Metabolomic Investigation of Melanoma Metastasis in a Patient-Derived Xenograft Mouse Model
| dc.contributor.advisor | Zhu, Hao | en |
| dc.contributor.committeeMember | DeBerardinis, Ralph J. | en |
| dc.contributor.committeeMember | Wang, Richard | en |
| dc.contributor.committeeMember | Morrison, Sean J. | en |
| dc.contributor.committeeMember | Davies, Michael | en |
| dc.creator | Shi, Xiaolei | en |
| dc.date.accessioned | 2019-09-03T19:55:46Z | |
| dc.date.available | 2019-09-03T19:55:46Z | |
| dc.date.created | 2017-08 | |
| dc.date.issued | 2017-07-19 | |
| dc.date.submitted | August 2017 | |
| dc.date.updated | 2019-09-03T19:55:47Z | |
| dc.description.abstract | Metabolic reprogramming is considered a major factor in cellular transformation and tumor initiation, but whether or how metabolism supports tumor metastasis remains an open question. This study seeks to identify metabolic predictors of metastasis, with the rationale that understanding metabolic changes accompanying metastasis may lead to new therapies to prevent metastatic cancer. We used a set of patient-derived xenograft mouse models of melanoma, in which the metastatic potential of individual tumor lines correlated strongly with the history of metastasis in the patient donors. Six tumor lines with low metastatic potential (L-met) and nine with high metastatic potential (H-met) were implanted into several mice individually, then several fragments were isolated from each tumor, yielding a total of 182 individual tumor fragments for metabolomics. A tandem mass spectrometry (MS/MS)-based analytical platform was used to characterize 133 metabolites extracted from each tumor specimen. We then used a suite of statistical tools to identify metabolites differentiating H-met from L-met tumors. We identified durable metabolomic signatures correlating with molecular and biological features of the tumors. BRAF-mutant tumors had metabolomic and metabolic flux features of enhanced glycolysis compared to BRAF-wild type tumors. Tumors that metastasized efficiently from their primary sites had elevated levels of metabolites related to protein methylation, including trimethyllysine (TML). TML levels correlated with histone H3 trimethylation at lysines 9 and 27, and methylation at these sites was also enhanced in efficiently metastasizing tumors. Erasing either of these marks by genetically or pharmacologically silencing the histone methyltransferases SETDB1 or EZH2 had no effect on primary tumor growth but reduced cellular invasiveness, circulating tumor cell count and metastatic spread. Thus, metabolite profiling can uncover targetable epigenetic requirements for the metastasis of human melanoma cells. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.oclc | 1117308652 | |
| dc.identifier.uri | https://hdl.handle.net/2152.5/7193 | |
| dc.language.iso | en | en |
| dc.subject | Disease Models, Animal | en |
| dc.subject | Melanoma | en |
| dc.subject | Metabolomics | en |
| dc.subject | Neoplasm Metastasis | en |
| dc.title | Metabolomic Investigation of Melanoma Metastasis in a Patient-Derived Xenograft Mouse Model | en |
| dc.type | Thesis | en |
| dc.type.material | text | en |
| thesis.degree.department | Graduate School of Biomedical Sciences | en |
| thesis.degree.discipline | Cancer Biology | en |
| thesis.degree.grantor | UT Southwestern Medical Center | en |
| thesis.degree.level | Doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |