Evidence map›Paper›PMID 29973242›Full record

ArticleBreast cancer research : BCR2018

Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors.

Martin Sjöström, Johan Staaf, Patrik Edén, Fredrik Wärnberg, Jonas Bergh, Per Malmström, Mårten Fernö, Emma Niméus, Irma Fredriksson

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Article in Breast cancer research : BCR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  12. Machine Learning & Molecular Radiation Tumor Biomarkers.Seminars in radiation oncology · 2023
    Review
  13. Evolution-Informed Strategies for Combating Drug Resistance in Cancer.International journal of molecular sciences · 2023
    Review
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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.

Martin SjöströmFaculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund University, Lund, Sweden. Martin.Sjostrom@med.lu.se.ORCID 0000-0002-2629-9966
Johan StaafFaculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund University, Lund, Sweden.
Patrik EdénDepartment of Theoretical Physics and Computational Biology, Lund University, Lund, Sweden.
Fredrik WärnbergDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Jonas BerghDepartment of Oncology and Pathology, Cancer Center Karolinska, Karolinska Institutet, Stockholm, Sweden.
Per MalmströmFaculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund University, Lund, Sweden.
Mårten FernöFaculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund University, Lund, Sweden.
Emma NiméusFaculty of Medicine, Department of Clinical Sciences Lund, Oncology and Pathology, Lund University, Lund, Sweden.
Irma FredrikssonDepartment of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer.

methodsFresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel.

resultsDerived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response.

conclusionsOur targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer.

Indexed as

PrognosisBreast NeoplasmsCombined Modality TherapyFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMastectomy, SegmentalMiddle AgedNeoplasm ProteinsNeoplasm Recurrence, LocalRadiation ToleranceRadiotherapy, AdjuvantReceptors, EstrogenRisk FactorsTranscriptomeNeoplasm ProteinsReceptors, EstrogenBreast cancerGene expressionIpsilateral breast tumor recurrenceLocal recurrenceNanostringnCounterRadioresistanceRadiosensitivityRadiotherapy

Identifiers

PMID29973242
PMCPMC6033283

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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.