Project description:Circulating microRNAs (miRNAs) in serum may serve as promising diagnostic biomarkers for patients with gastric cancer (GC). Using quantitative reverse transcription polymerase chain reaction (qRT-PCR) based Exiqon panel, we identified 58 differentially expressed miRNAs from 3 GC pool samples and 1 normal control (NC) pool in the initial screening phase. Identified miRNAs were further validated in the training (49 GC VS. 47 NCs) and validation phases (154 GC VS. 120 NCs) using qRT-PCR. Consequently, six serum miRNAs (miR-10b-5p, miR-132-3p, miR-185-5p, miR-195-5p, miR-20a-3p and miR-296-5p) were significantly overexpressed in GC compared with NCs. The areas under the receiver operating characteristic (ROC) curve of the six-miRNA panel were 0.764 and 0.702 for the training and validation phases, respectively. In conclusion, we identified a six-miRNA panel in serum for the detection of GC.
Project description:MicroRNAs (miRNAs), 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 miRNAs in large cohorts to identify the miRNAs that can be used to detect breast cancer in the early stage. We comprehensively evaluated serum miRNA expression profiles using highly sensitive microarray analysis. A total of 1,280 serum samples of breast cancer patients stored in the National Cancer Center Biobank were used. Additionally, 2,836 serum samples were obtained from non-cancer controls and 514 from patients with other types of cancers or benign diseases. The samples were divided to 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 miRNAs that detect breast cancer, and the test cohort was used to validate that combination. miRNA expression was compared between breast cancer and non-breast cancer serum , and a combination of five miRNAs (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p, and miR-6875-5p) was found 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 Additionally, the combination could detect breast cancer in the early stage (sensitivity of 98.0% for T0).
Project description:MicroRNAs (miRNAs), 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 miRNAs in large cohorts to identify the miRNAs that can be used to detect breast cancer in the early stage. We comprehensively evaluated serum miRNA expression profiles using highly sensitive microarray analysis. A total of 1,280 serum samples of breast cancer patients stored in the National Cancer Center Biobank were used. Additionally, 2,836 serum samples were obtained from non-cancer controls and 514 from patients with other types of cancers or benign diseases. The samples were divided to 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 miRNAs that detect breast cancer, and the test cohort was used to validate that combination. miRNA expression was compared between breast cancer and non-breast cancer serum , and a combination of five miRNAs (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p, and miR-6875-5p) was found 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 Additionally, the combination could detect breast cancer in the early stage (sensitivity of 98.0% for T0). 1280 breast cancer serums (74 in training cohort, 1206 in test cohort), 54 benign breast diseases serums in test cohort, 2836 non-cancer control serums (1493 in training cohort, 1343 in test cohort), 514 non-breast benign diseases serums in training cohort. 150 of the non-cancer control serums in training cohort and 412 of the non-breast benign diseases serums in training cohort have been uploaded previously and are avaialable under GSE59856 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59856).
Project description:The aim of this study was to identify and evaluate exosomal miRNAs in serum as early diagnostic markers for gastric cancer (GC). Methods: Using next-generation sequencing (NGS) and bioinformatics, we identified candidate serum exosomal miRNA markers for early detection of GC in patients. The candidates were further validated by qRT-PCR in 50 newly recruited early-stage GC patients and matched healthy individuals. Results: NGS revealed that the average mappable reads in the RNA libraries were about 6.5 million per patient. A total of 66 up and 13 down-regulated exosomal miRNAs were found in the screened cohort after removal of log2 transformed read counts <5 and p >0.05. In the validation cohort, by comparing candidate exosomal miRNAs levels in early-stage GC patients and healthy individuals, higher levels of miR-92b-3p, let-7g-5p, miR-146b-5p and miR-9-5p were found to be significantly associated with GC. Diagnostic power of the combined panels of the exosomal miRNAs or the combination of exosomal miRNAs and CEA outperformed that of single exosomal miRNA marker for establishing a diagnosis of early-stage GC. In addition, serum levels of exosomal miR-92b-3p were significantly associated with low adhesion, let-7g-5p and miR-146b-5p were significantly correlated with nerve infiltration, and miR146b-5p was statistically correlated with tumor invasion depth in early-stage GC. Conclusions: Serum exosomal miR-92b-3p, -146b-5p, -9-5p, and let-7g-5p may serve as potential noninvasive biomarkers for early diagnosis of GC. Further validation of these candidate exosomal miRNAs in larger experimental cohorts are required in order to confirm the diagnostic values.
Project description:Breast Cancer is the cancer with most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients versus 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based upon the expression levels of 5 microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the over-expression and down-regulation of proteins differently expressed in the serum of breast cancer patients versus that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a-5p, mir-497-5p, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of mir-125b-5p, miR-29c-3p, mir-16-5p, miR-1260, and miR-451a was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of mir-16-5p with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and use of the predictor here described might be of potential importance for breast cancer prediction.