Evidence map›Paper›PMID 42026129›Full record

ArticleNPJ precision oncology2026

Integrative immune subtyping of HNSCC reveals clinically relevant phenotypes and treatment-associated transitions.

Indu Khatri, Terezinha de Souza, Saskia D van Asten, Merzu Belete, Felipe A Vieira Braga, Merel Jongmans, Sriram Sridhar, Brandon W Higgs, Iris C R M Kolder

Abstract read
In one paragraph

Article in NPJ precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Indu KhatriTranslational Data Science, Genmab B.V., Utrecht, The Netherlands. inkh@genmab.com.
Terezinha de Souza *Translational Data Science, Genmab B.V., Utrecht, The Netherlands.
Saskia D van Asten *Translational Data Science, Genmab B.V., Utrecht, The Netherlands.
Merzu BeleteTranslational Data Science, Genmab Inc., Princeton, NJ, USA.
Felipe A Vieira BragaDiscovery Data Science, Genmab B.V., Utrecht, The Netherlands.
Merel JongmansTranslational Data Science, Genmab B.V., Utrecht, The Netherlands.
Sriram SridharTranslational Data Science, Genmab Inc., Princeton, NJ, USA.
Brandon W HiggsTranslational Data Science, Genmab Inc., Princeton, NJ, USA.
Iris C R M KolderTranslational Data Science, Genmab B.V., Utrecht, The Netherlands. iko@genmab.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Head and neck squamous cell carcinoma (HNSCC) shows marked heterogeneity in clinical behavior, treatment response, and immune contexture. Existing molecular and immune classification systems are often derived from small, homogeneous cohorts and lack integration of multimodal data, limiting clinical relevance. We performed an integrated multi-omics analysis of transcriptomic and genomic data (copy number alterations and single-nucleotide variants) from 1149 tumors across 1102 HNSCC patients spanning multiple treatment settings. Using Similarity Network Fusion (SNF) on immune-related gene profiles, we identified immune subtype clusters (ISCs) and characterized them through mutational, transcriptional, immune cell enrichment, hypoxia, and established molecular subtype analyses. Clinical associations, including progression-free survival, were evaluated in first-line and post-metastatic settings. Four ISCs were defined: ISC1, immune-cold and EMT-enriched; ISC2, immune-activated; ISC3, mixed immune-regulatory with stromal enrichment; and ISC4, immunosuppressed. These subtypes showed distinct clinical outcomes and differential responses to checkpoint inhibitors, chemotherapy, and combination therapies. Analysis of 44 patients with matched pre- and post-treatment tumors revealed dynamic immune-state transitions, with checkpoint inhibition promoting immune activation and chemotherapy enriching immunosuppressive signaling. This study establishes a clinically relevant immune subtyping framework for HNSCC that captures dynamic tumor-immune states linked to treatment response and survival, supporting its utility in guiding immune-based therapies.

Identifiers

PMID42026129
PMCPMC13282393

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Registered trials

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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.