Dickkopf-1 (DKK1) is a secreted modulator of Wnt signaling that is frequently overexpressed in tumors and associated with poor clinical outcomes. DKN-01 is a humanized monoclonal therapeutic antibody that binds DKK1 with high affinity and has demonstrated clinical activity in gastric/gastroesophageal junction (G/GEJ) patients with elevated tumoral expression of DKK1. Here we report on the validation of a DKK1 RNAscope chromogenic in situ hybridization assay to assess DKK1 expression in G/GEJ tumor tissue. To reduce pathologist time, potential pathologist variability from manual scoring and support pathologist decision making, a digital image analysis algorithm that identifies tumor cells and quantifies the DKK1 signal was developed. Following CLIA guidelines the DKK1 RNAscope chromogenic in situ hybridization assay and digital image analysis algorithm were successfully validated for sensitivity, specificity, accuracy, and precision. The DKK1 RNAscope assay in conjunction with the digital image analysis solution is acceptable for prospective screening of G/GEJ adenocarcinoma patients. The work described here will further advance the companion diagnostic development of our DKK1 RNAscope assay and could generally be used as a guide for the validation of RNAscope assays with digital image quantification.
Dickkopf-1 (DKK1) is a secreted modulator of Wnt signaling that is frequently overexpressed in tumors and associated with a poor prognosis. In this study we demonstrate an approach for clinically validating a RNAscope chromogenic in situ hybridization (CISH) assay for determining the level of DKK1 RNA in Gastric (G) and Gastroesophageal (GEJ) tumor tissues according to CLIA guidelines. This two-step process validated first the performance of the wet assay along with the ability of a pathologist to manually score the CISH signal according to a dot-based H-score paradigm, and second the ability of image analysis (IA) software (Flagship Biosciences) to unbiasedly and reproducibly quantify DKK1 staining in the same set of samples. The DKK1 CISH assay for manual scoring passed all pre-determined criteria of sensitivity, specificity, accuracy, and precision. 100% of the 40 evaluated G/GEJ tissues demonstrated acceptable staining in target tumor cells and absence in non-target cells. 100% of the evaluated tissues passed sensitivity with a broad dynamic range of signal expression across target cells, and negligible background staining. Reproducibility was measured by blinded pathology scoring of a serial subset of 12 cases, resulting in 11/12 (92%) with concordant DKK1 H-scores. Accuracy was assessed with a DKK1 qPCR assay on a 20-sample subset and a significant correlation with the H-score data was observed. The IA algorithm also passed all pre-determined criteria of sensitivity, specificity, accuracy, and precision. 36/40 samples (90%) passed analytical specificity with the IA algorithm correctly classifying staining on true cells belonging to the tumor. Failed samples were attributed to non-specific alkaline phosphatase activity, which in practice would be disregarded by the reviewing pathologist. 100% of samples passed the sensitivity criteria of appropriate cell identification and classification. IA precision compared H-scores across 3 days of staining, with 11/12 (92%) cases having concordant DKK1 H-scores and an ICC of 0.9009 (95% CI: 0.7117-0.9601). Digital H-scores were highly correlated to the validated manual H-scores of the 40-sample set (r = 0.72, p <0.0001). Taken together, these data demonstrate a clinically validated DKK1 RNAscope CISH laboratory-derived test (LDT) for manual and IA-assisted pathologist interpretation. The DKK1 RNAscope LDT is currently being applied as part of a phase 2 clinical study of DKN-01 in combination with tislelizumab to prospectively identify previously treated G/GEJ adenocarcinoma patients with elevated DKK1 tumor expression (NCT04363801). Citation Format: Charles Caldwell, Mike Kagey, Sofia Reitsma, Will Paces, Elizabeth Bueche, Vitria Adisetiyo, Roberto Gianani. Clinical validation of a Dickkopf-1 (DKK1) chromogenic in-situ hybridization (CISH) assay for manual and image-analysis assisted pathologist interpretation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 433.
PD-L1 (22C3) checkpoint inhibitor therapy represents a mainstay of modern cancer immunotherapy for non-small cell lung cancer (NSCLC). In vitro diagnostic (IVD) PD-L1 antibody staining is widely used to predict clinical intervention efficacy. However, pathologist interpretation of this assay is cumbersome and variable, resulting in poor positive predictive value concerning patient therapy response. To address this, we developed a digital assay (DA) termed Tissue Insight (TI) 22C3 NSCLC, for the quantification of PD-L1 in NSCLC tissues, including digital recognition of macrophages and lymphocytes. We completed clinical validation of this digital image analysis solution in 66 NSCLC patient samples, followed by concordance studies (comparison of PD-L1 manual and digital scores) in an additional 99 patient samples. We then combined this DA with three distinct immune cell recognition algorithms for detecting tissue macrophages, alveolar macrophages, and lymphocytes to aid in sample interpretation. Our PD-L1 (22C3) DA was successfully validated and had a scoring agreement (digital to manual) higher than the inter-pathologist scoring. Furthermore, the number of algorithm-identified immune cells showed significant correlation when compared with those identified by immunohistochemistry in serial sections stained by double immunofluorescence. Here, we demonstrated that TI 22C3 NSCLC DA yields comparable results to pathologist interpretation while eliminating the intra- and inter-pathologist variability associated with manual scoring while providing characterization of the immune microenvironment, which can aid in clinical treatment decisions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.