Metabolic nanosensors for the identification of tumoral metabo-phenotypes
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Universidad de Granada
DepartamentoUniversidad de Granada. Programa de Doctorado en Farmacia
Ripoll Lorente, María Consuelo. Metabolic nanosensors for the identification of tumoral metabo-phenotypes. Granada: Universidad de Granada, 2019. [http://hdl.handle.net/10481/56471]
SponsorshipTesis Univ. Granada.
In this Thesis, several QD-based nanosensors have been designed and optimized, specifically taking advantage of the long PL lifetime of the QDs for the use of FLIM microscopy. In this regard, we have described a family of nanosensors, in which QDs of different sizes were modified with cyclam or cyclen, exhibiting a selective response towards Zn2+ ions. The sensing mechanism was based on a photo-induced electron transfer, causing the enhancement of the average PL lifetime of the QDs in the presence of Zn2+ ions. The performance of these nanosensors was tested in bulk solution and by FLIM imaging on glass slides and inside living cells. We have also developed a family of pH nanosensors with different applications in the study of the cellular metabolism. One of the sensors was employed in the estimation of the pH extracellular media. The second nanosensor was designed to be delivered inside mitochondria, and report on the intra-mitochondrial pH by means of FLIM imaging. We applied these nanosensors in the study of the metabolic behavior of five different breast cancer cell lines, related to the current clinical classification of breast cancer tissues. These experiments demonstrated that MC7, ZR751 and SKBR3 cell lines showed an extracellular pH higher than that of MDA-MB-231 and MDA-MB-468 cells. In contrast, when the nanosensors were applied inside mitochondria, we found that MCF7 cells exhibited a lower intramitochondrial pH lower than that of SKBR3, MDAMB- 231 and MDA-MB-468 cells. In this Thesis, we have performed a metabolic study of different breast cancer models. To do this, we have subjected the aforementioned breast cancer cell lines to different metabolic inhibitors to elucidate the sensitivity and response of the cellular populations. After subjecting the cell lines to inhibition by AOA transaminase inhibitor, we obtained a first metabolic classification based on the dependence of the cell lines on the metabolites aspartate and pyruvate and, therefore, we established the importance of the redox balance for their metabolism. In order to investigate whether the metabolism of the glycolytic cell lines depends on mitochondrial metabolism, we used a mitochondrial membrane-decoupling agent, BAM15, to explore the ATP dependence of the lines. The triple negative (MDA-MB-231 and MDA-MB-468) and SKBR3 cell lines were sensitive to this inhibition. Dependence on NAD+ and glycolysis was then tested using the inhibitors phenformin and Akt, respectively. For both inhibitors, the cell lines MCF7, ZR751 and SKBR3 were sensitive. With these results, we could clearly establish that the cell lines MCF7 and ZR751 show a glycolysis-dependent metabolism. However, the triple negative cell lines show a profile dependent on mitochondrial metabolism. Finally, the SKBR3 cell line exhibits a metabolism that shares some common features between the other two metabophenotypes. Finally, the ultimate aim of this Thesis was to correlate the pH differences found in different breast cancer cell lines using QD-based nanosensors with the metabolic classification proposed in this work. When analyzing the nanosensing results together, one may suggest that there are two clearly distinct profiles: the one composed of the triple negative cell lines, MDA-MB-231 and MDA-MB-468, and that of the MCF7 and possibly ZR751 (the tries to introduce the intramitochondrial nanosensor in these cells were unsuccessful). These results are perfectly in line with the metabolic profiling and the metabophenotype classification proposed in this work. Table 5.3.1 shows the final full definition of the metabophenotypes, with the addition of the pH information gathered from the application of the QD nanosensors. The metabophenotype 3, with dependence on the mitochondrial oxidative metabolism, displayed lower extracellular pH and high intra-mitochondrial pH (9.2-9.3). In contrast, the more glycolytic cell lines, metabophenotype 1, exhibited extracellular values around 8, and we found a significantly lower intramitochondrial pH in MCF7 cells (8.6). Interestingly, the HER2 positive cell line SKBR3 may present an intermediate metabolic profile, with properties lying between the other two: extracellular pH closer to metabophenotype 1, but intramitochondrial pH similar to metabophenotype 3. In summary, the combined use of pH sensitive nanoparticles and FLIM technologies might be further considered for potential diagnostic approaches based in the metabolic features of cancer cells.