Dataset Information

Droplet digital polymerase chain reaction for detection and quantification of cell-free DNA TP53 target somatic mutations in oral cancer.

ABSTRACT:

Background

TP53 mutation is a driver mutation of oral carcinogenesis. This study investigated cancerous and cell-free DNA (cfDNA) in patients with oral squamous cell carcinoma (OSCC) to detect the target hotspot somatic mutation of TP53.

Objective

TP53 target hotspot mutations were determined in surgically resected primary tumor samples from 107 OSCC patients.

Methods

Cancerous and cfDNA samples were examined for mutations through droplet digital polymerase chain reaction (ddPCR) by using mutation-specific assays. The ddPCR results were evaluated alongside clinicopathological data.

Results

In total, 23 cases had target TP53 mutations in varying degrees. We found that OSCC had relatively low cfDNA shedding, and mutations were at low allele frequencies. Of these 23 cases, 13 had target TP53 mutations in their corresponding cfDNA. Target somatic mutations in cancerous DNA and cfDNA are related to cervical lymph node metastasis. The cfDNA concentration is related to primary tumor size, lymph node metastasis, and OSCC stage.

Conclusions

Our results show that the detection of TP53 target somatic mutations in OSCC patients by using ddPCR is technically feasible. Low levels of cfDNA may produce different results between cancerous tissue and cfDNA analyses. Future research on cfDNA may quantify diagnostic biomarkers in the surveillance of OSCC patients.

SUBMITTER: Lin LH

PROVIDER: S-EPMC8925125 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Droplet digital polymerase chain reaction for detection and quantification of cell-free DNA TP53 target somatic mutations in oral cancer.

Lin Li-Han LH Cheng Hui-Wen HW Liu Chung-Ji CJ

Cancer biomarkers : section A of Disease markers 20220101 1

<h4>Background</h4>TP53 mutation is a driver mutation of oral carcinogenesis. This study investigated cancerous and cell-free DNA (cfDNA) in patients with oral squamous cell carcinoma (OSCC) to detect the target hotspot somatic mutation of TP53.<h4>Objective</h4>TP53 target hotspot mutations were determined in surgically resected primary tumor samples from 107 OSCC patients.<h4>Methods</h4>Cancerous and cfDNA samples were examined for mutations through droplet digital polymerase chain reaction ( ...[more]

PMID: 34366328

Similar Datasets

Project description:Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

Dataset Information

Droplet digital polymerase chain reaction for detection and quantification of cell-free DNA TP53 target somatic mutations in oral cancer.

Background

Objective

Methods

Results

Conclusions

Publications

Droplet digital polymerase chain reaction for detection and quantification of cell-free DNA TP53 target somatic mutations in oral cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets