Hypermethylated PCDHGB7 as a Biomarker for Early Detection of Endometrial Cancer in Endometrial Brush Samples and Cervical Scrapings

Endometrial cancer (EC) is one of the most common gynecologic cancers in developed countries. Presently, it is imperative to develop a reliable, noninvasive, or minimally invasive detection method for EC. We explored the possibility of using DNA methylation marker from endometrial brush samples (with a “Tao brush”) and cervical scrapes (with a “Pap brush”) for early detection of EC. We analyzed the methylation data of EC and normal endometrial tissues from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. An optimized methylation-sensitive restriction enzyme combined with real-time fluorescent quantitative PCR (MSRE-qPCR) was used for methylation detection. Included in the training set were 143 endometrial tissues, 103 Tao, and 109 Pap brush samples. The validation set included 110 Tao and 112 Pap brush samples. PCDHGB7 was significantly hypermethylated in EC compared with normal endometrial tissues in the TCGA and GEO data sets (AUC >0.95), which was verified in clinical samples. In the Pap brush samples, the AUC was 0.86 with 80.65% sensitivity and 82.81% specificity, whereas the Tao brush samples exhibited higher specificity (95.31%). The combination of Tao and Pap brush samples significantly increased the sensitivity to 90.32%. In the validation set, the final model yielded a sensitivity of 98.61%, specificity of 60.53%, positive predictive value of 82.56%, and negative predictive value of 95.83%. These results demonstrate the potential application of the novel methylation marker, hypermethylated PCDHGB7, in cervical scrapings and endometrial brush, which provides a viable, noninvasive, or minimally invasive method for early endometrial cancer detection across different clinical features and histologies to supplement current hysteroscopy diagnosis.

Circulating tumor DNA methylation marker MYO1-G for diagnosis and monitoring of colorectal cancer

Background Circulating tumor DNA (ctDNA) is a promising diagnostic and prognostic marker for many cancers and has been actively investigated in recent years. Previous studies have already demonstrated the potential use of ctDNA methylation markers in the diagnosis and prognostication of colorectal cancer (CRC). This retrospective study validated the value of methylation biomarker MYO1-G (cg10673833) in CRC diagnosis and disease monitoring using digital droplet PCR (ddPCR), a biomarker selected from our previous study due to its highest diagnostic efficiency. Methods Blood samples of CRC and control samples from tumor-free individuals at two institutions were collected to quantify the methylation ratio using ddPCR. Area under curve (AUC) was calculated after constructing receiver operating characteristic curve (ROC) for CRC diagnosis. Sensitivity and specificity were estimated and comparisons of methylation ratio in different groups were performed. Results We collected 673 blood samples from 272 patients diagnosed with stage I-IV CRC and 402 normal control samples. The methylation biomarker discriminated patients with CRC from normal controls with high accuracy (area under curve [AUC] = 0.94) and yielded a sensitivity of 84.3% and specificity of 94.5%. Besides, methylation ratio of MYO1-G was associated with tumor burden and treatment response. The methylation ratio was significantly lower in patients after their radical operation than when compared with those before surgeries (P < 0.001). Methylation ratio was significantly higher in patients with disease progression than those with stable disease (P = 0.002) and those with complete response or partial response (P = 0.009). Conclusions Together, our study indicated that this methylation marker can serve as a potential biomarker for diagnosing and monitoring CRC.

Impact of molecular surgical margin analysis on the prediction of pancreatic cancer recurrences after pancreaticoduodenectomy

Background Pancreatic cancer is one of the lethal cancers among solid malignancies. Pathological diagnosis of surgical margins is sometimes unreliable due to tissue shrinkage, invisible field cancerization and skipped lesions like tumor budding. As a result, tumor recurrences sometimes occur even from the pathologically negative surgical margins. Methods We applied molecular surgical margin (MSM) analysis by tissue imprinting procedure to improve the detection sensitivity of tiny cancerous cells on the surgical specimen surface after pancreatoduodenectomy. Surgical specimens were collected from 45 pancreatic cancer cases who received subtotal stomach preserving pancreatoduodenectomy at Nagoya University Hospital during 2017–2019. Quantitative methylation-specific PCR (QMSP) of the original methylation marker panel (CD1D, KCNK12, PAX5) were performed and analyzed with postoperative survival outcomes. Results Among 45 tumors, 26 cases (58%) were QMSP-positive for CD1D, 25 (56%) for KCNK12 and 27 (60%) for PAX5. Among the 38 tumors in which at least one of the three markers was positive, CD1D-positive cancer cells, KCNK12-positive cancer cells, and PAX5-positive cancer cells were detected at the surgical margin in 8 cases, 7 cases and 10 cases, respectively. Consequently, a total of 17 patients had at least one marker detected at the surgical margin by QMSP, and these patients were defined as MSM-positive. They were associated with significantly poor recurrence-free survival (p = 0.002) and overall survival (p = 0.005) than MSM-negative patients. Multivariable analysis showed that MSM-positive was the only significant independent factor for worse recurrence-free survival (hazard ratio: 3.522, 95% confidence interval: 1.352–9.179, p = 0.010). On the other hand, a significant proportion of MSM-negative cases were found to have received neoadjuvant chemotherapy (p = 0.019). Conclusion Pancreatic cancer-specific methylation marker panel was established to perform MSM analysis. MSM-positive status might represent microscopically undetectable cancer cells on the surgical margin and might influence the postoperative long-term outcomes.

Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis

Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54–99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56–100%), and AUPRC = 0.9220 (95% CI: 91.02–94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72–99.27%), and AUPRC = 0.9111 (95% CI: 88.45–93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07–98.91%), and AUPRC = 0.8640 (95% CI: 82.82–89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72–97.87%) and a specificity of 98.70% (95% CI: 86.36–100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75–99.55%), and AUPRC = 0.9800 (95% CI: 96.6–99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95–96.34%), and AUPRC = 0.9490 (95% CI: 91.7–98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography.

A panel of DNA methylation markers for the classification of consensus molecular subtypes 2 and 3 in patients with colorectal cancer.

3545 Background: Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). Currently available assays can identify CMS1 and CMS4 cases well, while a dedicated test to distinguish CMS2 and 3 is lacking. This study aimed to identify a panel of methylation markers to distinguish between CMS2 and 3 in patients with CRC. Methods: Fresh-frozen tumor tissue of 239 patients with stage I-III CRC was included. CMS classification was performed on RNA-seq data using the single-sample-prediction parameter from the “CMSclassifier” package. Methylation profiles were obtained using the Infinium HumanMethylation450 BeadChip. We performed adaptive group-regularised logistic ridge-regression with post-hoc group-weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3 based on 15, 10 or 5 markers. Data from TCGAwas used for validation. Results: Overall methylation profiles differed between CMS2 and CMS3. Group-regularisation of the probes was done based on their location either relative to a CpG island or relative to a gene present in the CMS classifier resulting in two different prediction models and subsequently different marker panels. For both panels, even when using only 5 markers, sensitivity, specificity, and accuracy were > 90%. Validation showed comparable performances. Conclusions: Our highly sensitive and specific methylation marker panel can be used to distinguish CMS2 and 3. This enables development of a qPCR DNA methylation assay in patients with CRC to provide a specific and non-invasive classification tool.

A novel DNA methylation marker for the urine-based liquid biopsies to detect bladder cancer.

e16503 Background: For bladder cancer (BC), the 5-year survival rate for patients with localized tumors can reach as high as 92%, but only 45% for those with tumors spreading to nearby regions. Cystoscopy combined with tissue biopsy can miss 10-40% of the cancer cases due to multiple factors. Meanwhile, the method is invasive, causing physical discomfort and psychological trauma for the patients. Therefore, development of a noninvasive, sensitive, and specific diagnostic alternative is needed. By analyzing TCGA data and improving analytic technology currently available, we have developed an easy-to-use, convenient, and accurate detection approach for BC relying on a single methylation marker. Methods: We searched TCGA database and selected a total of 366 candidate markers including those that have been published for subsequent examination and analyzed 446 primer pairs and probe sets. Using quantitative methylight method, we narrowed the field down to top 5 performers for subsequent urine-based testing of 270 samples. Finally, two markers were selected for validation testing in a group of 530 urine samples, consisting of 161 bladder cancers, 244 normal controls, 80 renal carcinomas, and 45 carcinomas of renal pelvis and ureter. In addition, we detected the methylation level and mRNA expression of target gene in 8 bladder cancer cell lines and 1 normal bladder epithelial cell line by MSP, qMSP and qPCR. Results: Methylation marker DMRTA2 had a sensitivity of 85.7%, an AUC value of 0.924, and an accuracy of 90.6%. The specificity, from a control group consisting of patients with lithangiuria, prostatoplasia, and prostatitis as well as healthy individuals, is 93.9% (138/161). Notably, the methylation assay had the highest sensitivities for tumors at stages of T1 (94.4%) and T2 (96.6%) compared with T3 (80.0%), T4 (71.4%), and unknown stage (90.0%). While methylation was observed in 34/45 urine samples from patients with carcinomas of renal pelvis and ureter, a good sensitivity of 75.6%, it was detected at extremely low rate of 7.5% (6/80) in those with interfering cancers of kidney and prostate. Additionally, the assay specificity was significantly affected by the age of the cancer patients and selection of healthy controls, critical aspects to be carefully considered during the design and development phase of the methylation-specific testing. Compared with SV-HUC-1, the normal bladder epithelial cell line, DMRTA2 gene was hypermethylated in 8 bladder cancer cell lines, which is consistent with the results of MSP and qMSP. The mRNA levels of DMRTA2 were low in some bladder cancer cell lines, such as T24, J82, UM-UC-3 and RT4, however were fairly high levels in 5637, SCaBER, TCCSUP and SW780. Conclusions: Our data demonstrated that a single-target DNA methylation signature could be highly effective to detect bladder cancer via urine samples.

Identification of DNA methylation markers for early detection of CRC indicates a role for nervous system-related genes in CRC

Purpose Colonoscopy and the fecal immunochemical test (FIT) are currently the most widely used screening modalities for colorectal cancer (CRC), however, both with their own limitations. Here we aim to identify and validate stool-based DNA methylation markers for the early detection of CRC and investigate the biological pathways prone to DNA methylation. Methods DNA methylation marker discovery was performed using The Cancer Genome Atlas (TCGA) colon adenocarcinoma data set consisting of normal and primary colon adenocarcinoma tissue. The performance of the five best candidate markers and a previously identified marker, NDRG4, was evaluated on tissues and whole stool samples of healthy subjects and CRC patients using quantitative MSP assays. The results were compared and combined with FIT data. Finally, pathway and gene ontology enrichment analyses were performed using ToppFun, GOrilla and clusterProfiler. Results GDNF, HAND2, SLC35F3, SNAP91 and SORCS1 were ranked as the best performing markers. Gene combinations of all five markers, NDRG4 and FIT were evaluated to establish the biomarker panel with the highest diagnostic potential, resulting in the identification of GDNF/SNAP91/NDRG4/FIT as the best performing marker panel. Pathway and gene ontology enrichment analyses revealed that genes associated with the nervous system were enriched in the set of best performing CRC-specific biomarkers. Conclusion In silico discovery analysis using TCGA-derived data yielded a novel DNA-methylation-based assay for the early detection of CRC, potentially improving current screening modalities. Additionally, nervous system-related pathways were enriched in the identified genes, indicating an epigenetic regulation of neuronal genes in CRC.