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The structural complexity of chromosome 1p centromeric region has been an obstacle for fine mapping of tumor suppressor genes in this area.
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Also, systematic mapping of tumor-specific transcriptional networks and identification of negative genetic interactions have been applied as a feature to identify therapeutic targets for cancer [ 66, 83].
Given that chromosomal copy number changes occur frequently in human cancer, approaches allowing the mapping of tumor-specific copy number changes from plasma DNA using array-CGH [ 76] or NGS of plasma DNA [ 77- 81] had been developed.
For instance, reproducible digital mapping of tumor-specific mutant HLA peptides during cancer progression will facilitate stratification of patients who might best benefit from innovative immunotherapeutic interventions (Gubin et al., 2014; Snyder et al., 2014; Schumacher et al., 2015).
Given that chromosomal copy number changes occur frequently in human cancer, we developed an approach allowing the mapping of tumor-specific copy number changes from plasma DNA employing array-CGH [ 33].
Our investigation allowed us to build a detailed map of tumor vasculature in human Kaposi sarcoma.
Informed with this initial information, ICA then provides a map of tumor extent.
Figure 5 shows a screenshot of mutation map of tumor antigen epidermal growth factor receptor (EGFR) in TANTIGEN.
Even though, PCA and ICA extract significant features to provide a map of tumor probability to be used in an intraoperative context.
While CSI experiments were used to produce color maps of tumor metabolism, the in vivo kinetic data were collected with a slice-selective spectroscopy protocol.
It has been proven to enhance classification features from mammograms for breast cancer detection [ 15] and also for other cancer types: maps of tumor probability have been extracted from the ICA of RGB fluorescence images taken from the skin [ 16].
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