Evidence map›Paper›PMID 40065328›Full record

ArticleJournal of experimental & clinical cancer research : CR2025

Extraction of a stromal metastatic gene signature in breast cancer via spatial profiling.

Giorgio Bertolazzi, Valeria Cancila, Davide Vacca, Beatrice Belmonte, Daniele Lecis, Parsa Sirati Moghaddam, Arianna Di Napoli, Mario Paolo Colombo, Giancarlo Pruneri, Giannino Del Sal and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Giorgio Bertolazzi *Department of Medicine and Surgery, Kore University of Enna, Enna, Italy.
Valeria Cancila *Tumor Immunology Unit, Department of Health Sciences, University of Palermo, Palermo, Italy.
Davide VaccaTumor Immunology Unit, Department of Health Sciences, University of Palermo, Palermo, Italy.
Beatrice BelmonteTumor Immunology Unit, Department of Health Sciences, University of Palermo, Palermo, Italy.
Daniele LecisMolecular Immunology Unit, Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
Parsa Sirati MoghaddamTumor Immunology Unit, Department of Health Sciences, University of Palermo, Palermo, Italy.
Arianna Di NapoliDepartment of Clinical and Molecular Medicine, Sant' Andrea Hospital, Sapienza University of Rome, Rome, Italy.
Mario Paolo ColomboMolecular Immunology Unit, Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
Giancarlo PruneriDepartment of Diagnostic Innovation, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy.
Giannino Del SalAdvanced Pathology Laboratory, IFOM ETS, the AIRC Institute of Molecular Oncology, Via Adamelllo 16, Milan, 20239, Italy.
Giorgio ScitaAdvanced Pathology Laboratory, IFOM ETS, the AIRC Institute of Molecular Oncology, Via Adamelllo 16, Milan, 20239, Italy.
Matteo FassanDepartment of Medicine, Surgical Pathology & Cytopathology Unit, University of Padua, Padua, Italy.
Andrea Vecchione *Department of Clinical and Molecular Medicine, Sant' Andrea Hospital, Sapienza University of Rome, Rome, Italy.
Silvio Bicciato *Department of Molecular Medicine, University of Padua, Padua, Italy.
Claudio Tripodo *Advanced Pathology Laboratory, IFOM ETS, the AIRC Institute of Molecular Oncology, Via Adamelllo 16, Milan, 20239, Italy. claudio.tripodo@ifom.eu.

Funding

Fondazione AIRC per la ricerca sul cancro ETS 22759
6 · The paper itself

Abstract

backgroundThe identification of molecular features characterizing metastatic disease is a critical area of oncology research, as metastatic foci often exhibit distinct biological behaviors compared to primary tumors. While the focus has largely been on the neoplastic cells themselves, the characterization of the associated stroma remains largely underexplored, with significant implications for understanding metastasis. MAIN BODY: By employing spatially resolved transcriptomics, we analyzed the transcriptional features of primary breast adenocarcinoma and its associated metastatic foci, on a representative set of microregions. We identified a stromal metastatic (Met) signature, which was subsequently validated across transcriptomic reference human breast cancer (BC) datasets and in spatial transcriptomics of a murine model.

conclusionWe discuss the potential of a stromal Met signature to pinpoint metastatic breast cancer, serving as a prognostic tool that can provide a foundation for the exploration of tumor-extrinsic molecular hallmarks of BC metastatic foci.

Indexed as

Breast NeoplasmsStromal CellsTranscriptomeAnimalsBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiceNeoplasm MetastasisBiomarkers, TumorMetastatic diseasePrognostic biomarkerSpatial transcriptomicsStromal microenvironment

Identifiers

PMID40065328
PMCPMC11892262

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.