Clinical value of nine circulating miRNAs in prognosis and diagnosis of PDAC
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PROVIDER: PRJNA684475 | ENA |
REPOSITORIES: ENA
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Project description:Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas. Since early disease symptoms are undefined and specific biomarkers are lacking, about 80% of patients present with advanced, inoperable tumors that represent a daunting challenge. Therefore, new sensitive and minimally invasive diagnostic tools are required to detect pancreatic cancer. The miRNA has been emerged as promising cancer biomarkers for PDAC. Nowadays, have been identified several miRNAs in serum or plasma of PDAC patients. However, there are not many of common miRNAs between them, and not all the studies have compared the serum/ plasma expression with the corresponding miRNAs present in the pancreatic tumor tissue. Due to this and considering that PDAC is the seventh leading cause of cancer death in Mexico, we initially identified the miRNAs that are differentially expressed in tissue from PDAC patients residing in the Mexican Republic, to later find out which of these miRNAs are overexpressed in the serum of patients with this type of cancer. In this way, nine common miRNAs were identified in tissue and serum of PDAC patients, of which four of them (miRNAs 223-3p, miR 210-3p, miR100-5p and miR-221 3p) could be proposed as a signature for the diagnosis of PDAC with a sensitivity and specificity of 0.74 and 0.82 respectively for patients residing in the Mexican Republic. The 56 target mRNA of these 9 miRNAs were found to be mainly enriched in fatty acid oxidation, glucose homeostasis, amino acid transport organonitrogen compound catabolism. Finally, four of the target mRNA may serve as a prognostic marker for PDAC in tissue samples.
2020-12-12 | GSE163031 | GEO
Project description:Background: Tumor stage predicts pancreatic cancer (PDAC) prognosis, but prolonged and short survivals have been described in patients with early-stage tumors. Circulating microRNA (miRNA) are an emerging class of suitable biomarkers for PDAC prognosis. Our aim was to identify whether serum miRNA signatures predict survival of early-stage PDAC. Methods: Se-rum RNA from archival 15 stage I-III PDAC patients and 4 controls was used for miRNAs ex-pression profile (Agilent microarrays). PDAC patients with comparable age, gender, diabetes, jaundice and surgery were classified according to survival: less than 14 months (7/15 pts, group A) and more than 22 months (8/15 pts, group B). Bioinformatic data analysis was performed by two-class Significance Analysis of Microarray (SAM) algorithm. Binary logistic regression analyses considering PDAC diagnosis and outcome as dependent variables, and ROC analyses were also performed. Results: 2549 human miRNAs were screened out. At SAM, 76 differen-tially expressed miRNAs were found among controls and PDAC (FDR = 0.4%), the large major-ity (50/76, 66%) of them being downregulated in PDAC with respect to controls. Six miRNAs were independently correlated with early PDAC, and among these, hsa-miR-6821-5p was asso-ciated with the best ROC curve area in distinguishing controls from early PDAC. Among the 71 miRNAs differentially expressed between groups A and B, the most significant were hsa-miR-3135b expressed in group A only, hsa-miR-6126 and hsa-miR-486-5p expressed in group B only. Eight miRNAs were correlated with the presence of lymph-node metastases; among these, hsa-miR-4669 is of potential interest. hsa-miR-4516, increased in PDAC and found as an independent predictor of survival, has among its putative targets a series of gens involved in key pathways of cancer progression and dissemination, such as Wnt and p53 signaling pathways. Conclusions: A series of serum miRNAs was identified as potentially useful for the early diag-nosis of PDAC, and for establishing a prognosis
2021-07-20 | GSE168996 | GEO
Project description:Serum miRNA profiling for early PDAC diagnosis and prognosis: a retrospective study
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2012-05-09 | E-GEOD-36682 | biostudies-arrayexpress
Project description:To develop diagnostic and prognostic biomarkers, we compared methylation profiles of HCC tissues and normal blood by analyzing 485,000 CpG markers and identified a HCC enriched methylation marker panel compared to that of normal blood. We found there was a highly correlation of methylation profiles between DNA from HCC cancer tissue and matched plasma ctDNA within the same patient. We then selected 10 markers from this panel and created a combined diagnosis score (cd-score) which showed high diagnostic specificity and sensitivity in both a training cohort and an independent validation cohort. We also showed the cd-score correlate highly with tumor load, treatment response and stage and is superior to that by AFP. We also showed the cd-score correlate highly with tumor load, treatment response and stage and is superior to that by AFP. Additional, we generated 8 markers from unicox and LASSO-cox analysis and created a combined prognosis score (cp-score) which could predict prognosis and survival. Together, these findings demonstrated the utility of ctDNA methylation markers in the diagnosis, treatment evaluation and prognosis of HCC.
2019-01-01 | GSE93203 | GEO
Project description:This study aimed to identify the genetic signatures associated with disease prognosis in bladder cancer. We used 165 primary bladder cancer samples, 23 recurrent non-muscle invasive tumor tissues, 58 normal looking bladder mucosae surrounding cancer and 10 normal bladder mucosae for microarray analysis. Hierarchical clustering was used to stratify the prognosis-related gene classifiers. For validation, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) of top-ranked 14 genes was performed. On unsupervised hierarchical clustering using prognosis related gene-classifier, tumors were divided into 2 groups. The high risk gene signatures had significantly poor prognosis compared to low risk gene signatures (P<0.001 by the log-rank test, respectively). The prognosis-related gene classifiers correlated significantly with recurrence of non-muscle invasive bladder cancer (hazard ratio, 4.09; 95% confidence interval [CI], 1.94 to 8.64; P<0.001), and progression (hazard ratio, 23.68; 95% confidence interval [CI], 4.91 to 114.30; P<0.001), cancer-specific survival (hazard ratio, 29.25; 95% confidence interval [CI], 3.47 to 246.98; P=0.002) and overall survival (hazard ratio, 23.33; 95% confidence interval [CI], 4.97 to 109.50; P<0.001) of muscle invasive bladder cancer (p < 0.001, respectively). No patient with non-muscle invasive bladder cancer experienced cancer progression in low risk gene signature group. Prognosis-related gene classifiers validated by RT- PCR showed identical results. Prognosis related gene-classifiers provided strong predictive value for disease outcome. These gene classifiers could assist in selecting patients who might benefit from more aggressive therapeutic intervention or surveillance. Keywords: Gene expression, Bladder cancer, Prognosis 165 primary bladder cancer samples and 23 recurrent non-muscle invasive tumor tissues from 14 patients were taken in the Chungbuk National University Hospital. Only histologically verified transitional cell carcinoma samples were selected. Simultaneously 58 normal looking bladder mucosae surrounding cancer were obtained during the operation, which were histologically confirmed normal. Also, 10 normal bladder mucosae were obtained from patients with benign disease. The normal controls were determined to be free of cancer after revealing no malignant cells on urine cytology and no observable bladder cancer on cystoscopic examination during operation for their diseases, and were histologically reconfirmed normal.
2010-05-28 | E-GEOD-13507 | biostudies-arrayexpress