Dubinett, S. M. | bioRxiv Science

bioRxiv2018

Molecular Subtyping reveals Immune Alterations associated with Progression of Bronchial Premalignant Lesions

Bronchial premalignant lesions (PMLs) are precursors of lung squamous cell carcinoma, but have variable outcome, and we lack tools to identify and treat PMLs at highest risk for progression to invasive cancer. Profiling endobronchial biopsies of PMLs obtained from high-risk smokers by RNA-Seq identified four PML subtypes with differences in epithelial and immune processes. One molecular subtype (Proliferative) is enriched with dysplastic lesions and exhibits up-regulation of metabolic and cell cycle pathways and down-regulation of ciliary processes. RNA-Seq profiles from normal-appearing uninvolved large airway brushings could identify subjects with Proliferative lesions with high specificity. Expression of interferon signaling and antigen processing/presentation pathways are decreased in progressive/persistent Proliferative lesions and immunofluorescence indicates a depletion of innate and adaptive immune cells in these lesions. Molecular biomarkers measured in PMLs or the uninvolved airway can enhance histopathological grading and suggests that immunoprevention strategies may be effective in intercepting the progression of PMLs to lung cancer.

cancer biology↗

bioRxiv2017

Summarizing Performance for Genome Scale Measurement of miRNA: Reference Samples and Metrics

BackgroundThe potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls.\n\nResultsThree pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes.\n\nConclusionsThe set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

genomics↗