Evidence map›Paper›PMID 40361136›Full record

ArticleBreast cancer research : BCR2025

Association between transcriptomic metrics of exogenous antigen presentation and adaptive immunity with locoregional recurrence in localized estrogen receptor negative breast cancer: retrospective review of multi-institutional datasets.

Timothy J Robinson, Casey L Liveringhouse, Christopher Wilson, Sam Friedman, Justyn Nakashima, Matthew N Mills, Jacob D Purcell, Nicholas B Figura, Du Dongliang, Ram Thapa and 5 more

Abstract readMulticenter Study
In one paragraph

Article in Breast cancer research : BCR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

15 authors.

Timothy J RobinsonDepartment of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA.
Casey L LiveringhouseDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Christopher WilsonBiostatistics and Bioinformatics Shared Resource, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Sam FriedmanDepartment of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA.
Justyn NakashimaDepartment of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA.
Matthew N MillsDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Jacob D PurcellMichigan State University College of Human Medicine, East Lansing, MI, USA.
Nicholas B FiguraDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Du DongliangDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Ram ThapaBiostatistics and Bioinformatics Shared Resource, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Eric WelshBiostatistics and Bioinformatics Shared Resource, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Kamran A AhmedDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
G Daniel GrassDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Brooke L FridleyBiostatistics and Bioinformatics Shared Resource, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Roberto DiazDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA. Roberto.Diaz@Moffitt.Org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscriptomic features of breast cancer locoregional recurrence (LRR) remain poorly understood. We therefore sought to investigate transcriptomic features associated with LRR in newly diagnosed invasive breast tumors from our institutional dataset.

methodsTranscriptomic profiling was performed on 632 tumors from consecutive patients treated within our health system for newly diagnosed non-metastatic breast cancer. Univariable Cox models identified genes whose expression was associated with LRR (q-value < 0.05). Up-regulated (UR) genes were defined as hazard ratio (HR) > 1 and down-regulated (DR) genes were defined as HR < 1. Gene set enrichment analyses were performed for UR and DR gene sets and validated within two external cohorts of ER- tumors.

resultsWith a median follow-up of 7.6 years, we observed 38 LRRs: 28/481 (5.8%) in ER + and 10/151 (6.6%) in ER-. There were 43 UR and 7 DR genes associated with LRR in ER + tumors, while 417 UR and 1150 DR genes were associated with LRR in ER- tumors. UR genes in ER + tumors were enriched for roles in cell proliferation (q < 0.05). In contrast, LRR in ER- tumors was most strongly associated with DR genes enriched for MHC-II-mediated antigen presentation and T cell activation (q < 0.05). In external cohorts of ER- tumors, 97 significant DR genes (p < 0.05) were enriched for 18 pathways, including 5 pathways involved in MHC-II signaling, antigen presentation and T-cell activation.

conclusionsTranscriptomic patterns associated with LRR appear distinct between ER + and ER- tumors. In ER + tumors, LRR appears predominantly associated with proliferation, whereas ER- LRR suggests a robust pattern of suppressed antigen presentation via MHC-II.

Indexed as

Adaptive ImmunityAntigen PresentationBreast NeoplasmsNeoplasm Recurrence, LocalTranscriptomeAdultAgedBiomarkers, TumorDatasets as TopicFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedPrognosisReceptors, EstrogenBiomarkers, TumorReceptors, EstrogenBreast cancerEstrogen receptor negativeImmune responseLocoregional control

Identifiers

PMID40361136
PMCPMC12070507

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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.