MicroRNA expression profiling of sputum for the detection of early and locally advanced non-small-cell lung cancer: a prospective case–control study

R. Razzak, E.L.R. Bédard, J.O. Kim, S. Gazala, L. Guo, S. Ghosh, A. Joy, T. Nijjar, E. Wong, W.H. Roa

Abstract


Background

Non-small-cell lung cancer (nsclc) is associated with very poor overall survival because 70% of patients present with locally advanced or metastatic disease at the time of diagnosis. Micrornas (mirnas) are a class of short, noncoding rna molecules whose presence in samples of biologic fluids such as sputum has demonstrated promise as a potential means of detecting nsclc. We investigated the stage-specific nsclc detection potential of an efficient panel of 3 mirnas (mir-21, mir-210, mir-372) using a single sputum sample.

Methods

A single spontaneously expectorated sputum sample was prospectively collected from 21 early nsclc (≤stage ii) patients, 22 advanced nsclc (≥stage iii) patients, and 10 control subjects. Mirna expression profiles were determined by quantitative real-time polymerase chain reaction and were analyzed by unsupervised hierarchical cluster analysis.

Results

Mean tumour size (±95% confidence interval) in the early and advanced nsclc patients was 3.3 cm ± 0.9 cm and 4.8 cm ± 0.7 cm respectively. Adenocarcinoma constituted 61.9% of the early and 45.5% of the advanced nsclc cases respectively. In comparing the early nsclc group with the control group, the mirna panel yielded a diagnostic sensitivity of 67% and a specificity of 90.0%. For the advanced nsclc group, the mirna panel detected nsclc with a sensitivity and specificity of 64% and 100% respectively.

Conclusions

A sputum mir-21, mir-210, and mir-372 expression profile might provide a sensitive and highly specific means for detecting nsclc. Sputum mirna analysis demonstrates promise as a potential complementary screening tool.


Keywords


Non-small-cell lung cancer; nsclc; screening; mirna; sputum; rt-pcr

Full Text:

PDF HTML


DOI: http://dx.doi.org/10.3747/co.23.2830






Copyright © 2019 Multimed Inc.
ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)