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. 2025 Apr 9;10(4):104543. doi: 10.1016/j.esmoop.2025.104543

Prevalence and clinical impact of germline pathogenic variants in breast cancer: a descriptive large single-center study

A Rodriguez-Hernandez 1,2,3, O Martínez-Sáez 1,2,3,4, F Brasó-Maristany 1,2,4,5,6,7, B Conte 1,2,4, R Gómez 1,2,4, I García-Fructuoso 1,2,4, B Fratini 8,9, E Segui 1,2,3,4, M Potrony 10,11, E Sanfeliu 2,12, S Cobo 2, P Galvan 2, L Moreno 3,13,14, E Grau 3,13,14, MR Aceituno 2, JA Puig-Butille 10, J Oriola 10, G Goberna 2, P Blasco 2, O Castillo 2, V Sirenko 2, A Aguirre 2, M Vidal 1,4, M Muñoz 1,2,4, T Ramon Y Cajal 1,2, F Balaguer 3,13,14, A Prat 1,2,3,4,7,15,∗, B Adamo 1,2,3,4
PMCID: PMC12008705  PMID: 40209283

Abstract

Background

Germline (likely) pathogenic variants (PVs) are identified in 5%-10% of patients with breast cancer (BC) and play a critical role in guiding clinical management, including the use of targeted therapies such as poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi). High-risk genes such as BRCA1, BRCA2, and PALB2, and moderate-risk genes such as CHEK2 and ATM, influence BC risk and treatment decisions. This study evaluates the prevalence and clinical impact of PVs in a large consecutive cohort.

Materials and methods

A retrospective analysis was conducted on 912 individuals with BC who underwent germline testing at the Hospital Clinic of Barcelona from 2016 to 2023. Genetic testing for 14 BC and Lynch syndrome genes was carried out using the TruSight Hereditary Cancer Panel. Statistical analyses were carried out to assess associations between germline results and clinical characteristics, including eligibility for PARPi therapy.

Results

Of the 912 individuals, 129 (14.1%) had a PV, with BRCA2 (31.8%) and BRCA1 (24%) being the most frequently altered genes. Additionally, 16.2% carried variants of uncertain significance, most commonly in ATM and BRCA2 genes. Patients with PV were younger compared with PV-negative individuals (median age: 43.5 versus 48.2 years, P = 0.006), more likely to have bilateral BC (13.3% versus 5.8%, P = 0.002), and more frequently diagnosed with triple-negative BC (TNBC; 28.7% versus 20.8%, P = 0.046). Of those with PVs, 39.1% completed a bilateral mastectomy, 36.7% had a risk-reducing salpingo-oophorectomy, and 22.7% had both surgeries. PV detection was associated with higher stages at diagnosis (stage IV: 13.0% versus 5.9%, P < 0.001). In the metastatic cohort, 12.9% received PARPi therapy, with 80.7% harboring BRCA1/2 PVs. In early BC, 13.1% met the criteria for adjuvant PARPi.

Conclusions

The identification of germline PVs significantly influences surgical decisions and systemic therapies. Genetic testing for patients with BC optimizes care, particularly in selecting candidates for PARPi in both early and advanced BC, improving management and prevention strategies.

Key words: breast cancer, germline testing, pathogenic germline variants, PARP inhibitors

Highlights

  • •

    Germline (likely) PVs were detected in 14.1% (129/912) of the cohort.

  • •

    High-risk PV carriers were younger, with more bilateral BC, stage IV, and TNBC than PV-negative patients.

  • •

    Basal-like subtype was overrepresented in high-risk PV carriers, while LumA/B and HER2-enriched were similarly distributed.

  • •

    Germline testing guided PARPi therapy for 12.9% of patients with metastatic BC.

Introduction

Breast cancer (BC) remains the most common malignancy among females and a leading cause of cancer-related mortality.1 Germline (likely) pathogenic variants (PVs), hereafter collectively referred to as PVs, are detected in 5%-10% of BC cases, and it is essential to identify them given their critical role in guiding treatment decisions.2, 3, 4, 5 High-risk genes such as BRCA1, BRCA2, PALB2, and TP53, and moderate-risk genes such as CHEK2 and ATM, significantly influence the risk of developing BC.2,6, 7, 8 The detection of PVs has implications for surgical choices, adjuvant therapies, and risk-reducing procedures, particularly in patients with a family history or early-onset BC.9 Triple-negative breast cancer (TNBC) and estrogen receptor-positive (ER-positive) BC display varying associations with different PVs.10, 11, 12, 13, 14, 15, 16 Understanding the prevalence and characteristics of PVs in patients with BC is crucial for optimizing management and improving outcomes.2,6,17, 18, 19, 20, 21, 22, 23, 24, 25 This study presents a single-center experience of germline testing in 912 consecutive patients with BC, providing insights into PV detection and its clinical relevance.

Materials and methods

Study population

This retrospective, single-center study included 1060 consecutive individuals with a personal history of invasive BC who met regional criteria for germline genetic testing at the Hospital Clinic of Barcelona, Spain (Supplementary Table S1, available at https://doi.org/10.1016/j.esmoop.2025.104543). Patients were referred to the hereditary cancer unit between January 2016 and January 2023. Written informed consent was obtained from all participants to carry out the germline testing, and this study was approved by the Ethics Committee of the Hospital Clinic of Barcelona (HCB/2021/0062).

Patients with an in situ BC, a BC diagnosis before 2000 [due to differences in treatment options and immunohistochemistry (IHC) and molecular information], or missing clinical information were excluded, resulting in a final cohort of 912 patients (Supplementary Figure S1, available at https://doi.org/10.1016/j.esmoop.2025.104543). The cohort was divided into two groups: (i) negative group (PV negative), comprising BC patients with no (likely) PV, (likely) benign, or with variant of uncertain significance (VUS) without clinical impact, and (ii) the PV carrier group, comprising those with PV or likely pathogenic variant (LPV) in BC-related genes and Lynch syndrome-related genes including BRCA1, BRCA2, PALB2, ATM, CHEK2, BARD1, RAD51C, RAD51D, TP53, and PTEN, and as opportunistic testing including MLH1, MSH2, and MSH6. BRCA1, BRCA2, PALB2, PTEN, and TP53 were categorized as high-risk genes, while ATM, CHEK2, BARD1, RAD51C, RAD51D, and MSH2 were considered moderate risk.6

Clinical data and family history were obtained from medical records. Germline testing criteria were based on current guidelines,6,19 and the primary reason for testing was used for analysis (Supplementary Table S1, available at https://doi.org/10.1016/j.esmoop.2025.104543). Family cancer history was documented for first-, second-, and third-degree relatives, including various cancer types. Personal cancer history included specific cancers but excluded in situ BC and BC relapses. To explore the use of poly (ADP-ribose) polymerase inhibitors (PARPi), all patients with metastatic disease (stage IV) either at inclusion or who progressed to stage IV during the study period were included in the analysis.

Hormone receptor status was assessed via immunohistochemistry (IHC), human epidermal growth factor receptor 2 (HER2) status via IHC and FISH, and intrinsic subtypes were based on Prosigna® or PAM50 data.26

Germline genetic testing

DNA were extracted from peripheral blood samples using the Magnapure 96 system (Roche, Indianapolis, IN). Next-generation sequencing (NGS) libraries were prepared using the TruSight Rapid Capture Kit and Hereditary Cancer Panel (Illumina, San Diego, CA), with sequencing carried out on the MiSeq platform. Analysis focused on BC susceptibility genes (BRCA1, BRCA2, PALB2, etc.) and Lynch syndrome-related genes (MLH1, MSH2, and MSH6).14 BARD1 was tested in patients referred from 2021, accounting for 35.2% (321/912) of the cohort.

Detected variants were classified per the American College of Medical Genetics (ACMG) guidelines into five categories: likely PVs, PVs, VUS, likely benign, or benign.27 Sanger sequencing was used to confirm all indel PVs.

More details on the genetic analysis can be found in another study conducted by our group.28 If needed, a draft of this manuscript can be provided for further reference.

Statistical analysis

For analysis, LPVs and PVs were combined and referred to as PV. Clinical characteristics were compared between the PV carrier and PV-negative groups using the chi-square or Fisher’s exact test, as appropriate. Age at diagnosis was assessed using the Mann–Whitney U or Kruskal–Wallis test due to non-normal distribution. Logistic regression models were used to analyze the association between clinical variables and the presence of PVs, adjusting for age, sex, personal cancer history, TNBC subtype, bilateral BC, and stage at diagnosis. A P value of <0.05 was considered statistically significant, with a false discovery rate (Benjamini–Hochberg) correction applied for multiple comparisons. Data collection and cleaning were conducted between 2021 and 2023, and statistical analysis was carried out between 2023 and 2024. All analyses were carried out using R version 4.3.2.

Results

Study population characteristics

Between January 2016 and January 2023, 912 individuals with a personal history of invasive BC underwent genetic counseling and germline testing at the Hospital Clinic of Barcelona (Supplementary Figure S1, available at https://doi.org/10.1016/j.esmoop.2025.104543). The median age of the cohort was 47.6 years (range 24.4-88.6 years), and 98.5% were female (n = 898). The cohort was predominantly white or European ethnicity (95.0%), followed by a smaller percentage of Hispanic or South or Central American (2.4%) (Supplementary Table S2, available at https://doi.org/10.1016/j.esmoop.2025.104543).

A total of 831 individuals (91.1%) met the clinical criteria for suspicion of hereditary cancer syndrome, which included family aggregation of cancers (n = 357), BC diagnosis before age 40 years (n = 199), TNBC before age 60 years (n = 162), related tumors (n = 49), multiple BCs in the same individual (n = 36), male BC (n = 12), or Ashkenazi Jewish ancestry (n = 1). Among the 81 individuals (6.9%) who did not meet these criteria, 63 (77.8%) underwent genetic testing for potential therapeutic benefits, with 39.7% (n = 23) of patients with stage IV de novo BC referred for genetic testing to explore the use of PARPi (Supplementary Table S2, available at https://doi.org/10.1016/j.esmoop.2025.104543).

The clinical characteristics of the overall cohort showed that the majority had hormone receptor-positive (HR-positive)/HER2-negative BC (62.4%, n = 563), while 22.0% (n = 198) had TNBC, and 15.6% (n = 141) had HER2-positive BC. Out of the 912 tested, 129 individuals (14.1%) carried a PV, and 783 individuals (85.9%) had no PV identified in BC-related genes (Figure 1A). BRCA2 was the most frequently affected gene, with 41 PVs (31.8%), followed by BRCA1 with 31 PVs (24.0%), CHEK2 with 17 PVs (13.2%), and ATM with 15 PVs (11.6%). PALB2 PVs were detected in 13 individuals (10.0%), TP53 in 5 (3.9%), and other less frequent PVs included BARD1, MSH2, PTEN, and RAD51C (each detected in 1.6% of or fewer individuals) (Figure 1B) (Supplementary Table S3, available at https://doi.org/10.1016/j.esmoop.2025.104543).

Figure 1.

Figure 1

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Germline genetic testing results. (A) Results of germline testing in patients with breast cancer (n = 912). (B) Distribution of (likely) pathogenic variants among PV carriers (n = 129). PV, (likely) pathogenic variant; VUS, variant of uncertain significance.

Two patients were found to have two distinct PVs: one carried both BRCA2 and MSH6 variants, while another carried both PALB2 and CHEK2 variants. VUS were identified in 16.2% (n = 148) of individuals (Figure 1A), with the majority occurring in ATM (25.7%), BRCA2 (15.5%), and PALB2 (10.8%) (Supplementary Table S4, available at https://doi.org/10.1016/j.esmoop.2025.104543).

Clinical predictors of PVs

Table 1 presents a comparison of demographic and clinical characteristics between PV carriers and PV-negative patients. Individuals with PVs were significantly younger at the time of BC diagnosis, with a median age of 43.5 years compared with 48.2 years for those without PVs (P = 0.006). Premenopausal status was more common in individuals with PVs (68.3% versus 56.9%, P = 0.023). Additionally, individuals with PVs were more likely to have a personal history of other cancers (19.4% versus 11.8%, P = 0.022). Differences in clinical criteria for germline testing between the PV carriers and PV-negative groups were not statistically significant (P = 0.271), but a higher proportion of individuals with PVs had a personal history of BC diagnosed at ≤40 years of age (27.9%) or TNBC diagnosed at ≤60 years of age (20.2%) compared with the negative group (20.8% and 17.4%, respectively).

Table 1.

Differences in clinical characteristics between the PV-negative and the PV-carriers group

Characteristics PV-negative (n = 783) PV-carriers (n = 129) P-value
Sex, n (%)
 Female 774 (98.9) 124 (96.1) 0.036
 Male 9 (1.2) 5 (3.9)
Age at diagnosis, years, median (range) 48.16 (24.44-88.55) 43.46 (28.27-74.13) 0.006
Age at diagnosis (groups), n (%)
 ≤50 years 445 (56.8) 84 (65.1) 0.082
 >50 years 338 (43.2) 45 (34.9)
Age at diagnosis (groups), n (%)
 ≤40 years 178 (22.7) 46 (35.7) 0.002
 >40 years 605 (77.3) 83 (64.3)
Menopausal status, n (%)
 Premenopausal 431 (56.9%) 84 (68.%) 0.023
 Postmenopausal 326 (43.1) 39 (31.7)
Ethnicity, n (%)
 White or European 738 (94.3) 120 (93.0) 0.208
 Hispanic or South or Central American 20 (2.6) 2 (1.6)
 Asian or Southeast Asian 12 (1.5) 3 (2.3)
 Middle Eastern or North African 3 (0.4) 2 (1.6)
 Black, African, or Caribbean 1 (0.1) 1 (0.8)
 Ashkenazi Jews 1 (0.1) 0
Criteria for genetic testing, n (%)
 Family aggregation 315 (40.2) 42 (32.6) 0.271
 Breast cancer and aged ≤40 years 163 (20.8) 36 (27.9)
 TNBC and aged ≤60 years 136 (17.4) 26 (20.2)
 Therapeutic benefit 56 (7.2) 7 (5.4)
 Related tumors in the same patient 42 (5.3) 7 (5.5)
 ≥ 2 breast cancers 31 (4.0) 5 (3.9)
 Not meeting clinical criteria 16 (2.0) 2 (1.6)
 Family not informative 15 (1.9) 0
 Male breast cancer 8 (1.0) 4 (3.1)
 Ashkenazi Jews 1 (0.1) 0
Family cancer history, n (%)a
 No 173 (22.3) 23 (18.4) 0.392
 Yes 604 (77.7) 102 (81.6)
Personal cancer historyb, n (%)
 No 689 (88.2) 104 (80.6%) 0.024
 Yes 92 (11.8) 25 (19.4)
Histology, n (%)
 Invasive ductal carcinoma 642 (85.9) 106 (84.8) 0.942
 Invasive lobular carcinoma 52 (7.0) 10 (8.0)
 Others 53 (7.1) 9 (7.2)
Grade of differentiation, n (%)
 Low grade (1 and 2) 425 (69.8) 65 (63.7) 0.267
 High grade (3) 184 (30.2) 37 (36.3)
Stage at diagnosis, n (%)
 I 286 (39.4) 30 (26.1) 0.005
 II 315 (43.4) 58 (50.4)
 III 82 (11.3) 12 (10.4)
 IV 43 (5.9) 15 (13.0)
cT, n (%)
 ≤2 cm 323 (45.0) 37 (34.3) 0.097
 2-5 cm 278 (38.7) 52 (48.1)
 >5 cm 117 (16.3) 19 (17.6)
cN, n (%)
 Negative 472 (65.6) 67 (60.9) 0.374
 Positive 248 (34.4) 43 (39.1)
IHC subtype, n (%)
 HR+/HER2– 489 (63.3) 74 (57.4) 0.065
 HR+/HER2+ 83 (10.7) 16 (12.4)
 HR–/HER2+ 40 (5.2) 2 (1.6)
 TNBC 161 (20.8) 37 (28.7)
Bilateral breast cancer, n (%)
 No 729 (94.2) 111 (86.7) 0.002
 Yes 45 (5.8) 17 (13.3)
TNBC, n (%)
 No 612 (79.2) 92 (71.3) 0.046
 Yes 161 (20.8) 37 (28.7)
Intrinsic subtypes, n (%)
 Luminal A 148 (43.9) 28 (38.4) 0.247
 Luminal B 85 (25.2) 18 (25.7)
 HER2-enriched 53 (15.7) 9 (12.3)
 Basal-like 51 (15.1) 18 (24.7)
Neoadjuvant chemotherapy, n (%)
 No 397 (54.8) 61 (53.0) 0.767
 Yes 327 (45.2) 54 (47.0)
Type of surgery, n (%)
 Lumpectomy 419 (58.4) 56 (49.6) 0.014
 Mastectomy 281 (39.2) 49 (43.4)
 Bilateral mastectomy 17 (2.4) 8 (7.1)
Adjuvant chemotherapy, n (%)
 No 442 (61.9) 57 (51.4) 0.044
 Yes 272 (38.1) 54 (48.6)
Adjuvant hormone therapy, n (%)
 No 201 (27.5) 40 (35.7) 0.065
 Yes 531 (72.5) 72 (64.3)
Carboplatin NA/A n (%)
 No 618 (88.4) 94 (81.0) 0.041
 Yes 81 (11.6) 22 (19.0)
Radiotherapy, n (%)
 No 149 (21.0) 35 (31.0) 0.022
 Yes 560 (79.0) 78 (69.0)
Risk-reducing mastectomy (RRM), n (%)
 No 687 (95.2) 78 (60.9) <0.001
 Yes 35 (4.8) 50 (39.1)
Risk-reducing salpingo-oophorectomy (RRSO), n (%)
 No 707 (97.7) 81 (63.3) <0.001
 Yes 17 (2.3) 47 (36.7)
RRM + RRSO, n (%)
 No 719 (99.6) 99 (77.3) <0.001
 Yes 3 (0.4) 29 (22.7)
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Statistically significant results are highlighted in bold (P < 0.05).

cN, node involvement at diagnosis; cT, tumor size at diagnosis; ER, estrogen receptor; ER, estrogen receptor; HR+, ER ≥1%; HR−, ER <1%; HER2, human epidermal growth factor receptor 2; HER2+, positive (IHC 3+ or FISH positive); HR, hormone receptor; IHC, immunohistochemical subtype; LPV, likely pathogenic variant; NA/A, neoadjuvant and/or adjuvant chemotherapy; PV, pathogenic variant; TNBC, triple-negative breast cancer; VUS, variant of uncertain significance.

a

Family history of cancer: first-, second-, and third-degree relatives.

b

Personal cancer history included the diagnosis of other cancers except a second breast cancer.

Histologically, no significant differences were observed between groups. Invasive ductal carcinoma was the predominant histology in both groups (84.8% in the PV carrier group and 85.9% in the PV-negative group). Invasive lobular carcinoma and other subtypes were similarly distributed between the two groups. No significant differences were observed in histological grade, tumor size, or node involvement between groups (Table 1).

In multivariable logistic regression analysis, age at BC diagnosis as a continuous variable was inversely associated with PV-positive results [odds ratio (OR) 0.96, 95% confidence interval (CI) 0.94-0.98, P < 0.001]. Male sex was significantly associated with PVs (OR 5.32, 95% CI 1.01-22.26, P = 0.052) as were a personal history of cancer other than BC (OR 2.30, 95% CI 1.27-4.04, P = 0.011), stage IV disease at diagnosis (OR 3.84, 95% CI 1.82-7.92, P = 0.001), and bilateral breast cancer (OR 2.69, 95% CI 1.35-5.14, P = 0.010). TNBC was significantly associated with PVs in the univariable analysis (P = 0.047); however, this association was not statistically significant in the multivariable analysis (OR 1.55, 95% CI 0.96-2.46, P = 0.093) (Table 2).

Table 2.

Association of clinical variables with PV carriers

Variables Univariable analysis (OR, 95% CI) P value Multivariable analysis (OR, 95% CI)a P value Adj P valueb
Agec 0.97 (0.96-0.99) 0.008 0.96 (0.94-0.98) <0.001 <0.001
Sex: male versus female 3.46 (1.05-10.20) 0.028 5.32 (1.01-22.26) 0.029 0.052
Personal cancer history yes versus no 1.80 (1.09-2.89) 0.018 2.30 (1.27-4.04) 0.005 0.011
Stage II versus stage I at diagnosis 1.75 (1.11-2.84) 0.019 1.57 (0-96-2.59) 0.073 0.093
Stage III versus stage I at diagnosis 1.40 (0.66-2.78) 0.360 1.38 (0.64-2.83) 0.388 0.388
Stage IV versus stage I at diagnosis 3.33 (1.62-6.61) <0.001 3.84 (1.82-7.92) <0.001 0.001
Bilateral breast cancer yes versus no 2.48 (1.34-4.41) 0.003 2.69 (1.35-5.14) 0.003 0.010
TNBC yes versus no 1.52 (1.00-2.30) 0.047 1.55 (0.96-2.46) 0.065 0.093
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Statistically significant results are highlighted in bold (P < 0.05).

Adj, adjusted; CI, confidence of interval; OR, odds ratio; PV, pathogenic variant; TNBC, triple-negative breast cancer.

a

Multivariable analyses were adjusted with age, sex, family history, personal cancer history, stage at diagnosis, bilateral breast cancer, and TNBC subtype.

b

Adjusted (Adj) P values were calculated using the false discovery rate (Benjamini–Hochberg) correction method.

c

Age as a continuous variable.

High-risk and moderate-risk PVs compared with the negative group

Compared with PV-negative patients, PV carrier with PVs in high-risk genes (i.e. BRCA1, BRCA2, PALB2, TP53, and PTEN) (n = 92) were younger at diagnosis (42.8 versus 48.2 years; P = 0.002) and more likely to have bilateral BC (15.4% versus 5.8%; P = 0.001), stage IV disease (12.3% versus 5.9%; P = 0.008), and TNBC (38.0% versus 20.8%; P < 0.001) (Supplementary Table S5, available at https://doi.org/10.1016/j.esmoop.2025.104543). In multivariable logistic regression analysis, clinical variables associated with high-risk PVs were younger age (OR 0.95, 95% CI 0.93-0.97, P < 0.001), personal history of cancer other than BC (OR 2.33, 95% CI 1.14-4.56, P = 0.029), stage IV at diagnosis (OR 4.35, 95% CI 1.72-10.42, P = 0.002), bilateral breast cancer (OR 3.83, 95% CI 1.80-7.82, P = 0.001), and TNBC subtype (OR 2.41, 95% CI 1.43-4.02, P = 0.002) (Supplementary Table S6, available at https://doi.org/10.1016/j.esmoop.2025.104543). In contrast, individuals with moderate-risk PVs (ATM, CHEK2, BARD1, RAD51C, and MSH2) did not exhibit any clinical difference compared with PV-negative individuals (Supplementary Tables S7 and S8, available at https://doi.org/10.1016/j.esmoop.2025.104543).

IHC subtype distribution by PV gene

The IHC subtype distribution among PV carriers revealed that 57.4% had HR-positive/HER2-negative BC, 28.7% had TNBC, and 14.0% had HER2-positive BC. Notably, BRCA1 PVs were predominantly associated with TNBC (77.4%), whereas BRCA2 PVs were primarily associated with HR-positive/HER2-negative BC (70.7%), with only 14.6% having TNBC and 14.6% HER2-positive BC. Among PALB2 carriers, 69.2% had HR-positive/HER2-negative and 30.8% had TNBC, while among CHEK2 carriers, 76.5% had HR-positive/HER2-negative (Figure 2). Multinomial analysis demonstrated significant associations between BRCA1 and TNBC (OR 10.41, 95% CI 4.40-24.62, P < 0.001), and TP53 and HER2-positive BC (OR 11.92, 95% CI 1.23-115.58, P = 0.032) (Supplementary Table S9, available at https://doi.org/10.1016/j.esmoop.2025.104543).

Figure 2.

Figure 2

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The distribution by immunohistochemistry subtypes. (A) Patients with negative genetic testing (n = 783). (B) PV carriers (n = 129), per gene [BRCA1 (n = 31), BRCA2 (n = 41), PALB2 (n = 13), CHEK2 (n = 17), ATM (n = 15)], and other genes [(BARD1 (n = 1), MSH2 (n = 2), PTEN (n = 2), RAD51C (n = 1), TP53 (n = 5)]. HER2-2, human epidermal growth factor receptor-2; HR, hormone receptor; PV, (likely) pathogenic variant; TNBC, triple-negative breast cancer.

While the distribution of Prosigna/PAM50-based intrinsic subtypes did not differ significantly between the PV carriers and PV-negative groups (P = 0.247), a higher numerical proportion of basal-like subtypes was observed in tumors from PV carriers (24.7% versus 15.1%; P = 0.055). This difference was statistically significant when comparing high-risk PV carriers to PV-negative individuals (32.7% versus 15.1%; P = 0.031) (Supplementary Table S5, available at https://doi.org/10.1016/j.esmoop.2025.104543), but not in individuals with moderate-risk PVs (4.8% versus 15.1%; P = 0.284) (Supplementary Table S7, available at https://doi.org/10.1016/j.esmoop.2025.104543). The luminal A, luminal B, and HER2-enriched subtypes were similarly distributed between groups (Table 1).

Impact of germline results on treatment

The presence of PVs significantly influenced both surgical and systemic treatment decisions. PV carriers underwent more surgical interventions, with 43.4% undergoing therapeutic mastectomy compared with 39.2% in the PV-negative group (P = 0.014). Similarly, bilateral mastectomies were carried out more frequently in individuals with PVs (7.1% versus 2.4%; P = 0.014). Regarding adjuvant treatment, individuals with PVs were more likely to receive adjuvant chemotherapy (48.6% versus 38.1%; P = 0.044) and platinum-based chemotherapy (19.0% versus 11.6%; P = 0.041). Although the rates of neoadjuvant chemotherapy were similar between groups (47.0% versus 45.2%; P = 0.767), individuals with PVs showed a non-significant trend toward being less likely to receive adjuvant hormone therapy (64.3% versus 72.5%; P = 0.065).

In those who received neoadjuvant chemotherapy, there was no difference in pathological complete response (pCR) between the PV carriers and PV-negative groups (38.5% versus 38.1%; P = 1.00). Among individuals with PVs, 39.1% underwent risk-reducing mastectomy (RRM), and 36.7% had a risk-reducing salpingo-oophorectomy (RRSO). Notably, 22.7% underwent both surgeries (RRM + RRSO) (Table 1).

A closer examination of individuals with high-risk PVs (e.g. BRCA1, BRCA2, PALB2, TP53) showed a statistically non-significant higher prevalence of mastectomies and bilateral mastectomies (56.1%) (n = 46) compared with those with PVs in moderate-risk genes [35.5% (n = 11); P = 0.134]. High-risk PV carriers also received more platinum-based chemotherapy (24.1% versus 6.1%; P = 0.034) and less adjuvant hormone therapy (54.3% versus 90.3%; P < 0.001). Regarding risk-reducing surgeries, 46.2% (n = 42) of individuals with high-risk PVs underwent RRM, compared with 21.6% (n = 8) of those with moderate-risk PVs (P = 0.018). Similarly, RRSO was more prevalent in high-risk PV carriers, with 47.3% (n = 43) undergoing the procedure, compared with only 10.8% (n = 4) in the moderate-risk group (P < 0.001). All individuals who underwent both RRM and RRSO carried a high-risk PV (n = 29; 100%).

In the cohort of individuals with stage IV BC at diagnosis or relapse during follow-up (n = 203), 12.9% (n = 26) received treatment with PARPi. Among these patients, 18 (69.2 PV%) had a germline PV in BRCA1/2, 1 had in CHEK2, and 1 in RAD51C. Three individuals had somatic pathogenic variants in BRCA1/2, while three were negative for germline PV and unknown BRCA1/2 somatic variants. The patients without BRCA1/2 variants were treated within clinical trials. Regarding treatment with PARPi, 76.9% (n = 20) received olaparib, including three who were treated in combination with immunotherapy, while 23.1% (n = 6) received talazoparib. Among patients with germline BRCA1/2 PVs, 44.4% (8/18) achieved a complete radiological response (CR) or partial response (PR), and the median duration of response was 5.4 months (range 1.2-20.2 months). Among patients with somatic PVs in BRCA1/2 (n = 3), two experienced a PR and one had progressive disease. The patient with a germline PV in CHEK2 who received PARPi as sixth-line therapy achieved a PR, while the patient with a germline PV in RAD51C treated in the second line had stable disease (SD) for 5.4 months (Figure 3). In early-stage BC, 99 individuals met the OlympiA trial criteria for adjuvant olaparib.29 Of these, 13.1% (n = 13) carried a germline PV in BRCA1/2. None of the early-stage individuals in our cohort received PARPi in the adjuvant setting (Supplementary Table S10, available at https://doi.org/10.1016/j.esmoop.2025.104543).

Figure 3.

Figure 3

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Swimmer plot of metastatic breast cancer patients treated with PARP inhibitors. A total of 26 patients received treatment with PARP inhibitors in a metastatic setting, across different lines of therapy and with various BRCA1/2 statuses. CR, complete response; gBRCA1/2, germline pathogenic variants (PV) in BRCA1/2; gCHEK2, germline PV in CHEK2; gRAD51C, germline PV in RAD51C; PD, progression disease; PFS, progression-free survival; PR, partial response; sBRCA1/2, somatic PV in BRCA1/2; SD, stable disease.

Discussion

Our study reports findings from a cohort of 912 patients with BC who underwent germline testing for 14 BC and Lynch syndrome-related genes. We detected PVs in 14.1% of patients, a higher rate than typically reported in unselected cohorts,30 which likely reflects our cohort’s selection based on clinical criteria such as family history, early-onset disease, and TNBC. High-risk PVs in genes such as BRCA1, BRCA2, PALB2, and TP53 significantly influence management decisions, including surgical options like RRMs and the use of adjuvant therapies.2,26,31

The distribution of PVs in our cohort revealed BRCA2 as the most prevalent mutation, in contrast to earlier studies where BRCA1 was more commonly found.32,33 This shift may be enhanced by the broader application of genetic testing in HR-positive BC, where BRCA2 variants are more frequent,34 and improvement in NGS techniques. Additionally, 6.9% of our cohort had stage IV disease at diagnosis, where BRCA2 variants have been more commonly described than BRCA1 PVs.35,36 The inclusion of moderate-risk genes (ATM, CHEK2, RAD51C, and others) further highlights the complexity of genetic predisposition in BC.18

We also found that 16.9% of our cohort carried VUS, predominantly in ATM. Among the genes tested, ATM is one of the largest, with 66 exons, but its exons are not frequently mutated. Consequently, clinical and functional data for many ATM variants are limited.37 While VUS have been reported in 10%-20% of BC cases, their clinical implications remain unclear, and patient management should not rely solely on these findings.38 Continuous monitoring and potential reclassification of VUS are essential, as some variants may later be reclassified as pathogenic or benign.39

Consistent with prior knowledge, key clinical variables, such as younger age at BC onset, male sex, bilateral BC, and a personal history of cancer other than a second BC, were significantly associated with PV detection, particularly for high-risk genes. In contrast, moderate-risk genes were less clearly linked to specific clinical characteristics.12,30,40,41 Despite the fact that TNBC was highly predictive of BRCA1 variants, more than half of the PVs were found in patients with a luminal phenotype, underscoring the importance of testing beyond TNBC.10,11,32,42 In our cohort, we present novel findings on intrinsic subtypes. High-risk PV carriers were enriched in the basal-like subtype, with no significant differences in other intrinsic subtypes (LumA, LumB, HER2-enriched), as previously reported.43

In line with prior results, surgical decisions were influenced by PV status, with patients carrying PVs being more likely to undergo bilateral mastectomies at diagnosis or eventual risk-reducing surgeries.9,44,45 Notably, 21.6% of moderate-risk PV carriers also underwent RRMs, despite limited evidence supporting this intervention. This points to the need for refined guidelines to prevent overtreatment in moderate-risk PV carriers.45,46

The advent of PARPi has transformed treatment for patients with BC with BRCA1/2 PVs. PARPi have demonstrated significant improvements in survival outcomes, both in early and metastatic settings, leading to expanded recommendations for genetic testing.20, 21, 22,25,26,47 Germline testing guided PARPi therapy for 12.9% of metastatic patients and identified 13.1% of patients with early-stage BC who would have met the criteria for adjuvant PARPi, highlighting the growing importance of germline testing in personalized treatment strategies.

Despite the strengths of our study, such as the relatively large sample size, there are limitations to consider. The retrospective design and selection bias based on clinical criteria may have affected some of the clinical variables and outcomes. Additionally, the relatively small number of PVs detected for individual genes limits our ability to make definitive conclusions about the clinical differences between PV carriers and PV-negative individuals. Although PV rates decrease as testing criteria are broadened for therapeutic purposes, our clinical predictors of PVs remain consistent with previously reported findings.12,40,41,48

Our findings have important clinical implications, particularly for optimizing genetic testing strategies in low-resource settings. Given the financial and infrastructural constraints that limit access to comprehensive genetic testing, the use of clinically available variables—such as age at diagnosis, sex, cancer stage, bilateral BC, histologic subtype, and personal and family history—can serve as a practical and cost-effective approach to identifying individuals at higher risk of carrying a PV. By leveraging these factors, health care providers can prioritize genetic testing for those most likely to benefit, ensuring that limited resources are allocated efficiently. Additionally, our study’s reliance on a targeted gene panel comprising well-established BC susceptibility and Lynch syndrome genes further supports the feasibility of this approach in settings where extensive sequencing may not be accessible. Expanding access to genetic testing through strategies such as mainstreaming, point-of-care testing, and telemedicine-based genetic counseling could help overcome existing barriers.49, 50, 51 Future research should focus on refining predictive models based on clinical data and evaluating the real-world impact of integrating these strategies into routine oncology care, with the goal of improving early detection and personalized management of hereditary BC worldwide.

In conclusion, while germline testing in BC has been generalized to facilitate therapeutic approach, clinical and pathologic features remain important and useful predictors of PV in high-risk-associated genes in clinical practice. Our study underscores the clinical importance of germline testing in BC, particularly in patients with high-risk factors such as early-onset disease, bilateral BC, or a personal history of cancer. Germline information significantly impacts surgical and systemic treatment decisions, particularly in advanced-stage disease and adjuvant settings where PARPi can be a key therapeutic option. It is crucial to ensure equitable access to genetic testing while prioritizing patients most likely to benefit from early detection. Future research should focus on understanding the implications of PVs in moderate-risk genes and further validate these findings across diverse populations through prospective, multicenter studies.

Acknowledgments

Funding

This work was support by Contracte Clínic Recerca ‘Clínic-La Pedrera’ [to ARH] (no grant number).

Disclosure

OM-S reports advisory/consulting fees from Reveal Genomics, Roche and AstraZeneca; lecture fees from Daiichi Sankyo, Novartis, Pfizer and Eisai and travel expenses from Gilead and Novartis. FB-M reports patents filed: PCT/EP2022/086493, PCT/EP2023/060810, EP23382703 and EP23383369, and part time employment by Reveal Genomics; received funding from Fundación científica AECC Ayudas Investigador AECC 2021 (INVES21943BRAS). BC was supported by research funding from GILEAD; travel expenses from Roche, Pfizer, Pharma Nutra; honoraria/invited speaker: AstraZeneca, GILEAD. RG reports honoraria/invited speaker: Novartis, Daiichi Sankyo and MSD. IG-F Daiichi-Sankyo, invited speaker, personal and travel expenses; Eisai, invited speaker, personal fees; Gilead, other, personal, travel expenses; Lilly, other, personal, travel expenses; Menarini-Stemline, other, personal, travel expenses; Novartis, invited speaker, personal and travel expense. ES was supported by Contracte Clínic Recerca “Emili Letang i Josep Font” 2022 and I Predoctoral Grant in Precision Oncology, 2022 (Cátedra UB IOP); personal fees for educational events and/or materials from Novartis, Pfizer, Eisai, and Daiichi Sankyo; advisory fees from Pfizer and Seagen; and travel and accommodation expenses from Gilead, Daiichi Sankyo, Novartis, and Lilly. AP reports advisory and consulting fees from AstraZeneca, Roche, Pfizer, Novartis, Daiichi Sankyo, Ona Therapeutics, and Peptomyc; lecture fees from AstraZeneca, Roche, Novartis, and Daiichi Sankyo; stockholder and employee of Reveal Genomics. All other authors have declared no conflicts of interest.

Data sharing

The data from this study are not publicly accessible, as participants did not consent to public sharing. However, researchers may request access to the data for academic purposes, contingent on a data transfer agreement and approval from the ethics committee.

Supplementary data

Supplemental Figure 1.

Supplemental Figure 1

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Supplemental Material
mmc1.docx (83.4KB, docx)

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