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An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines.

ABSTRACT: We present the development and validation of a mathematical model that predicts how glucose dynamics influence metabolism and therefore tumor cell growth. Glucose, the starting material for glycolysis, has a fundamental influence on tumor cell growth. We employed time-resolved microscopy to track the temporal change of the number of live and dead tumor cells under different initial glucose concentrations and seeding densities. We then constructed a family of mathematical models (where cell death was accounted for differently in each member of the family) to describe overall tumor cell growth in response to the initial glucose and confluence conditions. The Akaikie Information Criteria was then employed to identify the most parsimonious model. The selected model was then trained on 75% of the data to calibrate the system and identify trends in model parameters as a function of initial glucose concentration and confluence. The calibrated parameters were applied to the remaining 25% of the data to predict the temporal dynamics given the known initial glucose concentration and confluence, and tested against the corresponding experimental measurements. With the selected model, we achieved an accuracy (defined as the fraction of measured data that fell within the 95% confidence intervals of the predicted growth curves) of 77.2 ± 6.3% and 87.2 ± 5.1% for live BT-474 and MDA-MB-231 cells, respectively.

SUBMITTER: Yang J

PROVIDER: S-EPMC8277046 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction: Amplification at chromosome 8q24 is one of the most frequent genomic abnormalities in human cancers and is associated with reduced survival duration in breast and ovarian cancers. The minimal amplified region encodes c-MYC and the non-coding RNA, PVT1 including miR-1204 encoded in exon 1b. Here we analyzed the genomic changes at chromosome 8q24.21 in breast cancer and the functional roles of miR-1204 in breast and ovarian cancer progression. Methods: The genomic changes at chromosome 8q24.21 were detected in 997 breast cancer tumors and 40 breast cancer cell lines. Expression of miR-1204 in breast and ovarian cancer cell lines was investigated by qRT-PCR method. The role of miR-1204 in the tumorigenesis of breast and ovarian cancer was explored using both knockdown and overexpression of miR-1204 in vitro. Candidate miR-1204 target genes from two independent expression microarray datasets and computational predict programs were identified and further validated by qRT-PCR and western blot methods. The role of inhibition of miR-1204 on tamoxifen sensitivity in breast cancer cells was also investigated. Results: MiR-1204 is frequently co-amplified with MYC and expression of miR-1204 is strongly correlated with the expression and amplification of the noncoding PVT1 transcript and less so with MYC in human breast and ovarian cancer cells. Inhibition of miR-1204 decreases cell proliferation and increased apoptosis in breast and ovarian cancer cell lines with 8q24 amplification, but not in lines without amplification and so may be involved in Myc-induced apoptosis. Additionally, overexpression of miR-1204 enhances both breast and ovarian cancer cell growth and Myc-initiated Rat1A cell transformation. Computational and experimental analyses 30 promising candidate miR-1204 target genes. mRNA levels for these genes were assessed after over expression and knockdown of miR-1204 as were protein levels for 10 genes for which antibodies were available. These studies implicated VDR and ESR1 as miR-1204 targets. Inhibition of miR-1204 increased response to tamoxifen in Estrogen Receptor negative breast cancer cell lines. Conclusions: We conclude that amplification of miR-1204 contributes to breast and ovarian pathophysiology at least in part, by increasing proliferation and down regulating apoptosis and by decreasing expression of VDR and ESR1. Seven cell line sample pairs, where samples are LNA transfected with antimiR-1204 or antimiR-1204 control

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An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines.

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