The quantitative sensitivity and dynamic range of conventional immunohistochemistry (IHC) with 3,3′-diaminobenzidine (IHC-DAB) used in pathological diagnosis in hospitals are poor, because enzyme activity can affect the IHC-DAB chromogenic reaction. Although fluorescent IHC can effectively increase the quantitative sensitivity of conventional IHC, tissue autofluorescence interferes with the sensitivity. Here, we created new fluorescent nanoparticles called phosphor-integrated dots (PIDs). PIDs have 100-fold greater brightness and a more than 300-fold greater dynamic range than those of commercially available fluorescent nanoparticles, quantum dots, whose fluorescence intensity is comparable to tissue autofluorescence. Additionally, a newly developed image-processing method enabled the calculation of the PID particle number in the obtained image. To quantify the sensitivity of IHC using PIDs (IHC-PIDs), the IHC-PIDs method was compared with fluorescence-activated cell sorting (FACS), a method well suited for evaluating total protein amount, and the two values exhibited strong correlation (R = 0.94). We next applied IHC-PIDs to categorize the response to molecular target-based drug therapy in breast cancer patients. The results suggested that the PID particle number estimated by IHC-PIDs of breast cancer tissues obtained from biopsy before chemotherapy can provide a score for predicting the therapeutic effect of the human epidermal growth factor receptor 2-targeted drug trastuzumab.

The aim of this preliminary study was to retrospectively evaluate the usefulness of high b-value diffusion-weighted MR imaging (DWI) in the detection of gallbladder carcinoma. Fifteen patients with gallbladder carcinoma and 14 other patients were included in this study. All patients and subjects underwent DWI, and images were evaluated by two radiologists. The area under the receiver operating characteristic curve (AUC), apparent diffusion coefficient (ADC) measurement, sensitivity and specificity were calculated. An AUC yielded 0.980 (95% CI, 0.850-0.999) and 0.941 (95% CI, 0.791-0.990) for the two radiologists. The mean sensitivity and specificity were 83.3% and 100%, respectively. The mean ADC value of gallbladder carcinoma was (1.28 +/- 0.41)x10(-3) mm(2)/s and that of control gallbladder lesions was (1.92 +/- 0.21)x10(-3) mm(2)/s (P < 0.01). According to the results of our preliminary study, high b-value DWI might be a useful tool for detecting gallbladder carcinoma by measuring the ADC value and direct visual assessment.

In this study, MR imaging correctly depicted location, extension, and origin of tumor. High-spatial-resolution MR imaging has potential for presurgical staging of tumors in this region.

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It is difficult to predict the TP53 status by p53 immunohistochemistry (IHC). We aimed to improve the accuracy of p53 IHC with p53-regulated proteins for predicting the TP53 mutation status. TP53 mutations were detected in 19 of 38 breast cancer patients (50%). Five of 7 cases of protein-truncating mutation of TP53 were completely negative for p53 IHC, whereas 11 of 12 cases of TP53 point mutation were strongly positive for p53 IHC. Therefore, to avoid false negatives, we extracted p53-dependent universally downregulated genes using microarray analysis from 38 breast cancer patients and 2 p53-inducible cell lines. From 9 commonly repressed genes, we evaluated 3 genes, baculoviral IAP repeat-containing 5 (BIRC5), polo-like kinase 1 (PLK1), and BUB1 mitotic checkpoint serine/threonine kinase (BUB1), which were previously identified as p53-dependent repressed genes. PLK1≥Allred total score (TS) 5 showed the highest correlation with TP53 mutation. To decrease false positivity, we evaluated p21 IHC. Although strong staining of p21 was observed in 4 cases (10.5%), all 4 were wild-type TP53. Thus, p53 mutation-like (p53mt-like) IHC was identified by p53 TS7,8 with PLK1≥TS 5 and p21 TS≤6. p53 mt-like IHC correlated with TP53 mutation (predictive value=0.94). In other 157 breast cancer cases, p53 mt-like was an independent prognostic marker in multivariate analysis and a strong prognostic factor. Stratification with p53 mt-like IHC identified patients with a poorer prognosis. In conclusion, we identified reliable IHC conditions to predict the TP53 status of breast cancer patients.