Published papers

Purpose: Male breast cancer (MBC) is a rare cancer accounting for only 1% of all male cancers and is, therefore, poorly studied. We aimed to characterize the subtypes of MBC in Japanese patients based on genetic profiling, the presence of tumor-infiltrating cells, and the expression of immunohistochemical markers. Methods: This retrospective study included 103 patients with MBC diagnosed between January 2009 and December 2019 at various hospitals in Japan. Clinicopathological patient characteristics were obtained from medical records, and formalin-fixed paraffin-embedded tissue specimens were analyzed for histological markers, mutations of 126 genes, BRCA1 methylation, and stromal tumor-infiltrating lymphocytes. Results: The median patient age was 71 (range 31–92) years. T1-stage tumors were the most frequent (47.6%), and most were node negative (77.7%). The majority of tumors were positive for estrogen receptor (98.1%), progesterone receptor (95.1%), and androgen receptor (96.1%), and BRCA2 was the most frequently mutated gene (12.6%). The most common treatment was surgery (99.0%), either total mastectomy (91.1%) or partial mastectomy (7.0%). Survival analysis showed a 5-year recurrence-free survival rate of 64.4% (95% confidence interval [CI] 46.7–88.8) and a 5-year overall survival rate of 54.3% (95% CI 24.1–100.0). Conclusion: Japanese MBC is characterized by a high rate of hormonal receptor positivity and BRCA2 somatic mutation. Due to the observed clinicopathological differences in MBC between the Western countries and Japan, further prospective studies are needed to evaluate the most suitable treatment strategies.

Background: The homeobox (HOX) family consists of 39 genes whose expressions are tightly controlled and coordinated within the family, during development. We performed a comprehensive analysis of this gene family in cancer settings. Methods: Gene correlation analysis was performed using breast cancer data available in The Cancer Genome Atlas (TCGA) and data from the patients admitted to our hospital. We also analyzed the data of normal breast tissue (GSE20437). We next collected gene expression and prognosis data of breast cancer patients (GSE11121, GSE7390, GSE3494, and GSE2990) and performed unsupervised hierarchal clustering by the HOX gene expression pattern and compared prognosis. We additionally performed this analysis to leukemia (available in TCGA) and sarcoma (GSE20196) data. Results: Gene correlation analysis showed that the proximal HOX genes exhibit strong interactions and are expressed together in breast cancer, similar to the expression observed during development. However, in normal breast tissue, less interactions were observed. Breast cancer microarray meta-data classified by the HOX gene expression pattern predicted the prognosis of luminal B breast cancer patients (p = 0.016). Leukemia (p = 0.00016) and sarcoma (p = 0.018) presented similar results. The Wnt signaling pathway, one of the major upstream signals of HOX genes in development, was activated in the poor prognostic group. Interestingly, poor prognostic cancer presented stronger correlation in the gene family compared to favorable prognostic cancer. Conclusion: Comprehensive analysis of the HOX family demonstrated their similar roles in cancer and development, and indicated that the strong interaction of HOX genes might be specific to malignancies, especially in the case of poor prognostic cancer.

Although the categorization of ultrasound using the Breast Imaging Reporting and Data System (BI-RADS) has become widespread worldwide, the problem of inter-observer variability remains. To maintain uniformity in diagnostic accuracy, we have developed a system in which artificial intelligence (AI) can distinguish whether a static image obtained using a breast ultrasound represents BI-RADS3 or lower or BI-RADS4a or higher to determine the medical management that should be performed on a patient whose breast ultrasound shows abnormalities. To establish and validate the AI system, a training dataset consisting of 4028 images containing 5014 lesions and a test dataset consisting of 3166 images containing 3656 lesions were collected and annotated. We selected a setting that maximized the area under the curve (AUC) and minimized the difference in sensitivity and specificity by adjusting the internal parameters of the AI system, achieving an AUC, sensitivity, and specificity of 0.95, 91.2%, and 90.7%, respectively. Furthermore, based on 30 images extracted from the test data, the diagnostic accuracy of 20 clinicians and the AI system was compared, and the AI system was found to be significantly superior to the clinicians (McNemar test, p < 0.001). Although deep-learning methods to categorize benign and malignant tumors using breast ultrasound have been extensively reported, our work represents the first attempt to establish an AI system to classify BI-RADS3 or lower and BI-RADS4a or higher successfully, providing important implications for clinical actions. These results suggest that the AI diagnostic system is sufficient to proceed to the next stage of clinical application.

Due to the increasing complexity of cancer treatment, ensuring safety and maintaining the quality of life during treatment are important issues. Patient-reported outcomes (PROs) in oncology are essential for assessing patient symptoms. A feasibility study was undertaken on breast cancer patients by building a PRO data collection system based on LINE, one of the most popular social network service applications in Japan. In this study, one or more predefined PRO questions for each breast cancer patient's clinical situation were sent to the patient’s LINE application daily. The patient selected a predefined answer by tapping the screen, but no free-text answers were allowed. Seventy-three patients were enrolled. The median observation period was 435 days (84-656 days), and the total number of PROs collected was 16,417, with a mean of 224.9 reports per patient. Patients on adjuvant endocrine therapy were notified of 2.5 questions per week, and the median number of responses per week and response rate were 2.387 (1.687-11.627) and 95.5%, respectively. Analyzing the results by age group, the number of responses from those aged 60 and above was equal to or higher than that of the younger age group. It was also possible to track each patient’s PROs accurately. These results suggested that the design of the system, based on an application used daily, instead of using specifically prepared applications for collecting electronic PROs, was the reason for the favorable acceptance from patients and the satisfactory response rate from all age groups, including the elderly.

Background: Triple-negative breast cancer (TNBC) is a biologically heterogeneous disease that is often associated with worse outcomes compared with other subtypes such as hormone receptor-positive tumors and HER2-positive tumors. While chemotherapy remains the mainstay of standard therapy for metastatic TNBC (mTNBC), several novel treatments have been developed over the past few years. In this review article, we review the major developments in the management of patients with mTNBC. Summary: The combination of chemotherapy and immunotherapy is a potential therapeutic option for PD-L1-positive mTNBC, as the FDA recently approved atezolizumab (Tecentriq) and pembrolizumab (Keytruda) in combination with chemotherapy. Also, 2 targeted therapies-olaparib (Lynparza) and talazoparib (Talzenna)-are FDA approved for the management of mTNBC with germline BRCA mutations, and sacituzumab govitecan, an anti-Trop2 antibody-drug conjugate (ADC), was recently approved for previously treated mTNBC. A number of promising therapies are on the horizon, including AKT inhibitors for PI3K-altered TNBC as well as other ADCs. Key Message: The successful clinical development of immunotherapies, PARP inhibitors, and ADCs for the management of mTNBC has improved the survival outcome of patients. Over the coming years, the therapeutic developments in precision medicine will likely change the mTNBC landscape, and might make the current definition of TNBC as breast cancer that is estrogen receptor negative, progesterone receptor negative, and HER2 negative obsolete.

Background: Eribulin mesylate (eribulin) is an efficient microtubule inhibitor that is used for metastatic breast cancer. However, breast cancer can develop resistance to eribulin. This resistance mechanism needs to be elucidated. Methods: A transposon mutagenesis screen was conducted using a pPB-SB-CMV-puro-SD plasmid and pCMV-PBase transposase. Viability and cytotoxicity were analyzed by MTT assay and flow cytometry, respectively. Real-time PCR and western blot were used for gene expression analysis. In addition, vivo study was also designed to analyze therapy efficiency. Results: TAB2, which is part of the nuclear factor-kappa B (NF-κB) pathway, was identified as a candidate eribulin-resistant gene. TAB2 down-regulation resulted in significantly lower cell viability and higher cytotoxicity of cells treated with eribulin, while TAB2 up-regulation showed opposite results. Similarly, combination of NF-κB inhibitors [Bay-117082 and QNZ (quinazoline derivative)] with eribulin showed significantly lower cell viability and higher drug cytotoxicity than single agent treatment with eribulin in MDA-MB-231 cells. However, QNZ increased NF-κB activity in MCF7 cells by up-regulating TAB2, which reduced the sensitivity to eribulin. Furthermore, combination of Bay-117082 with eribulin induced greater regression of MDA-MB-231 tumors compared to eribulin monotherapy in vivo. Conclusions: These results consistently illustrated that TAB2-NF-κB pathway may increases resistance to eribulin in breast cancer models. Moreover, these results support the use of a combination strategy of eribulin with NF-κB inhibitors, and provide evidence that transposon mutagenesis screens are capable of identifying drug-resistant genes.