MiRNA profiling in esophageal precancerous for malignancy progression risk assessment

SROVNAL, Josef, Ondřej SLABÝ, Jiří EHRMANN, Jan GREGAR, Lenka RADOVÁ, Kateřina ŠTAFFOVÁ a Marian HAJDÚCH. MiRNA profiling in esophageal precancerous for malignancy progression risk assessment. In 106th Annual Meeting of the American Association for Cancer Research 2015, Philadelphia. 2015.

Základní údaje

• Originální název: MiRNA profiling in esophageal precancerous for malignancy progression risk assessment
• Autoři: SROVNAL, Josef, Ondřej SLABÝ, Jiří EHRMANN, Jan GREGAR, Lenka RADOVÁ, Kateřina ŠTAFFOVÁ a Marian HAJDÚCH.
• Vydání: 106th Annual Meeting of the American Association for Cancer Research 2015, Philadelphia, 2015.

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Konferenční abstrakt
• Obor: 30200 3.2 Clinical medicine
• Stát vydavatele: Spojené státy
• Utajení: není předmětem státního či obchodního tajemství
• Organizační jednotka: Středoevropský technologický institut
• Klíčová slova anglicky: miRNA; aesophageal carcinoma; progression
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

Background: Barrett’s esophagus (BE) is a metaplastic disease with risk to develop esophageal adenocarcinoma (EAC). Current screening method for BE patients (endoscopy and biopsy) is discomfort, expensive and relatively risky for patients. Moreover, the procedure is complicated by subjective histopathology examination and only 2% of BE patients annually progress to adenocarcinoma. The aim of our study was to identify miRNA profiles in order to predict cancer progression in high-risk BE patients. Methods and patients: FFPE samples were obtained from 113 patients (35 EAC, 21 low-grade dysplasia of esophagus, 33 BE and 24 healthy control). There were 74 males and 39 females; mean age was 55.9 years, range 15 - 94 years. Total RNA was purified from FFPE biopsy samples using proteinase K treatment followed by RNeasy kit (Qiagen). Microarray analysis was performed using the GeneChip miRNA 3.0 Array (Affymetrix). The data were analyzed using “R” software and the Bioconductor package. Results: In total, 113 GeneChip miRNA 3.0 Arrays were performed in 113 patients. Expression profiles of 1733 human miRNAs were analyzed. In supervised clustering analysis we found 8 differentially expressed miRNAs (p<0.001 or logFC 2) in BE patients compared to EAC patients and 10 differentially expressed miRNAs (p<0.001 or logFC 2) in LGD patients compared to EAC patients. One of the dominant findings was decreased expression of miR-223 in EAC and LGD samples, which is known to function as a tumor suppressor blocking E2F1. Using LOOCV classifier with 13 miRNAs signature we were able to correctly classify 86 from 113 samples (AUC=0.840). Prediction model fails mostly in LGD prediction (18/21), probably due to incorrect pathological classification. Conclusion: We have identified miRNA profiles and signature allowing for better diagnostics of cancer progression in BE and LGD patients, which, however, will require further validation.