Dataset Information

Clinical Application of Next-Generation Sequencing in Patients With Breast Cancer: Real-World Data.

ABSTRACT:

Purpose

Next-generation sequencing (NGS)-based tumor panel testing has been reimbursed by the Korean government since 2017. We evaluated the use of NGS-based tumor panel testing in real-world clinical practice, focusing on molecular profiling (MP)-guided breast cancer treatment.

Methods

A total of 137 breast cancer patients underwent NGS panel testing between December 2017 and July 2020 at Seoul National University Bundang Hospital (SNUBH). Samples from patients were profiled using an in-house SNUBH pan-cancer panel. Sixty-four patients were profiled on SNUBH Pan_Cancer v1.0, targeting 89 genes, while 73 patients were profiled on SNUBH Pan_Cancer v2.0, targeting 546 genes.

Results

Breast cancer subtypes included hormone receptor+/human epidermal growth factor receptor 2 (HER2)- (n = 87), triple-negative (n = 44), and HER2+ (n = 6). Most patients had locally advanced or metastatic cancers (92%). Approximately 92% (126/137) of the patients had significant genomic alterations (tiers I and II), and 62% (85/137) had targetable genomic alterations. The most common targetable genomic alterations were PIK3CA (39%) and ESR1 mutations (9%), followed by ERBB2 (7%), PTEN (7%), BRCA2 (6%), and BRCA1 mutations (4%). Of the 81 patients with locally advanced/metastatic breast cancer with targetable genomic alterations, 6 (7.4%) received MP-guided treatments, including PARP inhibitor (n = 4), ERBB2-directed therapy (n = 1), and PI3K inhibitor (n = 1). Among these 6 patients, 4 participated in clinical trials, 1 underwent treatment at their own expense, and 1 received drugs through an expanded access program. The remaining 66 patients (81%) with targetable genomic alteration did not receive MP-guided treatment due to lack of matched drugs and/or clinical trials, poor performance status, and/or financial burden.

Conclusion

NGS panel testing allowed MP-guided treatment in only 4.7% (6/127) of patients with advanced breast cancer in a real-world setting. The availability of matched drugs is critical for the realistic implementation of personalized treatment.

SUBMITTER: Suh KJ

PROVIDER: S-EPMC9629971 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

Clinical Application of Next-Generation Sequencing in Patients With Breast Cancer: Real-World Data.

Suh Koung Jin KJ Kim Se Hyun SH Kim Yu Jung YJ Shin Heechul H Kang Eunyoung E Kim Eun-Kyu EK Lee Sejoon S Woo Ji Won JW Na Hee Young HY Ahn Soomin S Jang Bum-Sup BS Kim In Ah IA Park So Yeon SY Kim Jee Hyun JH

Journal of breast cancer 20220628 5

<h4>Purpose</h4>Next-generation sequencing (NGS)-based tumor panel testing has been reimbursed by the Korean government since 2017. We evaluated the use of NGS-based tumor panel testing in real-world clinical practice, focusing on molecular profiling (MP)-guided breast cancer treatment.<h4>Methods</h4>A total of 137 breast cancer patients underwent NGS panel testing between December 2017 and July 2020 at Seoul National University Bundang Hospital (SNUBH). Samples from patients were profiled usin ...[more]

PMID: 35914747

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Project description:Over the last two decades, the use of Next-Generation Sequencing (NGS) in medical oncology has increased the likelihood of identifying druggable mutations that may be potentially susceptible to targeted treatments. The European Society for Medical Oncology (ESMO) currently does not recommend the use of the NGS test to determine the therapeutic course of patients with metastatic breast cancer (mBC) in daily clinical practice. However, the aim of this work is to evaluate the potential contribution of the NGS test in selecting targeted therapies for patients with mBC. Data were retrospectively collected from 101 patients diagnosed with metastatic breast cancer and treated at the Modena Cancer Center between January 2015 and April 2022. A NGS test was performed on the tumor tissue of each patient at the Laboratory of Molecular Pathology of the University Hospital of Modena. This study analyzed the clinical-pathological characteristics and mutational profile of the population using NGS tests, with a focus on actionable mutations that could be targeted in advanced stages of clinical development. The indicator of this study was to quantify the actionable mutations that resulted in a change of cancer treatment. In total, 101 patients with metastatic breast cancer were analyzed, including 86 with luminal phenotype, 10 who were HER2-positive and 5 who were triple-negative. Median age was 52 years. NGS analysis was conducted on 47 samples of primary breast cancer, 52 on metastatic sites of disease and 2 on liquid biopsies. A total of 85 gene mutations were found. The most common mutations were identified in the PIK3CA (47%), FGFR (19%) and ERBB2 genes (12%), and to a lesser extent in other genes. Of the 61 patients with pathogenic mutations, 46 (75%) had at least one actionable mutation. Of these, nine received treatment with a molecular target drug: eight patients with a mutation of the PIK3CA gene were treated with alpelisib and fulvestrant; one patient with FGFR1/2 amplifications received TAS120. Median PFS for these patients was 3.8 months. The study results show that using the NGS test on cancer tissue of metastatic breast cancer could influence the therapeutic choices, considering the small sample size and limited follow-up. About 9% of the study population had their therapy modified based on the results of NGS. The growing number of detectable mutations and increased accessibility of the test may lead to a greater number of potential therapeutic implications for the NGS assay. Perspectives suggest that NGS analysis can be implemented in daily clinical practice, particularly in contexts where a Molecular Tumor Board (MTB) is active.

Dataset Information

Clinical Application of Next-Generation Sequencing in Patients With Breast Cancer: Real-World Data.

Purpose

Methods

Results

Conclusion

Publications

Clinical Application of Next-Generation Sequencing in Patients With Breast Cancer: Real-World Data.

Similar Datasets

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