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Domenyuk, V; Gatalica, Z; Santhanam, R; Wei, X; Stark, A; Kennedy, P; Toussaint, B; Levenberg, S; Wang, J; Xiao, N; Greil, R; Rinnerthaler, G; Gampenrieder, SP; Heimberger, AB; Berry, DA; Barker, A; Quackenbush, J; Marshall, JL; Poste, G; Vacirca, JL; Vidal, GA; Schwartzberg, LS; Halbert, DD; Voss, A; Magee, D; Miglarese, MR; Famulok, M; Mayer, G; Spetzler, D.
Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes.
Nat Commun. 2018; 9(1): 1219
Doi: 10.1038/s41467-018-03631-z
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- Co-Autor*innen der Med Uni Graz
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Rinnerthaler Gabriel
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- Abstract:
- Assessing the phenotypic diversity underlying tumour progression requires the identification of variations in the respective molecular interaction networks. Here we report proof-of-concept for a platform called poly-ligand profiling (PLP) that surveys these system states and distinguishes breast cancer patients who did or did not derive benefit from trastuzumab. We perform tissue-SELEX on breast cancer specimens to enrich single-stranded DNA (ssDNA) libraries that preferentially interact with molecular components associated with the two clinical phenotypes. Testing of independent sample sets verifies the ability of PLP to classify trastuzumab-treated patients according to their clinical outcomes with ROC-AUC of 0.78. Standard HER2 testing of the same patients gives a ROC-AUC of 0.47. Kaplan-Meier analysis reveals a median increase in benefit from trastuzumab-containing treatments of 300 days for PLP-positive compared to PLP-negative patients. If prospectively validated, PLP may increase success rates in precision oncology and clinical trials, thus improving both patient care and drug development.
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