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Development and analytical performance of a molecular diagnostic for anti-PD1 response on the nCounter Dx Analysis System.
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2016
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EngineeringMolecular DiagnosticImmune Gx SignatureImmunologyImmunoeditingMolecular BiologyPathologyImmunotherapeuticsImmunotherapyTumor BiologyAnti-pd1 ResponseMolecular CharacterizationBioanalysisTotal Standard DeviationTumor ImmunityAnalytical ChemistryAnalytical PerformanceClinical ChemistryMolecular DiagnosticsRadiation OncologyCancer ResearchMolecular OncologyMedicineImmune SurveillanceBiomedical AnalysisPharmacologyAdvanced MelanomaLung CancerPrognostic BiomarkersCancer ImmunosurveillanceCancer GenomicsImmune Checkpoint InhibitorOncology
3034 Background: Pembrolizumab is a humanized anti-PD1 antibody that is FDA approved for use in patients with advanced melanoma and in selected patients with metastatic non-small-cell lung cancer. It has also shown clinical activity in a number of other tumor types in clinical trials, but there is need for a precise and accurate test that can identify patients most likely to benefit from therapy. Several immune-related gene expression (Gx) signatures in formalin fixed, paraffin embedded (FFPE) tissue were previously reported to enrich for responders to pembrolizumab across different tumor types. We have developed a clinical trial assay, referred to here as the anti-PD1 Gx test, based on genes repeatedly found to be associated with improved response to pembrolizumab in a number of cancers. Here we describe the development and analytical performance of the anti-PD1 Gx test in multiple tumor types. Methods: The anti-PD1 Predictor Score (PS) algorithm was trained using RNA from FFPE specimens from all cancer types in the KEYNOTE-012 trial and several cancer types in the KEYNOTE-028 trial (anal canal, biliary tract, colorectal, esophageal, and ovarian) to determine the final genes and weightings. Analytical precision from RNA, reproducibility from multiple tissue blocks, impact of intra-tumor heterogeneity, and sensitivity to RNA input amount were measured across operators using samples from multiple tumor types. The robustness of the assay was evaluated with the inclusion of adjacent non-tumor tissue. Results: The total standard deviation in anti-PD1 PS was < 5% of the score range with random error being the major source of variance. The assay was robust across the specified RNA input range and against the inclusion of non-tumor tissue. The major source of variability in Gx across multiple tumor types was associated with the tumors’ immune Gx signature rather than intra-tumor variability or even tumor type. Conclusions: The NanoString anti-PD1 Gx test is a robust assay, which profiles immune related Gx across multiple cancer types. The assay is well suited to clinical applications and its ability to identify responders to anti-PD1 therapy is being investigated in multiple indications in several studies.