A live cell biosensor protocol for high-resolution screening of therapy-resistant cancer cells
Viral D. Oza, Colin S. Williams, Jessica S. Blackburn
Abstract
The Genetically Encoded Death Indicator (GEDI) is a ratiometric, dual-fluorescence biosensor that enables real-time detection of cell death through calcium influx. Originally developed for use in neurodegeneration models, GEDI can be applied to cancer cells to quantify therapy-induced death at single-cell resolution.
Introduction
Evasion of apoptosis is a hallmark of cancer and measuring apoptotic events is a key determinant of treatment response [1–3]. Programmed cell death can occur as early as 30 minutes after therapy exposure and is influenced by multiple intrinsic and extrinsic pathways, making precise measurement of cell death essential for identifying new vulnerabilities in cancer cells [4,5].
Materials and method
The protocol described in this peer-reviewed article is published on protocols.io(dx.doi.org/10.17504/protocols.io.eq2ly4d7qlx9/v1) and is included for printing purposes as S1 File with this article.
Results and discussion
This protocol demonstrates how to use the Genetically Encoded Death Indicator (GEDI) biosensor to measure therapy-induced cell death in cancer cells. We selected SF8628, a H3K27M pediatric diffuse midline glioma (pDMG) cell line due to its documented intratumoral heterogeneity and prior use in radiosensitization and xenograft studies [10–15]. GEDI was stably transduced into SF8628 cells and FACS enriched for high mApple expression using appropriate positive and negative controls (S3 Fig).
Acknowledgments
The authors acknowledge the University of Kentucky the Flow Cytometry and Immune Monitoring core for the use of their facilities. We thank Steven Finkbeiner (The Gladstone Institutes) for the GEDI plasmid.
Citation: Oza VD, Williams CS, Blackburn JS (2026) A live cell biosensor protocol for high-resolution screening of therapy-resistant cancer cells. PLoS One 21(2): e0343016. https://doi.org/10.1371/journal.pone.0343016
Editor: Shuo Qie, Tianjin Medical University Cancer Institute and Hospital: Tianjin Medical University Cancer Institute & Hospital, CHINA
Received: September 16, 2025; Accepted: January 30, 2026; Published: February 17, 2026
Copyright: © 2026 Oza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Data Availability Statement: All data underlying the findings are included within the manuscript and its Supporting Information files. Representative raw and post-processed imaging datasets, along with all analysis code, are publicly available in the GitHub repository “GEDI_Cancer”. Full raw imaging datasets are available from the corresponding author without restriction. Associated content io.protocol DOI: https://dx.doi.org/10.17504/protocols.io.eq2ly4d7qlx9/v1.
Funding: National Institutes of Health, Grant/Award Numbers R37CA227656 (to J.S.B.) and F99CA294265 (to V.D.O.) [https://www.nih.gov/] and the Kentucky Pediatric Cancer Research Trust Fund PON27282400002665 [https://www.chfs.ky.gov/agencies/dph/dpqi/cdpb/Pages/pcrtf.aspx]. This research is also supported by the Flow Cytometry and Immune Monitoring Shared Resource of the Markey Cancer Center (P30CA177558) [https://ukhealthcare.uky.edu/markey-cancer-center/research/srf/flow]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
