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Background: Chemopreventive agent (CPA) treatment is one of the main preventive options for lung cancer. However, few studies have been done on pharmacodynamic biomarkers of known CPAs for lung cancer. Materials and methods: In this study, we treated mouse models of lung squamous cell carcinoma with three different CPAs (MEK inhibitor: AZD6244, PI-3K inhibitor: XL-147 and glucocorticoid: Budesonide) and examined circulating exosomal miRNAs in the plasma of each mouse before and after treatment. Results: Compared to baselines, we found differentially expressed exosomal miRNAs after AZD6244 treatment (n = 8, FDR < 0.05; n = 55, raw p-values < 0.05), after XL-147 treatment (n = 4, FDR < 0.05; n = 26, raw p-values < 0.05) and after Budesonide treatment (n = 1, FDR < 0.05; n = 36, raw p-values < 0.05). In co-expression analysis, we found that modules of exosomal miRNAs reacted to CPA treatments differently. By variable selection, we identified 11, 9 and nine exosomal miRNAs as predictors for AZD6244, XL-147 and Budesonide treatment, respectively. Integrating all the results, we highlighted 4 miRNAs (mmu-miR-215-5p, mmu-miR-204-5p, mmu-miR-708-3p and mmu-miR-1298-5p) as the key for AZD6244 treatment, mmu-miR-23a-3p as key for XL-147 treatment, and mmu-miR-125a-5p and mmu-miR-16-5p as key for Budesonide treatment. Conclusions: This is the first study to use circulating exosomal miRNAs as pharmacodynamic biomarkers for CPA treatment in lung cancer. [ABSTRACT FROM AUTHOR]

Objectives Cell free tumor DNA (cfDNA) circulating in blood has a great potential as biomarker for cancer clinical management. The objective of this study is to evaluate if cfDNA in blood plasma is detectable in early stage lung cancer patients. Materials and methods We extracted cfDNAs and tumor tissue DNAs from 8 lung adenocarcinoma patients. We also extracted cfDNAs from 8 normal controls. To evaluate copy number variations (CNV) and identify potential mutations, we performed low pass whole genome sequencing and targeted sequencing of 50 cancer genes. To accurately reflect the tumor-associated genomic abnormality burden in plasma, we developed a new scoring algorithm, plasma genomic abnormality (PGA) score, by summarizing absolute log2 ratios in most variable genomic regions. We performed digital PCR and allele-specific PCR to validate mutations detected by targeted sequencing. Results and conclusions The median yield of cfDNA in 400ul plasma was 4.9ng (range 2.25–26.98 ng) in patients and 2.32 ng (range 1.30–2.81 ng) in controls ( p = 0.003). The whole genome sequencing generated approximately 20 million mappable sequence reads per subject and 5303 read counts per 1 Mb genomic region. Log2 ratio-based CNV analysis showed significant chromosomal abnormality in cancer tissue DNAs and subtle but detectable differences in cfDNAs between patients and controls. Genomic abnormality analysis showed that median PGA score was 9.28 (7.38–11.08) in the 8 controls and 19.50 (5.89–64.47) in the 8 patients ( p = 0.01). Targeted deep sequencing in tumor tissues derived from the 8 patients identified 14 mutations in 12 different genes. The PCR-based assay confirmed 3 of 6 selected mutations in cfDNAs. These results demonstrated that the PGA score and cfDNA mutational analysis could be useful tool for the early detection of lung cancer. These blood-based genomic and genetic assays are noninvasive and may sensitively distinguish early stage disease when combined with other existing screening strategies including low-dose CT scanning. [ABSTRACT FROM AUTHOR]

Background Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer. Objective To identify and evaluate plasma exosomal miRNAs for prognosis in castration-resistant prostate cancer (CRPC). Design, setting, and participants RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using quantitative real-time polymerase chain reaction in a follow-up cohort of 100 CRPC patients. Outcome measurements and statistical analysis Cox regression and Kaplan-Meier survival analyses were used to evaluate survival association using candidate miRNAs along with clinical prognostic factors. Results and limitations RNA sequencing in screening cohort generated approximately 6.80 million mappable reads per patient. Of those with normalized read counts ≥5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (false discover rate < 0.05). Of those, higher levels of miR-1290 and -375 were significantly associated with poor overall survival ( p < 0.004) in the follow-up cohort. Incorporation of miR-1290/-375 into putative clinical prognostic factors-based models in CRPC stage significantly improved predictive performance with a time-dependent area under the curve increase from 0.66 to 0.73 ( p = 6.57 × 10 −6 ). Conclusions Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further evaluation of these candidate miRNAs. Patient summary In this study, we evaluated whether small RNAs circulating in blood could be used to predict clinical outcomes in late-stage prostate cancer patients. We identified two blood-based small RNAs whose levels showed significant association with survival. Our results warrant further investigation because the noninvasive blood-based test has great potential in the management of late-stage prostate cancer. [ABSTRACT FROM AUTHOR]