MicroRNA signature predict chemotherapy response in patients with advanced colorectal cancer

ABSTRACT: The aim of our study was to evaluate the ability of miRNA expression patterns to predict chemotherapy response in a cohort of 39 patients with metastatic colorectal carcinoma To define miRNA signature, samples were obtained from tumor tissue samples of 39 patients . Patients were divided into responders or non-responders according to tresponse treatment with a chemotherapy regimen that included fluoropyrimidines and either oxaliplatin or irinotecan .Tumor response was evaluated by conventional methods according to the standard RECIST 1.0 criteria: a complete response (CR) was defined as the disappearance of all measurable and evaluable evidence of disease; a partial response (PR) was defined as a > 30% decrease in the sum of the longest diameters of target lesions; stable disease (SD) was considered if the tumor burden decreased less than 30% or increased less than 20%; and progressive disease (PD) was indicated by a >20% increase in the sum of the longest diameters of target lesions or the appearance of any new lesion. Patients were classified according to best response to chemotherapy in two groups: those that achieved an objective response (Responders [R]: CR + PR) and those that did not (Non-responders [NR]: SD + PD). Mature human miRNA expression was detected and quantified using the TaqMan® Low Density Arrays (TLDA). The Human MicroRNA Card Set v2.0 array is a two card set containing a total of 384 TaqMan® MicroRNA Assays per card to enable accurate quantification of 667 human microRNAs, all catalogued in the miRBase database. Expression of target miRNAs was normalized in relation to the expression of MammU6. Cycle threshold (Ct) values were calculated using the SDS software v.2.3 using automatic baseline settings and a threshold of 0.2. Relative quantification of miRNA expression was calculated by the 2−ΔCt method (Applied Biosystems user bulletin no. 2 (P/N 4303859)).

ORGANISM(S): Homo sapiens

SUBMITTER: Sonia Molina-Pinelo 

PROVIDER: E-GEOD-48664 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress