Protein drug target activation homogeneity in the face of intra- tumor heterogeneity: implications for precision medicine

Parasido EM, A Silvestri, V Canzonieri, C Belluco, Diodoro MG, M Milione, F Melotti, Ruggero De Maria Marchiano, L Liotta, Petricoin EF, M. Pierobon*

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolopeer review

6 Citazioni (Scopus)

Abstract

Introduction: Recent studies indicated tumors may be comprised of heterogeneous molecular subtypes and incongruent molecular portraits may emerge if di erent areas of the tumor are sampled. This study explored the impact of intra- tumoral heterogeneity in terms of activation/phosphorylation of FDA approved drug targets and downstream kinase substrates.\r\nMaterial and methods: Two independent sets of liver metastases from colorectal cancer were used to evaluate protein kinase-driven signaling networks within di erent areas using laser capture microdissection and reverse phase protein array.\r\nResults: Unsupervised hierarchical clustering analysis indicated that the signaling architecture and activation of the MAPK and AKT-mTOR pathways were consistently maintained within di erent regions of the same biopsy. Intra-patient variability of the MAPK and AKT-mTOR pathway were <1.06 fold change, while inter-patients variability reached fold change values of 5.01.\r\nConclusions: Protein pathway activation mapping of enriched tumor cells obtained from di erent regions of the same tumor indicated consistency and robustness independent of the region sampled. This suggests a dominant protein pathway network may be activated in a high percentage of the tumor cell population. Given the genomic intra-tumoral variability, our data suggest that protein/phosphoprotein signaling measurements should be integrated with genomic analysis for precision medicine based analysis.
Lingua originaleInglese
pagine (da-a)48534-48544
Numero di pagine11
RivistaOncotarget
Numero di pubblicazione8 (30)
DOI
Stato di pubblicazionePubblicato - 2017

All Science Journal Classification (ASJC) codes

  • Oncologia

Keywords

  • precision medicine

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