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Comparison of continuous measures across diagnostic PD-L1 assays in non-small cell lung cancer using automated image analysis.

ABSTRACT: Tumor programmed cell death ligand-1 (PD-L1) expression is a key biomarker to identify patients with non-small cell lung cancer who may have an enhanced response to anti-programmed cell death-1 (PD-1)/PD-L1 treatment. Such treatments are used in conjunction with PD-L1 diagnostic immunohistochemistry assays. We developed a computer-aided automated image analysis with customized PD-L1 scoring algorithm that was evaluated via correlation with manual pathologist scores and used to determine comparability across PD-L1 immunohistochemistry assays. The image analysis scoring algorithm was developed to quantify the percentage of PD-L1 positive tumor cells on scans of whole-slide images of archival tumor samples from commercially available non-small cell lung cancer cases, stained with four immunohistochemistry PD-L1 assays (Ventana SP263 and SP142 and Dako 22C3 and 28-8). The scans were co-registered and tumor and exclusion annotations aligned to ensure that analysis of each case was restricted to comparable tissue areas. Reference pathologist scores were available from previous studies. F1, a statistical measure of precision and recall, and overall percentage agreement scores were used to assess concordance between pathologist and image analysis scores and between immunohistochemistry assays. In total, 471 PD-L1-evalulable samples were amenable to image analysis scoring. Image analysis and pathologist scores were highly concordant, with F1 scores ranging from 0.8 to 0.9 across varying matched PD-L1 cutoffs. Based on F1 and overall percentage agreement scores (both manual and image analysis scoring), the Ventana SP263 and Dako 28-8 and 22C3 assays were concordant across a broad range of cutoffs; however, the Ventana SP142 assay showed very different characteristics. In summary, a novel automated image analysis scoring algorithm was developed that was highly correlated with pathologist scores. The algorithm permitted quantitative comparison of existing PD-L1 diagnostic assays, confirming previous findings that indicate a high concordance between the Ventana SP263 and Dako 22C3 and 28-8 PD-L1 immunohistochemistry assays.

SUBMITTER: Widmaier M

PROVIDER: S-EPMC7051919 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Comparison of continuous measures across diagnostic PD-L1 assays in non-small cell lung cancer using automated image analysis.

Widmaier Moritz M Wiestler Tobias T Walker Jill J Barker Craig C Scott Marietta L ML Sekhavati Farzad F Budco Alexei A Schneider Katrin K Segerer Felix J FJ Steele Keith K Rebelatto Marlon C MC

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc 20190916 3

Tumor programmed cell death ligand-1 (PD-L1) expression is a key biomarker to identify patients with non-small cell lung cancer who may have an enhanced response to anti-programmed cell death-1 (PD-1)/PD-L1 treatment. Such treatments are used in conjunction with PD-L1 diagnostic immunohistochemistry assays. We developed a computer-aided automated image analysis with customized PD-L1 scoring algorithm that was evaluated via correlation with manual pathologist scores and used to determine comparab ...[more]

PMID: 31527709

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Project description:Different clones, protocol conditions, instruments, and scoring/readout methods may pose challenges in introducing different PD-L1 assays for immunotherapy. The diagnostic accuracy of using different PD-L1 assays interchangeably for various purposes is unknown. The primary objective of this meta-analysis was to address PD-L1 assay interchangeability based on assay diagnostic accuracy for established clinical uses/purposes. A systematic search of the MEDLINE database using PubMed platform was conducted using "PD-L1" as a search term for 01/01/2015 to 31/08/2018, with limitations "English" and "human". 2,515 abstracts were reviewed to select for original contributions only. 57 studies on comparison of two or more PD-L1 assays were fully reviewed. 22 publications were selected for meta-analysis. Additional data were requested from authors of 20/22 studies in order to enable the meta-analysis. Modified GRADE and QUADAS-2 criteria were used for grading published evidence and designing data abstraction templates for extraction by reviewers. PRISMA was used to guide reporting of systematic review and meta-analysis and STARD 2015 for reporting diagnostic accuracy study. CLSI EP12-A2 was used to guide test comparisons. Data were pooled using random-effects model. The main outcome measure was diagnostic accuracy of various PD-L1 assays. The 22 included studies provided 376 2×2 contingency tables for analyses. Results of our study suggest that, when the testing laboratory is not able to use an Food and Drug Administration-approved companion diagnostic(s) for PD-L1 assessment for its specific clinical purpose(s), it is better to develop a properly validated laboratory developed test for the same purpose(s) as the original PD-L1 Food and Drug Administration-approved immunohistochemistry companion diagnostic, than to replace the original PD-L1 Food and Drug Administration-approved immunohistochemistry companion diagnostic with a another PD-L1 Food and Drug Administration-approved companion diagnostic that was developed for a different purpose.

Project description:BackgroundImmune checkpoint therapies (ICTs) targeting the programmed cell death-1 (PD1)/programmed cell death ligand-1 (PD-L1) pathway have improved outcomes for patients with non-small cell lung cancer (NSCLC), particularly those with high PD-L1 expression. However, the predictive value of manual PD-L1 scoring is imperfect and alternative measures are needed. We report an automated image analysis solution to determine the predictive and prognostic values of the product of PD-L1+ cell and CD8+ tumor infiltrating lymphocyte (TIL) densities (CD8xPD-L1 signature) in baseline tumor biopsies.MethodsArchival or fresh tumor biopsies were analyzed for PD-L1 and CD8 expression by immunohistochemistry. Samples were collected from 163 patients in Study 1108/NCT01693562, a Phase 1/2 trial to evaluate durvalumab across multiple tumor types, including NSCLC, and a separate cohort of 199 non-ICT- patients. Digital images were automatically scored for PD-L1+ and CD8+ cell densities using customized algorithms applied with Developer XD™ 2.7 software.ResultsFor patients who received durvalumab, median overall survival (OS) was 21.0 months for CD8xPD-L1 signature-positive patients and 7.8 months for signature-negative patients (p = 0.00002). The CD8xPD-L1 signature provided greater stratification of OS than high densities of CD8+ cells, high densities of PD-L1+ cells, or manually assessed tumor cell PD-L1 expression ≥25%. The CD8xPD-L1 signature did not stratify OS in non-ICT patients, although a high density of CD8+ cells was associated with higher median OS (high: 67 months; low: 39.5 months, p = 0.0009) in this group.ConclusionsAn automated CD8xPD-L1 signature may help to identify NSCLC patients with improved response to durvalumab therapy. Our data also support the prognostic value of CD8+ TILS in NSCLC patients who do not receive ICT.Trial registrationClinicalTrials.gov identifier: NCT01693562 . Study code: CD-ON-MEDI4736-1108. Interventional study (ongoing but not currently recruiting). Actual study start date: August 29, 2012. Primary completion date: June 23, 2017 (final data collection date for primary outcome measure).

Dataset Information

Comparison of continuous measures across diagnostic PD-L1 assays in non-small cell lung cancer using automated image analysis.

Publications

Comparison of continuous measures across diagnostic PD-L1 assays in non-small cell lung cancer using automated image analysis.

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