Cell-Free RNA Content in Peripheral Blood as Potential Biomarkers for Detecting Circulating Tumor Cells in Non-Small Cell Lung Carcinoma

Yu, Xinmin; Wu, Yichen; Xiang, Liangzhong; Huang, Xiancong; Hou, Xiuxiu; Wang, Jiuli; Cheng, Xiang-Liu; Mao, Weimin; Ling, Zhi‐Qiang

doi:10.3390/ijms17111845

Cited by 16 publications

(11 citation statements)

References 38 publications

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“…Therefore, as a non-invasive test, liquid biopsy has the potential to complement tissue biopsies and is fairly convenient to monitor responses to EGFR-TKI treatment and drug resistance [ 19 , 20 ]. Circulating tumor DNA (ctDNA) has been approved by the Committee for Medicinal Products for Human Use of the European Medicines Agency [ 21 ] to assess EGFR mutation status in patients with NSCLC for whom it is not possible to obtain a tumor sample. Indeed, ctDNA exhibits high accuracy for EGFR mutation status analysis and is commercially available.…”

Section: Discussionmentioning

confidence: 99%

“…Meanwhile, ctDNA analysis has been applied in clinical practice. The sensitivity of ctDNA has been reported to range from 70.0–75.0%, which may be promoted by highly sensitive technologies that are relatively costly for the patients (e.g., digital droplet PCR and next generation sequencing) [ 21 ]. Therefore, it is imperative to explore non-invasive, convenient, and economical tumor markers as supplements to predict EGFR mutation status and to monitor EGFR-TKI treatment in NSCLC patients.…”

Section: Discussionmentioning

confidence: 99%

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Circulating plasma microRNAs as potential markers to identify EGFR mutation status and to monitor epidermal growth factor receptor-tyrosine kinase inhibitor treatment in patients with advanced non-small cell lung cancer

Zheng

et al. 2017

Oncotarget

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We aimed to identify a panel of circulating plasma microRNAs that can predict EGFR mutation status and monitor epidermal growth factor receptor-tyrosine kinase inhibitor treatment in patients with non-small cell lung cancer. Microarrays were performed for the preliminary screening of dysregulated microRNAs in 9 EGFR mutation-positive patients versus healthy controls. MiR-107 was upregulated and miR-195 was downregulated in the exon 19 deletion versus wild-type group. The areas under the receiver operating characteristic curves for miR-107, miR-195, and a panel of these 2 microRNAs were 0.72, 0.75, and 0.74, with sensitivities and specificities of 64.7% and 76.6%, 71.8% and 69.1%, and 71.7% and 78.9%, respectively. MiR-122 was significantly upregulated in the p.L858R versus wild-type group. An area under the receiver operative characteristic curve of 0.75 suggests that miR-122 might be a specific biomarker for patients with the p.L858R mutation. In addition, dynamic changes in these 3 microRNAs were also found to correlate with responses to epidermal growth factor receptor-tyrosine kinase inhibitor treatment, indicating that circulating plasma microRNAs may represent potential biomarkers for monitoring epidermal growth factor receptor-tyrosine kinase inhibitor treatment. This study demonstrates the prospective application of circulating plasma microRNAs as potential non-invasive, convenient biomarkers for patients with EGFR-sensitive mutations.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Circulating plasma microRNAs as potential markers to identify EGFR mutation status and to monitor epidermal growth factor receptor-tyrosine kinase inhibitor treatment in patients with advanced non-small cell lung cancer

Zheng

et al. 2017

Oncotarget

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“…Thus, DIEM can also be used to filter single cell RNA-seq data. We expect our expression-based filtering to be more useful for tissues where cell-free RNA 24,25 , hemoglobin from lysed red blood cells, or total RNA from a diversity of lysed cells are more prominent.…”

Section: Discussionmentioning

confidence: 99%

Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

Alvarez

Rahmani

Garske

et al. 2019

Preprint

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Single-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. Contrary to single-cell RNA seq (scRNA-seq), we observe that snRNA-seq is commonly subject to contamination by high amounts of extranuclear background RNA, which can lead to identification of spurious cell types in downstream clustering analyses if overlooked. We present a novel approach to remove debris-contaminated droplets in snRNA-seq experiments, called Debris Identification using Expectation Maximization (DIEM). Our likelihood-based approach models the gene expression distribution of debris and cell types, which are estimated using EM. We evaluated DIEM using three snRNA-seq data sets: 1) human differentiating preadipocytes in vitro, 2) fresh mouse brain tissue, and 3) human frozen adipose tissue (AT) from six individuals. All three data sets showed various degrees of extranuclear RNA contamination. We observed that existing methods fail to account for contaminated droplets and led to spurious cell types. When compared to filtering using these state of the art methods, DIEM better removed droplets containing high levels of extranuclear RNA and led to higher quality clusters. Although DIEM was designed for snRNA-seq data, we also successfully applied DIEM to single-cell data. To conclude, our novel method DIEM removes debris-contaminated droplets from single-cell-based data fast and effectively, leading to cleaner downstream analysis. Our code is freely available for use at https://github.com/marcalva/diem. Overview of a novel EM-based approach to cluster and remove debris droplets from snRNA-seq data Code AvailabilityThe DIEM program is freely available for use at https://github.com/marcalva/diem. Contributions M.A., E.R., E.H., and P.P. conceived the study and designed the analysis. M.A., K.M.G., and J.B. designed, performed, and interpreted nuclei isolation experiments. M.A. and K.M.G. designed and performed snRNA-seq experiments and collected data. M.A., E.R. B.J., Z.M., K.M.G., and J.B. analyzed and interpreted snRNA-seq data. M.A., E.R., E.H. and P.P designed the DIEM method. J.R.P., C.J.Y., K.H.P. and P.P. designed and supervised nuclei isolation and snRNA-seq experiments. M.A., E.R., B.J., Z.M., E.H., and P.P. wrote the manuscript.

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“…Several studies found that high copy numbers of ctDNA were associated with shorter OS and DFS 37–39. High levels of ctDNA could be indicative of higher overall tumor burden in patients with stage II–III compared with patients with stage IB disease 40.…”

Section: Discussionmentioning

confidence: 99%

<p>Differential effects of adjuvant EGFR tyrosine kinase inhibitors in patients with different stages of non-small-cell lung cancer after radical resection: an updated meta-analysis</p>

Wang

Liu

et al. 2019

CMAR

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Purpose A survival improvement was achieved with adjuvant chemotherapy in non-small-cell lung cancer (NSCLC) patients, but its differential effects among patients with different stages remained controversial. This study aimed to compare the beneficial effects of adjuvant tyrosine kinase inhibitor (TKI) therapy with those of traditional therapy on NSCLC patients, specifically on EGFR-mutant and stage II–IIIA patients, who might benefit most from such treatment. Methods MEDLINE, Embase, and the Cochrane Library were searched, and the results were screened independently according to certain criteria by two authors. Disease-free survival (DFS) and overall survival (OS) with HRs were used as the summary statistics. Results A total of 2,915 publications were identified and screened. Six randomized control trials and three retrospective cohort studies of 2,467 patients with acceptable quality were included. The overall EGFR mutation rate was 48.62%. DFS was significantly improved in all the patients (HR, 0.77; 95% CI, 0.68–0.88) and in the subgroup of EGFR-mutant patients (HR, 0.49; 95% CI, 0.40–0.61). The difference of 5-year OS in the subgroup of EGFR-mutant patients (HR, 0.48; 95% CI, 0.31–0.72) was statistically significant, while in all the patients (HR, 1.01; 95% CI, 0.85–1.19), the difference was not significant. In the subgroups of studies in which <50% of patients were in stage I (HR, 0.46; 95% CI, 0.35–0.60) and >30% of patients were in stage IIIA (HR, 0.46; 95% CI, 0.35–0.60), DFS was significantly improved, while in the subgroups of studies in which <30% of patients were in stage IIIA (HR, 0.90; 95% CI, 0.77–1.04) and >50% of patients were in stage I (HR, 0.90; 95% CI, 0.77–1.04), DFS was not significantly improved. Conclusion Stage IIIA NSCLC patients might benefit more from adjuvant TKIs than stage I NSCLC patients after radical resection.

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Cell-Free RNA Content in Peripheral Blood as Potential Biomarkers for Detecting Circulating Tumor Cells in Non-Small Cell Lung Carcinoma

Cited by 16 publications

References 38 publications

Circulating plasma microRNAs as potential markers to identify EGFR mutation status and to monitor epidermal growth factor receptor-tyrosine kinase inhibitor treatment in patients with advanced non-small cell lung cancer

Circulating plasma microRNAs as potential markers to identify EGFR mutation status and to monitor epidermal growth factor receptor-tyrosine kinase inhibitor treatment in patients with advanced non-small cell lung cancer

Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

<p>Differential effects of adjuvant EGFR tyrosine kinase inhibitors in patients with different stages of non-small-cell lung cancer after radical resection: an updated meta-analysis</p>

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