RASSF1A methylation as a biomarker for detection of colorectal cancer and hepatocellular carcinoma

BACKGROUND Studies have validated the potential of methylated cell-free DNA as a biomarker in various tumors,and methylated DNA in plasma may be a potential biomarker for cancer.AIM To evaluate the diagnostic value of RASSF1A methylation in plasma for colorectal cancer(CRC)and hepatocellular carcinoma(HCC).METHODS A total of 92 CRC patients,67 colorectal polyp(CRP)patients,63 HCC patients,and 66 liver cirrhosis(LC)patients were enrolled.The plasma DNA was subjected to DNA extraction,double-strand DNA concentration determination,bisulfite conversion,purification,single-strand DNA concentration determination,and digital polymerase chain reaction(PCR)detection.The methylation rate was calculated.The diagnostic value was evaluated by the area under the curve(AUC).RESULTS The age and sex in the CRC and CRP groups and the HCC and LC groups were also matched.The DNA methylation rate of RASSF1A in plasma in the CRC group was 2.87±1.80,and that in the CRP group was 1.50±0.64.DNA methylation of RASSF1A in plasma showed a significant difference between the CRC and CRP groups.The AUC of RASSF1A methylation for discriminating the CRC and CRP groups was 0.82(0.76-0.88).The AUCs of T1,T2,T3 and T4 CRC and CRP were 0.83(0.72-0.95),0.87(0.78-0.95),0.86(0.77-0.95),and 0.75(0.64-0.85),respectively.The DNA methylation rate of RASSF1A in plasma in the HCC group was 4.45±2.93,and that in the LC group was 2.46±2.07.DNA methylation of RASSF1A in plasma for the HCC and LC groups showed a significant difference.The AUC of RASSF1A methylation for discriminating the HCC and LC groups was 0.70(0.60-0.79).The AUCs of T1,T2,T3 and T4 HCC and LC were 0.80(0.61,1.00),0.74(0.59-0.88),0.60(0.42-0.79),and 0.68(0.53-0.82),respectively.CONCLUSION RASSF1A methylation in plasma detected by digital PCR may be a potential biomarker for CRC and HCC.

Early detection of colorectal cancer based on circular DNA and common clinical detection indicators

BACKGROUND Colorectal cancer(CRC) is the third most common cancer worldwide, and it is the second leading cause of death from cancer in the world, accounting for approximately 9% of all cancer deaths. Early detection of CRC is urgently needed in clinical practice.AIM To build a multi-parameter diagnostic model for early detection of CRC.METHODS Total 59 colorectal polyps(CRP) groups, and 101 CRC patients(38 early-stage CRC and 63 advanced CRC) for model establishment. In addition, 30 CRP groups,and 62 CRC patients(30 early-stage CRC and 32 advanced CRC) were separately included to validate the model. 51 commonly used clinical detection indicators and the 4 extrachromosomal circular DNA markers NDUFB7, CAMK1D, PIK3CD and PSEN2 that we screened earlier. Four multi-parameter joint analysis methods:binary logistic regression analysis, discriminant analysis, classification tree and neural network to establish a multi-parameter joint diagnosis model.RESULTS Neural network included carcinoembryonic antigen(CEA), ischemia-modified albumin(IMA),sialic acid(SA), PIK3CD and lipoprotein a(LPa) was chosen as the optimal multi-parameter combined auxiliary diagnosis model to distinguish CRP and CRC group, when it differentiated 59CRP and 101 CRC, its overall accuracy was 90.8%, its area under the curve(AUC) was 0.959(0.934,0.985), and the sensitivity and specificity were 91.5% and 82.2%, respectively. After validation,when distinguishing based on 30 CRP and 62 CRC patients, the AUC was 0.965(0.930-1.000), and its sensitivity and specificity were 66.1% and 70.0%. When distinguishing based on 30 CRP and 32early-stage CRC patients, the AUC was 0.960(0.916-1.000), with a sensitivity and specificity of 87.5% and 90.0%, distinguishing based on 30 CRP and 30 advanced CRC patients, the AUC was 0.970(0.936-1.000), with a sensitivity and specificity of 96.7% and 86.7%.CONCLUSION We built a multi-parameter neural network diagnostic model included CEA, IMA, SA, PIK3CD and LPa for early detection of CRC, compared to the conventional CEA, it showed significant improvement.

Droplet digital polymerase chain reaction assay for methylated ring finger protein 180 in gastric cancer

BACKGROUND Gastric cancer(GC)is one of the most prevalent malignant tumors that endangers human health.Early diagnosis is essential for improving the prognosis and survival rate of GC patients.Ring finger protein 180(RNF180)is involved in the regulation of cell differentiation,proliferation,apoptosis,and tumorigenesis,and aberrant hypermethylation of CpG islands in the promoter is strongly associated with the occurrence and development of GC.Thus,methylated RNF180 can be used as a potential biomarker for GC diagnosis.AIM To use droplet digital polymerase chain reaction(ddPCR)to quantify the methylation level of the RN180 gene.A reproducible ddPCR assay to detect methylated RNF180 from trace DNA was designed and optimized.METHODS The primer and probe were designed and selected,the conversion time of bisulfite was optimized,the ddPCR system was adjusted by primer concentration,amplification temperature and amplification cycles,and the detection limit of ddPCR was determined.RESULTS The best conversion time for blood DNA was 2 h 10 min,and that for plasma DNA was 2 h 10 min and 2 h 30 min.The results of ddPCR were better when the amplification temperature was 56°C and the number of amplification cycles was 50.Primer concentrations showed little effect on the assay outcome.Therefore,the primer concentration could be adjusted according to the reaction system and DNA input.The assay required at least 0.1 ng of input DNA.CONCLUSION In summary,a ddPCR assay was established to detect methylated RNF180,which is expected to be a new diagnostic biomarker for GC.

Blood index panel for gastric cancer detection

BACKGROUND Gastric cancer is a common malignant tumor.Early detection and diagnosis are crucial for the prevention and treatment of gastric cancer.AIM To develop a blood index panel that may improve the diagnostic value for discriminating gastric cancer and gastric polyps.METHODS Thirteen tumor-related detection indices,38 clinical biochemical indices and 10 cytokine indices were examined in 139 gastric cancer patients and 40 gastric polyp patients to build the model.An additional 68 gastric cancer patients and 22 gastric polyp patients were enrolled for validation.After area under the curve evaluation and univariate and multivariate analyses.RESULTS Five tumor-related detection indices,12 clinical biochemical indices and 1 cytokine index showed significant differences between the gastric cancer and gastric polyp groups.Carbohydrate antigen(CA)724,phosphorus(P)and ischemia-modified albumin(IMA)were included in the blood index panel,and the area under the curve(AUC)of the index panel was 0.829(0.754,0.905).After validation,the AUC was 0.811(0.700,0.923).Compared to the conventional index CA724,the blood index panel showed significantly increased diagnostic value.CONCLUSION We developed an index model that included CA724,P and IMA to discriminate the gastric cancer and gastric polyp groups,which may be a potential diagnostic method for clinical practice.