Histology-based Prediction of Therapy Response to Neoadjuvant Chemotherapy for Esophageal and Esophagogastric Junction Adenocarcinomas Using Deep Learning

Abstract

Background: Quantifying treatment response to gastroesophageal junction (GEJ) adenocarcinomas is crucial to provide optimal therapeutic strategy. Routinely taken tissue samples provide an opportunity to enhance existing PET/CT-based therapy response evaluation. Our objective was to investigate if deep learning algorithms are capable to predict the therapy response of GEJ patients to neoadjuvant chemotherapy based on histological tissue samples. Methods: This diagnostic study recruited 67 patients with GEJ I-III from the multicentric non-randomized MEMORI trial including 3 German university hospitals TUM (Munich), LMU (Munich), and UME (Essen). All patients underwent baseline PET/CT scans and esophageal biopsy before and 14-21 days after treatment initiation. Treatment response was defined as a ≥ 35% decrease in SUVmax from baseline. Several deep learning algorithms were developed to predict PET/CT-based responders and non-responders to neoadjuvant chemotherapy using digitized histopathological whole slide images. Results: The resulting models were trained on TUM (n=25 pre-therapy, n=47 on-therapy) patients and evaluated on our internal validation cohort from LMU and UME (n=17 pre-therapy, n=15 on-therapy). Compared with multiple architectures, the best pre-therapy network achieves an area under the precision-recall curve (AUPRC) of 0.81 (95% confidence interval (CI), 0.61-1.00), area under the precision-recall curve (AUPRC) of 0.82 (95% CI, 0.61-1.00), balanced accuracy of 0.78 (95% CI, 0.60-0.94), and a Matthews correlation coefficient (MCC) of 0.55 (95% CI, 0.18-0.88). The best on-therapy network achieves an AUROC of 0.84 (95% CI, 0.64-1.00), AUPRC of 0.82 (95% CI, 0.56-1.00), balanced accuracy of 0.80 (95% CI, 0.63-1.00), and MCC of 0.71 (95% CI, 0.38-1.00), solving a task beyond the pathologists' capabilities. Conclusions: The findings suggest that the networks can predict treatment response using WSI with high accuracy even pre-therapy, suggesting morphological tissue biomarkers. Subject to further validation, this could lead to earlier therapy intensification compared to current PET/CT diagnostic system for non-responder.

Competing Interest Statement

KLP reports personal fees from ABX outside the submitted work. KS reports her work at the advisory board of TRIMT GmbH. Wilko Weichert reports research grants from Roche, MSD, BMS, and AstraZeneca; Advisory board, lectures, and speaker bureaus from Roche, MSD, BMS, AstraZeneca, Pfizer, Merck, Lilly, Boehringer, Novartis, Takeda, Bayer, Janssen, Amgen, Astellas, Illumina, Eisai, Siemens, Agilent, ADC, GSK und Molecular Health. The work of J.T.S. is supported by the German Cancer Consortium (DKTK) and by the German Federal Ministry of Education and Research (BMBF; 01KD2206A/SATURN3). J.T.S. receives honoraria as a consultant or for continuing medical education presentations from AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Immunocore, MSD Sharp Dohme, Novartis, Roche/Genentech, and Servier. His institution receives research funding from Abalos Therapeutics, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eisbach Bio, and Roche/Genentech; he holds ownership and serves on the Board of Directors of Pharma15, all outside the submitted work. All other authors have declared no conflicts of interest.

Clinical Trial

NCT02287129

Clinical Protocols

https://clinicaltrials.gov/ct2/show/NCT02287129

Funding Statement

This work was supported by a grant from the Schäfersnolte-Gedächtnis-Stiftung. The Memori trial was funded by the German Cancer Consortium (DKTK). The funders had no role in the design and conduct of the study; collection, management analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. We thank the tissue-bank of Klinikum Rechts der Isar and TUM (MTBIO) for their excellent technical support.

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:

The Ethics Committee of University Hospital Rechts der Isar gave ethical approval for the MEMORI trial, which is also registered under NCT02287129.

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 participants of this study did not give written consent for their data to be shared publicly. There is no additional data available.

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