Research ArticleOriginal Article

Association between 15 known or potential breast cancer susceptibility genes and breast cancer risks in Chinese women

Fenfen Fu, Dongjie Zhang, Li Hu, Senthil Sundaram, Dingge Ying, Ying Zhang, Shuna Fu, Juan Zhang, Lu Yao, Ye Xu and Yuntao Xie
Cancer Biology & Medicine February 2022, 19 (2) 253-262; DOI: https://doi.org/10.20892/j.issn.2095-3941.2021.0358

Abstract

Objective: There are many hereditary breast cancer patients in China, and multigene panel testing has been a new paradigm of genetic testing for these patients and their relatives. However, the magnitude of breast cancer risks related to multiple breast cancer susceptibility genes are largely unknown in Chinese women.

Methods: We screened pathogenic variants in 15 established or potential breast cancer susceptibility genes from 8,067 consecutive Chinese female breast cancer patients and 13,129 Chinese cancer-free female controls. These breast cancer patients were unselected for age at diagnosis or family history.

Results: We found that pathogenic variants in TP53 [odds ratio (OR): 16.9, 95% confidence interval (CI): 5.2–55.2]; BRCA2 (OR: 10.4, 95% CI: 7.6–14.2); BRCA1 (OR: 9.7, 95% CI: 6.3–14.8); and PALB2 (OR: 5.2, 95% CI: 3.0–8.8) were associated with a high risk of breast cancer. ATM, BARD1, CHEK2, and RAD51D were associated with a moderate risk of breast cancer with ORs ranging from 2-fold to 4-fold. In contrast, pathogenic variants of NBN, RAD50, BRIP1, and RAD51C were not associated with increased risk of breast cancer in Chinese women. The pathogenic variants of PTEN, CDH1, and STK11 were very rare, so they had a limited contribution to Chinese breast cancer. Patients with pathogenic variants of TP53, BRCA1, BRCA2, and PALB2 more often had early-onset breast cancer, bilateral breast cancer, and a family history of breast cancer and/or any cancer.

Conclusions: This study provided breast cancer risk assessment data for multiple genes in Chinese women, which is useful for genetic testing and clinical management of Chinese hereditary breast cancer.

keywords

Introduction

Breast cancer is the most frequent malignant tumor in Chinese women, with approximately 268,600 newly-diagnosed cases per year. Furthermore, the burden of breast cancer is still increasing1–3. It is estimated that nearly 10% of unselected breast cancer patients in China carry pathogenic variants in cancer susceptibility genes4. Detecting these pathogenic variants and precisely estimating their risks for breast cancer will provide the basis for prevention and management of hereditary breast cancers. Advances in sequencing technology have made multigene testing, or “panel testing,” a routine option to detect pathogenic variants for potential breast cancer patients and their relatives. These panels usually contain established breast cancer susceptibility genes, such as BRCA1, BRCA2, PALB2, TP53, CHEK2, and ATM, and potential breast cancer susceptibility genes, such as BARD1, BRIP1, RAD50, RAD51C, and RAD51D5,6. However, the magnitude of breast cancer risks associated with these known or potential breast cancer genes is largely unknown in Chinese women.

Large case-control association studies that quantify the breast cancer risks of multiple genes from panel testing have been mainly conducted in Caucasian women or other populations7–14. However, these data may not be generally applicable to Chinese women. Although the frequencies of pathogenic variants of breast cancer genes in Chinese women are comparable to those in other ethnicities4,15,16, studies by our group or other groups have shown substantial differences in the spectrum of pathogenic variants of breast cancer susceptibility genes between Chinese and non-Chinese ethnicities, with up to one-third of the pathogenic variants in Chinese women not being found in Caucasian women17–22. Moreover, early-onset breast cancer (i.e., diagnosed at or before the age of 40 years) is more common in Chinese women than Caucasian women1. Therefore, the breast cancer risks in specific genes in Chinese women may differ from those in other populations. In this study, we therefore screened pathogenic variants in 15 established or potential breast cancer susceptibility genes in 8,067 unselected Chinese female breast cancer patients and 13,129 Chinese cancer-free female controls, then compared the risk-related phenotypes between the patients with pathogenic variants and those without a pathogenic variant. We aimed to determine the breast cancer risks of the 15 breast cancer genes in Chinese women.

Materials and methods

Study population

A total of 8,085 consecutive breast cancer patients who were treated at the Breast Center of Peking University Cancer Hospital & Institute from October 2003 to May 2015 underwent 62-gene panel sequencing, as described in our previous report4. Eighteen male breast cancer patients were excluded from the analysis, and the remaining 8,067 female breast cancer patients were included in this study. Early-onset breast cancer patients were defined as patients diagnosed at or before the age of 40 years. Family history of breast cancer was defined as the breast cancer patient having 1 or more breast cancer patients in the first-, second-, or third-degree relatives, and family history of any cancer was defined as the breast cancer patient having 1 or more cancer patients (any kind of cancer) in the first-, second-, or third-degree relatives. The family history of breast or other cancer was collected from medical records and/or telephone interviews. A total of 13,129 Chinese women (ages ≥ 18 years) without a personal history of any cancer were recruited from the general population and were considered as a reference control for this case-control study. Written informed consents were obtained from all participants. This study was reviewed and approved by the Ethics Committee of Peking University Cancer Hospital & Institute (Approval No.2011041205) and was performed in accordance with the Declaration of Helsinki.

Sequencing assay

For the breast cancer cohort, genomic DNA extracted from peripheral blood was used for 62-gene panel sequencing at an average depth of 200-fold coverage of the target region, as described in our previous study4. We selected 15 established or potential breast cancer susceptibility genes from the 62-gene panel for further analysis based on published studies5,7,23,24, including 10 established breast cancer susceptibility genes (BRCA1, BRCA2, PALB2, TP53, PTEN, CDH1, STK11, ATM, CHEK2, and NBN) and 5 potential breast cancer susceptibility genes (BARD1, BRIP1, RAD50, RAD51C, and RAD51D). For the control cohort, genomic DNA extracted from buccal swabs was used for whole-exome sequencing at an average depth of 100-fold coverage of the target region. Reads were aligned to the reference human genome, GRCh37. Germline variations were called with GATK. Annotations were defined using ANNOVAR (https://annovar.openbioinformatics.org/en/latest/).

Variant classification

In this study, we analyzed germline variants in the 15 established or potential breast cancer susceptibility genes. Only variants with < 1% population frequency in the population databases including 1,000 Genomes (https://www.1000genomes.org), NHLBI Exome Sequencing Project (ESP6500, https://evs.gs.washington.edu/EVS/), and the Exome Aggregation Consortium (ExAC, https://exac.broadinstitute.org) were collected. Among these, the truncating variants (nonsense and frameshift variants) were included in this study, but the truncating variants in the last 55 base pairs of the penultimate exon or last exon that potentially avoided nonsense-mediated messenger RNA decay and did not influence known functional domains, were excluded. For splice-site, synonymous, nonsynonymous, in-frame, and stop-loss variants, only variants classified as pathogenic or likely pathogenic by ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) were included in the analysis. The variants with conflicting interpretations of pathogenicity in ClinVar were further annotated according to the ACMG/AMP standards and guidelines25, with supporting data from function prediction software, public literature, and curated databases (Supplementary Table S1). Variants classified to be pathogenic or likely pathogenic were considered as pathogenic in this study.

Statistical analysis

Case-control association analysis within each gene was performed using logistic regression. The strength of associations with breast cancer was estimated by the odds ratio (OR) and corresponding 95% confidence interval (CI). Genes were categorized as high risk (OR ≥ 5.0), moderate risk (2.0 ≤ OR < 5.0), or of no clinical relevance (OR < 2.0)7. Categorical variables between mutation carriers and noncarriers were compared using the chi-square test or Fisher’s exact test, where appropriate. Continuous variables were tested using a t-test. Two-sided P values less than 0.05 were considered to be statistically significant. All analyses were performed using SPSS 20.0 statistical software for Windows (SPSS, Chicago, IL, USA).

Results

Characteristics of the study population

The 8,067 consecutive Chinese female breast cancer patients analyzed in this study were unselected for age at diagnosis or family history. The median age at diagnosis for breast cancer patients was 50 years (range: 19–98 years) (Table 1). Among them, 18.2% were diagnosed at or before the age of 40 years (early-onset breast cancer), and 10.0% had a family history of breast cancer. A total of 13,129 Chinese women without a personal history of cancer were enrolled as controls. The median age at entry was 33 years (range: 18–84 years) (Table 1). The majority of breast cancer cases (95.8%) and controls (93.6%) were of Chinese Han descent (Table 1).

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Table 1

Characteristic of the study population

Pathogenic germline variants detected in breast cancer cases and controls

Pathogenic germline variants of the 15 genes were found in 654 (8.11%) breast cancer cases and 251 (1.91%) controls (Table 2). Fourteen breast cancer patients and 1 control had pathogenic variants in 2 different genes (double variant carriers; data not shown). For breast cancer cases, BRCA2 (284, 3.52%) was the most frequently mutated gene, followed by other established breast cancer susceptibility genes: BRCA1 (146, 1.81%), PALB2 (57, 0.71%), and TP53 (31, 0.38%). For controls, BRCA2 (46, 0.35%) still ranked as the most frequently mutated gene, followed by the candidate genes, RAD50 (31, 0.24%) and BRIP1 (29, 0.22%). Notably, pathogenic germline variants of PTEN, CDH1, and STK11 were extremely rare in Chinese breast cancer patients or controls (Table 2). Furthermore, in all 533 pathogenic germline variants of the 15 genes analyzed in this study, 385 (72.2%) variants have been reported in the latest version of the ClinVar dataset (Supplementary Table S2).

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Table 2

Breast cancer risks of the 15 genes estimated by case-control association analysis in Chinese women

Risk estimation in the 15 genes based on this case-control study

Breast cancer risks for each of the genes were estimated by comparing the frequency of pathogenic variants identified in breast cancer cases to controls. Logistic regression results showed that 8 genes in this study were significantly associated with increased risk of breast cancer in Chinese women (Table 2). Among these genes, TP53 (OR: 16.9, 95% CI: 5.2–55.2); BRCA2 (OR: 10.4, 95% CI: 7.6–14.2); BRCA1 (OR: 9.7, 95% CI: 6.3–14.8); and PALB2 (OR: 5.2, 95% CI: 3.0–8.8) were classified as high risk breast cancer susceptibility genes in Chinese women (Table 2). BARD1 (OR: 3.1, 95% CI: 1.3–7.2); CHEK2 (OR: 2.5, 95% CI:1.4–4.6); RAD51D (OR: 2.2, 95% CI: 1.3–3.8); and ATM (OR: 2.1, 95% CI: 1.2–3.6) were classified as moderate risk breast cancer risk genes (Table 2). The 8 high or moderate risk susceptibility genes accounted for 7.5% of unselected Chinese breast cancer patients in this study (5.2% for BRCA1/2 and 2.3% for the other genes). In contrast, NBN, RAD50, BRIP1, and RAD51C were not associated with increased risks of breast cancer in Chinese women (Table 2). In addition, pathogenic variants of PTEN (5 cases), CDH1 (1 case), and STK11 (1 case and 1 control) were too rare to estimate their risks of breast cancer in Chinese women (Table 2). The breast cancer risks of susceptibility genes were higher after being adjusted for age (Supplementary Table S3).

We further estimated breast cancer risks for each of the genes based on pathogenic truncating variants (Supplementary Table S4). Among these, BRCA1, BRCA2, and PALB2 were still classified as high risk, and ATM, BARD1, CHEK2, and RAD51D were still classified as moderate risk breast cancer susceptibility genes in Chinese women (Supplementary Table S4). As the majority of pathogenic variants in the TP53 gene were missense, the truncating variants in the TP53 gene were too rare to estimate the risk of breast cancer in this study (Supplementary Table S4).

We further analyzed the breast cancer risks of the 15 genes stratified by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 status in this case-control study. Among the ER and/or PR+ and HER2- subgroups, TP53 (OR: 15.9, 95% CI: 4.6–54.6); BRCA2 (OR: 12.8, 95% CI: 8.9–17.7); BRCA1 (OR: 5.6, 95% CI: 3.5–9.2); and PALB2 (OR: 6.0, 95% CI: 3.4–10.5) were still classified as high risk breast cancer susceptibility genes (Table 3). CHEK2 (OR: 2.5, 95% CI: 1.2–5.0) and ATM (OR: 2.7, 95% CI: 1.5–4.9) were classified as moderate risk susceptibility genes (Table 3), while BARD1 and RAD51D were not significantly associated with risk in this subgroup (Table 3). Among the HER2+ group, only TP53 (OR: 23.8, 95% CI: 6.5–86.6) was classified as a high risk breast cancer susceptibility gene, while BRCA2 (OR: 4.5, 95% CI: 2.8–7.2); BRCA1 (OR: 3.4, 95% CI: 1.7–6.8); PALB2 (OR: 3.2, 95% CI: 1.4–7.3); and CHEK2 (OR: 3.8, 95% CI: 1.7–8.5) were classified as moderate risk breast cancer susceptibility genes (Table 3). Among the triple negative subgroup, TP53, BRCA1, BRCA2, PALB2, BRAD1, and RAD51D were all classified as high risk breast cancer susceptibility genes (Table 3). Of these, BRCA1 had the highest risk of breast cancer susceptibility (OR: 42.1, 95% CI: 26.8–66.2) (Table 3).

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Table 3

Breast cancer risks of the 15 genes stratified by ER, PR, and HER2 status of breast cancer cases

The impact of breast cancer susceptibility genes on clinical characteristics

Pathogenic variants in breast cancer susceptibility genes are usually associated with risk-related phenotypes, such as early-onset breast cancer, bilateral breast cancer, and higher frequencies of family cancer history26. We therefore compared these risk-related characteristics between the patients with pathogenic variants and those without any pathogenic variant. Double variant carriers were excluded from the clinical characteristic analysis.

The mean age at diagnosis of breast cancer patients with pathogenic variants of TP53 (41.8 years vs. 51.4 years, P = 5.00 × 10−6); BRCA2 (47.8 years vs. 51.4 years, P = 2.95 × 10−7); BRCA1 (44.7 years vs. 51.4 years, P = 1.01 × 10−11); PALB2 (47.6 years vs. 51.4 years, P = 0.02); and RAD51D (46.3 years vs. 51.4 years, P = 0.02) was significantly younger than that of noncarriers (Table 4). Similarly, pathogenic variants of TP53, BRCA2, BRCA1, and RAD51D were significantly associated with early-onset breast cancer (Table 4), and pathogenic variants of TP53, BRCA2, BRCA1, and NBN were significantly associated with premenopausal breast cancer (Table 4). Among these, the TP53 gene, which conferred the highest risk of breast cancer, was also associated with the youngest mean age at diagnosis and the highest frequency of early-onset breast cancer (Table 4). In addition, the high risk genes (TP53, BRCA2, and BRCA1) were significantly associated with bilateral breast cancer (Table 4). When comparing the family history of cancer, all high risk and moderate risk genes except for RAD51D were significantly associated with higher frequencies of family history of breast cancer and/or family history of any cancer (Table 4). In summary, all 8 high or moderate risk susceptibility genes in this study affected 1 or more risk-related phenotypes. In contrast, the 4 genes that were not associated with increased risk of breast cancer in this study (NBN, RAD50, BRIP1, and RAD51C) had no effect on any of the risk-related phenotypes (Table 4).

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Table 4

Comparison of risk-related clinical characteristics between patients with germline pathogenic variant and noncarriers

TP53, PTEN, STK11, and CDH1 are associated with Li-Fraumeni syndrome, Cowden syndrome, Peutz-Jeghers syndrome, and hereditary diffuse gastric cancer syndrome27–30. Among the 31 breast cancer patients with the TP53 pathogenic variant in this study, only 3 patients (9.7%) met the criteria for the Li-Fraumeni syndrome. After excluding the 3 patients with Li-Fraumeni syndrome, the TP53 gene was still significantly associated with a high risk of breast cancer in Chinese women (OR: 15.2, 95% CI: 4.6–50.1, P = 2.00 × 10−9), which suggested that women with TP53 pathogenic variants but without a family history of Li-Fraumeni syndrome still had a high risk of breast cancer. None of the 5 breast cancer patients with the PTEN variant met the Cowden syndrome criteria, and the patient with STK11 variant did not meet the Peutz-Jeghers criteria. The patient with the CDH1 variant in this study did not present with lobular breast cancer, nor with a personal history or family history of gastric cancer, although there were 255 (3.2%) invasive lobular breast cancer patients in this study.

Discussion

In this study, we screened pathogenic variants in 15 established or potential breast cancer susceptibility genes in 8,067 Chinese unselected female breast cancer patients and 13,129 Chinese cancer-free female controls. Our results classified TP53, BRCA1, BRCA2, and PALB2 as high risk, and ATM, BARD1, CHEK2, and RAD51D as moderate risk breast cancer susceptibility genes in Chinese women. In contrast, our study revealed that NBN, RAD50, BRIP1, and RAD51C were not associated with an increased risk of breast cancer, and PTEN, CDH1, and STK11 had a very limited contribution to Chinese breast cancer.

We found that the TP53 gene conferred the highest risk of breast cancer in Chinese women (OR: 16.9), and patients carrying pathogenic variants of the TP53 gene had the youngest mean age at diagnosis. Pathogenic variants of the TP53 gene were also associated with a high risk of breast cancer in Japanese women9. However, 2 recent large-scale case-control studies of Caucasian women reported that the TP53 gene was not significantly associated with breast cancer risk13,14. This difference might be explained by the observation that the prevalence of TP53 pathogenic variants in Asian breast cancer patients was much higher than that in Caucasian breast cancer patients9,13,14,31. In addition, a previous study based on patients with Li-Fraumeni syndrome reported a very high relative risk of breast cancer (OR: 105) for the TP53 gene27. This difference might be explained by that the TP53 variant carriers in our study were identified from unselected breast cancer patients, and only a minority of them met the Li-Fraumeni Chompret criteria. Importantly, our results showed that Chinese women with TP53 pathogenic variants but without a family history of Li-Fraumeni syndrome had a high risk of breast cancer (OR = 15.2).

This case-control study showed approximately a 10-fold increased risk of breast cancer for BRCA1/2 pathogenic variant carriers, when compared with noncarriers in Chinese women. Recent case-control studies in Caucasian women have reported relative risks of breast cancer for the BRCA1 and BRCA2 genes of 5.9–10.6-fold and 3.3–5.9-fold, respectively8,13,14, which were lower than the magnitude of breast cancer risks estimated in this study. This difference might be explained by sample selection and ethnic differences.

The PALB2 gene was recently classified as a high risk breast cancer susceptibility gene in Caucasian women, with 53% cumulative risk to age 80 years and 7-fold relative risk for female breast cancer7,32, which was comparable to the breast cancer risk of the BRCA2 gene in Caucasian women8,13,33. However, our results and a recent study from another group34 both suggested that PALB2 conferred 5-fold increased risk for breast cancer in Chinese women, indicating that the risk associated with the PALB2 gene was lower than that of BRCA1/2 genes in Chinese women, although the magnitude of risk for the PALB2 gene reached the threshold of high risk genes.

This study classified ATM, BARD1, CHEK2, and RAD51D as moderate risk breast cancer susceptibility genes in Chinese women. Although ATM and CHEK2 were identified as classic moderate risk genes in Caucasian women35, the risks of the 2 genes in Chinese women are still worth investigating because it has been reported that the risk of pathogenic variants of the 2 genes was highly related to location and the type of variants, and considerable differences in the spectrum of ATM and CHEK2 variants were observed between Chinese and Caucasian ethnicities. For example, the dominant negative ATM p.Val2424Gly variant confers a much higher risk than truncating variants of the ATM gene (OR: 8.0–11.0 for p.Val2424Gly and OR: 2.2 for truncating variants)35–37. CHEK2 c.1100delC, the most frequent truncating variant in Caucasian women, confers a higher risk than the common missense mutation, CHEK2 p.Ile157Thr38–40. However, these specific variants, such as ATM p.Val2424Gly and CHEK2 c.1100delC, were absent in Chinese women20,21. In summary, our study defined ATM and CHEK2 as moderate risk genes for breast cancer in Chinese women. Some large case-control studies in Caucasian women showed that BRAD1 and RAD51D were breast cancer susceptibility genes7,13, while other studies did not reach this conclusion8,14. Our results indicated that BRAD1 and RAD51D were moderate risk breast cancer susceptibility genes in Chinese women. In addition, breast cancer patients with the BRAD1 and RAD51D pathogenic variants were associated with a higher frequency of family cancer history and early-onset breast cancer, respectively. These clinical characteristics also suggested that BARD1 and RAD51D were breast cancer susceptibility genes in Chinese women.

The pathogenic variants of PTEN, CDH1, and STK11 were too rare in our study to estimate their risks of breast cancer in Chinese women, which suggested that these genes had a very limited contribution to breast cancer in unselected Chinese women. In addition, the pathogenic variant carriers for PTEN, CDH1, and STK11 identified from unselected breast cancer patients in this study did not meet the criteria for the Cowden syndrome, hereditary diffuse gastric cancer syndrome, and Peutz-Jeghers syndrome, respectively. Additional larger case-control studies or segregation analysis in families might be needed to fully elucidate the breast cancer risks for PTEN, CDH1, and STK11 in Chinese women. NBN serves as an established breast cancer susceptibility gene in the latest guidelines, because many studies reported that NBN c.657del5 (a founder variant in the Slavic population) was associated with increased risk of breast cancer41,42. However, NBN c.657del5 was absent in Chinese breast cancer patients and cancer-free controls in this study, and our results showed that other truncating variants of NBN were not associated with breast cancer risk. Our study did not support RAD50, BRIP1 and RAD51C as breast cancer susceptibility genes in the Chinese population, consistent with results from case-control studies in Caucasian women7,8,11,14.

This study also showed that breast cancer susceptibility genes conferred different risks in breast cancer molecular subgroups. For example, pathogenic variants in BRCA1 conferred the highest breast cancer risk in the triple negative subgroup than that in other subgroups. Pathogenic variants in TP53 conferred the highest breast cancer risk in the HER2+ subgroup than that in other subgroups. In addition, the ATM and CHEK2 genes were classified as moderate risk susceptibility genes in the ER and/or PR+ and HER2- subgroups, but were not associated with a risk in the triple negative subgroup. These findings were consistent with previous case-control studies8,12–14.

This study had some limitations. The ages of the cancer-free controls were younger than those of the breast cancer cases. It therefore may have underestimated the risks based on logistic regression models. However, our previous study based on the kin-cohort method found that the cumulative breast cancer risks in BRCA1/2 carriers up to the age of 70 years were 37.9% and 36.5% in Chinese women, respectively43, which were also 10-fold higher risks than noncarriers (3.6% by the age of 70 years). Similar results based on 2 different methods confirmed the reliability of our findings, although some bias existed in this case-control study.

Conclusions

This large case-control study classified TP53, BRCA2, BRCA1, and PALB2 as high risk, and ATM, BARD1, CHEK2, and RAD51D as moderate risk breast cancer susceptibility genes in Chinese women. In contrast, the study showed that NBN, RAD50, BRIP1, and RAD51C were not associated with an increased risk of breast cancer, and PTEN, CDH1, and STK11 had a very limited contribution to Chinese breast cancer. These results suggested that the 8 high or moderate risk susceptibility genes should be covered in panel testing for high risk Chinese breast cancer patients and their relatives. Overall, our risk assessment data should be useful for the prevention and early detection of Chinese women who carry a pathogenic variant in the 8 breast cancer susceptibility genes.

Supporting Information

Grant support

This study was supported by grants from the National Natural Science Foundation of China (Grant Nos. 81772824, 81372832, and 81974422).

Conflict of interest statement

No potential conflicts of interest are disclosed.

Author contributions

Conceived and designed the analysis: Yuntao Xie and Li Hu.

Collected the data: Fenfen Fu and Dongjie Zhang.

Contributed data or analysis tools: Senthil Sundaram, Dingge Ying, Ying Zhang, Shuna Fu, Juan Zhang, Lu Yao, and Ye Xu.

Performed the analysis: Fenfen Fu, Dongjie Zhang, and Li Hu.

Wrote the manuscript: Li Hu and Yuntao Xie.

Footnotes

  • ↵*These authors contributed equally to this work.

  • Received June 15, 2021.
  • Accepted August 20, 2021.
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References

  1. 1.↵
    2. Fan L,
    3. Strasser-Weippl K,
    4. Li J-J,
    5. Louis JS,
    6. Finkelstein DM,
    7. Yu K-D, et al.
    Breast cancer in China. Lancet Oncol. 2014; 15: e279–89.
    OpenUrlCrossRefPubMed
  2. 2.
    2. Chen W,
    3. Zheng R,
    4. Baade PD,
    5. Zhang S,
    6. Zeng H,
    7. Bray F, et al.
    Cancer statistics in China, 2015: cancer statistics in China, 2015. CA Cancer J Clin. 2016; 66: 115–32.
    OpenUrlCrossRefPubMed
  3. 3.↵
    2. Jiang X,
    3. Tang H,
    4. Chen T.
    Epidemiology of gynecologic cancers in China. J Gynecol Oncol. 2017; 29: e7.
  4. 4.↵
    2. Sun J,
    3. Meng H,
    4. Yao L,
    5. Lv M,
    6. Bai J,
    7. Zhang J, et al.
    Germline mutations in cancer susceptibility genes in a large series of unselected breast cancer patients. Clin Cancer Res. 2017; 23: 6113–9.
    OpenUrlAbstract/FREE Full Text
  5. 5.↵
    2. Daly MB,
    3. Pilarski R,
    4. Yurgelun MB,
    5. Berry MP,
    6. Buys SS,
    7. Dickson P, et al.
    NCCN guidelines insights: genetic/familial high-risk assessment: breast, ovarian, and pancreatic, Version 1.2020. J Natl Compr Cancer Netw. 2020; 18: 380–91.
    OpenUrl
  6. 6.↵
    2. Easton DF,
    3. Pharoah PDP,
    4. Antoniou AC,
    5. Tischkowitz M,
    6. Tavtigian SV,
    7. Nathanson KL, et al.
    Gene-panel sequencing and the prediction of breast-cancer risk. N Engl J Med. 2015; 372: 2243–57.
    OpenUrlCrossRefPubMed
  7. 7.↵
    2. Couch FJ,
    3. Shimelis H,
    4. Hu C,
    5. Hart SN,
    6. Polley EC,
    7. Na J, et al.
    Associations between cancer predisposition testing panel genes and breast cancer. JAMA Oncol. 2017; 3: 1190.
    OpenUrl
  8. 8.↵
    2. Kurian AW,
    3. Hughes E,
    4. Handorf EA,
    5. Gutin A,
    6. Allen B,
    7. Hartman A-R, et al.
    Breast and ovarian cancer penetrance estimates derived from germline multiple-gene sequencing results in Women. JCO Precis Oncol. 2017; 1: 1–12.
    OpenUrl
  9. 9.↵
    2. Momozawa Y,
    3. Iwasaki Y,
    4. Parsons MT,
    5. Kamatani Y,
    6. Takahashi A,
    7. Tamura C, et al.
    Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls. Nat Commun. 2018; 9: 4083.
    OpenUrlCrossRefPubMed
  10. 10.
    2. Li J,
    3. Meeks H,
    4. Feng B-J,
    5. Healey S,
    6. Thorne H,
    7. Makunin I, et al.
    Targeted massively parallel sequencing of a panel of putative breast cancer susceptibility genes in a large cohort of multiple-case breast and ovarian cancer families. J Med Genet. 2015; 53: 34–42.
    OpenUrl
  11. 11.↵
    2. Slavin TP,
    3. Maxwell KN,
    4. Lilyquist J,
    5. Vijai J,
    6. Neuhausen SL,
    7. Hart SN, et al.
    The contribution of pathogenic variants in breast cancer susceptibility genes to familial breast cancer risk. NPJ Breast Cancer. 2017; 3: 22.
    OpenUrl
  12. 12.↵
    2. Shimelis H,
    3. LaDuca H,
    4. Hu C,
    5. Hart SN,
    6. Na J,
    7. Thomas A, et al.
    Triple-negative breast cancer risk genes identified by multigene hereditary cancer panel testing. J Natl Cancer Inst. 2018; 110: 855–62.
    OpenUrlCrossRefPubMed
  13. 13.↵
    2. Consortium BCA,
    3. Dorling L,
    4. Carvalho S,
    5. Allen J,
    6. González-Neira A,
    7. Luccarini C, et al.
    Breast cancer risk genes — association analysis in more than 113,000 women. N Engl J Med. 2021; 384: 428–39.
    OpenUrlCrossRefPubMed
  14. 14.↵
    2. Hu C,
    3. Hart SN,
    4. Gnanaolivu R,
    5. Huang H,
    6. Lee KY,
    7. Na J, et al.
    A population-based study of genes previously implicated in breast cancer. N Engl J Med. 2021; 384: 440–51.
    OpenUrlCrossRefPubMed
  15. 15.↵
    2. Buys SS,
    3. Sandbach JF,
    4. Gammon A,
    5. Patel G,
    6. Kidd J,
    7. Brown KL, et al.
    A study of over 35,000 women with breast cancer tested with a 25-gene panel of hereditary cancer genes. Cancer. 2017; 123: 1721–30.
    OpenUrlCrossRefPubMed
  16. 16.↵
    2. Tung N,
    3. Lin NU,
    4. Kidd J,
    5. Allen BA,
    6. Singh N,
    7. Wenstrup RJ, et al.
    Frequency of germline mutations in 25 cancer susceptibility genes in a sequential series of patients with breast cancer. J Clin Oncol. 2016; 34: 1460–8.
    OpenUrlAbstract/FREE Full Text
  17. 17.↵
    2. Zhang J,
    3. Sun J,
    4. Chen J,
    5. Yao L,
    6. Ouyang T,
    7. Li J, et al.
    Comprehensive analysis of BRCA1 and BRCA2 germline mutations in a large cohort of 5931 Chinese women with breast cancer. Breast Cancer Res Treat. 2016; 158: 455–62.
    OpenUrlCrossRef
  18. 18.
    2. Li J,
    3. Jing R,
    4. Wei H,
    5. Wang M,
    6. Xiaowei Q,
    7. Liu H, et al.
    Germline mutations in 40 cancer susceptibility genes among Chinese patients with high hereditary risk breast cancer. Int J Cancer. 2019; 144: 281–9.
    OpenUrl
  19. 19.
    2. Bhaskaran SP,
    3. Chandratre K,
    4. Gupta H,
    5. Zhang L,
    6. Wang X,
    7. Cui J, et al.
    Germline variation in BRCA1 / 2 is highly ethnic-specific: evidence from over 30,000 Chinese hereditary breast and ovarian cancer patients. Int J Cancer. 2019; 145: 962–73.
    OpenUrlCrossRefPubMed
  20. 20.↵
    2. Fan Z,
    3. Ouyang T,
    4. Li J,
    5. Wang T,
    6. Fan Z,
    7. Fan T, et al.
    Identification and analysis of CHEK2 germline mutations in Chinese BRCA1/2-negative breast cancer patients. Breast Cancer Res Treat. 2018; 169: 59–67.
    OpenUrl
  21. 21.↵
    2. Yang Z,
    3. Ouyang T,
    4. Li J,
    5. Wang T,
    6. Fan Z,
    7. Fan T, et al.
    Prevalence and characterization of ATM germline mutations in Chinese BRCA1/2-negative breast cancer patients. Breast Cancer Res Treat. 2019; 174: 639–47.
    OpenUrl
  22. 22.↵
    2. Wu Y,
    3. Ouyang T,
    4. Li J,
    5. Wang T,
    6. Fan Z,
    7. Fan T, et al.
    Spectrum and clinical relevance of PALB2 germline mutations in 7657 Chinese BRCA1/2-negative breast cancer patients. Breast Cancer Res Treat. 2019; 179: 605–14.
    OpenUrl
  23. 23.↵
    2. Rainville IR,
    3. Rana HQ.
    Next-generation sequencing for inherited breast cancer risk: counseling through the complexity. Curr Oncol Rep. 2014; 16: 371.
    OpenUrlCrossRefPubMed
  24. 24.↵
    2. Stratton MR,
    3. Rahman N.
    The emerging landscape of breast cancer susceptibility. Nat Genet. 2007; 40: 17–22.
    OpenUrl
  25. 25.↵
    2. Richards S,
    3. Aziz N,
    4. Bale S,
    5. Bick D,
    6. Das S,
    7. Gastier-Foster J, et al.
    Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015; 17: 405–23.
    OpenUrlCrossRefPubMed
  26. 26.↵
    2. Kleibl Z,
    3. Kristensen VN.
    Women at high risk of breast cancer: molecular characteristics, clinical presentation and management. Breast. 2016; 28: 136–44.
    OpenUrl
  27. 27.↵
    2. Hwang S-J,
    3. Lozano G,
    4. Amos CI,
    5. Strong LC.
    Germline p53 mutations in a cohort with childhood sarcoma: sex differences in cancer risk. Am J Hum Genet. 2003; 72: 975–83.
    OpenUrlCrossRefPubMed
  28. 28.
    2. Hearle N,
    3. Schumacher V,
    4. Menko FH,
    5. Olschwang S,
    6. Boardman LA,
    7. Gille JJP, et al.
    Frequency and spectrum of cancers in the Peutz-Jeghers syndrome. Clin Cancer Res. 2006; 12: 3209–15.
    OpenUrlAbstract/FREE Full Text
  29. 29.
    2. Hansford S,
    3. Kaurah P,
    4. Li-Chang H,
    5. Woo M,
    6. Senz J,
    7. Pinheiro H, et al.
    Hereditary diffuse gastric cancer syndrome: CDH1 mutations and beyond. JAMA Oncol. 2015; 1: 23.
    OpenUrlPubMed
  30. 30.↵
    2. Tan M-H,
    3. Mester JL,
    4. Ngeow J,
    5. Rybicki LA,
    6. Orloff MS,
    7. Eng C.
    Lifetime cancer risks in individuals with germline PTEN mutations. Clin Cancer Res. 2012; 18: 400–7.
    OpenUrlAbstract/FREE Full Text
  31. 31.↵
    2. Sheng S,
    3. Xu Y,
    4. Guo Y,
    5. Yao L,
    6. Hu L,
    7. Ouyang T, et al.
    Prevalence and clinical impact of TP53 germline mutations in Chinese women with breast cancer. Int J Cancer. 2020; 146: 487–95.
    OpenUrl
  32. 32.↵
    2. Yang X,
    3. Leslie G,
    4. Doroszuk A,
    5. Schneider S,
    6. Allen J,
    7. Decker B, et al.
    Cancer risks associated with germline PALB2 pathogenic variants: an International study of 524 families. J Clin Oncol. 2019; 38: 674–85.
    OpenUrl
  33. 33.↵
    2. Kuchenbaecker KB,
    3. Hopper JL,
    4. Barnes DR,
    5. Phillips K-A,
    6. Mooij TM,
    7. Roos-Blom M-J, et al.
    Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017; 317: 2402.
    OpenUrlCrossRefPubMed
  34. 34.↵
    2. Zhou J,
    3. Wang H,
    4. Fu F,
    5. Li Z,
    6. Feng Q,
    7. Wu W, et al.
    Spectrum of PALB2 germline mutations and characteristics of PALB2-related breast cancer: screening of 16,501 unselected patients with breast cancer and 5890 controls by next-generation sequencing. Cancer. 2020; 126: 3202–8.
    OpenUrlPubMed
  35. 35.↵
    2. Southey MC,
    3. Goldgar DE,
    4. Winqvist R,
    5. Pylkäs K,
    6. Couch F,
    7. Tischkowitz M, et al.
    PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. J Med Genet. 2016; 53: 800–11.
    OpenUrlAbstract/FREE Full Text
  36. 36.
    2. Goldgar DE,
    3. Healey S,
    4. Dowty JG,
    5. Silva LD,
    6. Chen X,
    7. Spurdle AB, et al.
    Rare variants in the ATM gene and risk of breast cancer. Breast Cancer Res. 2011; 13: R73.
    OpenUrlCrossRefPubMed
  37. 37.↵
    1. (UK) TBCSC,
    2. Renwick A,
    3. Thompson D,
    4. Seal S,
    5. Kelly P,
    6. Chagtai T, et al.
    ATM mutations that cause ataxia-telangiectasia are breast cancer susceptibility alleles. Nat Genet. 2006; 38: 873–5.
    OpenUrlCrossRefPubMed
  38. 38.↵
    2. Kilpivaara O,
    3. Vahteristo P,
    4. Falck J,
    5. Syrjäkoski K,
    6. Eerola H,
    7. Easton D, et al.
    CHEK2 variant I157T may be associated with increased breast cancer risk: CHEK2 1157T and breast cancer risk. Int J Cancer. 2004; 111: 543–7.
    OpenUrlCrossRefPubMed
  39. 39.
    Consortium CBCC-C. CHEK2*1100delC and susceptibility to breast cancer: a collaborative analysis involving 10,860 breast cancer cases and 9,065 controls from 10 studies. Am J Hum Genet. 2004; 74: 1175–82.
    OpenUrlCrossRefPubMed
  40. 40.↵
    2. Meijers-Heijboer H,
    3. Ouweland A van den,
    4. Klijn J,
    5. Wasielewski M,
    6. Snoo A de,
    7. Oldenburg R, et al.
    Low-penetrance susceptibility to breast cancer due to CHEK2*1100delC in noncarriers of BRCA1 or BRCA2 mutations. Nat Genet. 2002; 31: 55–9.
    OpenUrlCrossRefPubMed
  41. 41.↵
    2. Steffen J,
    3. Nowakowska D,
    4. Niwińska A,
    5. Czapczak D,
    6. Kluska A,
    7. Piątkowska M, et al.
    Germline mutations 657del5 of the NBS1 gene contribute significantly to the incidence of breast cancer in Central Poland. Int J Cancer. 2006; 119: 472–5.
    OpenUrlCrossRefPubMed
  42. 42.↵
    2. Zhang G,
    3. Zeng Y,
    4. Liu Z,
    5. Wei W.
    Significant association between Nijmegen breakage syndrome 1 657del5 polymorphism and breast cancer risk. Tumor Biol. 2013; 34: 2753–7.
    OpenUrl
  43. 43.↵
    2. Yao L,
    3. Sun J,
    4. Zhang J,
    5. He Y,
    6. Ouyang T,
    7. Li J, et al.
    Breast cancer risk in Chinese women with BRCA1 or BRCA2 mutations. Breast Cancer Res Treat. 2016; 156: 441–5.
    OpenUrl
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