Yasuyo Suzuki

Genetic analyses in patients with familial isolated hyperparathyroidism and hyperparathyroidism–jaw tumour syndrome

Background  A subset of familial isolated primary hyperparathyroidism (FIHP) is a variant of hyperparathyroidism–jaw tumour syndrome (HPT‐JT).

Human endoplasmic reticulum oxidoreductin 1-α is a novel predictor for poor prognosis of breast cancer.

Human endoplasmic reticulum oxidoreductin 1‐α (hERO1‐α) is an oxidizing enzyme that exists in the endoplasmic reticulum and its expression is augmented under hypoxia. It regulates a redox state of various kinds of protein through reoxidation of “client” protein disulfide isomerase. Interestingly, although the expression of hERO1‐α in normal tissues was comparatively limited, various types of cancer cells expressed it in large amounts. Therefore, we examined the role of ERO1‐α in tumor growth using murine breast cancer line 4T1 and found that knockdown of murine ERO1‐α inhibited in vivo tumor growth and decreased lung metastasis compared with wild‐type 4T1. Moreover, we investigated the relationship between expression of hERO1‐α and prognosis in breast cancer patients. Seventy‐one patients with breast cancer who underwent surgery between 2005 and 2006 in Sapporo Medical University Hospital (Sapporo, Japan) were analyzed in this study. Significant differences were found between the hERO1‐α‐positive group (n = 33) and hERO1‐α‐negative group (n = 38) in nuclear grade (P < 0.001) and intrinsic subtype (P = 0.021) in univariate analysis. More importantly, in multivariate analysis of disease‐free survival by Cox regression, expression of hERO1‐α was the only independent prognosis factor (P = 0.035). Finally, in univariate survival analysis, patients positive for hERO1‐α had significantly shorter disease‐free survival and overall survival than those patients negative for hERO1‐α. These findings indicate that the expression of hERO1‐α in cancer cells is associated with poorer prognosis and thus can be a prognostic factor for patients with breast cancer.

Pigmented mammary Paget's disease mimicking melanoma: report of three cases

Pigmented mammary Pagets disease (PMPD) is a rare subtype of mammary Pagets disease. The differential diagnosis of PMPD and melanoma is difficult clinically and sometimes histopathologically. Here we present three cases of PMPD with a variable-sized lesion. All cases showed an irregular-shaped black-brown macule, one of which was accompanied by nipple retraction. Dermoscopically, all cases showed reticular pigmentation with or without irregular black dots, regression structures and streaks, which were indistinguishable from those of melanoma. In all but one of the cases, preoperative examinations confirmed the presence of a subcutaneous mammary lesion. All patients underwent a total mastectomy with the histopathological results indicating invasive ductal carcinoma. These cases emphasize how difficult it is to distinguish PMPD from melanoma. Dermoscopic features also mimic those of melanoma, but the reticular pigmentation seen in all cases could be a feature specific to PMPD. For suspicious cases, histopathological assessment using immunohistochemistry is highly recommended.

Use of the dye-guided sentinel lymph node biopsy method alone for breast cancer metastasis to avoid unnecessary axillary lymph node dissection

For sentinel lymph node biopsy (SLNB), a combination of dye-guided and γ-probe-guided methods is the most commonly used technique. However, the number of institutes in which the γ-probe-guided method is able to be performed is limited, since special equipment is required for the method. In this study, SLNB with the dye-guided method alone was evaluated, and the clinicopathological characteristics were analyzed to identify any factors that were predictive of whether the follow-up axillary lymph node dissection (ALND) was able to be omitted. A total of 374 patients who underwent SLNB between 1999 and 2009 were studied. The SLN identification rate was analyzed, in addition to the false-positive and false-negative rates and the correlation between the clinicopathological characteristics and axillary lymph node metastases. The SLN was identified in 96.8% of cases, and, out of the patients who had SLN metastasis, 63.0% did not exhibit metastasis elsewhere. The sensitivity was 96.4% and the specificity was 100%. The false-negative rate was 3.6%. Univariate analyses revealed significant differences in the lymph vessel invasion (ly) status, nuclear grade (NG), maximum tumor size and the percentage of the area occupied by the tumor cells in the SLN (SLN occupation ratio) between the patients with and without non-SLN metastasis, indicating that these factors may be predictive of axillary lymph node metastasis. Multivariate analysis revealed that ly status was an independent risk factor for non-SLN metastasis. In conclusion, SLN with the dye-guided method alone provided a high detection rate. The study identified a predictive factor for axillary lymph node metastasis that may improve the patients’ quality of life.

Lymph node shape in computed tomography imaging as a predictor for axillary lymph node metastasis in patients with breast cancer

The aim of the present study was to evaluate whether preoperative computed tomography (CT) is a useful modality for the diagnosis of axillary lymph node metastasis. The axillary lymph node status was examined in patients with primary breast cancer who had undergone surgery. In total, 75 patients were analyzed with preoperative contrast CT images, following which the patients underwent an intraoperative sentinel lymph node biopsy to determine possible predictors of axillary lymph node metastasis. The lymph node shape was classified into three groups, which included fat-, clear-and obscure-types. Multivariate analysis revealed that clear-type lymph nodes in preoperative contrast CT imaging may be an independent predictor of lymph node metastasis (odds ratio, 15; P=0.003). Therefore, the results indicated that preoperative CT examination is useful to predict axillary lymph node metastasis.

The prediction models for postoperative overall survival and disease-free survival in patients with breast cancer

The goal of this study is to establish a method for predicting overall survival (OS) and disease‐free survival (DFS) in breast cancer patients after surgical operation. The gene expression profiles of cancer tissues from the patients, who underwent complete surgical resection of breast cancer and were subsequently monitored for postoperative survival, were analyzed using cDNA microarrays. We detected seven and three probes/genes associated with the postoperative OS and DFS, respectively, from our discovery cohort data. By incorporating these genes associated with the postoperative survival into MammaPrint genes, often used to predict prognosis of patients with early‐stage breast cancer, we constructed postoperative OS and DFS prediction models from the discovery cohort data using a Cox proportional hazard model. The predictive ability of the models was evaluated in another independent cohort using Kaplan–Meier (KM) curves and the area under the receiver operating characteristic curve (AUC). The KM curves showed a statistically significant difference between the predicted high‐ and low‐risk groups in both OS (log‐rank trend test P = 0.0033) and DFS (log‐rank trend test P = 0.00030). The models also achieved high AUC scores of 0.71 in OS and of 0.60 in DFS. Furthermore, our models had improved KM curves when compared to the models using MammaPrint genes (OS: P = 0.0058, DFS: P = 0.00054). Similar results were observed when our model was tested in publicly available datasets. These observations indicate that there is still room for improvement in the current methods of predicting postoperative OS and DFS in breast cancer.