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Updated: May 9, 2026
07:42
Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
Published on: February 7, 2021
Acquired Resistance to Immune Checkpoint Inhibitors Across Tumor Types: A Reconstructed Individual Patient Data
Yago Garitaonaindia1, Rikke Andersen1, Mario Presti1
11National Center for Cancer Immune Therapy (CCIT-DK), Copenhagen University Hospital, Herlev and Gentofte, Herlev, Denmark.
Summary
Most patients who initially benefit from cancer immunotherapy develop acquired resistance to immunotherapy (ARI) within 3 years. The strength of the initial antitumor response, not tumor type, predicts ARI incidence.
Area of Science:
- Oncology
- Immunotherapy
- Cancer Research
Background:
- Immune checkpoint inhibitors (CPIs) offer lasting remission for some cancer patients.
- Acquired resistance to immunotherapy (ARI) is disease progression after initial CPI benefit.
- The incidence of ARI across tumor types is largely unknown.
Purpose of the Study:
- To estimate the overall incidence of ARI across various tumor types.
- To examine the association between ARI and initial tumor response to CPIs.
Main Methods:
- Pooled analysis of progression-free survival (PFS) curves from 41 phase III CPI trials in solid tumors.
- Included 15,199 patients across 11 tumor types with an overall response rate (ORR) ≥20%.
- Used PFS ≥6 months as a proxy for response, aligning with the Society for Immunotherapy of Cancer (SITC) definition of ARI.
Main Results:
- The estimated pan-cancer ARI rate was 73.5% at 3 years, varying from 25.4% to 83.1% across tumor types.
- Approximately 1 million patients globally may develop ARI annually.
- Complete response (CR), partial response (PR), and stable disease (SD) rates correlated with ARI, indicating response strength is key.
Conclusions:
- A significant proportion of patients responding to CPIs develop ARI.
- The variability in ARI incidence is explained by the initial antitumor response (CR, PR, SD rates).
- The strength of the antitumor response, rather than tumor histology, predicts ARI rates.
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