Evidence map›Paper›PMID 42181284›Full record

ArticleiScience2026

A unified single-cell atlas of HNSCC: Toward characterizing HPV- and sex-associated TME variability.

Cristina Conde-Lopez, Divyasree Marripati, Maria Jose Besso, Mareike Roscher, Rui Han, Wahyu Wijaya Hadiwikarta, Moshe Elkabets, Jochen Hess, Ina Kurth

Abstract read
In one paragraph

Article in iScience, 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. Review
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.

Cristina Conde-LopezGerman Cancer Research Center Heidelberg (DKFZ), Radiooncology/Radiobiology, Heidelberg, Germany.
Divyasree MarripatiThe Shraga Segal Department of Microbiology, Immunology, and Genetics, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Maria Jose BessoGerman Cancer Research Center Heidelberg (DKFZ), Radiooncology/Radiobiology, Heidelberg, Germany.
Mareike RoscherGerman Cancer Research Center Heidelberg (DKFZ), Service Unit for Radiopharmaceuticals and Preclinical Studies, Heidelberg, Germany.
Rui HanDepartment of Otorhinolaryngology, Head and Neck Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Wahyu Wijaya HadiwikartaGerman Cancer Research Center Heidelberg (DKFZ), Radiooncology/Radiobiology, Heidelberg, Germany.
Moshe ElkabetsThe Shraga Segal Department of Microbiology, Immunology, and Genetics, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Jochen HessDepartment of Otorhinolaryngology, Head and Neck Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Ina KurthGerman Cancer Research Center Heidelberg (DKFZ), Radiooncology/Radiobiology, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Head and neck squamous cell carcinoma (HNSCC) is highly heterogeneous, with variations driven by human papillomavirus (HPV) status and sex. However, existing single-cell RNA sequencing (scRNA-seq) studies are often limited in sample size and lack standardized methodologies, limiting cross-study comparisons. To address this, we integrated scRNA-seq data from 78 patients (274,911 cells) across multiple studies, creating a unified HNSCC atlas that harmonizes annotations and enables robust tumor microenvironment (TME) analyses. Using STACAS for semi-supervised integration and automated annotation tools such as Ikarus and scGate, we improved tumor and immune cell classification. Leveraging our atlas, we identified HPV-specific shifts in immune and stromal composition, with HPV+ tumors enriched in adaptive immune cells and HPV- tumors showing more stromal and myeloid populations. Preliminary sex-stratified analyses suggested distinct microenvironmental patterns, warranting further investigation. This publicly available atlas provides a comprehensive framework for reproducibly studying HNSCC biology, improving patient stratification, and may help inform personalized therapies.

Indexed as

bioinformaticsbiological databasecancercomputational bioinformatics

Identifiers

PMID42181284
PMCPMC13191048

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LicenceCC BY
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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.