A4 and GRM3. Targeting S100A4 and GRM3 may help prevent bone metastasis.Item Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds(Cancers, 2021-01) Woollam, Mark; Wang, Luqi; Grocki, Paul; Liu, Shengzhi; Siegel, Amanda P.; Kalra, Maitri; Goodpaster, John V.; Yokota, Hiroki; Agarwal, MangilalPrevious 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.