Publications by authors named "Mukti R Parikh"
Breast cancer metastasis to the bone continues to be a major health problem, with approximately 80% of advanced breast cancer patients expected to develop bone metastasis. Although the problem of bone metastasis persists, current treatment options for metastatic cancer patients are limited. In this study, we investigated the preventive role of the active vitamin D metabolite, 1α,25-dihydroxyvitamin D (1,25(OH)2D), against the metastatic potential of breast cancer cells using a novel three-dimensional model (rMET) recapitulating multiple steps of the bone metastatic process.
View Article and Find Full Text PDFMetastasis remains a leading cause of morbidity and mortality from solid tumors. Lack of comprehensive systems to study the progression of metastasis contributes to the low success of treatment. We developed a novel three-dimensional in vitro reconstructed metastasis (rMet) model that incorporates extracellular matrix (ECM) elements characteristic of the primary (breast, prostate, or lung) and metastatic (bone marrow, BM) sites.
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- Tissue culture is essential for studying cell functions in health and disease, but traditional methods often struggle with primary cells due to the lack of proper extracellular matrix (ECM).
- A new 3D tissue culture method called the rBM system enables the growth of primary bone marrow cells by using ECM that mimics the natural bone environment, allowing cell survival and function for up to 30 days.
- This innovative system supports the study of cell behavior and the testing of new therapies, while also allowing for the isolation and analysis of these cells for further research.
We demonstrate the first application of Raman spectroscopy in diagnosing nonmalignant, premalignant, malignant, and metastatic stages of breast cancer in a three-dimensional (3-D) cell culture model that closely mimics an in vivo environment. Comprehensive study comparing classification in two-dimensional (2-D) and 3-D cell models was performed using statistical methods composed of principal component analysis for exploratory analysis and outlier removal, partial least squares discriminant analysis, and elastic net regularized regression for classification. Our results show that Raman spectroscopy with an appropriate classification tool has excellent resolution to discriminate the four stages of breast cancer progression, with a near 100% accuracy for both 2-D and 3-D cell models.
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