Diagnostic value of circular free DNA for colorectal cancer detection

BACKGROUND Minimally invasive or noninvasive, sensitive and accurate detection of colorectal cancer (CRC) is urgently needed in clinical practice. AIM To identify a noninvasive, sensitive and accurate circular free DNA marker detected by digital polymerase chain reaction (dPCR) for the early diagnosis of clinical CRC. METHODS A total of 195 healthy control (HC) individuals and 101 CRC patients (38 in the early CRC group and 63 in the advanced CRC group) were enrolled to establish the diagnostic model. In addition, 100 HC individuals and 62 patients with CRC (30 early CRC and 32 advanced CRC groups) were included separately to validate the model. CAMK1D was dPCR. Binary logistic regression analysis was used to establish a diagnostic model including CAMK1D and CEA. RESULTS To differentiate between the 195 HCs and 101 CRC patients (38 early CRC and 63 advanced CRC patients), the common biomarkers CEA and CAMK1D were used alone or in combination to evaluate their diagnostic value. The area under the curves (AUCs) of CEA and CAMK1D were 0.773 (0.711, 0.834) and 0.935 (0.907, 0.964), respectively. When CEA and CAMK1D were analyzed together, the AUC was 0.964 (0.945, 0.982). In differentiating between the HC and early CRC groups, the AUC was 0.978 (0.960, 0.995), and the sensitivity and specificity were 88.90% and 90.80%, respectively. In differentiating between the HC and advanced CRC groups, the AUC was 0.956 (0.930, 0.981), and the sensitivity and specificity were 81.30% and 95.90%, respectively. After building the diagnostic model containing CEA and CAMK1D, the AUC of the CEA and CAMK1D joint model was 0.906 (0.858, 0.954) for the validation group. In differentiating between the HC and early CRC groups, the AUC was 0.909 (0.844, 0.973), and the sensitivity and specificity were 93.00% and 83.30%, respectively. In differentiating between the HC and advanced CRC groups, the AUC was 0.904 (0.849, 0.959), and the sensitivity and specificity were 93.00% and 75.00%, respectively. CONCLUSION We built a diagnostic model including CEA and CAMK1D for differentiating between HC individuals and CRC patients. Compared with the common biomarker CEA alone, the diagnostic model exhibited significant improvement.

[1]  Kathrin M. Seibt,et al.  ECCsplorer: a pipeline to detect extrachromosomal circular DNA (eccDNA) from next-generation sequencing data , 2022, BMC Bioinformatics.

[2]  Qiyao Peng,et al.  Extrachromosomal Circular DNA (eccDNA): From Chaos to Function , 2022, Frontiers in Cell and Developmental Biology.

[3]  Haijian Zhang,et al.  Extrachromosomal circular DNA: a new potential role in cancer progression , 2021, Journal of Translational Medicine.

[4]  A. Dutta,et al.  ATAC-Seq-based Identification of Extrachromosomal Circular DNA in Mammalian Cells and Its Validation Using Inverse PCR and FISH. , 2021, Bio-protocol.

[5]  K. Pantel,et al.  Liquid Biopsy: From Discovery to Clinical Application. , 2021, Cancer discovery.

[6]  Kun Wang,et al.  Extrachromosomal Circular DNAs: Origin, formation and emerging function in Cancer , 2021, International journal of biological sciences.

[7]  S. Chakrabortty,et al.  Exosome-based liquid biopsies in cancer: opportunities and challenges , 2021, Annals of oncology : official journal of the European Society for Medical Oncology.

[8]  Ming-hua Sui,et al.  CircPRKCI regulates proliferation, migration and cycle of lung adenocarcinoma cells by targeting miR-219a-5p-regulated CAMK1D. , 2021, European review for medical and pharmacological sciences.

[9]  Yicheng Liang,et al.  Expression of CAMK1 and its association with clinicopathologic characteristics in pancreatic cancer , 2020, Journal of cellular and molecular medicine.

[10]  N. Ji,et al.  Extrachromosomal circular DNAs are common and functional in esophageal squamous cell carcinoma , 2020, Annals of translational medicine.

[11]  P. Neužil,et al.  PCR past, present and future , 2020, BioTechniques.

[12]  Y. Shibata,et al.  ATAC-seq identifies thousands of extrachromosomal circular DNA in cancer and cell lines , 2020, Science Advances.

[13]  Jia Li Ren,et al.  [Digital PCR and its application in biological detection]. , 2020, Yi chuan = Hereditas.

[14]  J. Houseley,et al.  The adaptive potential of circular DNA accumulation in ageing cells , 2020, Current Genetics.

[15]  Howard Y. Chang,et al.  Circular ecDNA promotes accessible chromatin and high oncogene expression , 2019, Nature.

[16]  Hongyu Zhao,et al.  Next-generation sequencing in liquid biopsy: cancer screening and early detection , 2019, Human Genomics.

[17]  Y. Shibata,et al.  Small extrachromosomal circular DNAs, microDNA, produce short regulatory RNAs that suppress gene expression independent of canonical promoters , 2019, Nucleic acids research.

[18]  J. L. Costa,et al.  Liquid Biopsy beyond Circulating Tumor Cells and Cell-Free DNA , 2019, Acta Cytologica.

[19]  Anindya Dutta,et al.  Discoveries of Extrachromosomal Circles of DNA in Normal and Tumor Cells. , 2018, Trends in genetics : TIG.

[20]  Phenix-Lan Quan,et al.  dPCR: A Technology Review , 2018, Sensors.

[21]  Songbin Fu,et al.  Molecular characterization of cell-free eccDNAs in human plasma , 2017, Scientific Reports.

[22]  Jiaqi Lin,et al.  [Progress in digital PCR technology and application]. , 2017, Sheng wu gong cheng xue bao = Chinese journal of biotechnology.

[23]  E. Mitchell,et al.  Carcinoembryonic Antigen in the Staging and Follow-up of Patients with Colorectal Cancer , 2005, Cancer investigation.

[24]  P. Polakis Wnt signaling and cancer. , 2000, Genes & development.

[25]  L. Plank,et al.  Droplet digital PCR as a novel dia-gnostic tool. , 2021, Klinicka onkologie : casopis Ceske a Slovenske onkologicke spolecnosti.

[26]  Yuelong Shu,et al.  An Overview of Digital PCR. , 2017, Bing du xue bao = Chinese journal of virology.

[27]  E. Kuipers,et al.  Colorectal cancer , 2015, Nature Reviews Disease Primers.