Evidence map›Paper›PMID 35338086›Full record

ArticleJournal for immunotherapy of cancer2022

DNA methylation profiles differ in responders versus non-responders to anti-PD-1 immune checkpoint inhibitors in patients with advanced and metastatic head and neck squamous cell carcinoma.

Angelika Martina Starzer, Gerwin Heller, Erwin Tomasich, Thomas Melchardt, Katharina Feldmann, Teresa Hatziioannou, Stefan Traint, Christoph Minichsdorfer, Ursula Schwarz-Nemec, Maja Nackenhorst and 4 more

Open access · goldAbstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.3field-weighted citation impact, top 10% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 1 country.

Angelika Martina StarzerDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-5867-8461
Gerwin HellerDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-8742-5631
Erwin TomasichDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Thomas MelchardtLaboratory for Immunological and Molecular Cancer Research, Department of Internal Medicine III with Hematology, Medical Oncology, Hemostaseology, Infectious Diseases, Rheumatology, Oncologic Center, Paracelsus Medical University Salzburg, Salzburg, Austria.
Katharina FeldmannDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Teresa HatziioannouDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Stefan TraintDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Christoph MinichsdorferDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Ursula Schwarz-NemecDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
Maja NackenhorstDepartment of Pathology, Medical University of Vienna, Vienna, Austria.
Leonhard MüllauerDepartment of Pathology, Medical University of Vienna, Vienna, Austria.
Matthias PreusserDepartment of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Anna Sophie Berghoff *Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria anna.berghoff@meduniwien.ac.at.ORCID 0000-0001-9379-6797
Thorsten Fuereder *Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria.
Medical University of Vienna · ATParacelsus Medical University · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiomarkers for response prediction to anti-programmed cell death 1 (PD-1) immune checkpoint inhibitors (ICI) in patients with head and neck squamous cell carcinoma (HNSCC) are urgently needed for a personalized therapy approach. We investigated the predictive potential of inflammatory parameters and DNA methylation profiling in patients with HNSCC treated with anti-PD-1 ICI.

methodsWe identified patients with HNSCC that were treated with anti-PD-1 ICI therapy in the recurrent or metastatic setting after progression to platinum-based chemotherapy in two independent centers. We analyzed DNA methylation profiles of >850.000 CpG sites in tumor specimens of these patients by Infinium MethylationEPIC microarrays, immune cell density in the tumor microenvironment (CD8, CD3, CD45RO, forkhead box P3 (FOXP3), CD68), PD-1 and programmed cell death ligand 1 (PD-L1) expression by immunohistochemistry, and blood inflammation markers (platelet-to-lymphocyte ratio, leucocyte-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio). DNA methylation profiles and immunological markers were bioinformatically and statistically correlated with radiological response to anti-PD-1 ICI.

results37 patients with HNSCC (median age of 62 years; range 49-83; 8 (21.6%) women, 29 (78.4%) men) were included (Center 1 N=26, 70.3%; Center 2 N=11, 29.7%). Median number of prior systemic therapies was 1 (range 1-4). Five out of 37 (13.5%) patients achieved an objective response to ICI. Median progression-free survival and median overall survival times were 3.7 months (range 0-22.9) and 9.0 months (range 0-38.8), respectively. Microarray analyses revealed a methylation signature including both hypomethylation and hypermethylation which was predictive for response to ICI and included several genes involved in cancer-related molecular pathways. Over-represented differentially methylated genes between responders and non-responders were associated with 'Axon guidance', 'Hippo signaling', 'Pathways in cancer' and 'MAPK signaling'. A statistically significant correlation of PD-L1 expression and response was present (p=0.0498).

conclusionsOur findings suggest that tumor DNA methylation profiling may be useful to predict response to ICI in patients with HNSCC.

Indexed as

B7-H1 AntigenHead and Neck NeoplasmsAgedAged, 80 and overDNA MethylationFemaleHumansImmune Checkpoint InhibitorsMaleMiddle AgedProgrammed Cell Death 1 ReceptorSquamous Cell Carcinoma of Head and NeckTumor MicroenvironmentB7-H1 AntigenImmune Checkpoint InhibitorsProgrammed Cell Death 1 ReceptorBiomarkers, TumorHead and Neck NeoplasmsImmunotherapyTranslational Medical ResearchTumor Microenvironment

Identifiers

PMID35338086
PMCPMC8961155
OpenAlexW4220690349

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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.