ReviewJournal for immunotherapy of cancer2024
Biomarker development for PD-(L)1 axis inhibition: a consensus view from the SITC Biomarkers Committee.
Review in Journal for immunotherapy of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Humanized avian embryo models replicate an immune tumor environment for rapid immunotherapy studies.EMBO molecular medicine · 2026Article
- Peripheral blood biomarkers in PD-1/PD-L1 immunotherapy: distinguishing predictive from prognostic biomarkers.Frontiers in immunology · 2026Review
- Bioinformatics and artificial intelligence in genomic data analysis: current advances and future directions.Molecular genetics and genomics : MGG · 2025Review
- Article
- Optimizing Anti-PD1 Immunotherapy: An Overview of Pharmacokinetics, Biomarkers, and Therapeutic Drug Monitoring.Cancers · 2025Review
- SITC vision: Opportunities for deeper understanding of mechanisms of anti-tumor activity, toxicity, and resistance to optimize cancer immunotherapy.Journal for immunotherapy of cancer · 2025Article
- The baseline circulating immunophenotype characteristics associate with PD(L)-1 targeted treatment response, irae onset, and prognosis.Scientific reports · 2025Article
- Society for Immunotherapy of Cancer (SITC) consensus statement on essential biomarkers for immunotherapy clinical protocols.Journal for immunotherapy of cancer · 2025Article
- The genetic architecture of bone metastases: unveiling the role of epigenetic and genetic modifications in drug resistance.Cancer drug resistance (Alhambra, Calif.) · 2025Review
- Tumor-Infiltrating Immune Cells and HLA Expression as Potential Biomarkers Predicting Response to PD-1 Inhibitor Therapy in Stage IV Melanoma Patients.Biomolecules · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Therapies targeting the programmed cell death protein-1/programmed death-ligand 1 (PD-L1) (abbreviated as PD-(L)1) axis are a significant advancement in the treatment of many tumor types. However, many patients receiving these agents fail to respond or have an initial response followed by cancer progression. For these patients, while subsequent immunotherapies that either target a different axis of immune biology or non-immune combination therapies are reasonable treatment options, the lack of predictive biomarkers to follow-on agents is impeding progress in the field. This review summarizes the current knowledge of mechanisms driving resistance to PD-(L)1 therapies, the state of biomarker development along this axis, and inherent challenges in future biomarker development for these immunotherapies. Innovation in the development and application of novel biomarkers and patient selection strategies for PD-(L)1 agents is required to accelerate the delivery of effective treatments to the patients most likely to respond.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.