Satoko Takizawa

MicroRNA (miRNA), which are stably present in serum, have been reported to be potentially useful for detecting cancer. In the present study, we examined the expression profiles of serum miRNA in several large cohorts to identify novel miRNA that can be used to detect early stage breast cancer. We comprehensively evaluated the serum miRNA expression profiles using highly sensitive microarray analysis. A total of 1280 serum samples of breast cancer patients stored in the National Cancer Center Biobank were used. In addition, 2836 serum samples were obtained from non-cancer controls, 451 from patients with other types of cancers, and 63 from patients with non-breast benign diseases. The samples were divided into a training cohort including non-cancer controls, other cancers and breast cancer, and a test cohort including non-cancer controls and breast cancer. The training cohort was used to identify a combination of miRNA that could detect breast cancer, and the test cohort was used to validate that combination. miRNA expressions were compared between patients with breast cancer and non-breast cancer, and a combination of five miRNA (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p and miR-6875-5p) was found to be able to detect breast cancer. This combination had a sensitivity of 97.3%, specificity of 82.9% and accuracy of 89.7% for breast cancer in the test cohort. In addition, this combination could detect early stage breast cancer (sensitivity of 98.0% for Tis).

A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9-10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.

Bladder cancer is the 9th leading cause of cancer death worldwide. The major problem in bladder cancer is primarily the high recurrence rate after drug treatment and resection. Although conventional screening methods, such as cystoscopy, urinary cytology and ultrasound sonography, have become widely used in clinical settings, the diagnostic performance of these modalities is unsatisfactory due to low accuracy or high invasiveness. Because circulating micro RNA (miRNA) profiles have recently been reported as an attractive tool for liquid biopsy in cancer screening, here, we performed global miRNA profiling of 392 serum samples of bladder cancer patients with 100 non-cancer samples and 480 samples of other types of cancer as controls. We randomly classified the bladder cancer and control samples into 2 cohorts, a training set (N = 486) and a validation set (N = 486). By comparing both controls, we identified specific miRNA, such as miR-6087, for diagnosing bladder cancer in the training and validation sets. Furthermore, we found that a combination of 7 miRNA (7-miRNA panel: miR-6087, miR-6724-5p, miR-3960, miR-1343-5p, miR-1185-1-3p, miR-6831-5p and miR-4695-5p) could discriminate bladder cancer from non-cancer and other types of tumors with the highest accuracy (AUC: .97; sensitivity: 95%; specificity: 87%). The diagnostic accuracy was high, regardless of the stage and grade of bladder cancer. Our data demonstrated that the 7-miRNA panel could be a biomarker for the specific and early detection of bladder cancer.

Lung cancer, the leading cause of cancer death worldwide, is most frequently detected through imaging tests. In this study, we investigated serum microRNAs (miRNAs) as a possible early screening tool for resectable lung cancer. First, we used serum samples from participants with and without lung cancer to comprehensively create 2588 miRNAs profiles; next, we established a diagnostic model based on the combined expression levels of two miRNAs (miR-1268b and miR-6075) in the discovery set (208 lung cancer patients and 208 non-cancer participants). The model displayed a sensitivity of 99% and specificity of 99% in the validation set (1358 patients and 1970 non-cancer participants) and exhibited high sensitivity regardless of histological type and pathological TNM stage of the cancer. Moreover, the diagnostic index markedly decreased after lung cancer resection. Thus, the model we developed has the potential to markedly improve screening for resectable lung cancer.

It is difficult to detect pancreatic cancer or biliary-tract cancer at an early stage using current diagnostic technology. Utilizing microRNA (miRNA) markers that are stably present in peripheral blood, we aimed to identify pancreatic and biliary-tract cancers in patients. With "3D-Gene", a highly sensitive microarray, we examined comprehensive miRNA expression profiles in 571 serum samples obtained from healthy patients, patients with pancreatic, biliary-tract, or other digestive cancers, and patients with non-malignant abnormalities in the pancreas or biliary tract. The samples were randomly divided into training and test cohorts, and candidate miRNA markers were independently evaluated. We found 81 miRNAs for pancreatic cancer and 66 miRNAs for biliary-tract cancer that showed statistically different expression compared with healthy controls. Among those markers, 55 miRNAs were common in both the pancreatic and biliary-tract cancer samples. The previously reported miR-125a-3p was one of the common markers; however, it was also expressed in other types of digestive-tract cancers, suggesting that it is not specific to cancer types. In order to discriminate the pancreato-biliary cancers from all other clinical conditions including the healthy controls, non-malignant abnormalities, and other types of cancers, we developed a diagnostic index using expression profiles of the 10 most significant miRNAs. A combination of eight miRNAs (miR-6075, miR-4294, miR-6880-5p, miR-6799-5p, miR-125a-3p, miR-4530, miR-6836-3p, and miR-4476) achieved a sensitivity, specificity, accuracy and AUC of 80.3%, 97.6%, 91.6% and 0.953, respectively. In contrast, CA19-9 and CEA gave sensitivities of 65.6% and 40.0%, specificities of 92.9% and 88.6%, and accuracies of 82.1% and 71.8%, respectively, in the same test cohort. This diagnostic index identified 18/21 operable pancreatic cancers and 38/48 operable biliary-tract cancers in the entire cohort. Our results suggest that the assessment of these miRNA markers is clinically valuable to identify patients with pancreato-biliary cancers who could benefit from surgical intervention.