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Robust messenger RNA (mRNA) markers in blood for lung cancer diagnosis

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE252168 | GEO | 2024/12/10

REPOSITORIES: GEO

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Project description:Decompression sickness (DCS) is a potentially fatal condition usually observed after scuba diving. It involves bubble formation in blood and tissues from dissolved inert gas (usually nitrogen or helium), secondary to decreases in ambient pressure (decompression).To the best of our knowledge, no study has evaluated a DCS-induced transcriptomic signature in humans. In this study, we aim to explore the evolution of leukocyte gene expression in human subjects with DCS compared to closely matched divers after uneventful diving using a hypothesis-free RNA sequencing approach .Recruitment of DCS cases (n = 7) and controls (n = 6) was carried out using specific criteria. For both DCS cases and controls, whole blood was sampled at two time points, T1 - within 8 hours of surfacing from diving and T2 - at 40-44 hours after surfacing. Prior to sampling at T2, subjects were fasted for 10 hours. Specific exclusion criteria included a) age < 18 years b) self-reported consumption of alcohol and/or strenuous physical activity before T2 c) symptoms suggestive of delayed DCS presentation in controls at T2 d) acute life-threatening clinical complications or death within 72 hours of surfacing. All cases received emergency HBO as per United States Navy Treatment Table Six between T1 and T2.For RNA isolation, 2.5mL of whole blood was collected in a PAXgene® Blood RNA Tube (PreAnalytiX, Qiagen/BD) from DCS cases and controls at both T1 and T2. The quality of RNA was evaluated by RNA Integrity Number (RIN) determination using the RNA6000 Nano protocol on an Agilent 2100 Bioanalyzer system (Agilent, USA). The RIN values for samples undergoing transcriptome analysis ranged from 7.8 to 9.3. Depletion of alpha and beta globin mRNA was carried out using the GLOBINclear™ kit (ThermoFisher Scientific). To minimize batch effects, all samples were processed simultaneously by the same investigator. RNA samples were submitted for library generation and sequencing by the Beijing Genomics Institute (BGI-Shenzhen). Briefly, poly(A) mRNA was enriched using poly(T) oligo-attached magnetic beads, followed by fragmentation. First strand cDNA synthesis was carried out using random hexamer N6 primers and reverse transcriptase. Following adaptor ligation to cDNA fragments, PCR amplification and purification, single stranded DNA circles were generated in a final library. DNA nanoballs (DNBs) were subsequently generated by rolling circle replication, which underwent paired end sequencing (100bp) on the BGI DNBseq platform.

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Robust messenger RNA (mRNA) markers in blood for lung cancer diagnosis

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