Cancer Res Treat.  2024 Jan;56(1):149-161. 10.4143/crt.2023.800.

Next-Generation Sequencing in Breast Cancer Patients: Real-World Data for Precision Medicine

• Lee H
• Cho YA
• Kim DG
• Cho EY

• KMID: 2550332
• DOI: http://doi.org/10.4143/crt.2023.800

Abstract

Purpose
Breast cancer is one of the most common causes of cancer-related death in females. Numerous drug-targetable biomarkers and predictive biomarkers have been developed. Some researchers have expressed doubts about the need for next-generation sequencing (NGS) studies in daily practice. This study analyzed the results of NGS studies on breast cancer at a single institute and evaluated the real-world applications of NGS data to precision medicine for breast cancer.
Materials and Methods
We retrospectively collected the results of NGS studies and analyzed the histopathologic features and genetic profiles of patients treated for breast cancer from 2010 to 2021. Seventy cases had data from CancerSCAN, a customized panel of 375 cancer-associated genes, and 110 cases had data from TruSight Oncology 500.
Results
The most frequently detected single nucleotide variant was the TP53 mutation (123/180, 68.3%), followed by PIK3CA muta-tions (51/180, 28.3%). Estrogen receptor 1 (ESR1) mutation was detected in 11 patients (6.1%), of whom 10 had hormone receptor–positive, human epidermal growth factor receptor 2–negative breast cancer, and two had no history of prior endocrine therapy. Based on their NGS study results, 13 patients (7.2%) received target therapy. Among them, four patients had a BRCA1 or BRCA2 germline mutation, and nine patients had a PIK3CA mutation.
Conclusion
NGS can provide information about predictive biomarkers and drug-targetable biomarkers that can enable treatment and participation in clinical trials based on precision medicine. Further studies should be conducted to excavate novel drug-targetable biomarkers and develop additional target therapies.

Keyword

Next-generation sequencing; Breast neoplasms; Precision medicine

Figure

• 

  Fig. 1. Schematic demonstration of clinicopathological characteristics and genetic alterations. ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; TMB, tumor mutation burden; TNBC, triple-negative breast cancer.

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  Fig. 2. The distribution of PIK3CA single nucleotide variants (SNVs) based on immunohistochemical subtypes. (A) Hormone receptor–positive, human epidermal growth factor receptor 2 (HER2)–negative breast cancer. (B) HER2-positive breast cancer. (C) Triple-negative breast cancer. The most frequent SNV in all subtypes was H1047R.

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  Fig. 3. The distribution of PIK3CA single nucleotide variants (SNVs) based on the therascreen panel. (A) The prevalence of PIK3CA SNVs included in the therascreen panel. (B) The distribution of PIK3CA SNVs not included in the therascreen panel.

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