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Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes.

Valeriy DomenyukZoran GatalicaRadhika SanthanamXixi WeiAdam StarkPatrick KennedyBrandon ToussaintSymon LevenbergJie WangNianqing XiaoRichard GreilGabriel RinnerthalerSimon P GampenriederAmy B HeimbergerDonald A BerryAnna BarkerJohn QuackenbushJohn L MarshallGeorge PosteJeffrey L VacircaGregory A VidalLee S SchwartzbergDavid D HalbertAndreas VossDaniel MageeMark R MiglareseMichael FamulokGünter MayerDavid Spetzler
Published in: Nature communications (2018)
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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