Mass spectrometry imaging for the investigation of intratumor heterogeneity
One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in can...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Kapitel/Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
2017
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| In: |
Applications of mass spectrometry imaging to cancer
Year: 2017, Pages: 201-230 |
| DOI: | 10.1016/bs.acr.2016.11.008 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1016/bs.acr.2016.11.008 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0065230X16300811 |
| Verfasserangaben: | B. Balluff, M. Hanselmann, R.M.A. Heeren |
MARC
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| 520 | |a One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research. | ||
| 650 | 4 | |a Cancer | |
| 650 | 4 | |a Clustering | |
| 650 | 4 | |a Intratumor heterogeneity | |
| 650 | 4 | |a Mass spectrometry imaging | |
| 650 | 4 | |a Tissue proteomics | |
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| 700 | 1 | |a Heeren, Ron M.A. |e VerfasserIn |0 (DE-588)18848325X |0 (DE-627)69940679X |0 (DE-576)135351561 |4 aut | |
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