A large-scale, multicentered trial evaluating the sensitivity and specificity of digital PCR versus ARMS-PCR for detecting ctDNA-based EGFR p.T790M in non-small-cell lung cancer patients

Xu, Jiachen; Wu, Wei; Wu, Chunyan; Mao, Yong; Qi, Xiaowei; Guo, Lin; Lu, Renquan; Xie, Shuhong; Lou, Jiatao; Zhang, Yu; Ding, Yiling; Guo, Zijian; Zhang, Li; Liang, Ning; Chen, Peng; Zhang, Cuicui; Tao, Min; Yu, Zhengyuan; Geng, Hua; Xu, Min; Shi, Meiqi; Wang, Li; Wei, Guo; Zhao, Jun; Li, Jianjie; Shi, Lixia; Zhang, Yan; Qin, Zhonghua; Liu, Jinghao; Ren, Jing; Yang, Zhenlin; Pan, Xin; Lv, Zhaoqing; Dong, Hao; Zhang, Jie; Ou, Jiajia; Li, Zhao-Liang; Kaji, Kavanaugh; Wang, Yan; Wang, Jie; Wang, Zhijie

doi:10.21037/tlcr-21-564

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…Therefore, compared with imaging or clinical symptoms, ctDNA analysis can monitor tumor dynamics in real-time so it can predict treatment response, disease progression, prognosis, and guide clinical decision-making at an early stage [ 71 , 75 , 76 ]. The prediction of EGFR mutation status by ctDNA was limited by detection technology [ 79 ]. Based on the results of tissue detection by cobas, the positive consistency of plasma T790M by cobas, droplet digital PCR (ddPCR), and NGS was 51%, 58%, and 66%, respectively [ 80 ].…”

Section: Liquid Biopsymentioning

confidence: 99%

Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients

Liu

Xiong

2021

Current Oncology

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Lung cancer ranks first in the incidence and mortality of cancer in the world, of which more than 80% are non-small cell lung cancer (NSCLC). The majority of NSCLC patients are in stage IIIB~IV when they are admitted to hospital and have no opportunity for surgery. Compared with traditional chemotherapy, specific targeted therapy has a higher selectivity and fewer adverse reactions, providing a new treatment direction for advanced NSCLC patients. Tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR-TKIs) are the widely used targeted therapy for NSCLC patients. Their efficacy and prognosis are closely related to the mutation status of the EGFR gene. Clinically, detecting EGFR gene mutation is often limited by difficulty obtaining tissue specimens, limited detecting technology, and economic conditions, so it is of great clinical significance to find indicators to predict EGFR gene mutation status. Clinicopathological characteristics, tumor markers, liquid biopsy, and other predictors are less invasive, economical, and easier to obtain. They can be monitored in real-time, which is supposed to predict EGFR mutation status and provide guidance for the accurate, individualized diagnosis and therapy of NSCLC patients. This article reviewed the correlation between the clinical indicators and EGFR gene mutation status in NSCLC patients.

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Section: Liquid Biopsymentioning

confidence: 99%

Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients

Liu

Xiong

2021

Current Oncology

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“…PCR was performed in a Bio-Rad CFX96 Touch™ PCR detection system (Bio-Rad Laboratories, Inc., USA) under the following conditions: initial denaturation at 95°C for 1 min, followed by 40 cycles that involved incubation at 95°C for 20 s, 55°C for 20 s, and 72°C for 30 s. The forward primer of LPCAT1 was “ACCTGCCTAATTACCTTCAAAC,” and the reverse primer of LPCAT1 was “TCCGCAATACCTATCTTCTCTC.” The forward primer of SERPINE1 was “GACTCCCTTCCCCGACTCCA,” and the reverse primer of SERPINE1 was “CGGTCATTCCCAGGTTCTCT.” The forward primer of STC2 was “GTGGGGTGTGGCGTGTTT,” and the reverse primer of STC2 was “TGGGAGGCTTCTGGATGG.” The forward primer of β -actin was “TCCCTGGAGAAGAGCTATGA,” and the reverse primer of β -actin was “AGGAAGGAAGGCTGGAAAAG.” All primers were synthesized by Servicebio (Servicebio, Wuhan, China). The β -actin gene served as an internal control, and the relative expression of 3 hub genes was determined using the 2 - ΔΔ Ct method [ 25 ]. The experiment was performed in triplicate on independent occasions.…”

Section: Methodsmentioning

confidence: 99%

A Novel Hypoxia-Related Gene Signature with Strong Predicting Ability in Non-Small-Cell Lung Cancer Identified by Comprehensive Profiling

Yang

Wang

Gong

et al. 2022

International Journal of Genomics

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Background. Non-small-cell lung cancer (NSCLC) is the most common malignant tumor among males and females worldwide. Hypoxia is a typical feature of the tumor microenvironment, and it affects cancer development. Circular RNAs (circRNAs) have been reported to sponge miRNAs to regulate target gene expression and play an essential role in tumorigenesis and progression. This study is aimed at identifying whether circRNAs could be used as the diagnostic biomarkers for NSCLC. Methods. The heterogeneity of samples in this study was assessed by principal component analysis (PCA). Furthermore, the Gene Expression Omnibus (GEO) database was normalized by the affy R package. We further screened the differentially expressed genes (DEGs) and differentially expressed circular RNAs (DEcircRNAs) using the DEseq2 R package. Moreover, we analyzed the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of DEGs using the cluster profile R package. Besides, the Gene Set Enrichment Analysis (GSEA) was used to identify the biological function of DEGs. The interaction between DEGs and the competing endogenous RNAs (ceRNA) network was detected using STRING and visualized using Cytoscape. Starbase predicted the miRNAs of target hub genes, and miRanda predicted the target miRNAs of circRNAs. The RNA-seq profiler and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Then, the variables were assessed by the univariate and multivariate Cox proportional hazard regression models. Significant variables in the univariate Cox proportional hazard regression model were included in the multivariate Cox proportional hazard regression model to analyze the association between the variables of clinical features. Furthermore, the overall survival of variables was determined by the Kaplan-Meier survival curve, and the time-dependent receiver operating characteristic (ROC) curve analysis was used to calculate and validate the risk score in NSCLC patients. Moreover, predictive nomograms were constructed and used to predict the prognostic features between the high-risk and low-risk score groups. Results. We screened a total of 2039 DEGs, including 1293 upregulated DEGs and 746 downregulated DEGs in hypoxia-treated A549 cells. A549 cells treated with hypoxia had a total of 70 DEcircRNAs, including 21 upregulated and 49 downregulated DEcircRNAs, compared to A549 cells treated with normoxia. The upregulated genes were significantly enriched in 284 GO terms and 42 KEGG pathways, while the downregulated genes were significantly enriched in 184 GO terms and 25 KEGG pathways. Moreover, the function analysis by GSEA showed enrichment in the enzyme-linked receptor protein signaling pathway, hypoxia-inducible factor- (HIF-) 1 signaling pathway, and G protein-coupled receptor (GPCR) downstream signaling. Furthermore, six hub modules and 10 hub genes, CDC45, EXO1, PLK1, RFC4, CCNB1, CDC6, MCM10, DLGAP5, AURKA, and POLE2, were identified. The ceRNA network was constructed, and it consisted of 4 circRNAs, 14 miRNAs, and 38 mRNAs. The ROC curve was constructed and calculated. The area under the curve (AUC) value was 0.62, and the optimal threshold was 0.28. Based on the optimal threshold, the patients were divided into the high-risk score and low-risk score groups. The survival rate in the high-risk score group was lower than that in the low-risk score group. The expression of SERPINE1, STC2, and LPCAT1; clinical stage; and age of the patient were significantly correlated with the high-risk score. Moreover, nomograms were established based on the risk factors in multivariate analysis, and the median survival time, 3-year survival probability, and 5-year survival were possibly predicted according to nomograms. Conclusion. The ceRNA network associated with NSCLC was identified, and the hub genes, circRNAs, might act as the potential biomarkers for NSCLC.

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“…Various technologies are commonly used for ctDNA genomic profiling in clinical settings. These include amplification-refractory mutation system (ARMS) polymerase chain reaction (PCR) or ARMS-PCR assays, , pyrophosphorolysis-activated polymerization (PAP) assays, , digital methods such as beads, emulsion, amplification, and magnetics (BEAMing), droplet digital PCR (ddPCR), , and next-generation sequencing (NGS) assays. , However, fluorescent assays typically exhibit lower analytical and clinical sensitivities, ranging from 75 to 100 copies/mL and 70% sensitivity, respectively . Digital PCR has proven to be more sensitive than ARMS-PCR assays; however, its multiplexing capability is limited, and it requires specialized equipment to partition samples into individual droplets .…”

Section: Gmr Biosensors For Cancer Screening and Detectionmentioning

confidence: 99%

Giant Magnetoresistance Based Biosensors for Cancer Screening and Detection

Mostufa,

Rezaei,

Yari

et al. 2023

ACS Appl. Bio Mater.

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Early-stage screening of cancer is critical in preventing its development and therefore can improve the prognosis of the disease. One accurate and effective method of cancer screening is using high sensitivity biosensors to detect optically, chemically, or magnetically labeled cancer biomarkers. Among a wide range of biosensors, giant magnetoresistance (GMR) based devices offer high sensitivity, low background noise, robustness, and low cost. With state-of-the-art micro-and nanofabrication techniques, tens to hundreds of independently working GMR biosensors can be integrated into fingernail-sized chips for the simultaneous detection of multiple cancer biomarkers (i.e., multiplexed assay). Meanwhile, the miniaturization of GMR chips makes them able to be integrated into point-of-care (POC) devices. In this review, we first introduce three types of GMR biosensors in terms of their structures and physics, followed by a discussion on fabrication techniques for those sensors. In order to achieve target cancer biomarker detection, the GMR biosensor surface needs to be subjected to biological decoration. Thus, commonly used methods for surface functionalization are also reviewed. The robustness of GMR-based biosensors in cancer detection has been demonstrated by multiple research groups worldwide and we review some representative examples. At the end of this review, the challenges and future development prospects of GMR biosensor platforms are commented on. With all their benefits and opportunities, it can be foreseen that GMR biosensor platforms will transition from a promising candidate to a robust product for cancer screening in the near future.

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A large-scale, multicentered trial evaluating the sensitivity and specificity of digital PCR versus ARMS-PCR for detecting ctDNA-based EGFR p.T790M in non-small-cell lung cancer patients

Cited by 11 publications

References 35 publications

Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients

Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients

A Novel Hypoxia-Related Gene Signature with Strong Predicting Ability in Non-Small-Cell Lung Cancer Identified by Comprehensive Profiling

Giant Magnetoresistance Based Biosensors for Cancer Screening and Detection

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