Abstract During the migration of cancer cells for metastasis, cancer cells can be exposed to fluid shear conditions. We examined two breast cancer cell lines, MDA-MB-468 (less metastatic) and MDA-MB-231 (more metastatic), and a benign MCF-10A epithelial cell line for their responsiveness in migration to fluid shear. We tested fluid shear at 15 dyne/cm2 that can be encountered during breast cancer cells traveling through blood vessels or metastasizing to mechanically active tissues such as bone. MCF-10A exhibited the least migration with a trend of migrating in the flow direction. Intriguingly, fluid shear played a potent role as a trigger for MDA-MB-231 cell migration, inducing directional migration along the flow with significantly increased displacement length and migration speed and decreased arrest coefficient relative to unflowed MDA-MB-231. In contrast, MDA-MB-468 cells were markedly less migratory than MDA-MB-231 cells, and responded very poorly to fluid shear. As a result, MDA-MB-468 cells did not exhibit noticeable difference in migration between static and flow conditions, as was distinct in root-mean-square (RMS) displacement—an ensemble average of all participating cells. These may suggest that the difference between more metastatic MDA-MB-231 and less metastatic MDA-MB-468 breast cancer cells could be at least partly involved with their differential responsiveness to fluid shear stimulatory cues. Our study provides new data in regard to potential crosstalk between fluid shear and metastatic potential in mediating breast cancer cell migration.
more »
« less
Synthesis of Novel Heterocyclic Ferrocenyl Chalcones and Their Biological Evaluation
Breast cancer is currently the most commonlydiagnosed cancer, with 287,850 new cases estimated for 2022 asreported by the American Cancer Society. Therefore, finding aneffective treatment for this disease is imperative. Chalcones are α,β-unsaturated systems found in nature. These compounds haveshown a wide array of biological activities, making them popularsynthetic targets. Chalcones consist of two aromatic substituentsconnected by an enone bridge; this arrangement allows for a largenumber of derivatives. Given the biological relevance of thesecompounds, novel ferrocene-heterocycle-containing chalcones weresynthesized and characterized based on a hybrid drug designapproach. These heterocycles included thiophene, pyrimidine,thiazolyl, and indole groups. Fourteen novel heterocyclic ferrocenyl chalcones were synthesized and characterized. Herein, we alsoreport their cytotoxicity against triple-negative breast cancer cell lines MDA-MB-231 and 4T1 and the noncancer lung cell lineMRC-5. System 3 ferrocenyl chalcones displayed superior anticancer properties compared to their system 1 analogues. System 3chalcones bearing five-membered heterocyclic substituents (thiophene, pyrazole, pyrrole, and pyrimidine) were the most activetoward the MDA-MB-231 cancer cell line with IC50 values from 6.59 to 12.51 μM. Cytotoxicity of the evaluated compounds in the4T1 cell line exhibited IC50 values from 13.23 to 213.7 μM. System 3 pyrazole chalcone had consistent toxicity toward both cell lines(IC50 ∼ 13 μM) as well as promising selectivity relative to the noncancer MRC-5 control. Antioxidant activity was also evaluated,where, contrary to anticancer capabilities, system 1 ferrocenyl chalcones were superior to their system 3 analogues. Antioxidantactivity comparable to that of ascorbic acid was observed for thiophene-bearing ferrocenyl chalcone with EC50 = 31 μM.
more »
« less
- PAR ID:
- 10535283
- Publisher / Repository:
- American Chemical Societry
- Date Published:
- Journal Name:
- ACS Omega
- Volume:
- 8
- Issue:
- 38
- ISSN:
- 2470-1343
- Page Range / eLocation ID:
- 34377 to 34387
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Electrophilic fluorine-mediated dearomative spirocyclization has been developed to synthesize a range of fluoro-substituted spiro-isoxazoline ethers and lactones. The in vitro biological assays of synthesized compounds were probed for anti-viral activity against human cytomegalovirus (HCMV) and cytotoxicity against glioblastomas (GBM6) and triple negative breast cancer (MDA MB 231). Interestingly, compounds 4d and 4n showed significant activity against HCMV (IC 50 ∼ 10 μM), while 4l and 5f revealed the highest cytotoxicity with IC 50 = 36 to 80 μM. The synthetic efficacy and biological relevance offer an opportunity to further drug-discovery development of fluoro-spiro-isoxazolines as novel anti-viral and anti-cancer agents.more » « less
-
Xu, Jinbo (Ed.)Abstract Motivation Motions of transmembrane receptors on cancer cell surfaces can reveal biophysical features of the cancer cells, thus providing a method for characterizing cancer cell phenotypes. While conventional analysis of receptor motions in the cell membrane mostly relies on the mean-squared displacement plots, much information is lost when producing these plots from the trajectories. Here we employ deep learning to classify breast cancer cell types based on the trajectories of epidermal growth factor receptor (EGFR). Our model is an artificial neural network trained on the EGFR motions acquired from six breast cancer cell lines of varying invasiveness and receptor status: MCF7 (hormone receptor positive), BT474 (HER2-positive), SKBR3 (HER2-positive), MDA-MB-468 (triple negative, TN), MDA-MB-231 (TN) and BT549 (TN). Results The model successfully classified the trajectories within individual cell lines with 83% accuracy and predicted receptor status with 85% accuracy. To further validate the method, epithelial–mesenchymal transition (EMT) was induced in benign MCF10A cells, noninvasive MCF7 cancer cells and highly invasive MDA-MB-231 cancer cells, and EGFR trajectories from these cells were tested. As expected, after EMT induction, both MCF10A and MCF7 cells showed higher rates of classification as TN cells, but not the MDA-MB-231 cells. Whereas deep learning-based cancer cell classifications are primarily based on the optical transmission images of cell morphology and the fluorescence images of cell organelles or cytoskeletal structures, here we demonstrated an alternative way to classify cancer cells using a dynamic, biophysical feature that is readily accessible. Availability and implementation A python implementation of deep learning-based classification can be found at https://github.com/soonwoohong/Deep-learning-for-EGFR-trajectory-classification. Supplementary information Supplementary data are available at Bioinformatics online.more » « less
-
Multi-omics data integration reveals correlated regulatory features of triple negative breast cancerTriple negative breast cancer (TNBC) is an aggressive type of breast cancer with very little treatment options. TNBC is very heterogeneous with large alterations in the genomic, transcriptomic, and proteomic landscapes leading to various subtypes with differing responses to therapeutic treatments. We applied a multi-omics data integration method to evaluate the correlation of important regulatory features in TNBC BRCA1 wild-type MDA-MB-231 and TNBC BRCA1 5382insC mutated HCC1937 cells compared with non-tumorigenic epithelial breast MCF10A cells. The data includes DNA methylation, RNAseq, protein, phosphoproteomics, and histone post-translational modification. Data integration methods identified regulatory features from each omics method that had greater than 80% positive correlation within each TNBC subtype. Key regulatory features at each omics level were identified distinguishing the three cell lines and were involved in important cancer related pathways such as TGFβ signaling, PI3K/AKT/mTOR, and Wnt/beta-catenin signaling. We observed overexpression of PTEN, which antagonizes the PI3K/AKT/mTOR pathway, and MYC, which downregulates the same pathway in the HCC1937 cells relative to the MDA-MB-231 cells. The PI3K/AKT/mTOR and Wnt/beta-catenin pathways are both downregulated in HCC1937 cells relative to MDA-MB-231 cells, which likely explains the divergent sensitivities of these cell lines to inhibitors of downstream signaling pathways. The DNA methylation and RNAseq data is freely available via GEO GSE171958 and the proteomics data is available via the ProteomeXchange PXD025238.more » « less
-
Abstract P‐glycoprotein (P‐gp, ABCB1) is a well‐researched ATP‐binding cassette (ABC) drug efflux transporter linked to the development of cancer multidrug resistance (MDR). Despite extensive studies, approved therapies to safely inhibit P‐gp in clinical settings are lacking, necessitating innovative strategies beyond conventional inhibitors or antibodies to reverse MDR. Photodynamic therapy is a globally approved cancer treatment that uses targeted, harmless red light to activate non‐toxic photosensitizers, confining its cytotoxic photochemical effects to disease sites while sparing healthy tissues. This study demonstrates that photodynamic priming (PDP), a sub‐cytotoxic photodynamic therapy process, can inhibit P‐gp function by modulating cellular respiration and ATP levels in light accessible regions. Using chemoresistant (VBL‐MDA‐MB‐231) and chemosensitive (MDA‐MB‐231) triple‐negative breast cancer cell lines, we showed that PDP decreases mitochondrial membrane potential by 54.4% ± 30.4 and reduces mitochondrial ATP production rates by 94.9% ± 3.46. Flow cytometry studies showed PDP can effectively improve the retention of P‐gp substrates (calcein) by up to 228.4% ± 156.3 in chemoresistant VBL‐MDA‐MB‐231 cells, but not in chemosensitive MDA‐MB‐231 cells. Further analysis revealed that PDP did not alter the cell surface expression level of P‐gp in VBL‐MDA‐MB‐231 cells. These findings indicate that PDP can reduce cellular ATP below the levels that is required for the function of P‐gp and improve intracellular substrate retention. We propose that PDP in combination with chemotherapy drugs, might improve the efficacy of chemotherapy and overcome cancer MDR.more » « less
An official website of the United States government

