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.
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:There is an urgent need for new biomarkers to enhance the clinical management of prostate cancer. Circulating microRNAs (miRNAs) are emerging as useful non-invasive markers of disease. The objective of this study was to test the utility of a mouse model of prostate cancer as a tool to discover serum miRNAs that could be applied in a clinical setting. Global miRNA profiling using microarrays identified 46 miRNAs at differential levels in the serum of TRansgenic Adenocarcinoma of Mouse Prostate (TRAMP) mice compared to their wild-type littermates.
Project description:There is an urgent need for new biomarkers to enhance the clinical management of prostate cancer. Circulating microRNAs (miRNAs) are emerging as useful non-invasive markers of disease. The objective of this study was to test the utility of a mouse model of prostate cancer as a tool to discover serum miRNAs that could be applied in a clinical setting. Global miRNA profiling using microarrays identified 46 miRNAs at differential levels in the serum of TRansgenic Adenocarcinoma of Mouse Prostate (TRAMP) mice compared to their wild-type littermates. Total RNA extracted from the serum of 9 mice with advanced disease was pooled into 3 groups (TRAMP serum RNA 1, 2 and 3). Serum RNA from age-matched wild-type littermates, pooled as above, served as the control set.
Project description:The overall goal of the study was to determine if serum or serum EV microRNAs added prognostic value to current clinical nomograms for prostate cancer. Serum was collected from 203 patients with biopsy-proven prostate cancer. EVs were isolated from the 132 serum samples. RNA was isolated from these serum and serum EV samples, and 61 microRNAs were quantified per sample on a custom qPCR plate. The microRNA data was normalized using NormFinder. The normalized microRNA data was then compared to adverse pathology and prostate biopsy Gleason grade group.
Project description:Exosomes may be used as biomarkers for the prediction and monitoring of response to anti-cancer treatment, yet relevant knowledge is very limited in the case of rectal cancer. Here we applied a combined proteomic and metabolomic approach to reveal exosome components connected with different responses to neoadjuvant radiotherapy in this group of patients and processes associated with identified discriminatory molecules. Moreover, the composition of serum-derived exosomes and a whole plasma was analyzed in parallel to compare the biomarker potential of both specimens, which revealed the highest capacity of exosome proteome to discriminate samples of patients with different responses to radiotherapy.
Project description:Serum microRNAs profiles of HER2 positive advanced breast cancer patients and their treatment response after the trastuzumab/pertuzumab/taxane therapy