ArticleThe Journal of surgical research2020
Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk.
Article in The Journal of surgical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.
- Systematic review and feasibility study on pre-analytical factors and genomic analyses on archival formalin-fixed paraffin-embedded breast cancer tissue.Scientific reports · 2024Pooled it
- Frequent mutated B2M, EZH2, IRF8, and TNFRSF14 in primary bone diffuse large B-cell lymphoma reflect a GCB phenotype.Blood advances · 2021Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundBreast cancer (BC) risk assessment models are statistical estimates based on patient characteristics. We developed a gene expression assay to assess BC risk using benign breast biopsy tissue.
methodsA NanoString-based malignancy risk (MR) gene signature was validated for formalin-fixed paraffin-embedded (FFPE) tissue. It was applied to FFPE benign and BC specimens obtained from women who underwent breast biopsy, some of whom developed BC during follow-up to evaluate diagnostic capability of the MR signature. BC risk was calculated with MR score, Gail risk score, and both tests combined. Logistic regression and receiver operating characteristic curves were used to evaluate these 3 models.
resultsNanoString MR demonstrated concordance between fresh frozen and FFPE malignant samples (r = 0.99). Within the validation set, 563 women with benign breast biopsies from 2007 to 2011 were identified and followed for at least 5 y; 50 women developed BC (affected) within 5 y from biopsy. Three groups were compared: benign tissue from unaffected and affected patients and malignant tissue from affected patients. Kruskal-Wallis test suggested difference between the groups (P = 0.09) with trend in higher predicted MR score for benign tissue from affected patients before development of BC. Neither the MR signature nor Gail risk score were statistically different between affected and unaffected patients; combining both tests demonstrated best predictive value (AUC = 0.71).
conclusionsFFPE gene expression assays can be used to develop a predictive test for BC. Further investigation of the combined MR signature and Gail Model is required. Our assay was limited by scant cellularity of archived breast tissue.
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