Dataset Information

High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer.

ABSTRACT: Validation of biomarkers is essential to advance the translational process to clinical application. Although there exists an increasing number of reports on small non-coding RNAs (microRNAs) as minimally-invasive markers from blood, serum or plasma, just a limited number is verified in follow-up studies. We used qRT-PCR to evaluate a known miRNA signature measured from blood that allowed for separation between patients with non-small cell lung cancer (NSCLC), COPD and healthy controls.From the data of our previous microarray studies we selected a panel of 235 miRNAs related to lung cancer and COPD. We observed a high concordance between the AUC values of our initial microarray screening and the qRT-PCR data (correlation of 0.704, p < 10-16). Overall, 90.3% of markers were successfully validated. Among the top markers that were concordant between both studies we found hsa-miR-20b-5p, hsa-miR-20a-5p, hsa-miR-17-5p, and hsa-miR-106a-5p. The qRT-PCR analysis also confirmed that non-small cell lung cancer patients could be accurately differentiated from unaffected controls: a subset of five markers was sufficient to separate NSCLC patients from unaffected controls with accuracy of 94.5% (specificity and sensitivity of 98% and 91%). Beyond differentiation from controls, we also succeeded in separating NSCLC patients from patients with COPD. MiRNAs that were identified as relevant for the separation between lung cancer and COPD by both qRT-PCR and the array-based studies included hsa-miR-26a-5p, hsa-miR-328-3p and hsa-miR-1224-3p. Although for differentiation between NSCLC patients from COPD patients more markers were required, still high accuracy rates were obtained (5 markers: 78.8%; 10 markers: 83.9%; 50 markers: 87.6%).

SUBMITTER: Leidinger P

PROVIDER: S-EPMC4826230 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer.

Leidinger Petra P Brefort Thomas T Backes Christina C Krapp Medea M Galata Valentina V Beier Markus M Kohlhaas Jochen J Huwer Hanno H Meese Eckart E Keller Andreas A

Oncotarget 20160101 4

Validation of biomarkers is essential to advance the translational process to clinical application. Although there exists an increasing number of reports on small non-coding RNAs (microRNAs) as minimally-invasive markers from blood, serum or plasma, just a limited number is verified in follow-up studies. We used qRT-PCR to evaluate a known miRNA signature measured from blood that allowed for separation between patients with non-small cell lung cancer (NSCLC), COPD and healthy controls.From the d ...[more]

PMID: 26672767

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Project description:BackgroundCT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.ResultsBlood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n?=?363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n?=?138 in the first validation and n?=?135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.ConclusionsSelecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.

Dataset Information

High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer.

Publications

High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer.

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