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. 2024 Sep 27;22(1):422.
doi: 10.1186/s12916-024-03638-y.

Age- and ethnic-driven molecular and clinical disparity of East Asian breast cancers

Ji Yoon Lee #  1   2 , Ji Won Lee #  3 , Min Sung Chung  4 , Jong Gwon Choi  5 , Sung Hoon Sim  6 , Hyo Jeong Kim  7 , Jeong Eun Kim  8 , Kyoung Eun Lee  9 , Yeon Hee Park  10 , Myoung Joo Kang  11 , Mi Sun Ahn  12 , Yee Soo Chae  13 , Ji Hyun Park  14 , Jee Hyun Kim  15 , Gun Min Kim  16 , Jae Ho Byun  17 , Keon Uk Park  18 , Ju Won Kim  3 , Seung Pil Jung  19 , Jung Hyun Lee  20 , Jung Seok An  20 , Byunghyun Jang  1   2 , Dayoung Yoon  1   2   21 , Jiwon Kim  1   2 , Jisoo Hong  1   2 , Harim Koo  1   2   22 , Kyu Ran Cho  23 , Cheol Yong Kim  23 , Jason K Sa  24   25 , Kyong Hwa Park  26
Affiliations

Age- and ethnic-driven molecular and clinical disparity of East Asian breast cancers

Ji Yoon Lee et al. BMC Med. .

Abstract

Background: Breast cancer (BC) is a complex disease with profound genomic aberrations. However, the underlying molecular disparity influenced by age and ethnicity remains elusive.

Methods: In this study, we aimed to investigate the molecular properties of 843 primary and metastatic BC patients enrolled in the K-MASTER program. By categorizing patients into two distinct age subgroups, we explored their unique molecular properties. Additionally, we leveraged large-scale genomic data from the TCGA and MSK-IMPACT studies to examine the ethnic-driven molecular and clinical disparities.

Results: We observed a high prevalence of PI3KCA mutations in K-MASTER HER2 + tumors, particularly in older patients. Moreover, we identified increased mutation rates in DNA damage response molecules, including ARID1A, MSH6, and MLH1. The K-MASTER patients were mainly comprised of triple-negative breast cancer (TNBC) and HER2-positive tumors, while the TCGA and MSK-IMPACT cohorts exhibited a predominance of hormone receptor-positive (HR +) subtype tumors. Importantly, GATA3 mutations were less frequently observed in East Asian patients, which correlated with poor clinical outcomes. In addition to characterizing the molecular disparities, we developed a gradient-boosting multivariable model to identify a new molecular signature that could predict the therapeutic response to platinum-based chemotherapy.

Conclusions: Our findings collectively provide unprecedented insights into the significance of age and ethnicity on the molecular and clinical characteristics of BC patients.

Keywords: Breast cancer; Ethnic diversity; Genomic alterations; Molecular subtypes; Precision medicine.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Genomic landscape of KM BRCA. A Overall characteristic of KM BRCA sample and clinical data. Clinical features of KM BRCA sample. B Genomic landscape of somatic mutations and copy number alterations of BRCA by age group. C Significantly mutated genes by age group in KM BRCA. D Ternary diagram depicting mutation proportion of all, YBC, and OBC group by molecular subtypes. The size of each node represents the number of tumors with the respective mutations, and the color spectrum indicates its relative frequency. E Mutational signature of all and molecular subtype. The size of each dot represents the proportion of samples of each tumor types. The red dot represents the YBC group, and the blue dot represents the OBC group. F Violin plots demonstrating signature differences of YBC and OBC group
Fig. 2
Fig. 2
Genomic difference of KM and MSK metastasis cohort. A Molecular subtype proportion of KM and MSK (left). Molecular subtype proportion of KM and MSK by age group (right). B Genomic landscape of somatic mutations and copy number alterations of YBC BRCA (left) and OBC BRCA (right). C Significantly mutated genes according to molecular subtypes in the KM and MSK groups. D Metastatic site frequency of KM BRCA metastasis. E Mutation frequency difference of KM and MSK by metastatic site
Fig. 3
Fig. 3
Overall survival analysis of BRCA. A Survival analysis of primary YBC K-MASTER and TCGA cohorts (left) and OBC K-MASTER and TCGA cohorts (right). B Survival analysis of metastasis K-MASTER and MSK cohorts. Differences in prognosis of primary or metastasis breast cancer in YBC and OBC groups. C Finding prognosis marker with somatic mutation and copy number alterations by primary YBC and OBC group in KM and TCGA. D Overall survival of primary KM YBC group with/without TP53 mutation (top) and primary KM OBC group with/without GATA3 mutation (bottom). E Finding prognosis marker with somatic mutation and copy number alterations by primary YBC and OBC group in KM and TCGA
Fig. 4
Fig. 4
Genomic characteristics analysis of platinum-based chemotherapy treated patient. A PFS of platinum-based therapy treated KM with deleterious DDR mutation. B OS of platinum-based therapy treated KM with deleterious DDR mutation. C OS of platinum-based therapy treated MSK with deleterious DDR mutation. D PFS of platinum-based chemotherapy patient by response. E Feature important score of genomic alterations by XGBoost. F Responder and non-responder group proportion in gene alteration. The asterisks indicate a statistically significant association (p < 0.05). G PFS of platinum-based therapy treated KM with curated gene set. H OS of platinum-based therapy treated KM with curated gene set. I OS of platinum-based therapy treated MSK with curated gene set. J Mutational signature proportion of responder and non-responder group (left) and signature difference (right)
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