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Purpose: To investigate a novel composite methodology of using targeted serum microRNAs (micro ribonucleic acid; miRNA) and urine metabolites for the accurate detection of early stage non-small cell lung cancer (NSCLC). Methods: Consecutively consenting NSCLC patients and matched control subjects were recruited to provide samples of serum for miRNA and/or urine for metabolite analyses. Serum miRNA levels were measured using quantitative real-time reverse-transcription with exogenous control, and the comparative delta cycle threshold (&#9651CT) method was used to calculate relative miRNA expression of two targeted miRNAs (miR-21 and miR-223). The concentrations of six targeted urinary metabolites in patients and healthy controls were measured using proton nuclear magnetic resonance (1H NMR) spectroscopy. A composite methodology of using the 35 accruals with both serum and urine biomarkers was then established with binary logistic regression, receiver operating characteristic (ROC) models with or without artificial intelligence (AI). Results: The ROC analysis of miRNA expression yielded a sensitivity of 96.4% and a specificity of 88.2% for the detection of early stage NSCLC, with area under the curve (AUC) = 0.91 (CI 95%: 0.80-1.0). Relative urinary concentrations of 4-methoxyphenylacetic acid (4MPLA) were significantly different between NSCLC and healthy control (p=0.008). The ROC analysis of 4MPLA yielded a sensitivity of 82.1% and a specificity of 88.2%, with AUC = 0.85. The composite process combining miRNA and metabolite expression demonstrated a sensitivity and specificity of nearly 100% and AUC=1. Conclusions: A highly specific, sensitive and non-invasive detection method for NSCLC was developed. Pending validation, this can potentially improve the early detection and, hence, the treatment and survival outcomes of patients.

Purpose: Gold nanoparticles (GNPs) have attracted significant attention in the treatment of cancer due to their potential as novel radiation enhancers, particularly when functionalized with various targeting ligands. The aim of this study was to assess the biodistribution and pharmacokinetic characteristics of a novel choline-bound GNP (choline-GNP) stabilized with polyethelenimine (PEI). Methods: Choline bound to 27 nm diameter GNPs was characterized using transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). Toxicity of choline-GNPs was examined on DU-145 prostate cancer cells using an MTT assay. Using balb/c mice bearing flank DU-145 prostate tumors, choline-GNPs bio-distribution was measured using inductively coupled mass spectroscopy (ICP-MS). Blood, heart, lung, liver, spleen, brain, kidney and tumor gold content were examined at multiple time points over a 24-hour period after tail vein injection. Results: An MTT assay using DU-145 prostate cancer cells yielded a 95% cell viability 72 hours after choline-GNP administration. The tumor GNP area under the concentration-time curve during the first 4 hours (AUC0-4) was 2.2 µg/ml h, representing 13% of the circulating blood GNP concentration over the same time period. The maximum intra-tumor GNP concentration observed was 1.4% of the injected dose per gram of tumor tissue (%ID/g) one hour post injection. Conclusions: GNPs functionalized with choline demonstrates a viable future nanoparticle platform with increased intra-tumor uptake as compared to unconjugated GNPs. Decreased intra-hepatic accumulation appears to be the reason for the improved systemic bioavailability. The next logical translational investigation will incorporate external beam radiation with the observed maximum intra-tumor uptake.

Purpose: MicroRNAs (miRNAs) post-transcriptionally regulate hundreds of gene targets involved in tumorigenesis thereby controlling vital biological processes, including cellular proliferation, differentiation and apoptosis. MiRNA profiling is an emerging tool for the potential early detection of a variety of malignancies. This study was conducyed to assess the feasibility and methodological robustness of quantifying sputum miRNAs, employing quantitative real-time polymerase chain reaction (RT-qPCR) and cluster analysis on an optimized miRNA profile as a novel approach for the early detection of non-small cell lung cancer (NSCLC). Methods: The relative expressions of 11 miRNAs in sputum (miR-21, miR-145, miR-155, miR-205, miR-210, miR-92, miR-17-5p, miR-143, miR-182, miR-372, and let-7a) in addition to U6 were retrospectively assessed in four NSCLC-positive and four negative controls. Subsequently, a set of five miRNAs (miR-21, miR-143, miR-155, miR-210, miR-372) was selected because of degree of relatedness observed in the cluster analysis and tested in the same sputum sample set. The five optimized miRNAs accurately clustered these eight retrospective patients into NSCLC positive cases and negative controls. The five miRNA panel was then prospectively quantified in the sputum of 30 study patients (24 NSCLC cases and six negative controls) in a double-blind fashion to validate a five miRNA panel using hierarchical cluster analysis. Results: The optimized five miRNA panel detected NSCLC (83.3% sensitivity and 100% specificity) in 30 prospectively accrued study patients. Conclusion: Sputum miRNA profiling using cluster analysis is a promising approach for the early detection of non-small cell lung cancer. Further investigation using this approach is warranted.