Polymerase chain reaction (PCR) variants requiring specific primer types are widely used in various PCR experiments, including generic PCR, inverse PCR, anchored PCR, and ARMS PCR. Few tools can be adapted for multiple PCR variants, and many tools select primers by filtration based on the given parameters, which result in frequent design failures. Here we introduce PrimerScore2, a robust high-throughput primer design tool that can design primers in one click for multiple PCR variants. It scores primers using a piecewise logistic model and the highest-scored primers are selected avoiding the issue of design failure and the necessity to loosen parameters to redesign, and it creatively evaluates specificity by predicting the efficiencies of all target/non-target products. To assess the prediction accuracy of the scores and efficiencies, two next generation sequencing (NGS) libraries were constructed-a 12-plex and a 57-plex-and the results showed that 17 out of 19 (89.5%) low-scoring pairs had a poor depth, 18 out of 19 (94.7%) high-scoring pairs had a high depth, and the depth ratios of the products were linearly correlated with the predicted efficiencies with a slope of 1.025 and a coefficient of determination (R2) 0.935. 116-plex and 114-plex anchored PCR panels designed by PrimerScore2 were applied to 26 maternal plasma samples with male fetuses, the results showed that the predicted fetal DNA fractions were concordant with fractions measured in gold standard method (Y fractions). PrimerScore2 was also used to design 77 monoplex Sanger sequencing primers, the sequencing results indicated that all the primers were effective.

BACKGROUND:The present study sought to identify a panel of DNA markers for noninvasive diagnosis using cell-free DNA (cfDNA) from urine supernatant or cellular DNA from urine sediments of hematuria patients. A panel of 48 bladder cancer-specific genes was selected. A next-generation sequencing-based assay with a cfDNA barcode-enabled single-molecule test was employed. Mutation profiles of blood, urine, and tumor sample from 16 bladder cancer patients were compared. Next, urinary cellular DNA and cfDNA were prospectively collected from 125 patients (92 bladder cancer cases and 33 controls) and analyzed using the 48-gene panel. The individual gene markers and combinations of markers were validated according to the pathology results. The mean areas under the receiver operating characteristic (ROC) curves (AUCs) obtained with the various modeling approaches were calculated and compared.RESULTS:This pilot study of 16 bladder cancer patients demonstrated that gene mutations in urine supernatant and sediments had better concordance with cancer tissue as compared with plasma. Logistic analyses suggested two powerful combinations of genes for genetic diagnostic modeling: five genes for urine supernatant (TERT, FGFR3, TP53, PIK3CA, and KRAS) and seven genes for urine sediments (TERT, FGFR3, TP53, HRAS, PIK3CA, KRAS, and ERBB2). The accuracy of the five-gene panel and the seven-gene panel in the validation cohort yielded AUCs of 0.94 [95% confidence interval (CI) 0.91-0.97] and 0.91 (95% CI 0.86-0.96), respectively. With the addition of age and gender, the diagnostic power of the urine supernatant five-gene model and the urine sediment seven-gene model improved as the revised AUCs were 0.9656 (95% CI 0.9368-0.9944) and 0.9587 (95% CI 0.9291-0.9883).CONCLUSIONS:cfDNA from urine bears great diagnostic potential. A five-gene panel for urine supernatant and a seven-gene panel for urine sediments are promising options for identifying bladder cancer in hematuria patients.

Objective: Detection of aberrant methylated genes in feces has been developed as an early screening method for colorectal cancer.The aim of this study was to probe the methylation status of SEPT9, BMP3, NDRG4, and SDC2 in stool and study whether methylation of these genes is associated with colorectal cancer.Materials and Methods: DNAs were isolated and purified from cancerous and non-cancerous stool samples and colorectal cancer tissue.Gene methylation levels were quantified by methylation-specific PCR on SEPT9, BMP3, NDRG4, and SDC2 and analyzed by a diagnostic model.Results: DNA methylation of SEPT9, NDRG4 and SDC2, but not BMP3, had diagnostic potential for detecting colorectal cancer.Moreover, integration of SEPT9, NDRG4, and SDC2 methylation demonstrated high feasibility for detecting colorectal cancer and adenoma, with better performance on colorectal cancer than adenoma. Conclusion:The methylation of SEPT9, NDRG4, and SDC2 in stool may be a potential biomarker for early screening of colorectal cancer.