Project description:Purpose: Serum markers that enable diagnosis in the early stage of lung cancer have not been discovered. We have developed a LC-MRM-MS assay for the identification of potential early marker proteins for lung adenocarcinoma.
Experimental design: LC-MRM-MS assay was used for measuring the level of 35 candidate peptides in plasma from 102 lung adenocarcinoma patients (including n=50, 16, 24, and 12 in stage I, II, III, and IV, respectively.) and 84 healthy controls. Stable isotope labeled standard peptides were synthesized to accurately measure the amount of these proteins.
Results: Seven proteins were found to be able to distinguish stage I patients from controls. These proteins were combined in to a protein marker panel which improved the sensitivity to discriminate stage I patients from controls and resulted in a high classification performance with cross-validated area under the curve=0.76. Besides, we found that low expression of eukaryotic initiation factor 4A-I and high expression of lumican showed significantly poor prognosis in overall survival (p=0.012 and 0.0074, respectively), which may be used as prognostic biomarkers for lung cancer.
Conclusion and clinical relevance: Proteins highlighted here may be used for early detection of lung adenocarcinoma or therapeutics development after validation in a larger cohort.
Project description:To determine the circRNA expression profile in early stage lung adenocarcinoma and matched non-tumor tissues, we used circRNA microArray analysis form Arraystar to examine the expression of circRNAs Lung adenocarcinoma, a form of NSCLC with high lethality at advanced stage, is becoming more popular in women, non- or never-smokers, and even young adult. However, there are no effective early diagnosis methods at present for patients to cure timely. Circular RNAs (circRNAs) as a special novel, stable, and conserved non-coding RNA in mammalian cells have been reported to be widely involved in the processes of cancer disease. Yet, it is still a puzzle which specific circRNAs are involved in the development of early stage lung adenocarcinoma. Here, tumour samples and paired adjacent normal tissues from 4 patients with early stage lung adenocarcinoma were selected for investigating the expression profile of circRNAs by using the high-throughput circRNA microarray. Bioinformatic analyses were conducted to screen those differentially expressed circRNAs. This work illustrates that clusters of circRNAs are aberrantly expressed in early stage lung adenocarcinoma, which might be able to provide potential targets for the early diagnosis of this disease and new genetic insights into lung cancer.
