Abstract

Gastric adenocarcinoma (GAd) is the third leading cause of cancer-related deaths worldwide. Most patients require perioperative chemotherapy, yet methods to accurately predict responses to therapy are lacking. Thus, patients may be unnecessarily exposed to considerable toxicities. Here, we present a novel methodology using patient-derived organoids (PDOs) that rapidly and accurately predicts the chemotherapy efficacy for GAd patients.

Methods: Endoscopic GAd biopsies were obtained from 19 patients, shipped overnight, and PDOs were developed within 24 h. Drug sensitivity testing was performed on PDO single-cells with current standard-of-care systemic GAd regimens and cell viability was measured. Whole exome sequencing was used to confirm the consistency of tumor-related gene mutations and copy number alterations between primary tumors, PDOs, and PDO single-cells.

Results: Overall, 15 of 19 biopsies (79%) were appropriate for PDO creation and single-cell expansion within 24 h of specimen collection and overnight shipment. With our PDO single-cell technique, PDOs (53%) were successfully developed. Subsequently, two PDO lines were subjected to drug sensitivity testing within 12 days from initial biopsy procurement. Drug sensitivity assays revealed unique treatment response profiles for combination drug regimens in both of the two unique PDOs, which corresponded with the clinical response.

Conclusions: The successful creation of PDOs within 24 h of endoscopic biopsy and rapid drug testing within 2 weeks demonstrate the feasibility of our novel approach for future applications in clinical decision making. This proof of concept sets the foundation for future clinical trials using PDOs to predict clinical responses to GAd therapies.

Document Type

Article

Publication Date

6-2023

Notes/Citation Information

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Digital Object Identifier (DOI)

https://doi.org/10.3390/cancers15113036

Funding Information

This research was supported by the John Wayne Cancer Institute Research Foundation pilot award, NIH grants P30CA177558 (UK Markey Cancer Center Biospecimen Procurement and Translational Pathology Shared Resource Facility and Biostatistics and Bioinformatics Shared Resource Facility), and training grant T32CA160003 (H.G.M. and M.M.H.).

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