Establishment of multiplex allele-specific blocker PCR for enrichment and detection of 4 common EGFR mutations in non-small cell lung cancer

Citrulline facilitates the glycolysis, proliferation, and metastasis of lung cancer cells by regulating RAB3C

Lung cancer (LC) is one of the major malignant diseases threatening human health. The study aimed to identify the effect of citrulline on the malignant phenotype of LC cells and to further disclose the potential molecular mechanism of citrulline in regulating the development of LC, providing a novel molecular biological basis for the clinical treatment of LC. The effects of citrulline on the viability, proliferation, migration, and invasion of LC cells (A549, H1299) were validated by CCK-8, colony formation, EdU, and transwell assays. The cell glycolysis was assessed via determining the glucose uptake, lactate production, ATP levels, extracellular acidification rate (ECAR), and oxygen consumption rate (OCR). RNA-seq and molecular docking were performed to screen for citrulline-binding target proteins. Western blotting experiments were conducted to examine the expression of related signaling pathway molecules. In addition, the impacts of citrulline on LC growth in vivo were investigated by constructing mouse models. Citrulline augmented the viability of LC cells in a concentration and time-dependent manner. The proliferation, migration, invasion, glycolysis, and EMT processes of LC cells were substantially enhanced after citrulline treatment. Bioinformatics analysis indicated that citrulline could bind to RAB3C protein. Western blotting results indicated that citrulline activated the IL-6/STAT3 pathway by binding to RAB3C. In addition, animal experiments disclosed that citrulline promoted tumor growth in mice. Citrulline accelerated the glycolysis and activated the IL6/STAT3 pathway through the RAB3C protein, consequently facilitating the development of LC.

Triple-recognition strategy for one-pot detection of single nucleotide variants by aligner-mediated cleavage-triggered exponential amplification

The detection of single nucleotide variants (SNVs) is important for the diagnosis and treatment of cancer. To date, researchers have devised several methods to detect SNVs, but most of them are complex and time-consuming. To improve SNVs detection specificity and sensitivity, we developed a triple-recognition strategy, which facilitates aligner-mediated cleavage-triggered exponential amplification (Trec-AMC-EXPAR) for the rapid, specific, and one-pot detection of SNV. Under optimized conditions, Trec-AMC-EXPAR detected two clinically significant SNVs, PIK3CAH1047R and EGFR L858R within 80 min, with a reliable detection of 0.1% SNV in the wide type, which is lower than that of allele-specific PCR (AS-PCR) for detecting SNV. Finally, by spiking into normal human serum samples, mutants mixed with the wild-type targets in different ratios were analyzed, resulting in the relative standard deviation (RSD) of recovery ratios <3%. The findings suggested the potential application of Trec-AMC-EXPAR in clinical disease diagnosis. In summary, the proposed Trec-AMC-EXPAR technique provides a novel fast and convenient method for one-pot detection of SNV with high sensitivity and specificity.

A universal and sensitive gene mutation detection method based on CRISPR-Cas12a

Single nucleotide mutations are highly related to the occurrence and development of cancer. The development of simple single nucleotide mutation detection methods with high sensitivity and specificity has great clinical significance for the prevention, diagnosis, treatment and prognosis evaluation of cancer. In recent years, CRISPR/Cas12a has been developed as a highly sensitive, simple and fast tool for nucleic acid detection. However, the specificity and universality of current detection methods based on it are still insufficient, so their clinical applications are limited. Herein, we developed a simple and rapid single nucleotide mutation detection method based on CRISPR/Cas12a system. This method not only solves the problem of PAM sequence restriction of CRISPR/Cas12a, but also significantly improves the specificity of CRISPR/Cas12a for single nucleotide mutation and greatly improves the sensitivity. We detected three clinically significant mutations, PTEN R130Q, BRAF V600E, and TP53 R248W, with a detection limit of 0.1%. Finally, we further verified the clinical practicability of this method. We selected TP53 R248W mutation site for testing. The accuracy of testing results for 10 clinical samples was as high as 100%. In conclusion, the detection method of specific PCR combined with CRISPR/Cas12a is simple, rapid, universal and highly sensitive. We believe that this method has promising application prospects in clinical diagnosis of cancer.

Detection and Quantification of ctDNA for Longitudinal Monitoring of Treatment in Non-Small Cell Lung Cancer Patients Using a Universal Mutant Detection Assay by Denaturing Capillary Electrophoresis

Background: Observation of anticancer therapy effect by monitoring of minimal residual disease (MRD) is becoming an important tool in management of non-small cell lung cancer (NSCLC). The approach is based on periodic detection and quantification of tumor-specific somatic DNA mutation in circulating tumor DNA (ctDNA) extracted from patient plasma. For such repetitive testing, complex liquid-biopsy techniques relying on ultra-deep NGS sequencing are impractical. There are other, cost-effective, methods for ctDNA analysis, typically based on quantitative PCR or digital PCR, which are applicable for detecting specific individual mutations in hotspots. While such methods are routinely used in NSCLC therapy prediction, however, extension to cover broader spectrum of mutations (e.g., in tumor suppressor genes) is required for universal longitudinal MRD monitoring.

Methods: For a set of tissue samples from 81 NSCLC patients we have applied a denaturing capillary electrophoresis (DCE) for initial detection of somatic mutations within 8 predesigned PCR amplicons covering oncogenes and tumor suppressor genes. Mutation-negative samples were then subjected to a large panel NGS sequencing. For each patient mutation found in tissue was then traced over time in ctDNA by DCE.

Results: In total we have detected a somatic mutation in tissue of 63 patients. For those we have then prospectively analyzed ctDNA from collected plasma samples over a period of up to 2 years. The dynamics of ctDNA during the initial chemotherapy therapy cycles as well as in the long-term follow-up matched the clinically observed response.

Conclusion: Detection and quantification of tumor-specific mutations in ctDNA represents a viable complement to MRD monitoring during therapy of NSCLC patients. The presented approach relying on initial tissue mutation detection by DCE combined with NGS and a subsequent ctDNA mutation testing by DCE only represents a cost-effective approach for its routine implementation.

PEAC: An Ultrasensitive and Cost-Effective MRD Detection System in Non-small Cell Lung Cancer Using Plasma Specimen

Circulating tumor DNA (ctDNA), a tumor-derived fraction of cell-free DNA (cfDNA), has emerged as a promising marker in targeted therapy, immunotherapy, and minimal residual disease (MRD) monitoring in postsurgical patients. However, ctDNA level in early-stage cancers and postsurgical patients is very low, which posed many technical challenges to improve the detection rate and sensitivity, especially in the clinical practice of MRD detection. These challenges usually include insufficient DNA input amount, limit of detection (LOD), and high experimental costs. To resolve these challenges, we developed an ultrasensitive ctDNA MRD detection system in this study, namely PErsonalized Analysis of Cancer (PEAC), to simultaneously detect up to 37 mutations, which account for 70–80% non-small cell lung cancer (NSCLC) driver mutations from low plasma sample volume and enables LOD of 0.01% at a single-site level. We demonstrated the high performance achieved by PEAC on both cfDNA reference standards and clinical plasma samples from three NSCLC patient cohorts. For cfDNA reference standards, PEAC achieved a specificity of 99% and a sensitivity of 87% for the mutations at 0.01% allele fraction. In the second cohort, PEAC showed 100% concordance rate between ddPCR and Next-generation sequencing (NGS) among 29 samples. In the third cohort, 22 of 59 patients received EGFR TKI treatment. Among them, three in four patients identified low level actionable gene mutations only by PEAC had partial responses after targeted therapy, demonstrating high ctDNA detection ability of PEAC. Overall, the developed PEAC system can detect the majority of NSCLC driver mutations using 8–10 ml plasma samples, and has the advantages of high detection sensitivity and lower costs compared with the existing technologies such as ddPCR and NGS. These advantages make the PEAC system quite appropriate for ctDNA and MRD detection in early-stage NSCLC and postsurgical recurrence monitoring.

A comprehensive system for detecting rare single nucleotide variants based on competitive DNA probe and duplex-specific nuclease

Single nucleotide variants (SNVs) have emerged as increasingly important biomarkers, particularly in the diagnosis and prognosis of cancers. However, most SNVs are rarely detected in blood samples from cancer patients as they are surrounded by abundant concomitant wild-type nucleic acids. Herein, we design a system that features a combination of competitive DNA probe system (CDPS) and duplex-specific nuclease (DSN) that we referred to as CAD. A theoretical model was established for the CAD system based on reaction networks. Guided by the theoretical model, we found that a minor loss in sensitivity significantly improved the specificity of the system, thus creating a theoretical discrimination factor (DF) > 100 for most conditions. This non-equivalent tradeoff between sensitivity and specificity provides a new concept for the analysis of rare DNA-sequence variants. As a demonstration of practicality, we applied as-proposed CAD system to identify low variant allele frequency (VAF) in a synthetic template (0.1% VAF) and human genomic DNA (1% VAF). This work promises complete guidance for the design of enzyme-based nucleic acid analysis.