Male breast cancer (MBC) is a rare disease representing less than 1.0% of all breast cancers (BCs) and less than 1.0% of all cancers in men (1). Despite its rarity, the annual incidence of MBC continues to arise and is estimated at about 1 per 100.000 men (2).

Increasing evidence indicates that MBC and female breast cancer (FBC) may be different, with unique molecular subtypes suggesting gender-specific differences in terms of biological and clinical behavior (3). Despite distinct features, therapeutic approaches for MBC are extrapolated from clinical management guidelines relating to FBC (4). Overall, MBC has a poorer outcome, likely due to its occurrence later in life, the delay in diagnosis compared with the female counterpart (5), or to gender-specific factors yet to be identified.

The development of Next Generation Sequencing (NGS) technologies has produced a large amount of research data about genomic alterations in a wide variety of cancers, including BC (6). These large-scale initiatives have identified genomic alterations that are potential therapeutic targets to guide individualized treatment (7). Actionable genomic alterations include genetic variants, Copy Number Variations (CNVs), Tumor Mutational Burden (TMB) and Microsatellite Instability (MSI). Tumor-infiltrating lymphocytes (TILs) have also been suggested to represent potentially useful prognostic and predictive biomarkers, especially in triple negative FBCs (8).

While therapies based on NGS findings are a new standard of care for treating a variety of cancers, only a few studies have been performed to comprehensively characterize tumor profiles in MBCs (9–12) and data on specific molecular biomarkers in MBC are lacking. Moreover, associations among new potential molecular biomarkers and clinical data remain unclear in MBC, cutting out male patients from new targeted treatments. Thus, there is a need to investigate molecular biomarkers predictive of response to innovative treatments for a more effective clinical management of MBC patients.

In this pilot study, we characterized the molecular tumor profiling of 15 MBCs by targeted gene panel sequencing to identify clinically actionable somatic variants, CNVs, TMB and MSI status that may represent new predictive biomarkers for MBC patients.

In this study, we characterized the molecular profiling of 15 MBC cases by large multigene panel sequencing, targeting 1.94 Mb of the genome at 523 cancer-relevant genes. To the best of our knowledge, at present only two studies explored the genomic landscape of MBC (10, 12).

The molecular landscape of our series, although relatively small, resembles and recapitulates the main molecular profiles of MBC as described so far.

In line with previous studies, we identified PIK3CA as the most frequently mutated gene in MBC. The PIK3CA somatic variant frequency in our MBC series was slightly higher than that reported by Piscuoglio et al. and Moelans et al. (10, 12), most likely because of differences in size or composition of the series examined. Overall, our results add to previous findings (18) highlighting the relevant role of PIK3CA alterations in MBC.

On the other hand, in line with previous studies (10, 12, 18, 19), our findings showed that TP53 somatic variants are rare in MBC. TP53 variants are frequently observed in FBCs, particularly with luminal B and triple negative subtypes (10, 12). The low frequency of these subtypes in MBCs might explain the low TP53 variant frequency observed.

In addition, pathogenic variants in other genes were identified at low frequencies in our series, highlighting MBC heterogeneity. Among these, ARID1A pathogenic variants might be promising therapeutic targets in BC. ARID1A deficiency due to somatic mutations have been associated with impaired DNA damage repair in BC, thus prompting the development of synthetic lethality-based therapeutic strategies for ARID1A-mutated neoplasms (20, 21).

In this study, CNVs were observed in about 87% of MBCs and all were gene copy number gains. These findings are consistent with previous evidence showing that genomic gains are more common in MBCs while genomic losses are less frequent (22–27).

In line with previous data (10), our results showed that copy gains of MYC (8q24.21 cytoband), CCND1 (11q13.3 cytoband) and MDM2 (12q15 cytoband) genes were frequent in MBCs.

MYC and CCND1 overexpression has been associated with resistance to endocrine therapy in BC (28, 29). Thus, our findings could be particularly relevant in the clinical management of MBC as endocrine therapy is most commonly used in MBC treatment (4).

MDM2 gain has been shown to significantly correlate with a worse survival of Luminal BC patients allowing a further stratification of Luminal BC based on MDM2 status (30). As Luminal is the most frequent subtype in MBCs, our findings may suggest that MDM2 amplification might be investigated as prognostic biomarker.

The gene panel design allowed for the evaluation of comprehensive molecular biomarkers, including TMB and MSI, by NGS approach. To the best of our knowledge, the evaluation of TMB and MSI has not yet been performed in MBCs. In our series, only two MBCs showed high-TMB and two high-MSI, while the majority of cases showed low-TMB and low-MSI. These results are in line with data showing that high-TMB and high-MSI phenotypes are rarely observed in FBCs (31, 32).

A specific aim of this study was to characterize clinically actionable somatic alterations that may represent new predictive biomarkers for MBC patients. Our findings showed that NGS multigene panel sequencing can allow for the identification of MBC patients eligible for precision/targeted therapy. In our series about 73% of MBCs showed molecular alterations useful for more individualized therapeutic options, besides treatments commonly used in MBC patients based on hormonal and HER2 status (4). Our results are consistent with data from FBC reporting actionable molecular alterations in about 80% of BCs (33).

According to OncoKB database, actionable targets identified in our study include alterations in BRCA1/2, PALB2, PIK3CA, high-TMB and high-MSI.

It is known that cells with loss of BRCA1/2 or PALB2 function have sensitivity to PARP inhibitors (34–36). In this series, four MBC cases harbored BRCA1/2 and PALB2 germline pathogenic variants and LOH occurred in two of them. According to OncoKB, BRCA1/2 and PALB2 pathogenic variants, with or without bi-allelic loss, predict response to PARP inhibitors.

The PI3K-AKT-mTOR signaling pathway plays an important role in the development of BC (37) and in driving endocrine resistance (38). Targeting the PI3K-AKT-mTOR signaling pathway has become a promising therapeutic option in BC treatment (39). Somatic variants at codons 542, 545 and 1047 of PIK3CA gene have been demonstrated to be responsive to Alpelisib, a phosphatidylinositol-3-kinase inhibitor (40, 41). Alpelisib, in combination with Fulvestrant, an ER antagonist, is now FDA-approved for patients PIK3CA-mutated, HR-positive, HER2- negative BC after endocrine therapy-based treatments or with disease progression (42). In our series, five (40%) MBC cases showed PIK3CA alterations reported as predictors of response to PI3Kα-specific inhibitor combined with estrogen receptor antagonist.

High-TMB values in solid tumors are associated with response to immune checkpoint inhibitors (43). In our series, the MBC case with the highest TMB-value showed bi-allelic PALB2 alteration (germline pathogenic variant and LOH). These findings are consistent with the hypothesis that PALB2-mutated BCs may be associated with high mutational load (44) and that the DNA repair genes inactivation may give rise to BC specific immune-phenotype, that could be leveraged with checkpoint blockade (45). Notably, the PALB2-mutated case was an ER-negative BC, a very rare occurrence in MBC, and some studies reported higher TMB values in ER-negative compared with ER-positive FBCs (46, 47). Further studies are needed to investigate possible associations between TMB status and clinical-pathologic variables in MBC.

While the clinical management of MSI phenotype is well-established in colorectal and endometrial cancers, the predictive value of MSI status in BC is not well-know and this is most likely due to the low frequency (1-2%) of MSI phenotype in BC (48, 49). In our series two MBCs showed a high-MSI phenotype. Specifically, one was a Luminal B/HER2 negative BC with high proliferation activity and the other a Luminal A with low proliferation activity. These results are in line with literature data showing that MSI phenotype can be detected across different BC subtypes (50),

It is interesting to note that all MBCs with a stable MSI also showed low-TMB and that the cases with high-MSI do not correspond to the cases with high-TMB, thus in line with findings suggesting that MSI is not necessary for high-TMB (51).

Despite the low prevalence, the MSI phenotype BC was shown to be highly responsive to immunotherapy with checkpoint inhibitors (52). Thus, our findings suggest that the determination of MSI phenotype as a biomarker of response to immune checkpoint inhibitors, potentially combined with TMB, could be crucial to better identify eligible MBC patients for this therapeutic approach. Further insights on the molecular profiles associated with TMB and MSI status in MBC cases with and without germline pathogenic variants in genes involved in genome stability may provide a better characterization of MBC somatic landscape and lead to a more accurate classification of MBC molecular subtypes, with potential therapeutic implications.

This study has a few limitations. First, it is a pilot, retrospective study on a small cohort of patients; thus, the occurrence of possible bias related to small numbers for the observed variant frequencies cannot be excluded and may affect the findings. Second, the variability in current computational methodologies for the identification of pathogenic somatic variants and the estimation of TMB represent a challenge. Our pipeline, whose results are shown here, is based on evidence from recent methodological comparisons (14, 15, 53). However, there is a need for standardization and harmonization of assessment methodologies and parameters across studies. For example, there is currently no consensus on the minimum variant allele frequency and total read depth to be considered for variant selection. Some studies highlight the importance of using an allelic frequency threshold of 5% (54–56). In our study, only two of the 40 somatic variants identified showed an allelic frequency <10.0% and a good read depth (>100). Foundation Medicine FoundationOne CDx panel is the only current NGS test approved by FDA to measure TMB (57). In this study, we used TruSight Oncology 500 Panel, since its size and gene composition allowed for both a comprehensive exploration of genomic landscape and the evaluation of molecular biomarkers such as TMB and MSI. Further studies including a larger number of MBCs are needed to validate our molecular findings and the computational methodologies proposed here.

Although MBC peculiarities need to be further investigated at genetic and molecular level, our results suggest that the use of targeted gene panel sequencing in clinical practice may represents a fundamental step in the improvement of MBC management. The identification of actionable molecular alterations may concur to establish, with greater precision, which MBC patients can benefit from new therapeutic strategies as well as being useful for the development of new drugs.

In conclusion, this study adds new data to the actionable genomic landscape of MBC highlighting the importance of the incorporation of NGS testing in the clinical management of MBC eventually leading to the implementation of precision medicine for MBC patients.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: European Nucleotide Archive PRJEB57620.

VV, VS, and MK analyzed genomic data. VV, VS, MK, LdF and LO interpreted the results. VV wrote the manuscript. VS, AB, GC, MK, LdF, BC, AC, GdA, GG and LO revised the manuscript and contributed to the language editing of the manuscript. VV, GP, SM, BC, MGP, AN, AC, GdA, GG and LO collected the clinical pathologic characteristics. GdA, BC, MGP performed and interpreted immunohistochemistry analyses. SM, AC, Gd and LO conceived, designed, and planned the study. All authors contributed to the article and approved the submitted version.