Robust messenger RNA (mRNA) markers in blood for lung cancer diagnosis
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ABSTRACT:
PROVIDER: PRJNA1057991 | ENA |
REPOSITORIES: ENA
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Project description:Background: Lung cancer (LC) is the leading cause of cancer deaths worldwide with more than 1.7 million deaths each year. Early detection of LC may be crucial to achieve efficient treatment and to increase survival. However, there are limitations to current methods for early detection of LC as they are too invasive and represent potential health hazards, necessitating improved tools to detect LC at an early stage. Blood-based gene expression profiling is an alternative, or additional tool for diagnostic purposes as blood samples are easily available, essentially non-invasive, and can be collected at a low cost. However, as the blood collection method can affect measured gene expression, the aim of this study was to identify mRNAs that are robust biomarkers for LC in blood. How: We sampled blood from 123 LC patients at the St. Olavs university hospital, and 180 controls from two different biobanks sampled on two different blood tubes (PAXgene and Tempus) and used Illumina (HT-12 v4) microarrays to measure whole blood gene expression. We did three analyses: (i) finding relevant gene expression differences between cases and controls, (ii) finding a robust set of genes to be used as a panel to identify presence of LC in blood, and (iii) identifying differences between patients with different pathological traits such as stage and histology. We collected phenotype data from questionnaires and hospital medical records, and evaluated the potential effects of CRP, tumour size, gender, and smoking habits. Results: By comparing cases and controls sampled on the same RNA sampling system (training set), we identified 355 significant genes (Bonferroni adjusted p < 0.05) with biological relevance. When evaluating these on our test set comprising of the same cases as used in the training set but analysed against controls from a different biobank sampled on a different RNA sampling system (test set), we found 50 genes that were robust as they were unaffected by either technical issues in sampling systems, biobank differences, gender, or pathological traits such as LC subtype or stadium. These findings were confirmed in three validation sets and the robust list’s diagnostic potential was validated on RNA sequencing data from a new cohort. By analysing the cases separately, we found seven genes distinguishing squamous cell carcinoma (SCC) from other LC subtypes, and six genes distinguishing early from late-stage LC patients. Pathway analyses and a literature survey indicated that the identified genes show biological relevance for cancer development and lung related diseases.
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