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O32-2 Micrornas in blood as biomarker of pleural malignant mesothelioma
  1. Angela Cecilia Pesatori1,2,
  2. Valentina Bollati1,
  3. Tommaso Cavalleri3,
  4. Chiara Favero1,
  5. Laura Dioni1,
  6. Carolina Mensi2,
  7. Claudia Bareggi2,
  8. Lorenzo Bordini2,
  9. Alessandro Palleschi2,
  10. Arianna Rimessi2,
  11. Aldo Todaro2,
  12. Dario Consonni2,
  13. Matteo Bonzini1
  1. 1Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan
  2. 2Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan
  3. 3Humanitas Clinical and Research Institute, Rozzano

Abstract

Objectives Malignant Pleural Mesothelioma (MPM) is an aggressive cancer refractory to current therapies caused almost exclusively by asbestos. New specific diagnostic markers for early MPM diagnosis are needed. MiRNAs are single stranded noncoding that post-transcriptionally regulate gene expression by triggering mRNA cleavage or repressing translation. Changes in miRNA expression have been implicated in several diseases and cancers, including MPM. miRNAs are stable molecules that can be easily investigated in different specimens (e.g. blood), and used as a disease biomarker. We examined if a specific miRNA signature in plasma may help to discriminate between malignant pleural mesothelioma patients (MPM) and healthy subjects with a Past Asbestos Exposure (PAE).

Methods We investigated 23 MPM patients and 19 healthy subjects with Past Asbestos Exposure (PAE). We screened 754 miRNAs in blood by TaqMan™ OpenArray® Human MiRNA Panel. The top-25 differential miRNAs were chosen for validation by Real time PCR. RNU48 was used as endogenous control. miRNA profiling between MPM and PAE subjects were compared using multiple linear and logistic regression models adjusted for age, sex, BMI, and smoking. Kaplan-Meier log rank test was used to evaluate the association between miRNA expression and survival in MPM patients.

Results After miRNA screening, 57 differential miRNAs in plasma were detected. Among the top 25 differential miRNAs, 16 were validated and were able to discriminate between MPM and PEA subjects. In receiver operating characteristic (ROC) curve analysis, the three best miRNAs were miR-103 (area under curve, AUC = 0.86), miR-98 (AUC = 0.86) and miR-148 (AUC = 0.85), all characterised by high sensitivity (100%) and low specificity (66–73%). When we combined the two first miRNA (103 and 98) with miRNA 30e-3p (Se 64%, Sp 93%) we found the best discriminating signature ((AUC 0.94; Se 95.5%, Sp 86.7%). Subjects with miRNA 103 and 98 expression above the median had better survival (p < 0.03).

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