Dataset Information

Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk.

ABSTRACT:

Background

Breast 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.

Methods

A 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.

Results

NanoString 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).

Conclusions

FFPE 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.

SUBMITTER: Sun J

PROVIDER: S-EPMC6900446 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Publications

Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk.

Sun James J Chen Dung-Tsa DT Li Jiannong J Sun Weihong W Yoder Sean J SJ Mesa Tania E TE Wloch Marek M Roetzheim Richard R Laronga Christine C Lee M Catherine MC

The Journal of surgical research 20190813

<h4>Background</h4>Breast 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.<h4>Methods</h4>A 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 di ...[more]

PMID: 31419640

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Project description:BackgroundIncreasing evidence showed that the clinical significance of the interaction between hypoxia and immune status in tumor microenvironment. However, reliable biomarkers based on the hypoxia and immune status in triple-negative breast cancer (TNBC) have not been well established. This study aimed to explore a gene signature based on the hypoxia and immune status for predicting prognosis, risk stratification, and individual treatment in TNBC.MethodsHypoxia-related genes (HRGs) and Immune-related genes (IRGs) were identified using the weighted gene co-expression network analysis (WGCNA) method and the single-sample gene set enrichment analysis (ssGSEA Z-score) with the transcriptomic profiles from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. Then, prognostic hypoxia and immune based genes were identified in TNBC patients from the METABRIC (N = 221), The Cancer Genome Atlas (TCGA) (N = 142), and GSE58812 (N = 107) using univariate cox regression model. A robust hypoxia-immune based gene signature for prognosis was constructed using the least absolute shrinkage and selection operator (LASSO) method. Based on the cross-cohort prognostic hypoxia-immune related gene signature, a comprehensive index of hypoxia and immune was developed and two risk groups with distinct hypoxia-immune status were identified. The prognosis value, hypoxia and immune status, and therapeutic response in different risk groups were analyzed. Furthermore, a nomogram was constructed to predict the prognosis for individual patients, and an independent cohort from the gene expression omnibus (GEO) database was used for external validation.ResultsSix cross-cohort prognostic hypoxia-immune related genes were identified to establish the comprehensive index of hypoxia and immune. Then, patients were clustered into high- and low-risk groups based on the hypoxia-immune status. Patients in the high-risk group showed poorer prognoses to their low-risk counterparts, and the nomogram we constructed yielded favorable performance to predict survival and risk stratification. Besides, the high-risk group had a higher expression of hypoxia-related genes and correlated with hypoxia status in tumor microenvironment. The high-risk group had lower fractions of activated immune cells, and exhibited lower expression of immune checkpoint markers. Furthermore, the ratio of complete response (CR) was greatly declined, and the ratio of breast cancer related events were significantly elevated in the high-risk group.ConclusionThe hypoxia-immune based gene signature we constructed for predicting prognosis was developed and validated, which may contribute to the optimization of risk stratification for prognosis and personalized treatment in TNBC patients.

Project description:ImportanceAmong patients who undergo the 21-gene assay (21-GA), 39% to 67% receive an intermediate risk result and may receive ambiguous treatment guidance. The 70-gene signature assay (70-GS) may be associated with physicians' treatment decisions in this population with early breast cancer.ObjectiveTo determine whether 70-GS findings are associated with physicians' decisions about adjuvant treatment and confidence in their recommendations and to evaluate the dichotomous (high- vs low-risk) and continuous distribution of 70-GS indices among this group of patients with intermediate risk.Design, setting, and participantsThe Prospective Study of MammaPrint in Breast Cancer Patients With an Intermediate Recurrence Score (PROMIS trial) was an impact study conducted from May 20, 2012, through December 31, 2015, that enrolled 840 patients with early-stage breast cancer and a 21-gene assay recurrence score of 18 to 30. Patients were treated in 58 US institutions.InterventionsThe 70-GS result was given to physicians before adjuvant treatment.Main outcomes and measuresChange in physician treatment decision before vs after receiving the 70-GS result. With a treatment change of greater than 20%, the odds ratio (OR) was applied.ResultsAmong the 840 patients who underwent 70-GS classification (mean age, 59 years; range, 27-93 years), 374 (44.5%) had a low-risk and 466 (55.5%) had a high-risk result. The distribution of 70-GS indices did not correlate with recurrence score within the 21-GA intermediate range, with 70-GS low- and high-risk patients observed at every recurrence score. A significant change in adjuvant treatment was associated with receiving the 70-GS classifications with an OR of 0.64 (95% CI, 0.50-0.82; McNemar test, P < .001) for all patients. Among the low-risk patients, 108 of 374 (28.9%) had chemotherapy removed from their treatment recommendation; among the high-risk patients, 171 of 466 (36.7%) had chemotherapy added. Results of the 70-GS were associated with the physician's adjuvant treatment recommendation; 409 high-risk patients (87.8%) were recommended to receive adjuvant chemotherapy, and 339 low-risk patients (90.6%) were recommended no chemotherapy. Physicians reported having greater confidence in their treatment recommendation in 660 cases (78.6%) based on 70-GS results.Conclusions and relevanceThe 70-GS provides clinically actionable information regarding patients classified as intermediate risk by the 21-GA and was associated with a change in treatment decision in 282 of these patients (33.6%). Chemotherapy was added or withheld by the treating physician based on the results of the 70-GS test. Physicians reported more confidence with their treatment recommendation after receiving 70-GS results.

Dataset Information

Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk.

Background

Methods

Results

Conclusions

Publications

Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk.

Similar Datasets

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