Evidence map›Paper›PMID 40221527›Full record

ArticleScientific reports2025

Interplay between MRI radiomics and immune gene expression signatures in oral squamous cell carcinoma.

Anna Corti, Deborah Lenoci, Valentina D A Corino, Davide Mattavelli, Marco Ravanelli, Tito Poli, Stefano Cavalieri, Lisa Licitra, Loris De Cecco, Luca Mainardi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. 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

10 authors.

Anna CortiDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, Milan, 20133, Italy. anna.corti@polimi.it.
Deborah LenociIntegrated Biology of Rare Tumors, Department of Research, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy.
Valentina D A CorinoDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, Milan, 20133, Italy.
Davide MattavelliUnit of Otorhinolaryngology-Head and Neck Surgery, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, ASST Spedali Civili of Brescia, University of Brescia, Brescia, Italy.
Marco RavanelliUnit of Radiology, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, ASST Spedali Civili of Brescia, University of Brescia, Brescia, Italy.
Tito PoliMaxillo-Facial Surgery Division, Head and Neck Department, University Hospital of Parma, Parma, Italy.
Stefano CavalieriHead and Neck Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Lisa LicitraHead and Neck Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Loris De Cecco *Integrated Biology of Rare Tumors, Department of Research, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy.
Luca Mainardi *Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, Milan, 20133, Italy.

Funding

Associazione Italiana Ricerca Cancro IG23573National Plan for NRRP Complementary Investments PNC0000003
6 · The paper itself

Abstract

With the advances in immunotherapy and the challenge of poor responsiveness in oral squamous cell carcinoma (OSCC) patients, understanding the tumor microenvironment is crucial. Radiogenomics offers the potential to provide pre-operative, non-invasive image-derived immune biomarkers. To this aim, the present study explores the capability of MRI-based radiomics to describe patients' immune state in OSCC. Seven MRI-based radiomic, 29 immune-related gene expression signatures were computed and deconvolution analysis was performed for a subset of OSCC from the BD2Decide database. A correlation-driven analysis identified key associations between radiomic and immune-related signatures and cell populations. Radiomic classifiers of the gene expression signatures were then developed to evaluate their capability to stratify patients based on immune status. MRI-based radiomic models showed promising results in predicting a gene expression signature associated with significant prognostic value for HNSCC patients who underwent radiotherapy (AUC = 0.92), suggesting these models' potential in distinguishing radioresistant from radiosensitive patients, aiding treatment decisions. Additionally, radiomic signatures reflected immune infiltrating cells in our cohort (M1, CD8 + T, B cells). MRI-radiomic signatures and associated models could become non-invasive methods to evaluate the prognosis and treatment choice in OSCC patients. Based on our promising results, and upon external validation, MRI-radiomics could enhance personalized medicine approaches.

Indexed as

Carcinoma, Squamous CellMagnetic Resonance ImagingMouth NeoplasmsSquamous Cell Carcinoma of Head and NeckTranscriptomeAgedBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisRadiomicsTumor MicroenvironmentBiomarkers, TumorCluster analysisHead and neck cancerMagnetic resonance imagingRadiogenomicRadiomic featuresTranscriptomic signaturesTumor microenvironment

Identifiers

PMID40221527
PMCPMC11993570

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.