Dataset Information

Somatic mutation detection using various targeted detection assays in paired samples of circulating tumor DNA, primary tumor and metastases from patients undergoing resection of colorectal liver metastases.

ABSTRACT: Assessing circulating tumor DNA (ctDNA) is a promising method to evaluate somatic mutations from solid tumors in a minimally-invasive way. In a group of twelve metastatic colorectal cancer (mCRC) patients undergoing liver metastasectomy, from each patient DNA from cell-free DNA (cfDNA), the primary tumor, metastatic liver tissue, normal tumor-adjacent colon or liver tissue, and whole blood were obtained. Investigated was the feasibility of a targeted NGS approach to identify somatic mutations in ctDNA. This targeted NGS approach was also compared with NGS preceded by mutant allele enrichment using synchronous coefficient of drag alteration technology embodied in the OnTarget assay, and for selected mutations with digital PCR (dPCR). All tissue and cfDNA samples underwent IonPGM sequencing for a CRC-specific 21-gene panel, which was analyzed using a standard and a modified calling pipeline. In addition, cfDNA, whole blood and normal tissue DNA were analyzed with the OnTarget assay and with dPCR for specific mutations in cfDNA as detected in the corresponding primary and/or metastatic tumor tissue. NGS with modified calling was superior to standard calling and detected ctDNA in the cfDNA of 10 patients harboring mutations in APC, ATM, CREBBP, FBXW7, KRAS, KMT2D, PIK3CA and TP53. Using this approach, variant allele frequencies in plasma ranged predominantly from 1 to 10%, resulting in limited concordance between ctDNA and the primary tumor (39%) and the metastases (55%). Concordance between ctDNA and tissue markedly improved when ctDNA was evaluated for KRAS, PIK3CA and TP53 mutations by the OnTarget assay (80%) and digital PCR (93%). Additionally, using these techniques mutations were observed in tumor-adjacent tissue with normal morphology in the majority of patients, which were not observed in whole blood. In conclusion, in these mCRC patients with oligometastatic disease NGS on cfDNA was feasible, but had limited sensitivity to detect all somatic mutations present in tissue. Digital PCR and mutant allele enrichment before NGS appeared to be more sensitive to detect somatic mutations.

SUBMITTER: Beije N

PROVIDER: S-EPMC5423131 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Somatic mutation detection using various targeted detection assays in paired samples of circulating tumor DNA, primary tumor and metastases from patients undergoing resection of colorectal liver metastases.

Beije Nick N Helmijr Jean C JC Weerts Marjolein J A MJA Beaufort Corine M CM Wiggin Matthew M Marziali Andre A Verhoef Cornelis C Sleijfer Stefan S Jansen Maurice P H M MPHM Martens John W M JWM

Molecular oncology 20161201 10

Assessing circulating tumor DNA (ctDNA) is a promising method to evaluate somatic mutations from solid tumors in a minimally-invasive way. In a group of twelve metastatic colorectal cancer (mCRC) patients undergoing liver metastasectomy, from each patient DNA from cell-free DNA (cfDNA), the primary tumor, metastatic liver tissue, normal tumor-adjacent colon or liver tissue, and whole blood were obtained. Investigated was the feasibility of a targeted NGS approach to identify somatic mutations in ...[more]

PMID: 28949453

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Project description:BackgroundObservations of recurrent somatic mutations in tumors have led to identification and definition of signaling and other pathways that are important for cancer progression and therapeutic targeting. As tumor cells contain both an individual's inherited genetic variants and somatic mutations, challenges arise in distinguishing these events in massively parallel sequencing datasets. Typically, both a tumor sample and a "normal" sample from the same individual are sequenced and compared; variants observed only in the tumor are considered to be somatic mutations. However, this approach requires two samples for each individual.ResultsWe evaluate a method of detecting somatic mutations in tumor samples for which only a subset of normal samples are available. We describe tuning of the method for detection of mutations in tumors, filtering to remove inherited variants, and comparison of detected mutations to several matched tumor/normal analysis methods. Filtering steps include the use of population variation datasets to remove inherited variants as well a subset of normal samples to remove technical artifacts. We then directly compare mutation detection with tumor-only and tumor-normal approaches using the same sets of samples. Comparisons are performed using an internal targeted gene sequencing dataset (n = 3380) as well as whole exome sequencing data from The Cancer Genome Atlas project (n = 250). Tumor-only mutation detection shows similar recall (43-60%) but lesser precision (20-21%) to current matched tumor/normal approaches (recall 43-73%, precision 30-82%) when compared to a "gold-standard" tumor/normal approach. The inclusion of a small pool of normal samples improves precision, although many variants are still uniquely detected in the tumor-only analysis.ConclusionsA detailed method for somatic mutation detection without matched normal samples enables study of larger numbers of tumor samples, as well as tumor samples for which a matched normal is not available. As sensitivity/recall is similar to tumor/normal mutation detection but precision is lower, tumor-only detection is more appropriate for classification of samples based on known mutations. Although matched tumor-normal analysis is preferred due to higher precision, we demonstrate that mutation detection without matched normal samples is possible for certain applications.

Project description:BackgroundMultiple liver metastases is considered a risk factor for overall survival of colorectal liver metastases patients (CRLM) after curative resection. However, whether the prognostic factors were constant in patients with various liver metastases (LM) numbers has not been adequately investigated. This retrospective study aimed to evaluate the changing of prognostic factors on overall survival (OS) in CRLM patients with various LM after curative resection.MethodsPatients who underwent liver resection for CRLM between January 2000 and November 2020 were retrospectively studied. They were divided into three subgroups according to LM numbers by X-tile analysis. Multivariable analysis identified prognostic factors in each subgroup. Nomograms were built using different prognostic factors in three subgroups, respectively. Performance of the nomograms was assessed according to the concordance index (C-index) and calibration plots. The abilities of different scoring systems predicting OS were compared by calculating the area under the time-dependent receiver operating characteristic (ROC) curve (AUC).ResultsA total of 1095 patients were included. Multivariable analysis showed tumor number increasing was an independent risk factor. Patients were subsequently divided into 3 subgroups according to the number of LM by X-tile analysis, namely solitary (n = 375), 2-4 (n = 424), and ≥ 5 (n = 296). The 3-year and 5-year OS rates were 64.1% and 54.0% in solitary LM group, 58.1% and 41.7% in 2-4 LM group, and 50.9% and 32.0% in ≥ 5 LM group, respectively (p < 0.001). In multivariable analysis, RAS mutation was the only constant independent risk factor in all subgroups. The nomograms were built to predict survival based on independent factors in three subgroups. The C-index for OS prediction was 0.707 (95% CI 0.686-0.728) in the solitary LM group, 0.695 (95% CI 0.675-0.715) in the 2-4 LM group, and 0.687 (95% CI 0.664-0.710) in the ≥ 5 LM group. The time-dependent AUC values of nomograms developed using different risk factors after stratifying patients by tumor number were higher than the traditional scoring systems without patient stratification.ConclusionsThe prognostic factors varied among CRLM patients with different LM numbers. RAS mutation was the only constant risk factor. Building prediction models based on different prognostic factors improve patient stratification.

Dataset Information

Somatic mutation detection using various targeted detection assays in paired samples of circulating tumor DNA, primary tumor and metastases from patients undergoing resection of colorectal liver metastases.

Publications

Somatic mutation detection using various targeted detection assays in paired samples of circulating tumor DNA, primary tumor and metastases from patients undergoing resection of colorectal liver metastases.

Similar Datasets

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