Abstract
ObjectivesVarious genomic alterations and genomic signatures, including ERBB2 amplification, mutations in PIK3CA, AKT1, and ESR1, and tumor mutational burden (TMB), have become important biomarkers for treatment selection in breast cancer (BC). This study aimed to investigate the mutational features of Chinese early-stage BC patients.MethodsTumors and matched blood samples collected from 589 Chinese patients with early-stage BC were sequenced using a commercial gene panel consisting of 520 cancer-related genes to analyze all types of genomic alterations and estimate the TMB status.ResultsA total of 18 genes were found to be more frequently mutated (P<0.05) or amplified (P<0.05) in stage T3–4 tumors as compared with T1–2 tumors. A total of 18 genes were found to be differentially mutated (P<0.05) or amplified (P<0.05) in patients with lymph node metastasis than those without lymph node metastasis. Younger patients (≤35 years) were more frequently identified with mutations or gene amplifications in eleven genes (P<0.05). TMB >10mutations/Mb were found in 5.7% of our cohort. Although the TMB was similar for various molecular subtypes between our cohort and the BC cohort of The Cancer Genome Atlas (TCGA) study, the TMB were statistically different for HR+/HER-, HR+/HER2+, and triple-negative subtypes between our cohort and African Americans in the TCGA study. As compared to the TCGA BC cohort, our cohort had a much earlier median age of diagnosis (48 vs. 58 years, P<0.001), and had significantly lower frequency of triple-negative subtype (11.5% vs. 18.4%, P<0.001) and invasive lobular BC (2.4% vs. 19.0%, P<0.001). Further subgroup analyses revealed that mutation rates in various genes including TP53, ERBB2, and PIK3CA were distinct for patients who were younger (≤35 years), had triple-negative or invasive lobular BC in our cohort than in the TCGA cohort.ConclusionsThis study revealed distinct mutational features of various molecular subtypes of early-stage BC among Chinese patients. Moreover, we provide new insights into the differences in early-stage BC between the East and West.
Highlights
Breast cancer is the most common cancer and the leading cause of cancer deaths in women globally and China [1, 2]
Next-generation sequencing (NGS) has accelerated the systematic characterization of the genomic landscape of breast cancer, which contributed to our current understanding of the unique and shared genomic features of the four breast cancer molecular subtypes [4,5,6,7]
Chinese patients diagnosed with various histology of early-stage breast cancer in Guangdong Provincial People's Hospital (GDPH) who submitted paired breast tissue samples and blood samples for targeted sequencing to Burning Rock Biotech, a clinical laboratory accredited by the College of American Pathologist (CAP) and certified by the Clinical Laboratory Improvement Amendments (CLIA), were included in this retrospective study
Summary
Breast cancer is the most common cancer and the leading cause of cancer deaths in women globally and China [1, 2]. While genomic studies of breast cancer are mainly performed in patients from Western countries [5, 8, 9], the increasing efforts in investigating the features of Chinese patients with breast cancer have revealed their unique epidemiological characteristics. As compared to Caucasians, the Chinese patients have an earlier age of onset for breast cancer with peak incidence observed between 45 and 55 years as well as a distinct molecular subtype distribution with a higher proportion of luminal and lower proportion of triple-negative subtypes [9]. To better understand the etiological differences between breast cancer in China and Western countries, we retrospectively analyzed the genomic data of 589 Chinese patients with various molecular and histological subtypes of early-stage (stage I–III) breast cancer to elucidate their mutational landscape. We performed subgroup analysis to compare the genomic data of a subgroup from our cohort to the breast cancer dataset from the Cancer Genome Atlas (TCGA) with similar clinicopathological features to identify distinct mutational features in our population
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