Accounting for intensity variation in image analysis of large-scale multiplexed clinical trial datasets

Abstract

Background: Tumour immunoprofiling captures tumour-microenvironment interactions and enables precision medicine. Multiplex immunofluorescence (mIF) imaging can provide comprehensive quantitative and spatial information for multiple immune markers. However, application at scale to clinical trial samples sourced from multiple institutions is challenging due to pre-analytical heterogeneity. Methods: We analysed 12'592 tissue microarray (TMA) spots from 3'545 colorectal cancers (CRC) sourced from more than 240 institutions in two clinical trials (QUASAR 2 and SCOT) stained for CD4, CD8, CD20, CD68, FoxP3, pan-cytokeratin and DAPI by mIF. TMA cores were multi-spectrally imaged by digital pathology and analysed by cell-based and pixel-based marker analysis. We developed and validated an adaptive thresholding method to account for inter- and intra-slide intensity variation in TMA analysis, compared the numerical results between analysis approaches and validated against the current gold standard of single-plex chromogenic immunohistochemistry (IHC). Results: Adaptive thresholding at a slide and spot level effectively ameliorated inter- and intra-slide intensity variation enabling high-throughput analysis of mIF-stained TMA cores by digital pathology and improving the image analysis results compared to methods using a single global threshold. Comparison of our mIF approach with CD8 IHC data derived from subsequent sections indicates the validity of our method (Spearman's rank correlation coefficients (SCC) between 0.63 and 0.66, p-value << 0.01). Evaluation of correlation between cell-based and pixel-based analysis results confirms equivalency (SCC > 0.8, p<< 0.01, except for CD20 in epithelium region) of both analytical approaches for precision immunoprofiling by mIF. Conclusions: This study reports an analytical approach to the largest multiparameter immunoprofiling study of clinical trial samples to date and establishes an adaptive thresholding method to account for inter- and intra-slide variation introduced by pre-analytical heterogeneity. This approach can enable the application of mIF immunoprofiling of clinical trial TMA datasets at scale.

Competing Interest Statement

DNC has participated in advisory boards for MSD and has received research funding on behalf of the TransSCOT consortium from HalioDx for analyses independent of this study. VHK has served as an invited speaker on behalf of Indica Labs, and has received project-based research funding from The Image Analysis Group and Roche outside of the submitted work. All other authors declare no competing interests.

Funding Statement

This study was funded by the Oxford NIHR Comprehensive Biomedical Research Centre (BRC), a Cancer Research UK (CRUK) Advanced Clinician Scientist Fellowship (C26642/A27963) to DC, CRUK award A25142 to the CRUK Glasgow Centre. V.H.K. acknowledges funding by the Promedica Foundation (F-87701-41-01). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. 

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethical approval for patient recruitment and sample collection in the SCOT and QUASAR 2 trial was obtained centrally and at all recruiting centers (REC reference number 07/S0703/136 and 04/MRE/11/18). Ethical approval for anonymised tumor molecular analysis was granted by Oxfordshire Research Ethics Committee B (REC 05\Q1605\66).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

The datasets pertaining to the SCOT trial used during the current study are available from the TransSCOT collaboration on reasonable request. Applications for analysis of TransSCOT samples are welcome and should be addressed to JH: Jennifer.Hay@glasgow.ac.uk. Datasets and samples from the QUASAR2 trial are available upon reasonable request and should be addressed to david.church@well.ox.ac.uk

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