Male breast cancer: A closer look at patient and tumor characteristics and factors associated with survival

Male Breast Cancer: An Updated Review of Patient Characteristics, Genetics, and Outcome

Male breast cancer (MBC) is a rare entity, underrepresented in population studies and clinical trials, resulting in management of MBC to be informed by current research on female breast cancer (FBC). A literature review was conducted by accessing relevant articles on 2 databases, by searching keywords "male breast cancer". A total of 29 articles from year 2011 to 2022 were selected for this review. The authors found that male breast cancer generally occurs later in life with higher stage, higher grade, and more estrogen receptor (ER) positive tumours. Most of the studies noted the mean age for MBCs at the time of presentation as >60 years. Risk factors for male breast cancer include family history, obesity, lower physical activity, and syndromes like the Klinefelter syndrome. Positive family history is much higher in MBC compared to FBC (30.9 vs. 18.4%). BRCA 2 cancers constitute a higher proportion compared to FBCs. A lot of genetic mutations have been observed. Some show promise to assess disease-specific survival and proliferative rate like TWIST1 and RUNX3, among others. MBCs usually present with a palpable lump in central region, with a bigger size and chance of nodal involvement and metastasis compared to FBCs. They are mostly infiltrating ductal type and hormone receptor positive, with worse histological grade. Treatment usually follows the same principles as FBCs (systemic therapy, surgical excision, and radiotherapy), with poorer prognosis to same treatment approach, possibly owing to its advanced stage at presentation. This is a rare entity which requires further research to ascertain need for different management approach than FBCs.

Clinical characteristics and prognostic factors of male breast cancer in China

Purpose

This study aimed to explore the clinical characteristics of male breast cancer (MBC) patients and the factors influencing their prognosis.

Methods

We conducted a retrospective case series analysis of 117 MBC cases who were treated at Zhejiang Cancer Hospital from 2009 to 2022. Cox proportional hazard model was used to identify prognostic factors of MBC. Nomogram was constructed based on these factors, which was further evaluated by C-index and calibration curves.

Results

A total of 115 MBC cases were finally included in our analyses, with median diagnosis age of 59 years. Of these cases, 80.0% were estrogen receptor (ER) positive, 79.2% were progesterone receptor (PR) positive, 48.7% were human epidermal growth factor receptor 2 (HER2) negative, and 42.6% had Ki67 levels higher than 15%. 108 (93.9%) cases underwent radical mastectomy, while only 3 (2.6%) received breast-conserving surgery. The Logrank test suggested that lymphocyte-to-monocyte ratio (LMR) was negatively associated with both overall survival (OS) and disease-free survival (DFS) of MBC, while platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) were only positively associated with OS (all P-values < 0.05). Multivariate regression analysis showed that age (HR 1.08, 95% CI 1.03-1.13) was significant prognostic factors for OS. Meanwhile, age (HR 1.06, 95% CI 1.02-1.10), histological differentiation grade (poorly differentiated/undifferentiated vs. well-differentiated: HR 2.55, 95% CI 1.05-6.17), and TNM stage (IV vs. I: HR 31.59, 95% CI 6.01-165.93) were also significant prognostic factors for DFS. Nomograms were developed for DFS, with C-indexes of 0.782, indicating good predictive performance.

Conclusion

Increased age, bigger tumor size, higher TNM stage, and lower histological differentiation grade were associated with poor MBC prognosis, and LMR, PLR, and NLR might be potential predictors for MBC prognosis.

Identification of a 5-gene-risk score model for predicting luminal A-invasive lobular breast cancer survival

Breast cancer is a devastating malignancy, among which the luminal A (LumA) breast cancer is the most common subtype. In the present study, we used a comprehensive bioinformatics approach in the hope of identifying novel prognostic biomarkers for LumA breast cancer patients. Transcriptomic profiling of 611 LumA breast cancer patients was downloaded from TCGA database. Differentially expressed genes (DEGs) between tumor samples and controls were first identified by differential expression analysis, before being used for the weighted gene co-expression network analysis. The subsequent univariate Cox regression and LASSO algorithm were used to uncover key prognostic genes for constructing multivariate Cox regression model. Patients were stratified into high-risk and low-risk groups according to the risk score, and subjected to multiple downstream analyses including survival analysis, gene set enrichment analysis (GSEA), inference on immune cell infiltration and analysis of mutation burden. Receiving operator curve analysis was also performed. A total of 7071 DEGs were first identified by edgeR package, pink module was found significantly associated with invasive lobular carcinoma (ILC). 105 prognostic genes and 9 predictors were identified, allowing the identification of a 5-key prognostic genes (LRRC77P, CA3, BAMBI, CABP1, ATP8A2) after intersection. These 5 genes, and the resulting Cox model, displayed good prognostic performance. Furthermore, distinct differences existed between two risk-score stratified groups at various levels. The identified 5-gene prognostic model will help deepen the understanding of the molecular and immunological mechanisms that affect the survival of LumA-ILC patients and guide and proper monitoring of these patients.