Diagnostic potential of hypermethylation of the cysteine dioxygenase 1 gene (CDO1) promoter DNA in pancreatic cancer

Advances in pancreatic cancer diagnosis: from DNA methylation to AI-Assisted imaging

INTRODUCTION

Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, MRI, and EUS, possess limitations in early PC diagnosis. Therefore, this review article explores the various innovative biomarkers for PC detection, such as DNA methylation, Noncoding RNAs, and proteomic biomarkers, and the role of AI in PC detection at early stages.

AREA COVERED

Innovative biomarkers, such as DNA methylation genes, show higher specificity and sensitivity in PC diagnosis. Additionally, various non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs, show high diagnostic accuracy and serve as diagnostic and prognostic biomarkers. Additionally, proteomic biomarkers retain higher diagnostic accuracy in different body fluids. Apart from this, the utilization of AI showed that AI surpassed the radiologist's diagnostic performance in PC detection.

EXPERT OPINION

The combination of AI and advanced biomarkers can revolutionize early PC detection. However, large-scale, prospective studies are needed to validate its clinical utility. Further. standardization of biomarker panels and AI algorithms is a vital step toward their reliable applications in early PC detection, ultimately improving patient outcomes.

Unraveling the clinical impact of differential DNA methylation in PDAC: A systematic review

INTRODUCTION

Despite significant efforts to improve clinical outcomes, pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate. The poor prognosis associated with this disease is multifactorial and associated with a highly variable genetic profile associated with its pathogenesis. Epigenetic modifications including DNA methylation further affect the expression of genetic material. However, there is no comprehensive understanding of the clinical impact of DNA methylation in PDAC.

METHODS

A systematic literature review was registered on the International Prospective Register of Systematic Reviews database (CRD42023451955) and followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. An electronic search was conducted using the following databases: CINAHL Plus, Cochrane Library, Embase, Web of Science, Ovid Medline, and Google Scholar. Inclusion criteria included studies of patients with a PDAC diagnosis and information regarding genes or CpG sites that potentially affect diagnosis, prognosis, or survival of PDAC.

RESULTS

The initial search retrieved 2402 articles, and 423 duplicates were excluded. After exclusion criteria was applied, 19 studies were included. The most common genes recorded as affecting tumor pathogenesis were SFRP1 (n = 3/19, 15.7 %) and NPTX2 (n = 2/19, 10,5 %). Studies indicated that hypermethylation of SFRP1 and NPTX2 were associated with poor prognosis.

CONCLUSIONS

PDAC is associated with a range of epigenetic modifications. Methylation of specific genes related to PDAC may influence survival and prognosis and be a therapeutic target. Individual patient epigenetic analysis may be a future direction in directing PDAC treatment and prognosis.

DNA methylation heterogeneity correlates with field cancerization and prognosis in lung adenocarcinoma patients

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer. The distinctive genetic and epigenetic modifications in tumors and paired non-malignant samples, such as adjacent peri-tumor and tumor-distant normal lung tissues, have not been adequately studied.

METHODS

We recruited 57 patients with resectable stage I-III LUAD and collected matched samples of the primary tumor, peri-tumoral tissues, and tumor-distant normal lung tissue. We performed bisulfite sequencing using a custom methylation panel to profile DNA methylation levels and obtained somatic variation landscape through targeted next-generation sequencing (NGS). We attempted to identify differential methylation blocks (DMBs) between the tumor, peri-tumor, and normal tissues.

RESULTS

We analyzed the DNA methylation patterns of matched tumor, peri-tumor, and normal lung tissue samples from 57 LUAD patients. No significantly different methylation blocks were found between peri-tumoral and normal tissues, while they both exhibited distinct methylation profiles compared to tumor tissues. A total of 1329 tumor-specific DMBs, which are potentially associated with aberrant gene expression in LUAD, were identified. Utilizing a consensus clustering algorithm, we classified the tumor samples into two subgroups (C1 and C2) based on distinct methylation profiles, independent of the patient's sex, tumor stage, smoking history, and tumor cell fraction. The C2 subgroup exhibited a higher malignancy density ratio (MD ratio), suggesting a more pronounced degree of field cancerization, while the C1 subgroup was characterized by a higher frequency of EGFR mutations. The DMBs between the two subgroups were enriched in the calcium signaling pathway. Notably, P2RX2 shows significant hypermethylation in the C2 subgroup, and its low expression in the external The Cancer Genome Atlas (TCGA) cohort may correlate with reduced overall survival in LUAD patients.

CONCLUSION

Our findings revealed distinct methylation patterns between tumor and pre-malignant samples, such as peri-tumor and normal tissues. Moreover, our study suggests that distinct clustering based on DNA methylation may indicate different prognoses in LUAD patients.

DNMT3L inhibits hepatocellular carcinoma progression through DNA methylation of CDO1: insights from big data to basic research

BACKGROUND

DNMT3L is a crucial DNA methylation regulatory factor, yet its function and mechanism in hepatocellular carcinoma (HCC) remain poorly understood. Bioinformatics-based big data analysis has increasingly gained significance in cancer research. Therefore, this study aims to elucidate the role of DNMT3L in HCC by integrating big data analysis with experimental validation.

METHODS

Dozens of HCC datasets were collected to analyze the expression of DNMT3L and its relationship with prognostic indicators, and were used for molecular regulatory relationship evaluation. The effects of DNMT3L on the malignant phenotypes of hepatoma cells were confirmed in vitro and in vivo. The regulatory mechanisms of DNMT3L were explored through MSP, western blot, and dual-luciferase assays.

RESULTS

DNMT3L was found to be downregulated in HCC tissues and associated with better prognosis. Overexpression of DNMT3L inhibits cell proliferation and metastasis. Additionally, CDO1 was identified as a target gene of DNMT3L and also exhibits anti-cancer effects. DNMT3L upregulates CDO1 expression by competitively inhibiting DNMT3A-mediated methylation of CDO1 promoter.

CONCLUSIONS

Our study revealed the role and epi-transcriptomic regulatory mechanism of DNMT3L in HCC, and underscored the essential role and applicability of big data analysis in elucidating complex biological processes.

Combination Analysis of PCDHGA12 and CDO1 DNA Methylation in Bronchial Washing Fluid for Lung Cancer Diagnosis

BACKGROUND

When suspicious lesions are observed on computer-tomography (CT), invasive tests are needed to confirm lung cancer. Compared with other procedures, bronchoscopy has fewer complications. However, the sensitivity of peripheral lesion through bronchoscopy including washing cytology is low. A new test with higher sensitivity through bronchoscopy is needed. In our previous study, DNA methylation of PCDHGA12 in bronchial washing cytology has a diagnostic value for lung cancer. In this study, combination of PCDHGA12 and CDO1 methylation obtained through bronchial washing cytology was evaluated as a diagnostic tool for lung cancer.

METHODS

A total of 187 patients who had suspicious lesions in CT were enrolled. PCDHGA12 methylation test, CDO1 methylation test, and cytological examination were performed using 3-plex LTE-qMSP test.

RESULTS

Sixty-two patients were diagnosed with benign diseases and 125 patients were diagnosed with lung cancer. The sensitivity of PCDHGA12 was 74.4% and the specificity of PCDHGA12 was 91.9% respectively. CDO1 methylation test had a sensitivity of 57.6% and a specificity of 96.8%. The combination of both PCDHGA12 methylation test and CDO1 methylation test showed a sensitivity of 77.6% and a specificity of 90.3%. The sensitivity of lung cancer diagnosis was increased by combining both PCDHGA12 and CDO1 methylation tests.

CONCLUSION

Checking DNA methylation of both PCDHGA12 and CDO1 genes using bronchial washing fluid can reduce the invasive procedure to diagnose lung cancer.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

The role of amino acid metabolism alterations in pancreatic cancer: From mechanism to application

The incidence of pancreatic cancer is increasing in both developed and developing Nations. In recent years, various research evidence suggested that reprogrammed metabolism may play a key role in pancreatic cancer tumorigenesis and development. Therefore, it has great potential as a diagnostic, prognostic and therapeutic target. Amino acid metabolism is deregulated in pancreatic cancer, and changes in amino acid metabolism can affect cancer cell status, systemic metabolism in malignant tumor patients and mistakenly involved in different biological processes including stemness, proliferation and growth, invasion and migration, redox state maintenance, autophagy, apoptosis and even tumor microenvironment interaction. Generally, the above effects are achieved through two pathways, energy metabolism and signal transduction. This review aims to highlight the current research progress on the abnormal alterations of amino acids metabolism in pancreatic cancer, how they affect tumorigenesis and development of pancreatic cancer and the application prospects of them as diagnostic, prognostic and therapeutic targets.

Employing machine learning using ferroptosis-related genes to construct a prognosis model for patients with osteosarcoma

Identifying effective biomarkers in osteosarcoma (OS) is important for predicting prognosis. We investigated the prognostic value of ferroptosis-related genes (FRGs) in OS. Transcriptome and clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus. FRGs were obtained from the ferroptosis database. Univariate COX regression and LASSO regression screening were performed and an FRG-based prognostic model was constructed, which was validated using the Gene Expression Omnibus cohort. The predictive power of the model was assessed via a subgroup analysis. A nomogram was constructed using clinical markers with independent prognostic significance and risk score results. The CIBERSORT algorithm was used to detect the correlation between prognostic genes and 22 tumor-infiltrating lymphocytes. The expression of prognostic genes in erastin-treated OS cell lines was verified via real-time PCR. Six prognostic FRGs (ACSL5, ATF4, CBS, CDO1, SCD, and SLC3A2) were obtained and used to construct the risk prognosis model. Subjects were divided into high- and low-risk groups. Prognosis was worse in the high-risk group, and the model had satisfactory prediction performance for patients younger than 18 years, males, females, and those with non-metastatic disease. Univariate COX regression analysis showed that metastasis and risk score were independent risk factors for patients with OS. Nomogram was built on independent prognostic factors with superior predictive power and patient benefit. There was a significant correlation between prognostic genes and tumor immunity. Six prognostic genes were differentially expressed in ferroptosis inducer-treated OS cell lines. The identified prognostic genes can regulate tumor growth and progression by affecting the tumor microenvironment.

Advances in biomarkers and techniques for pancreatic cancer diagnosis

Pancreatic cancer is the most lethal type of malignancy and is characterized by high invasiveness without severe symptoms. It is difficult to detect PC at an early stage because of the low diagnostic accuracy of existing routine methods, such as abdominal ultrasound, CT, MRI, and endoscopic ultrasound (EUS). Therefore, it is of value to develop new diagnostic techniques for early detection with high accuracy. In this review, we aim to highlight research progress on novel biomarkers, artificial intelligence, and nanomaterial applications on the diagnostic accuracy of pancreatic cancer.

Granulosa cell transcriptomic study reveals the differential regulation of lncRNAs and mRNAs related to follicle development in goat

Mammalian follicle development is a complex biological process regulated by several factors. More than 99% of the follicles in goat ovaries will be atresia and only a few will eventually mature and ovulate. To investigate the potential long noncoding RNAs (lncRNAs) that regulate the expression of genes associated with follicular dominance or atresia, RNA-seq was performed on dominant follicles (DFs) and subordinate follicles (SFs) of granulosa cells from goats at the first follicular wave. A total of 92 differentially expressed lncRNAs and 676 differentially expressed mRNAs were detected in both types of follicles. The qRT-PCR results were consistent with the transcriptome sequencing data. Kyoto Encyclopedia of Genes and Genomes analysis of the differentially expressed mRNAs revealed that LHR and LDLR are associated with follicle dominance and are involved in the ovarian steroidogenesis pathway. The co-located mRNAs CALM2 and PPP1CA were significantly enriched during oocyte meiosis and in the cAMP and oxytocin signaling pathways. The co-expressed mRNAs were significantly enriched in the estrogen signaling pathway and in ovarian steroidogenesis and progesterone-mediated oocyte maturation. A co-expression network of lncRNAs, target genes, and differentially expressed genes was constructed. Follicle development-related genes, such as LDLR, NOTCH1, and FGF12, were included. These findings expand the lncRNA catalog and provide a basis for further studies on the mechanism of regulating follicular development in goats.

Reliable Detection of Somatic Mutations for Pancreatic Cancer in Endoscopic Ultrasonography-Guided Fine Needle Aspirates with Next-Generation Sequencing: Implications from a Prospective Cohort Study

BACKGROUND OR PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA). However, the diagnostic adequacy of EUS-FNA is often limited by low cellularity leading to inconclusive results. We aimed to investigate the feasibility and added utility of targeted next-generation sequencing (NGS) on PDAC EUS-FNAs.

METHODS

EUS-FNAs were prospectively performed on 59 patients with suspected PDAC (2014-2017) at a high-volume center. FNAs were analyzed for the presence of somatic mutations using NGS to supplement cytopathologic evaluations and were compared to surgical specimens and circulating tumor DNA (ctDNA).

RESULTS

Fifty-nine patients with suspected PDAC were evaluated, and 52 were diagnosed with PDAC on EUS-FNA. Four of the remaining seven patients had inconclusive EUS-FNAs and were ultimately diagnosed with PDAC after surgical resection. Of these 56 cases of PDAC, 48 (85.7%) and 18 (32.1%) harbored a KRAS and/or TP53 mutation on FNA NGS, respectively. Particularly, in the four inconclusive FNA PDAC diagnoses (false negatives), half harbored KRAS mutations on FNA. No KRAS/TP53 mutation was found in remaining three non-PDAC cases. All EUS-FNA detected KRAS mutations were detected in 16 patients that underwent primary tumor NGS (100% concordance), while 75% KRAS concordance was found between FNA and ctDNA NGS.

CONCLUSION

Targeted NGS can reliably detect KRAS mutations from EUS-FNA samples and exhibits high KRAS mutational concordance with primary tumor and ctDNA. This suggests targeted NGS of EUS-FNA samples may enable preoperative ctDNA prognostication using digital droplet PCR and supplement diagnoses in patients with inconclusive EUS-FNA.

Analysis of Methylation-driven Genes in Pancreatic Ductal Adenocarcinoma for Predicting Prognosis

Purpose: Considerable variations in methylation profile have been found in various cancers to modulate tumorigenesis and affect prognosis. To provide a theoretical basis for early detection, prognosis evaluation and targeted treatment for patients with pancreatic ductal adenocarcinoma: PDAC, this study identified methylation-driven genes in PDAC and explored their prognostic performance.

Methods: The methylation, expression and clinical data of PDAC patients were extracted from TCGA database. Based on the β-mixture model of the MethylMix R package, the differential methylation status and connection between methylation and expression degree were examined to screen out methylation-driven genes in PDAC. COX analyses and lasso regressions were applied to construct a linear risk model based on methylation-driven genes. Univariate and multivariate analyses were performed to ensure the risk model was an independent prognostic factor. Joint survival analyses of methylation and gene expression were conducted to explore the prognostic value of component genes. The methylation sites in the key genes were also investigated.

Results: A total of 118 methylation-driven genes in PDAC were identified, and two genes (FOXI2, MYEOV) constituted the risk model whose AUC was 0.722 at one year of overall survival rate, displaying a better performance on survival prediction than other clinical features. Further survival analyses demonstrated that the expression of MYEOV and combined methylation and expression levels of the genes MYEOV and FOXI2 can be potential biomarkers for survival prediction and targets of drug manipulation of PDAC patients. Close relationships were discovered between two sites in MYEOV and one site in FOXI2 and the prognosis of PDAC patients.

Conclusion: Concentrating on DNA methylation, our study identified potential biomarkers and developed a reliable short-term predictive model for prognosis of PDAC patients.

Methylation-based Cell-free DNA Signature for Early Detection of Pancreatic Cancer

OBJECTIVES

The potential of DNA methylation alterations in early pancreatic cancer (PC) detection among pancreatic tissue cell-free DNA seems promising. This study investigates the diagnostic capacity of the 4-gene methylation biomarker panel, which included ADAMTS1, BNC1, LRFN5, and PXDN genes, in a case-control study.

METHODS

A genome-wide pharmacoepigenetic approach identified ADAMTS1, BNC1, LRFN5, and PXDN genes as putative targets. Tissue samples including stage I-IV PC (n = 44), pancreatic intraepithelial neoplasia (n = 15), intraductal papillary mucinous neoplasms (n = 24), and normal pancreas (n = 8), and cell-free DNA, which was acquired through methylation on beads technology from PC (n = 22) and control patients (n = 10), were included. The 2-∆ct was the outcome of interest and underwent receiver operating characteristic analysis to determine the diagnostic accuracy of the panel.

RESULTS

Receiver operating characteristic analysis revealed an area under the curve of 0.93 among ADAMTS1, 0.76 among BNC1, 0.75 among PXDN, and 0.69 among LRFN5 gene. The combination gene methylation panel (ADAMTS1, BNC1, LRFN5, and PXDN) had an area under the curve of 0.94, with a sensitivity of 100% and specificity of 90%.

CONCLUSIONS

This methylation-based biomarker panel had promising accuracy for PC detection and warranted further validation in prospective PC surveillance trials.

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.

Recent advances in blood-based and artificial intelligence-enhanced approaches for gastrointestinal cancer diagnosis

Gastrointestinal (GI) cancers are among the most common cancer types and leading causes of cancer-related deaths worldwide. There is a tremendous clinical need for effective early diagnosis for better healthcare of GI cancer patients. In this article, we provide a short overview of the recent advances in GI cancer diagnosis. In the first part, we discuss the applications of blood-based biomarkers, such as plasma circulating cell-free DNA, circulating tumor cells, extracellular vesicles, and circulating cell-free RNA, for cancer liquid biopsies. In the second part, we review the current trends of artificial intelligence (AI) for pathology image and tissue biopsy analysis for GI cancer, as well as deep learning-based approaches for purity assessment of tissue biopsies. We further provide our opinions on the future directions in blood-based and AI-enhanced approaches for GI cancer diagnosis, and we think that these fields will have more intensive integrations with clinical needs in the near future.

Epigenetic Alterations in Pancreatic Cancer Metastasis

Pancreatic cancer is the third leading cause of cancer-related deaths in the United States. Pancreatic ductal adenocarcinoma (PDA) is the most common (90%) and aggressive type of pancreatic cancer. Genomic analyses of PDA specimens have identified the recurrent genetic mutations that drive PDA initiation and progression. However, the underlying mechanisms that further drive PDA metastasis remain elusive. Despite many attempts, no recurrent genetic mutation driving PDA metastasis has been found, suggesting that PDA metastasis is driven by epigenetic fluctuations rather than genetic factors. Therefore, establishing epigenetic mechanisms of PDA metastasis would facilitate the development of successful therapeutic interventions. In this review, we provide a comprehensive overview on the role of epigenetic mechanisms in PDA as a critical contributor on PDA progression and metastasis. In particular, we explore the recent advancements elucidating the role of nucleosome remodeling, histone modification, and DNA methylation in the process of cancer metastasis.

Identification of methylation-driven genes prognosis signature and immune microenvironment in uterus corpus endometrial cancer

Background

Uterus corpus endometrial cancer (UCEC) is the main malignant tumor in gynecology, with a high degree of heterogeneity, especially in terms of prognosis and immunotherapy efficacy. DNA methylation is one of the most important epigenetic modifications. Studying DNA methylation can help predict the prognosis of cancer patients and provide help for clinical treatment. Our research aims to discover whether abnormal DNA methylation can predict the prognosis of UCEC and reflect the patient's tumor immune microenvironment.

Patients and methods

The clinical data, DNA methylation data, gene expression data and somatic mutation data of UCEC patients were all downloaded from the TCGA database. The MethylMix algorithm was used to integrate DNA methylation data and mRNA expression data. Univariate Cox regression analysis, Multivariate Cox regression analysis, and Lasso Cox regression analysis were used to determine prognostic DNA methylation-driven genes and to construct an independent prognostic index (MDS). ROC curve analysis and Kaplan–Meier survival curve analysis were used to evaluate the predictive ability of MDS. GSEA analysis was used to explore possible mechanisms that contribute to the heterogeneity of the prognosis of UCEC patients.

Results

3 differential methylation-driven genes (DMDGs) (PARVG, SYNE4 and CDO1) were considered as predictors of poor prognosis in UCEC. An independent prognostic index was finally established based on 3 DMDGs. From the results of ROC curve analysis and survival curve analysis, MDS showed excellent prognostic ability in TCGA-UCEC. A new nomogram based on MDS and other prognostic clinical indicators has also been successfully established. The C-index of the nomogram for OS prediction was 0.764 (95% CI = 0.702–0.826). GSEA analysis suggests that there were differences in immune-related pathways among patients with different prognosis. The abundance of M2 macrophages and M0 macrophages were significantly enhanced in the high-risk group while T cells CD8, Eosinophils and Neutrophils were markedly elevated in the low-risk group. Meanwhile, patients in the low-risk group had higher levels of immunosuppressant expression, higher tumor mutational burden and immunophenoscore (IPS) scores. Joint survival analysis revealed that 7 methylation-driven genes could be independent prognostic factors for overall survival for UCEC.

Conclusion

We have successfully established a risk model based on 3 DMDGs, which could accurately predict the prognosis of patients with UCEC and reflect the tumor immune microenvironment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02038-z.

Methylation patterns partition pancreatic cancer into distinct prognostic subtypes

In the initiation and progression of pancreatic cancer, DNA methylation plays a critical role. The present study attempts to explore specific prognosis subtypes based on DNA methylation data and develop an epigenetic signature to predict the overall survival (OS) of patients with pancreatic cancer.147 samples were included in the training cohort, whereas the validation cohort included 226 samples. The 298 OS-related methylation sites in the training cohort were selected for consensus clustering, and the authors identified three subtypes with a significant difference in prognosis. Cluster1 was associated with poor OS, low-grade disease and high lymph node involvement. In addition, we identified 33 specific methylation sites in Cluster1. Subsequently, we developed a robust qualitative signature consisting of 14 methylation sites to individually predict OS in the training cohort, and the predictive accuracy of this model was confirmed in the validation cohort. Functional enrichment analysis showed that the selected genes in the model were mainly enriched in known cancer-related pathways. Patients were divided into high- and low-risk groups by the model, and a significant difference in OS was observed between these groups. Classification based on the modeling of a specific DNA methylation site can reveal the heterogeneity of pancreatic cancer and provide guidance for clinicians in predicting the prognosis of pancreatic cancer and providing personalized treatment.

Prospective study to validate the clinical utility of DNA diagnosis of peritoneal fluid cytology test in gastric cancer

The clinical efficacy of DNA cytology test (CY) in gastric cancer (GC) has been retrospectively proposed using cancer‐specific methylation of cysteine dioxygenase type 1 (CDO1). We confirmed the clinical utility of DNA CY in a prospective cohort. Four hundred GC samples were prospectively collected for washing cytology (UMIN000026191), and detection of the DNA methylation of CDO1 was assessed by quantitative methylation‐specific PCR in the sediments. Endpoint was defined as the match rate between conventional CY1 and DNA CY1 (diagnostic sensitivity), and the DNA CY0 rate (diagnostic specificity) in pStage IA. DNA CY1 was detected in 45 cases (12.5%), while CY1 was seen in 31 cases (8.6%) of 361 chemotherapy‐naïve samples, where the sensitivity and specificity of the DNA CY in the peritoneal solutions were 74.2% and 96.5%, respectively. The DNA CY was positive for 3.5/0/4.9/11.4/58.8% in pStage IA/IB/II/III/IV, respectively (P < .01). In the multivariate analysis, DNA CY1 was independently correlated with pathological tumor depth (pT) (P = .0012), female gender (P = .0099), CY1 (P = .0135), P1 (P = .019), and carcinoembryonic antigen (CEA) (P = .036). The combination of DNA CY1 and P factor nearly all covered the potential peritoneal dissemination (P1 and/or CY1 and/or DNA CY1) (58/61:95.1%). DNA CY1 had a significantly poorer prognosis than DNA CY0 in GC patients (P < .0001). DNA CY1 detected by CDO1 promoter DNA methylation has a great value to detect minimal residual disease of the peritoneum in GC clinics, representing poor prognosis as a novel single DNA marker.

Predictive Significance of Promoter DNA Methylation of Cysteine Dioxygenase Type 1 (CDO1) in Metachronous Gastric Cancer

Purpose

Promoter DNA methylation of various genes has been associated with metachronous gastric cancer (MGC). The cancer-specific methylation gene, cysteine dioxygenase type 1 (CDO1), has been implicated in the occurrence of residual gastric cancer. We evaluated whether DNA methylation of CDO1 could be a predictive biomarker of MGC using specimens of MGC developing on scars after endoscopic submucosal dissection (ESD).

Materials and Methods

CDO1 methylation values (TaqMeth values) were compared between 33 patients with early gastric cancer (EGC) with no confirmed metachronous lesions at >3 years after ESD (non-MGC: nMGC group) and 11 patients with MGC developing on scars after ESD (MGCSE groups: EGC at the first ESD [MGCSE-1 group], EGC at the second ESD for treating MGC developing on scars after ESD [MGCSE-2 group]). Each EGC specimen was measured at five locations (at tumor [T] and the 4-point tumor-adjacent noncancerous mucosa [TAM]).

Results

In the nMGC group, the TaqMeth values for T were significantly higher than that for TAM (P=0.0006). In the MGCSE groups, TAM (MGCSE-1) exhibited significantly higher TaqMeth values than TAM (nMGC) (P<0.0001) and TAM (MGCSE-2) (P=0.0041), suggesting that TAM (MGCSE-1) exhibited CDO1 hypermethylation similar to T (P=0.3638). The area under the curve for discriminating the highest TaqMeth value of TAM (MGCSE-1) from that of TAM (nMGC) was 0.81, and using the cut-off value of 43.4, CDO1 hypermethylation effectively enriched the MGCSE groups (P<0.0001).

Conclusions

CDO1 hypermethylation has been implicated in the occurrence of MGC, suggesting its potential as a promising MGC predictor.

Identification of mRNAs and lncRNAs Involved in the Regulation of Follicle Development in Goat

Follicular development and maturation has a significant impact on goat reproductive performance, and it is therefore important to understand the molecular basis of this process. The importance of long non-coding RNAs (lncRNAs) in mammalian reproduction has been established, but little is known about the roles of lncRNAs in different follicular stages, especially in goats. In this study, RNA sequencing (RNA-seq) of large follicles (>10 mm) and small follicles (<3 mm) of Chuanzhong black goats was performed to investigate the regulatory mechanisms of lncRNAs and mRNAs in follicular development and maturation. A total of 8 differentially expressed lncRNAs (DElncRNAs) and 1,799 DEmRNAs were identified, and the majority of these were upregulated in small follicles. MRO, TC2N, CDO1, and NTRK1 were potentially associated with follicular maturation. KEGG pathway analysis showed that the DEmRNAs involved in ovarian steroidogenesis (BMP6, CYP11A1, CYP19A1, 3BHSD, STAR, LHCGR, and CYP51A1) and cAMP signaling play roles in regulating follicular maturation and developmental inhibition respectively. Five target pairs of DElncRNA-DEmRNA, namely, ENSCHIT00000001255-OTX2, ENSCHIT00000006005-PEG3, ENSCHIT00000009455-PIWIL3, ENSCHIT00000007977-POMP, and ENSCHIT00000000834-ACTR3 in co-expression analysis provide a clue in follicular development and maturation of lncRNA-mRNA interaction. Our findings provide a valuable resource for lncRNA studies, and could potentially provide a deeper understanding of the genetic basis and molecular mechanisms of goat follicular development and maturation.

Dipeptidyl peptidase like 6 promoter methylation is a potential prognostic biomarker for pancreatic ductal adenocarcinoma

BACKGROUND

Hypermethylation of gene promoters plays an important role in tumorigenesis. The present study aimed to identify and validate promoter methylation-driven genes (PMDGs) for pancreatic ductal adenocarcinoma (PDAC).

METHODS

Based on GSE49149 and the PDAC cohort of The Cancer Genome Atlas (TCGA), differential analyses of promoter methylation, correlation analysis, and Cox regression analysis were performed to identify PMDGs. The promoter methylation level was assessed by bisulfite sequencing polymerase chain reaction (BSP) in paired tumor and normal tissues of 72 PDAC patients. Kaplan-Meier survival analyses were performed to evaluate the clinical value of PMDGs.

RESULTS

In GSE49149, the β-value of the dipeptidyl peptidase like 6 (DPP6) promoter was significantly higher in tumor compared with normal samples (0.50 vs. 0.24, P<0.001). In the PDAC cohort of TCGA, the methylation level of the DPP6 promoter was negatively correlated with mRNA expression (r = -0.54, P<0.001). In a multivariate Cox regression analysis, hypermethylation of the DPP6 promoter was an independent risk factor for PDAC (hazard ratio (HR) = 543.91, P=0.002). The results of BSP revealed that the number of methylated CG sites in the DPP6 promoter was greater in tumor samples than in normal samples (7.43 vs. 2.78, P<0.001). The methylation level of the DPP6 promoter was moderately effective at distinguishing tumor from normal samples (area under ROC curve (AUC) = 0.74, P<0.001). Hypermethylation of the DPP6 promoter was associated with poor overall (HR = 3.61, P<0.001) and disease-free (HR = 2.01, P=0.016) survivals for PDAC patients.

CONCLUSION

These results indicate that DPP6 promoter methylation is a potential prognostic biomarker for PDAC.

Calcium Signaling Alterations Caused by Epigenetic Mechanisms in Pancreatic Cancer: From Early Markers to Prognostic Impact

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with high mortality rates. PDAC initiation and progression are promoted by genetic and epigenetic dysregulation. Here, we aimed to characterize the PDAC DNA methylome in search of novel altered pathways associated with tumor development. We examined the genome-wide DNA methylation profile of PDAC in an exploratory cohort including the comparative analyses of tumoral and non-tumoral pancreatic tissues (PT). Pathway enrichment analysis was used to choose differentially methylated (DM) CpGs with potential biological relevance. Additional samples were used in a validation cohort. DNA methylation impact on gene expression and its association with overall survival (OS) was investigated from PDAC TCGA (The Cancer Genome Atlas) data. Pathway analysis revealed DM genes in the calcium signaling pathway that is linked to the key pathways in pancreatic carcinogenesis. DNA methylation was frequently correlated with expression, and a subgroup of calcium signaling genes was associated with OS, reinforcing its probable phenotypic effect. Cluster analysis of PT samples revealed that some of the methylation alterations observed in the Calcium signaling pathway seemed to occur early in the carcinogenesis process, a finding that may open new insights about PDAC tumor biology.

The potential of liquid biopsies in gastrointestinal cancer

BACKGROUND

Liquid biopsy is a novel approach for cancer diagnosis, the value of which in human gastrointestinal (GI) cancer has been confirmed by the previous studies. This article summarized the recent advances in liquid biopsy with a focus on novel technologies and the use of it in the screening, monitoring, and treatment of human GI cancer.

CONTENT

The concept of liquid biopsy was first used to define the detection of circulating tumor cells (CTCs) in cancer patients, and has been expanded to other biomarkers in blood and body fluids, such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs) and circulating tumor RNA. If analyzed with proper and advanced techniques like next generation sequencing (NGS) or proteomics, liquid biopsies can open an enormous array of potential biomarkers. The amount changes of target biomarkers and the mutation of genetic materials provide quantitative and qualitative information, which can be utilized clinically for cancer diagnosis and disease monitoring.

SUMMARY

As a highly efficient, minimally invasive, and cost-effective approach to diagnose and evaluate prognosis of GI cancer, liquid biopsy has lots of advantages over traditional biopsy and is promising in future clinical utility. If the challenges are overcome in the near future, liquid biopsy will become a widely available and dependable option.

Promoter DNA Hypermethylation of the Cysteine Dioxygenase 1 (CDO1) Gene in Intraductal Papillary Mucinous Neoplasm (IPMN)

BACKGROUND

Intraductal papillary mucinous neoplasm (IPMN) involves adenoma (IPMA), a precancerous lesion, cancer (IPMC) including high-grade dysplasia (HGD), and invasive carcinoma (IC). DNA markers of IPMN are required for detection of invasive disease, and cysteine dioxygenase 1 (CDO1) gene promoter hypermethylation is a potential candidate. However, it has never been investigated in the context of IPMN.

PATIENTS AND METHODS

A total of 107 IPMN tumor tissues, including 41 IPMC and 66 IPMA, were studied. CDO1 promoter methylation was quantified using TaqMan quantitative methylation-specific polymerase chain reaction (qMSP) in patients with IPMN and other pancreatic cystic disorders after pancreatectomy.

RESULTS

The methylation values (TaqMeth Vs) of CDO1 increased when noncancerous pancreas tissues were compared with IPMA and HGD (p < 0.0001). Among IPMC, the TaqMeth Vs in IC were not significantly higher than in HGD. The TaqMeth Vs of the solid tumors were higher than those of the cystic tumors (p = 0.0016), which were in turn higher than the corresponding noncancerous tissues (p < 0.0001). Prognostic analysis revealed that high TaqMeth Vs (≥ 14.1) resulted in a poorer prognosis than low TaqMeth Vs (< 14.1) (p < 0.0001). In other pancreatic cystic diseases, only malignant mucinous cystic neoplasm showed DNA hypermethylation of its promoter. A pilot study in pancreatic juice confirmed methylation in all IPMN samples but not in benign pancreatic diseases (p = 0.0277).

CONCLUSIONS

CDO1 promoter hypermethylation is extremely specific to IPMN and may accumulate with IPMN tumor progression during the adenoma-carcinoma sequence. It might be a promising candidate as a diagnostic marker of pancreatic cystic diseases.

Circadian Genes as Therapeutic Targets in Pancreatic Cancer

Pancreatic cancer is one of the most lethal cancers worldwide due to its symptoms, early metastasis, and chemoresistance. Thus, the mechanisms contributing to pancreatic cancer progression require further exploration. Circadian rhythms are the daily oscillations of multiple biological processes regulated by an endogenous clock. Several evidences suggest that the circadian clock may play an important role in the cell cycle, cell proliferation and apoptosis. In addition, timing of chemotherapy or radiation treatment can influence the efficacy and toxicity treatment. Here, we revisit the studies on circadian clock as an emerging target for therapy in pancreatic cancer. We highlight those potential circadian genes regulators that are commonly affected in pancreatic cancer according to most recent reports.

Diagnostic potential of hypermethylation of the cysteine dioxygenase 1 gene (CDO1) promoter DNA in pancreatic cancer

DNA markers for pancreatic ductal adenocarcinoma (PDAC) are urgently needed for detection of minimally invasive disease. The epigenetic relevance of the cysteine dioxygenase 1 gene (CDO1) has been never investigated in PDAC. Three studies, including cellular experiments, tissue validation, and pilot testing for pancreatic cytology, were carried out. Promoter DNA methylation value (MV) of CDO1 was quantified by quantitative methylation‐specific PCR. CDO1 expression was consistent with its promoter DNA methylation in 7 PDAC cell lines. In 160 retrospectively collected primary PDAC tumor tissues, MV was significantly higher compared to the corresponding noncancerous pancreas (area under the receiver operating characteristic curve [AUC] = 0.97, P < .0001), and CDO1 hypermethylation was highly specific to PDAC tumor tissues. CDO1 hypermethylation group (MV over 19) was significantly associated with diverse prognostic factors in PDAC. Surprisingly, it was significantly higher in prospectively collected PDAC cytology samples (n = 37), including both pancreatic juice (n = 12) and endoscopic ultrasound‐fine needle aspiration (EUS‐FNA) cytology (n = 25) compared to pancreatic benign diseases (AUC = 0.96, P < .0001). Detection of PDAC was confirmed by DNA testing in 35 of 37 patients (95% sensitivity); thus, it was more sensitive than cytology (33%) or EUS‐FNA cytology (88%). Promoter DNA methylation of CDO1 is extremely specific for PDAC tumors, and accumulates with PDAC tumor progression. It could be a definitive diagnostic marker of PDAC in pancreatic juice or EUS‐FNA cytology.