Dataset Information

A Five-Gene-Pair-Based Prognostic Signature for Predicting the Relapse Risk of Early Stage ER+ Breast Cancer.

ABSTRACT: About 20-30% of early-stage breast cancer patients suffer relapses after surgery. To identify such high-risk patients, many signatures have been reported, but they lack robustness in data measured on different platforms. Here, we developed a signature which is robust across multiple profiling platforms, and identified reproducible omics features characterizing metastasis of estrogen receptor (ER)-positive breast cancer from the Gene Expression Omnibus database with the aid of the signature. Based on the stable within-sample relative expression orderings (REOs), we constructed a signature consisting of five gene pairs, named 5-GPS, whose REOs were significantly correlated with relapse-free survival using the univariate Cox regression model. Using 5-GPS, patients were classified into the low-risk and high-risk groups. Patients in the high-risk group have worse survival compared to those in the low-risk group using Kaplan-Meier curve analysis with the log-rank test. Applying 5-GPS to the RNA-sequencing data of stage I-IV breast cancer samples archived in The Cancer Genome Atlas (TCGA), we found that the proportion of the high-risk patients increases with the stage. The proposed REO-based signature shows potential in identifying early-stage ER+ breast cancer patients with high risk of relapse after surgery.

SUBMITTER: Li N

PROVIDER: S-EPMC7658391 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Five-Gene-Pair-Based Prognostic Signature for Predicting the Relapse Risk of Early Stage ER+ Breast Cancer.

Li Na N Cai Hao H Song Kai K Guo You Y Liang Qirui Q Zhang Jiahui J Chen Rou R Li Jing J Wang Xianlong X Guo Zheng Z

Frontiers in genetics 20201029

About 20-30% of early-stage breast cancer patients suffer relapses after surgery. To identify such high-risk patients, many signatures have been reported, but they lack robustness in data measured on different platforms. Here, we developed a signature which is robust across multiple profiling platforms, and identified reproducible omics features characterizing metastasis of estrogen receptor (ER)-positive breast cancer from the Gene Expression Omnibus database with the aid of the signature. Base ...[more]

PMID: 33193655

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Project description:ImportanceCurrent treatment cures most cases of early-stage, primary breast cancer. However, better techniques are required to identify which patients are at risk of relapse.ObjectiveTo assess the clinical validity of molecular relapse detection with circulating tumor DNA (ctDNA) analysis in early-stage breast cancer.Design, setting, and participantsThis prospective, multicenter, sample collection, validation study conducted at 5 United Kingdom medical centers from November 24, 2011, to October 18, 2016, assessed patients with early-stage breast cancer irrespective of hormone receptor and ERBB2 (formerly HER2 or HER2/neu) status who were receiving neoadjuvant chemotherapy followed by surgery or surgery before adjuvant chemotherapy. The study recruited 170 women, with mutations identified in 101 patients forming the main cohort. Secondary analyses were conducted on a combined cohort of 144 patients, including 43 patients previously analyzed in a proof of principle study.InterventionsPrimary tumor was sequenced to identify somatic mutations, and personalized tumor-specific digital polymerase chain reaction assays were used to monitor these mutations in serial plasma samples taken every 3 months for the first year of follow-up and subsequently every 6 months.Main outcomes and measuresThe primary end point was relapse-free survival analyzed with Cox proportional hazards regression models.ResultsIn the main cohort of 101 female patients (mean [SD] age, 54 [11] years) with a median follow-up of 35.5 months (interquartile range, 27.9-43.0 months), detection of ctDNA during follow-up was associated with relapse (hazard ratio, 25.2; 95% CI, 6.7-95.6; P < .001). Detection of ctDNA at diagnosis, before any treatment, was also associated with relapse-free survival (hazard ratio, 5.8; 95% CI, 1.2-27.1; P = .01). In the combined cohort, ctDNA detection had a median lead time of 10.7 months (95% CI, 8.1-19.1 months) compared with clinical relapse and was associated with relapse in all breast cancer subtypes. Distant extracranial metastatic relapse was detected by ctDNA in 22 of 23 patients (96%). Brain-only metastasis was less commonly detected by ctDNA (1 of 6 patients [17%]), suggesting relapse sites less readily detectable by ctDNA analysis.Conclusions and relevanceThe findings suggest that detection of ctDNA during follow-up is associated with a high risk of future relapse of early-stage breast cancer. Prospective studies are needed to assess the potential of molecular relapse detection to guide adjuvant therapy.

Project description:Background Currently, no gene-expression signature (GES) established from node-positive cohorts, able to predict breast cancer evolution after systemic adjuvant chemotherapy, exists. Methods Gene-expression profiles of 252 node-positive patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array representing 5,776 distinct genes. Findings In the training cohort, we established a 38-GES for the purpose of predicting time to distant metastasis. The 38-GES yielded unadjusted hazard ratio of 4.86 (95% CI=2.76-8.56). Even when adjusted with the two best clinicopathological prognostic scoring: NPI and Adjuvant!, 38-GES HR were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved mostly NPI and Adjuvant! intermediate-risk classified patients. NPI intermediate-risk patients (7-year MFS=87.2%) were divided into 2/3 (7-year MFS=95.5%) close to NPI low-risk group and 1/3 (7-year MFS=69.3%) close to NPI high-risk group (HR=6.97 [2.51-19.36]). Adjuvant! intermediate-risk patients (7-year MFS=88.0%) were divided into 2/3 (7-year MFS=94.8%) close to Adjuvant! low-risk group and 1/3 (7-year MFS=71.7%) close to Adjuvant! high-risk group (HR=5.31 [5.38-11.87]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n=224) generated from different microarray platforms. The 38-GES yielded unadjusted HR=2.95 (1.74-5.01). Furthermore, 38-GES showed performance in supplementary cohorts with different lymph-node status and endpoint (1,031 new patients). Interpretation The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and especially powerful to separate NPI or Adjuvant! intermediate-risk node-positive patients. Keywords: disease-state analysis 252 breast cancer patients at diagnosis examined with spotted cDNA nylon membrane. Patient details: PACS01x are 2 parts of a clinical trial : PACS01A : patients had received 6 cycles of FEC100 PACS01B : patients had received 3 cycles of FEC100 then 3 cycles of Docetaxel CCRG are patients from our local cancer center (Cancer Center René Gauducheau) included with the same criteria as PACS01A (6 cycles of FEC100).

Dataset Information

A Five-Gene-Pair-Based Prognostic Signature for Predicting the Relapse Risk of Early Stage ER+ Breast Cancer.

Publications

A Five-Gene-Pair-Based Prognostic Signature for Predicting the Relapse Risk of Early Stage ER+ Breast Cancer.

Similar Datasets

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