Dataset Information

Individualized Mutation Detection in Circulating Tumor DNA for Monitoring Colorectal Tumor Burden Using a Cancer-Associated Gene Sequencing Panel.

ABSTRACT:

Background

Circulating tumor DNA (ctDNA) carries information on tumor burden. However, the mutation spectrum is different among tumors. This study was designed to examine the utility of ctDNA for monitoring tumor burden based on an individual mutation profile.

Methodology

DNA was extracted from a total of 176 samples, including pre- and post-operational plasma, primary tumors, and peripheral blood mononuclear cells (PBMC), from 44 individuals with colorectal tumor who underwent curative resection of colorectal tumors, as well as nine healthy individuals. Using a panel of 50 cancer-associated genes, tumor-unique mutations were identified by comparing the single nucleotide variants (SNVs) from tumors and PBMCs with an Ion PGM sequencer. A group of the tumor-unique mutations from individual tumors were designated as individual marker mutations (MMs) to trace tumor burden by ctDNA using droplet digital PCR (ddPCR). From these experiments, three major objectives were assessed: (a) Tumor-unique mutations; (b) mutation spectrum of a tumor; and (c) changes in allele frequency of the MMs in ctDNA after curative resection of the tumor.

Results

A total of 128 gene point mutations were identified in 27 colorectal tumors. Twenty-six genes were mutated in at least 1 sample, while 14 genes were found to be mutated in only 1 sample, respectively. An average of 2.7 genes were mutated per tumor. Subsequently, 24 MMs were selected from SNVs for tumor burden monitoring. Among the MMs found by ddPCR with > 0.1% variant allele frequency in plasma DNA, 100% (8 out of 8) exhibited a decrease in post-operation ctDNA, whereas none of the 16 MMs found by ddPCR with < 0.1% variant allele frequency in plasma DNA showed a decrease.

Conclusions

This panel of 50 cancer-associated genes appeared to be sufficient to identify individual, tumor-unique, mutated ctDNA markers in cancer patients. The MMs showed the clinical utility in monitoring curatively-treated colorectal tumor burden if the allele frequency of MMs in plasma DNA is above 0.1%.

SUBMITTER: Sato KA

PROVIDER: S-EPMC4699643 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Individualized Mutation Detection in Circulating Tumor DNA for Monitoring Colorectal Tumor Burden Using a Cancer-Associated Gene Sequencing Panel.

Sato Kei A KA Hachiya Tsuyoshi T Iwaya Takeshi T Kume Kohei K Matsuo Teppei T Kawasaki Keisuke K Abiko Yukito Y Akasaka Risaburo R Matsumoto Takayuki T Otsuka Koki K Nishizuka Satoshi S SS

PloS one 20160104 1

<h4>Background</h4>Circulating tumor DNA (ctDNA) carries information on tumor burden. However, the mutation spectrum is different among tumors. This study was designed to examine the utility of ctDNA for monitoring tumor burden based on an individual mutation profile.<h4>Methodology</h4>DNA was extracted from a total of 176 samples, including pre- and post-operational plasma, primary tumors, and peripheral blood mononuclear cells (PBMC), from 44 individuals with colorectal tumor who underwent cu ...[more]

PMID: 26727500

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Project description:Postoperative monitoring for patients with colorectal cancer (CRC) requires sensitive biomarkers that are associated with medical response and adjuvant therapy following surgery. Conventional tumor biomarkers [including carcinoembryonic antigen (CEA), CA19-9 and CA125] are widely used, but none of the markers provide high sensitivity or specificity. Previous studies indicated that circulating tumor DNA (ctDNA) is useful for postoperative monitoring of patients with cancer. However, the majority of previous studies involved patients with lung cancer, and therefore further studies are required which investigate patients with CRC. The present study enrolled 11 patients with CRC. All patients underwent surgery, and a number of patients were treated with postoperative chemotherapy. Tumor tissues and serial blood samples were collected from each patient, and somatic mutations of each sample were obtained using next-generation sequencing. The mutation landscape and dynamic changes in mutations for each patient were analyzed, and these results were compared with the changes of CEA levels. A number of driver genes were selected, including tumor protein P53 (TP53), APC and KRAS, to monitor the postoperative outcome of the 11 patients with CRC. Driver mutations were detected in preoperative plasma in 7 patients, with markedly decreased mutation rates detected in postoperative plasma compared with preoperative plasma. Driver mutations were not detected in 4 patients in the preoperative or postoperative plasma. In 1 patient with metastatic rectal cancer, the rate of TP53 mutation increased from 8.95 (preoperative) to 71.4% (postoperative), and a new phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α mutation emerged. This patient succumbed to mortality six months following surgery, however there were no marked changes in CEA levels during periodic detection of CEA levels. In summary, ctDNA has a high sensitivity and specificity in prediction of the prognosis of patients with CRC.

Project description:BackgroundTumor mutational burden (TMB) is a promising biomarker for stratifying patient subpopulation who would benefit from immune checkpoint blockade (ICB) therapies. Although great efforts have been made for standardizing TMB measurement, mutation calling and TMB quantification can be challenging in samples with low tumor content including liquid biopsies. The effect of varying tumor content on TMB estimation by different assay methods has never been systematically investigated.MethodWe established a series of reference standard DNA samples derived from 11 pairs of tumor-normal matched human cell lines across different cancer types. Each tumor cell line was mixed with its matched normal at 0% (control), 1%, 2%, 5%, and 10% mass-to-mass ratio to mimic the clinical samples with low tumor content. TMB of these reference standards was evaluated by both ∼1000× whole-exome sequencing (wesTMB) and targeted panel sequencing (psTMB) at four different vendors. Both regression and classification analyses of TMB were performed for theoretical investigation and clinical practice purposes.ResultsLinear regression model was established that demonstrated in silico psTMB determined by regions of interest (ROI) as a great representative of wesTMB based on TCGA dataset. It was also true in our reference standard samples as the predicted psTMB interval based on the observed wesTMB captured the intended 90% of the in silico psTMB values. Although ∼1000× deep WES was applied, reference standard samples with less than 5% of tumor proportions are below the assay limit of detection (LoD) of wesTMB quantification. However, predicted wesTMB based on observed psTMB accurately classify (>0.97 AUC) for TMB high and low patient stratification even in samples with 2% of tumor content, which is more clinically relevant, as TMB determination should be a qualitative assay for TMB high and low patient classification. One targeted panel sequencing vendor using an optimized blood psTMB pipeline can further classify TMB status accurately (>0.82 AUC) in samples with only 1% of tumor content.ConclusionsWe developed a linear model to establish the quantitative correlation between wesTMB and psTMB. A set of DNA reference standards was produced in aid to standardize TMB measurements in samples with low tumor content across different targeted sequencing panels. This study is a significant contribution aiming to harmonize TMB estimation and extend its future application in clinical samples with low tumor content including liquid biopsy.

Dataset Information

Individualized Mutation Detection in Circulating Tumor DNA for Monitoring Colorectal Tumor Burden Using a Cancer-Associated Gene Sequencing Panel.

Background

Methodology

Results

Conclusions

Publications

Individualized Mutation Detection in Circulating Tumor DNA for Monitoring Colorectal Tumor Burden Using a Cancer-Associated Gene Sequencing Panel.

Similar Datasets

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