ArticleJournal for immunotherapy of cancer2021
Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors.
Article in Journal for immunotherapy of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 41 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Investigation of the Timely-coordinated Therapy of Patients With Metastatic Cancer by Radiotherapy Together With Immune Checkpoint Inhibition
Immune Biomarker Study for Head and Neck Cancer
Immune Biomarker Study for Salivary Gland Carcinoma
Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Monocyte-related markers as predictors of immune checkpoint inhibitor efficacy and immune-related adverse events: a systematic review and meta-analysis.Cancer metastasis reviews · 2025Pooled it
- Circulating immune cell profiling in advanced cervical and endometrial cancer patients treated with PD-1 blockade, radiotherapy, and immune modulation in the PRIMMO trial.Frontiers in immunology · 2026Trial
- Induction chemoimmunotherapy followed by CD8+ immune cell-based patient selection for chemotherapy-free radioimmunotherapy in locally advanced head and neck cancer.Journal for immunotherapy of cancer · 2022Trial
- Low Dose Radiation Therapy Induces Long-Lasting Reduction of Pain and Immune Modulations in the Peripheral Blood - Interim Analysis of the IMMO-LDRT01 Trial.Frontiers in immunology · 2021Trial
- Neutrophil-driven immunosuppression in cancer.Cell insight · 2026Review
- Exploratory immunomonitoring during radiochemotherapy in HNSCC and machine-learning reveal immune parameters associated with disease-free survival.NPJ precision oncology · 2026Article
- Circulating proteins as biomarkers of response to cancer immunotherapy (Review).International journal of oncology · 2026Review
- Targeting the cytokine-epigenetic axis: a new paradigm and prospects for disease treatment.European cytokine network · 2026Review
- From Berry to Bedside: Translational Potential of Berry-Derived Phytochemicals in HNSCC.Molecules (Basel, Switzerland) · 2026Review
- Peripheral blood biomarkers for predicting response to PD-1/PD-L1 inhibitors.Biomarker research · 2026Review
- Article
- Artificial Intelligence for Predicting Immunotherapy Efficacy in Non-Small Cell Lung Cancer.Journal of inflammation research · 2026Review
- Combination of ataxia telangiectasia and Rad3-related inhibition with ablative radiotherapy remodels the tumor microenvironment and enhances immunotherapy response in lung cancer.Cancer immunology, immunotherapy : CII · 2024Article
- Peripheral immune biomarkers for immune checkpoint inhibition of solid tumours.Clinical and translational medicine · 2024Review
- Translational Frontiers and Clinical Opportunities of Immunologically Fitted Radiotherapy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Review
- Deep Learning Based on Computed Tomography Predicts Response to Chemoimmunotherapy in Lung Squamous Cell Carcinoma.Aging and disease · 2024Article
- Machine Learning-assisted immunophenotyping of peripheral blood identifies innate immune cells as best predictor of response to induction chemo-immunotherapy in head and neck squamous cell carcinoma - knowledge obtained from the CheckRad-CD8 trial.Neoplasia (New York, N.Y.) · 2024Article
- Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy.BMJ oncology · 2024Article
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Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis.
methodsA total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients' peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status.
resultsWhole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14
conclusionOur study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood. TRIAL REGISTRATION NUMBER: NCT03453892.
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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.