Detection of early stage pancreatic cancer using 5-hydroxymethylcytosine signatures in circulating cell free DNA

Construction of a glycosylation-mediated fluorescent biosensor for label-free measurement of site-specific 5-hydroxymethylcytosine in cancer cells with zero background signal

BACKGROUND

5-hydroxymethylcytosine (5hmC) as an epigenetic modification can regulate gene expression, and its abnormal level is related with various tumor invasiveness and poor prognosis. Nevertheless, the current methods for 5hmC assay usually involve expensive instruments/antibodies, radioactive risk, high background, laborious bisulfite treatment procedures, and non-specific/long amplification time.

RESULTS

We develop a glycosylation-mediated fluorescent biosensor based on helicase-dependent amplification (HDA) for label-free detection of site-specific 5hmC in cancer cells with zero background signal. The glycosylated 5hmC-DNA (5ghmC) catalyzed by β-glucosyltransferase (β-GT) can be cleaved by AbaSI restriction endonuclease to generate two dsDNA fragments with sticky ends. The resultant dsDNA fragments are complementary to the biotinylated probes and ligated by DNA ligases, followed by being captured by magnetic beads. After magnetic separation, the eluted ligation products act as the templates to initiate HDA reaction, generating abundant double-stranded DNA (dsDNA) products within 20 min. The dsDNA products are measured in a label-free manner with SYBR Green I as an indicator. This biosensor can measure 5hmC with a detection limit of 2.75 fM and a wide linear range from 1 × 10-14 to 1 × 10-8 M, and it can discriminate as low as 0.001% 5hmC level in complex mixture. Moreover, this biosensor can measure site-specific 5hmC in cancer cells, and distinguish tumor cells from normal cells.

SIGNIFICANCE

This biosensor can achieve a zero-background signal without the need of either 5hmC specific antibody or bisulfite treatment, and it holds potential applications in biological research and disease diagnosis.

The role of biomarkers in the early detection of pancreatic cancer

Pancreatic surveillance can detect early-stage pancreatic cancer and achieve long-term survival, but currently involves annual endoscopic ultrasound and MRI/MRCP, and is recommended only for individuals who meet familial/genetic risk criteria. To improve upon current approaches to pancreatic cancer early detection and to expand access, more accurate, inexpensive, and safe biomarkers are needed, but finding them has remained elusive. Newer approaches to early detection, such as using gene tests to personalize biomarker interpretation, and the increasing application of artificial intelligence approaches to integrate complex biomarker data, offer promise that clinically useful biomarkers for early pancreatic cancer detection are on the horizon.

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma

BACKGROUND

One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma (PDAC) is that most patients are usually diagnosed at late stages. There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages.

AIM

To evaluate the potential value of radiomics analysis in the differentiation of early-stage PDAC from late-stage PDAC.

METHODS

A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography (CT) within 30 d prior to surgery were included in the study. Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system. Radiomics features were extracted from the region of interest (ROI) for each patient using Analysis Kit software. The most important and predictive radiomics features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy maximum relevance (MRMR) method. Random forest (RF) method was used to construct the radiomics model, and 10-times leave group out cross-validation (LGOCV) method was used to validate the robustness and reproducibility of the model.

RESULTS

A total of 792 radiomics features (396 from late arterial phase and 396 from portal venous phase) were extracted from the ROI for each patient using Analysis Kit software. Nine most important and predictive features were selected using Mann-Whitney U test, univariate logistic regression analysis, and MRMR method. RF method was used to construct the radiomics model with the nine most predictive radiomics features, which showed a high discriminative ability with 97.7% accuracy, 97.6% sensitivity, 97.8% specificity, 98.4% positive predictive value, and 96.8% negative predictive value. The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models.

CONCLUSION

The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

Role of ONECUT family transcription factors in cancer and other diseases

Members of ONECUT transcription factor play an essential role in several developmental processes, however, the atypical expression of ONECUT proteins lead to numerous diseases, including cancer. ONECUT family proteins promote cell proliferation, progression, invasion, metastasis, angiogenesis, and stemness. This family of proteins interacts with other proteins such as KLF4, TGF-β, VEGFA, PRC2, SMAD3 and alters their expression involved in the regulation of various signaling pathways including Jak/Stat3, Akt/Erk, TGF-β, Smad2/3, and HIF-1α. Furthermore, ONECUT proteins are proposed as predictive biomarkers for pancreatic and gastric cancers. The present review summarizes the involvement of ONECUT family proteins in the development and progression of various human cancers and other diseases.

Genome-wide 5-hydroxymethylcytosines in circulating cell-free DNA as noninvasive diagnostic markers for gastric cancer

BACKGROUND

5-Hydroxymethylcytosine-enriched gene profiles and regions show tissue-specific and tumor specific. There is a potential value to explore cell-free DNA 5-hydroxymethylcytosine feature biomarkers for early gastric cancer detection.

METHODS

A matched case‒control study design with 50 gastric cancer patients and 50 controls was performed to sequence the different 5-hydroxymethylcytosine modification features of cell free DNA. Significantly differential 5-hydroxymethylcytosine modification genes were identified to construct a gastric cancer diagnostic model. Data set from GEO was used as an external testing set to test the robustness of the diagnostic model.

RESULTS

Accounting for more than 90% of 5-hydroxymethylcytosine peaks were distributed in the gene body in both the gastric cancer and control groups. The diagnostic model was developed based on five different 5-hydroxymethylcytosine modification genes, FBXL7, PDE3A, TPO, SNTG2 and STXBP5. The model could effectively distinguish gastric cancer patients from controls in the training (AUC = 0.95, sensitivity = 88.6%, specificity = 94.3%), validation (AUC = 0.87, sensitivity = 73.3%, specificity = 93.3%) and testing (AUC = 0.90, sensitivity = 81.9%, specificity = 90.2%) sets. The risk scores of the controls from the model were significantly lower than those of gastric cancer patients in both our own data (P < 0.001) and GEO external testing data (P < 0.001), and no significant difference between different TNM stage patients (P = 0.09 and 0.66). Furthermore, there was no significant difference between the healthy control and benign gastric disease patients in the testing set from GEO (P = 0.10).

CONCLUSIONS

The characteristics of 5-hydroxymethylcytosine in cell free DNA are specific to gastric cancer patients, and the diagnostic model constructed by five genes' 5-hydroxymethylcytosine features could effectively identify gastric cancer patients.

Protein biomarkers and alternatively methylated cell-free DNA detect early stage pancreatic cancer

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed at an advanced stage. Liquid biopsy approaches may facilitate detection of early stage PDAC when curative treatments can be employed.

DESIGN

To assess circulating marker discrimination in training, testing and validation patient cohorts (total n=426 patients), plasma markers were measured among PDAC cases and patients with chronic pancreatitis, colorectal cancer (CRC), and healthy controls. Using CA19-9 as an anchor marker, measurements were made of two protein markers (TIMP1, LRG1) and cell-free DNA (cfDNA) pancreas-specific methylation at 9 loci encompassing 61 CpG sites.

RESULTS

Comparative methylome analysis identified nine loci that were differentially methylated in exocrine pancreas DNA. In the training set (n=124 patients), cfDNA methylation markers distinguished PDAC from healthy and CRC controls. In the testing set of 86 early stage PDAC and 86 matched healthy controls, CA19-9 had an area under the receiver operating characteristic curve (AUC) of 0.88 (95% CI 0.83 to 0.94), which was increased by adding TIMP1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.06), LRG1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02) or exocrine pancreas-specific cfDNA methylation markers at nine loci (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02). In the validation set of 40 early stage PDAC and 40 matched healthy controls, a combined panel including CA19-9, TIMP1 and a 9-loci cfDNA methylation panel had greater discrimination (AUC 0.86, 95% CI 0.77 to 0.95) than CA19-9 alone (AUC 0.82; 95% CI 0.72 to 0.92).

CONCLUSION

A combined panel of circulating markers including proteins and methylated cfDNA increased discrimination compared with CA19-9 alone for early stage PDAC.

Deep5hmC: Predicting genome-wide 5-Hydroxymethylcytosine landscape via a multimodal deep learning model

5-hydroxymethylcytosine (5hmC), a critical epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Using tissue-specific 5hmC sequencing data, we introduce Deep5hmC, a multimodal deep learning framework that integrates both the DNA sequence and the histone modification information to predict genome-wide 5hmC modification. The multimodal design of Deep5hmC demonstrates remarkable improvement in predicting both qualitative and quantitative 5hmC modification compared to unimodal versions of Deep5hmC and state-of-the-art machine learning methods. This improvement is demonstrated through benchmarking on a comprehensive set of 5hmC sequencing data collected at four time points during forebrain organoid development and across 17 human tissues. Notably, Deep5hmC showcases its practical utility by accurately predicting gene expression and identifying differentially hydroxymethylated regions in a case-control study of Alzheimer's disease.

5-Hydroxymethylcytosine: the many faces of the sixth base of mammalian DNA

Epigenetic phenomena play a central role in cell regulatory processes and are important factors for understanding complex human disease. One of the best understood epigenetic mechanisms is DNA methylation. In the mammalian genome, cytosines (C) in CpG dinucleotides were long known to undergo methylation at the 5-position of the pyrimidine ring (mC). Later it was found that mC can be oxidized to 5-hydroxymethylcytosine (hmC) or even further to 5-formylcytosine (fC) and to 5-carboxylcytosine (caC) by the action of 2-oxoglutarate-dependent dioxygenases of the TET family. These findings unveiled a long elusive mechanism of active DNA demethylation and bolstered a wave of studies in the area of epigenetic regulation in mammals. This review is dedicated to critical assessment of recent data on biochemical and chemical aspects of the formation and conversion of hmC in DNA, analytical techniques used for detection and mapping of this nucleobase in mammalian genomes as well as epigenetic roles of hmC in DNA replication, transcription, cell differentiation and human disease.

Cell-Free DNA 5-Hydroxymethylcytosine Signatures for Lung Cancer Prognosis

Accurate prognostic markers are essential for guiding effective lung cancer treatment strategies. The level of 5-hydroxymethylcytosine (5hmC) in tissue is independently associated with overall survival (OS) in lung cancer patients. We explored the prognostic value of cell-free DNA (cfDNA) 5hmC through genome-wide analysis of 5hmC in plasma samples from 97 lung cancer patients. In both training and validation sets, we discovered a cfDNA 5hmC signature significantly associated with OS in lung cancer patients. We built a 5hmC prognostic model and calculated the weighted predictive scores (wp-score) for each sample. Low wp-scores were significantly associated with longer OS compared to high wp-scores in the training [median 22.9 versus 8.2 months; p = 1.30 × 10-10; hazard ratio (HR) 0.04; 95% confidence interval (CI), 0.00-0.16] and validation (median 18.8 versus 5.2 months; p = 0.00059; HR 0.22; 95% CI: 0.09-0.57) sets. The 5hmC signature independently predicted prognosis and outperformed age, sex, smoking, and TNM stage for predicting lung cancer outcomes. Our findings reveal critical genes and signaling pathways with aberrant 5hmC levels, enhancing our understanding of lung cancer pathophysiology. The study underscores the potential of cfDNA 5hmC as a superior prognostic tool for guiding more personalized therapeutic strategies for lung cancer patients.

Plasma cell-free DNA hydroxymethylation profiling reveals anti-PD-1 treatment response and resistance biology in non-small cell lung cancer

BACKGROUND

Treatment with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) can yield durable antitumor responses, yet not all patients respond to ICIs. Current approaches to select patients who may benefit from anti-PD-1 treatment are insufficient. 5-hydroxymethylation (5hmC) analysis of plasma-derived cell-free DNA (cfDNA) presents a novel non-invasive approach for identification of therapy response biomarkers which can tackle challenges associated with tumor biopsies such as tumor heterogeneity and serial sample collection.

METHODS

151 blood samples were collected from 31 patients with non-small cell lung cancer (NSCLC) before therapy started and at multiple time points while on therapy. Blood samples were processed to obtain plasma-derived cfDNA, followed by enrichment of 5hmC-containing cfDNA fragments through biotinylation via a two-step chemistry and binding to streptavidin coated beads. 5hmC-enriched cfDNA and whole genome libraries were prepared in parallel and sequenced to obtain whole hydroxymethylome and whole genome plasma profiles, respectively.

RESULTS

Comparison of on-treatment time point to matched pretreatment samples from same patients revealed that anti-PD-1 treatment induced distinct changes in plasma cfDNA 5hmC profiles of responding patients, as judged by Response evaluation criteria in solid tumors, relative to non-responders. In responders, 5hmC accumulated over genes involved in immune activation such as inteferon (IFN)-γ and IFN-α response, inflammatory response and tumor necrosis factor (TNF)-α signaling, whereas in non-responders 5hmC increased over epithelial to mesenchymal transition genes. Molecular response to anti-PD-1 treatment, as measured by 5hmC changes in plasma cfDNA profiles were observed early on, starting with the first cycle of treatment. Comparison of pretreatment plasma samples revealed that anti-PD-1 treatment response and resistance associated genes can be captured by 5hmC profiling of plasma-derived cfDNA. Furthermore, 5hmC profiling of pretreatment plasma samples was able to distinguish responders from non-responders using T cell-inflamed gene expression profile, which was previously identified by tissue RNA analysis.

CONCLUSIONS

These results demonstrate that 5hmC profiling can identify response and resistance associated biological pathways in plasma-derived cfDNA, offering a novel approach for non-invasive prediction and monitoring of immunotherapy response in NSCLC.

Plasma cell-free DNA 5-hydroxymethylcytosine and whole-genome sequencing signatures for early detection of esophageal cancer

Esophageal cancer is a highly incidence and deadly disease with a poor prognosis, especially in developing countries. Owing to the lack of specific symptoms and early diagnostic biomarkers, most patients are diagnosed with advanced disease, leading to a 5-year survival rate of less than 15%. Early (n = 50) and middle-advanced (n = 50) esophageal squamous cell carcinoma (ESCC) patients, as well as 71 healthy individuals, underwent 5-hydroxymethylcytosine (5hmC) sequencing on their plasma cell-free DNA (cfDNA). A Northern Chinese cohort of cfDNA 5hmC dataset of 150 ESCC patients and 183 healthy individuals were downloaded for validation. A diagnostic model was developed using cfDNA 5hmC signatures and then improved by low-pass whole genome sequencing (WGS) features of cfDNA. Conserved cfDNA 5hmC modification motifs were observed in the two independent ESCC cohorts. The diagnostic model with 5hmC features achieved an AUC of 0.810 and 0.862 in the Southern and Northern cohorts, respectively, with sensitivities of 69.3-74.3% and specificities of 82.4-90.7%. The performance was well maintained in Stage I to Stage IV, with accuracy of 70-100%, but low in Stage 0, 33.3%. Low-pass WGS of cfDNA improved the AUC to 0.934 with a sensitivity of 82.4%, a specificity of 88.2%, and an accuracy of 84.3%, particularly significantly in Stage 0, with an accuracy up to 80%. 5hmC and WGS could efficiently differentiate very early ESCC from healthy individuals. These findings imply a non-invasive and convenient method for ESCC detection when clinical treatments are available and may eventually prolong survival.

Genome-wide and panel-based cell-free DNA characterization of patients with resectable esophageal adenocarcinoma

Circulating tumor DNA (ctDNA) holds promise in resectable esophageal adenocarcinoma (EAC) to predict patient outcome but is not yet sensitive enough to be clinically applicable. Our aim was to combine ctDNA mutation data with shallow whole-genome sequencing (sWGS)-derived copy number tumor fraction estimates (ichorCNA) to improve pathological response and survival prediction in EAC. In total, 111 stage II/III EAC patients with baseline (n = 111), post-neoadjuvant chemoradiotherapy (nCRT) (n = 68), and pre-surgery (n = 92) plasma samples were used for ctDNA characterization. sWGS (<5× coverage) was performed on all time-point samples, and copy number aberrations were estimated using ichorCNA. Baseline and pre-surgery samples were sequenced using a custom amplicon panel for mutation detection. Detection of baseline ctDNA was successful in 44.3% of patients by amplicon sequencing and 10.5% by ichorCNA. Combining both, ctDNA could be detected in 50.5% of patients. Baseline ctDNA positivity was related to higher T stage (cT3, 4) (p = 0.017). There was no relationship between pathological response and baseline ctDNA positivity. However, baseline ctDNA metrics (variant allele frequency > 1% or ichorCNA > 3%) were associated with a high risk of disease progression [HR = 2.23 (95% CI 1.22-4.07), p = 0.007]. The non-clearance of a baseline variant or ichorCNA > 3% in pre-surgery samples was related to early progression [HR = 4.58 (95% CI 2.22-9.46), p < 0.001]. Multi-signal analysis improves detection of ctDNA and can be used for prognostication of resectable EAC patients. Future studies should explore the potential of multi-modality sequencing for risk stratification and treatment adaptation based on ctDNA results. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Disease Diagnosis Based on Nucleic Acid Modifications

Nucleic acid modifications include a wide range of epigenetic and epitranscriptomic factors and impact a wide range of nucleic acids due to their profound influence on biological inheritance, growth, and metabolism. The recently developed methods of mapping and characterizing these modifications have promoted their discovery as well as large-scale studies in eukaryotes, especially in humans. Because of these pioneering strategies, nucleic acid modifications have been shown to have a great impact on human disorders such as cancer. Therefore, whether nucleic acid modifications could become a new type of biomarker remains an open question. In this review, we briefly look back at classical nucleic acid modifications and then focus on the progress made in investigating these modifications as diagnostic biomarkers in clinical therapy and present our perspective on their development prospects.

Coagulation parameters for the differential diagnosis of pancreatic cancer in the early stage: a retrospective study

BACKGROUND

In recent years, conventional coagulation (CC) and thromboelastography (TEG) parameters have been reported to be closely related to the progression of pancreatic cancer (PC). However, the potential utility of these parameters in differentiating benign and malignant pancreatic diseases is still unclear.

OBJECTIVES

A retrospective study was conducted to evaluate the efficacy of coagulation parameters in differentiating pancreatic cancer/early stage pancreatic cancer (EPC, TNM stages I and II) from benign control conditions, and to further explore whether coagulation parameters could improve the differential value of CA199.

METHODS

Receiver operating characteristic (ROC) curves and logistic regression analysis were used to identify the diagnostic value of each coagulation parameter or combination of parameters.

RESULTS

Compared with benign pancreatic disease (BPD), patients with pancreatic malignant tumors had significant coagulation disorders, specifically manifested as abnormal increases or decreases in several CC and TEG parameters (such as activated partial thromboplastin time (APTT), fibrinogen (FIB), D-dimer (DD2), K time, R time, Angle, maximum amplitude (MA), coagulation index (CI), and Ly30). In the training group, ROC curve showed that FIB, DD2, Angle, MA, and CI had favorable efficacy at differentiating PC or EPC from BPD (for PC, AUC = 0.737, 0.654, 0.627, 0.602, 0.648; for EPC, AUC = 0.723, 0.635, 0.630, 0.614, 0.648). However, several combined diagnostic indicators based on FIB, DD2 and CI failed to outperform the individual coagulation indexes in diagnostic efficiency. Combinations of certain coagulation indexes with CA199 outperformed CA199 alone at identifying PC or EPC, especially FIB + CA199 (for PC, AUC = 0.904; for EPC, AUC = 0.905), FIB + DD2 + CA199 (for PC, AUC = 0.902; for EPC, AUC = 0.900), FIB + CI + CA199 (for PC, AUC = 0.906; for EPC, AUC = 0.906), and FIB + DD2 + CI + CA199 (for PC, AUC = 0.905; for EPC, AUC = 0.900). The results from a validation set also confirmed that these combinations have advantageous diagnostic value for PC and EPC.

CONCLUSIONS

A significant hypercoagulable state was common in PC. Some CC and TEG parameters are valuable in the differential diagnosis of benign and malignant pancreatic diseases. In addition, coagulation indexes combined with CA199 can further enhance the differential diagnosis efficacy of CA199 in PC and EPC.

5-hydroxymethylcytosine sequencing in plasma cell-free DNA identifies unique epigenomic features in prostate cancer patients resistant to androgen deprivation therapy

Background

Currently there are no biomarkers to identify resistance to androgen-deprivation therapy (ADT) in men with hormone-naive prostate cancer. 5-hydroxymethylcytosines (5hmC) in the gene body are associated with gene activation and are critical for epigenomic regulation of cancer progression.

Objective

To evaluate whether 5hmC signature in cell-free DNA (cfDNA) predicts early ADT resistance.

Design Setting and Participants

Serial plasma samples from 55 prostate cancer patients receiving ADT were collected at three timepoints including baseline (prior to initiating ADT, N=55), 3-month (after initiating ADT, N=55), and disease progression (N=15) within 24 months or 24-month if no progression was detected (N=14). 20 of the 55 patients showed disease progression during the 24-month follow-up. The remaining 35 patients showed no progression in the same follow-up period.

Outcome Measurements and Statistical Analysis

cfDNA (5-10ng) was used for selective chemical labeling (hMe-Seal) sequencing to map 5hmC abundance across the genome. Read counts in gene bodies were normalized with DESeq2. Differential methylation and gene set enrichment analyses were performed to identify the 5hmC-enriched genes and biological processes that were associated with disease progression. Kaplan-Meir analysis was utilized to determine the association of 5hmC signatures with progression-free survival.

Results and Limitations

5hmC-sequencing generated an average of 18.6 (range 6.03 to 42.43) million reads per sample with 98% (95-99%) mappable rate. Baseline sample comparisons identified significant 5hmC difference in 1,642 of 23,433 genes between 20 patients with progression and 35 patients without progression (false discovery rate, FDR<0.1). Patients with progression showed significant enrichments in multiple hallmark gene sets with androgen responses as the top enriched gene set (FDR=1.19E-13). Interestingly, this enrichment was driven by a subgroup of patients with disease progression featuring a significant 5hmC hypermethylation of the gene sets involving AR, FOXA1 and GRHL2. To quantify overall activities of these gene sets, we developed a gene set activity score algorithm using a mean value of log2 ratios of gene read counts in an entire gene set. We found that the activity scores in these gene sets were significantly higher in this subgroup of patients with progression than in the remaining patients regardless of the progression status. Furthermore, the high activity scores in these gene sets were associated with poor progression-free survival (p <0.05). Longitudinal analysis showed that activity scores in this subgroup with progression were significantly reduced after 3-month ADT but returned to high levels when the disease was progressed.

Conclusions

5hmC-sequencing in cfDNA identified a subgroup of prostate cancer patients with preexisting activation (5hmC hypermethylation) of gene sets involving AR, FOXA1 and GRHL2 before initiating ADT. Activity scores in these gene sets may serve as sensitive biomarkers to determine treatment resistance, monitor disease progression and potentially identify patients who would benefit from upfront treatment intensification. More studies are needed to validate this initial finding.

Patient summary

There are no clinical tests to identify prostate cancer patients who will develop early resistance to androgen deprivation therapy within 24 months. In this study, we evaluated cell-free DNA epigenomic modification in blood and identified significant enrichment of 5-hydroxymethylation in androgen response genes in a subgroup of patients with treatment resistance. High level 5-hydroxylmethylation in these genes may serve as a discriminative biomarker to diagnose patients who are likely to experience early failure during androgen deprivation therapy.

The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer

Cell-free DNA (cfDNA) concentrations from patients with cancer are often elevated compared with those of healthy controls, but the sources of this extra cfDNA have never been determined. To address this issue, we assessed cfDNA methylation patterns in 178 patients with cancers of the colon, pancreas, lung, or ovary and 64 patients without cancer. Eighty-three of these individuals had cfDNA concentrations much greater than those generally observed in healthy subjects. The major contributor of cfDNA in all samples was leukocytes, accounting for ∼76% of cfDNA, with neutrophils predominating. This was true regardless of whether the samples were derived from patients with cancer or the total plasma cfDNA concentration. High levels of cfDNA observed in patients with cancer did not come from either neoplastic cells or surrounding normal epithelial cells from the tumor's tissue of origin. These data suggest that cancers may have a systemic effect on cell turnover or DNA clearance.

SIGNIFICANCE

The origin of excess cfDNA in patients with cancer is unknown. Using cfDNA methylation patterns, we determined that neither the tumor nor the surrounding normal tissue contributes this excess cfDNA-rather it comes from leukocytes. This finding suggests that cancers have a systemic impact on cell turnover or DNA clearance. See related commentary by Thierry and Pisareva, p. 2122. This article is featured in Selected Articles from This Issue, p. 2109.

Simultaneous sequencing of genetic and epigenetic bases in DNA

DNA comprises molecular information stored in genetic and epigenetic bases, both of which are vital to our understanding of biology. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases fail to capture common C-to-T mutations or distinguish 5-methylcytosine from 5-hydroxymethylcytosine. We present a single base-resolution sequencing methodology that sequences complete genetics and the two most common cytosine modifications in a single workflow. DNA is copied and bases are enzymatically converted. Coupled decoding of bases across the original and copy strand provides a phased digital readout. Methods are demonstrated on human genomic DNA and cell-free DNA from a blood sample of a patient with cancer. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. Simultaneous, phased reading of genetic and epigenetic bases provides a more complete picture of the information stored in genomes and has applications throughout biomedicine.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Deoxyribonucleic acid methylation driven aberrations in pancreatic cancer-related pathways

Pancreatic cancer (PanCa) presents a catastrophic disease with poor overall survival at advanced stages, with immediate requirement of new and effective treatment options. Besides genetic mutations, epigenetic dysregulation of signaling pathway-associated enriched genes are considered as novel therapeutic target. Mechanisms beneath the deoxyribonucleic acid methylation and its utility in developing of epi-drugs in PanCa are under trails. Combinations of epigenetic medicines with conventional cytotoxic treatments or targeted therapy are promising options to improving the dismal response and survival rate of PanCa patients. Recent studies have identified potentially valid pathways that support the prediction that future PanCa clinical trials will include vigorous testing of epigenomic therapies. Epigenetics thus promises to generate a significant amount of new knowledge of biological and medical importance. Our review could identify various components of epigenetic mechanisms known to be involved in the initiation and development of pancreatic ductal adenocarcinoma and related precancerous lesions, and novel pharmacological strategies that target these components could potentially lead to breakthroughs. We aim to highlight the possibilities that exist and the potential therapeutic interventions.

Using cfDNA and ctDNA as Oncologic Markers: A Path to Clinical Validation

The detection of circulating tumor DNA (ctDNA) in liquid biopsy samples as an oncological marker is being used in clinical trials at every step of clinical management. As ctDNA-based liquid biopsy kits are developed and used in clinics, companies work towards increased convenience, accuracy, and cost over solid biopsies and other oncological markers. The technology used to differentiate ctDNA and cell-free DNA (cfDNA) continues to improve with new tests and methodologies being able to detect down to mutant allele frequencies of 0.001% or 1/100,000 copies. Recognizing this development in technology, the FDA has recently given pre-market approval and breakthrough device designations to multiple companies. The purpose of this review is to look at the utility of measuring total cfDNA, techniques used to differentiate ctDNA from cfDNA, and the utility of different ctDNA-based liquid biopsy kits using relevant articles from PubMed, clinicaltrials.gov, FDA approvals, and company newsletters. Measuring total cfDNA could be a cost-effective, viable prognostic marker, but various factors do not favor it as a monitoring tool during chemotherapy. While there may be a place in the clinic for measuring total cfDNA in the future, the lack of standardization means that it is difficult to move forward with large-scale clinical validation studies currently. While the detection of ctDNA has promising standardized liquid biopsy kits from various companies with large clinical trials ongoing, their applications in screening and minimal residual disease can suffer from lower sensitivity. However, researchers are working towards solutions to these issues with innovations in technology, multi-omics, and sampling. With great promise, further research is needed before liquid biopsies can be recommended for everyday clinical management.

Thymic lymphoma detection in RORγ knockout mice using 5-hydroxymethylcytosine profiling of circulating cell-free DNA

A high incidence of thymic lymphoma has been noted in mice deficient of retinoid-related orphan receptor γ2 (RORγ2), which is required for differentiation of naïve CD4+ T cells into TH17 cells. Using a RORγ homozygous knockout (KO) mouse model of thymic lymphoma, we characterized this tumor progression and investigated the utility of 5-hydroxymethylcytosine (5hmC) signatures as a non-invasive circulating biomarker for early prediction of malignancy. No evidence for malignancy was noted in the wild-type mice, while primary thymic lymphoma with multi-organ metastasis was observed microscopically in 97% of the homozygous RORγ KO mice. The severity of thymic lymphoma was not age-dependent in the KO mice of 2 to 4 months old. Differential enrichment of 5hmC in thymic DNA and plasma cell-free DNA (cfDNA) was compared across different stages of tumor progression. Random forest modeling of plasma cfDNA achieved good predictivity (AUC = 0.74) in distinguishing early non-metastatic thymic lymphoma compared to cancer-free controls, while perfect predictivity was achieved with advanced multi-organ metastatic disease (AUC = 1.00). Lymphoid-specific genes involved in thymocyte selection during T cell development (Themis, Tox) were differentially enriched in both plasma and thymic tissue. This could help in differentiating thymic lymphoma from other tumors commonly detected in rodent carcinogenicity studies used in pharmaceutical drug development to inform human malignancy risk. Overall, these results provide a proof-of-concept for using circulating cfDNA profiles in rodent carcinogenicity studies for early risk assessment of novel pharmaceutical targets.

TET (Ten-eleven translocation) family proteins: structure, biological functions and applications

Ten-eleven translocation (TET) family proteins (TETs), specifically, TET1, TET2 and TET3, can modify DNA by oxidizing 5-methylcytosine (5mC) iteratively to yield 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxycytosine (5caC), and then two of these intermediates (5fC and 5caC) can be excised and return to unmethylated cytosines by thymine-DNA glycosylase (TDG)-mediated base excision repair. Because DNA methylation and demethylation play an important role in numerous biological processes, including zygote formation, embryogenesis, spatial learning and immune homeostasis, the regulation of TETs functions is complicated, and dysregulation of their functions is implicated in many diseases such as myeloid malignancies. In addition, recent studies have demonstrated that TET2 is able to catalyze the hydroxymethylation of RNA to perform post-transcriptional regulation. Notably, catalytic-independent functions of TETs in certain biological contexts have been identified, further highlighting their multifunctional roles. Interestingly, by reactivating the expression of selected target genes, accumulated evidences support the potential therapeutic use of TETs-based DNA methylation editing tools in disorders associated with epigenetic silencing. In this review, we summarize recent key findings in TETs functions, activity regulators at various levels, technological advances in the detection of 5hmC, the main TETs oxidative product, and TETs emerging applications in epigenetic editing. Furthermore, we discuss existing challenges and future directions in this field.

Liquid biopsies for cancer: From bench to clinic

Over the past two decades, liquid biopsy has been increasingly used as a supplement, or even, a replacement to the traditional biopsy in clinical oncological practice, due to its noninvasive and early detectable properties. The detections can be based on a variety of features extracted from tumor‑derived entities, such as quantitative alterations, genetic changes, and epigenetic aberrations, and so on. So far, the clinical applications of cancer liquid biopsy mainly aimed at two aspects, prediction (early diagnosis, prognosis and recurrent evaluation, therapeutic response monitoring, etc.) and intervention. In spite of the rapid development and great contributions achieved, cancer liquid biopsy is still a field under investigation and deserves more clinical practice. To better open up future work, here we systematically reviewed and compared the latest progress of the most widely recognized circulating components, including circulating tumor cells, cell-free circulating DNA, noncoding RNA, and nucleosomes, from their discovery histories to clinical values. According to the features applied, we particularly divided the contents into two parts, beyond epigenetics and epigenetic-based. The latter was considered as the highlight along with a brief overview of the advances in both experimental and bioinformatic approaches, due to its unique advantages and relatively lack of documentation.

Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA

BACKGROUND & AIMS

Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma.

METHODS

Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs.

RESULTS

5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%).

CONCLUSIONS

The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

BACKGROUND

Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable.

METHODS

We further investigated the diagnostic potential of combining two features (epigenetic markers and fragmentomic information) of cell-free DNA for detecting various types of cancers. To do this, we extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and studied them in 396 low-pass 5hmC sequencing data, which included four common cancer types and control samples.

RESULTS

In our analysis of 5hmC sequencing data from cancer samples, we observed aberrant ultra-long fragments (220-500 bp) that differed from normal samples in terms of both size and coverage profile. These fragments played a significant role in predicting cancer. Leveraging the ability to detect cfDNA hydroxymethylation and fragmentomic markers simultaneously in low-pass 5hmC sequencing data, we developed an integrated model that incorporated 63 features representing both fragmentomic features and hydroxymethylation signatures. This model achieved high sensitivity and specificity for pan-cancer detection (88.52% and 82.35%, respectively).

CONCLUSION

We showed that fragmentomic information in 5hmC sequencing data is an ideal marker for cancer detection and that it shows high performance in low-pass sequencing data.

Recent advances in understanding DNA methylation of prostate cancer

Epigenetic modifications, such as DNA methylation, is widely studied in cancer. DNA methylation patterns have been shown to distinguish between benign and malignant tumors in various cancers, including prostate cancer. It may also contribute to oncogenesis, as it is frequently associated with downregulation of tumor suppressor genes. Aberrant patterns of DNA methylation, in particular the CpG island hypermethylator phenotype (CIMP), have shown associative evidence with distinct clinical features and outcomes, such as aggressive subtypes, higher Gleason score, prostate-specific antigen (PSA), and overall tumor stage, overall worse prognosis, as well as reduced survival. In prostate cancer, hypermethylation of specific genes is significantly different between tumor and normal tissues. Methylation patterns could distinguish between aggressive subtypes of prostate cancer, including neuroendocrine prostate cancer (NEPC) and castration resistant prostate adenocarcinoma. Further, DNA methylation is detectable in cell-free DNA (cfDNA) and is reflective of clinical outcome, making it a potential biomarker for prostate cancer. This review summarizes recent advances in understanding DNA methylation alterations in cancers with the focus on prostate cancer. We discuss the advanced methodology used for evaluating DNA methylation changes and the molecular regulators behind these changes. We also explore the clinical potential of DNA methylation as prostate cancer biomarkers and its potential for developing targeted treatment of CIMP subtype of prostate cancer.

Cell-selective proteomics segregates pancreatic cancer subtypes by extracellular proteins in tumors and circulation

Cell-selective proteomics is a powerful emerging concept to study heterocellular processes in tissues. However, its high potential to identify non-cell-autonomous disease mechanisms and biomarkers has been hindered by low proteome coverage. Here, we address this limitation and devise a comprehensive azidonorleucine labeling, click chemistry enrichment, and mass spectrometry-based proteomics and secretomics strategy to dissect aberrant signals in pancreatic ductal adenocarcinoma (PDAC). Our in-depth co-culture and in vivo analyses cover more than 10,000 cancer cell-derived proteins and reveal systematic differences between molecular PDAC subtypes. Secreted proteins, such as chemokines and EMT-promoting matrisome proteins, associated with distinct macrophage polarization and tumor stromal composition, differentiate classical and mesenchymal PDAC. Intriguingly, more than 1,600 cancer cell-derived proteins including cytokines and pre-metastatic niche formation-associated factors in mouse serum reflect tumor activity in circulation. Our findings highlight how cell-selective proteomics can accelerate the discovery of diagnostic markers and therapeutic targets in cancer.

Diagnostic Bioliquid Markers for Pancreatic Cancer: What We Have vs. What We Need

Pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, currently has a dismal five-year survival rate of approximately 10% due to late diagnosis and a lack of efficient treatment options such as surgery. Furthermore, the majority of PDAC patients have surgically unresectable cancer, meaning cancer cells have either reached the surrounding blood vessels or metastasized to other organs distant from the pancreas area, resulting in low survival rates as compared to other types of cancers. In contrast, the five-year survival rate of surgically resectable PDAC patients is currently 44%. The late diagnosis of PDAC is a result of little or no symptoms in its early stage of development and a lack of specific biomarkers that may be utilized in routine examinations in the clinic. Although healthcare professionals understand the importance of early detection of PDAC, the research on the subject has lagged and no significant changes in the death toll of PDAC patients has been observed. This review is focused on understanding potential biomarkers that may increase the early diagnosis of PDAC patients at its surgically resectable stage. Here, we summarize the currently available biomarkers used in the clinic as well as those being developed with the hope of providing insight into the future of liquid biomarkers to be used in routine examinations for the early diagnosis of PDAC.

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.

Noninvasive detection of brain gliomas using plasma cell-free DNA 5-hydroxymethylcytosine sequencing

Liquid biopsy techniques based on deep sequencing of plasma cell-free DNA (cfDNA) could detect the low-frequency somatic mutations and provide an accurate diagnosis for many cancers. However, for brain gliomas, reliable performance of these techniques currently requires obtaining cfDNA from patients' cerebral spinal fluid, which is cumbersome and risky. Here we report a liquid biopsy method based on sequencing of plasma cfDNA fragments carrying 5-hydroxymethylcytosine (5hmC) using selective chemical labeling (hMe-Seal). We first constructed a dataset including 180 glioma patients and 229 non-glioma controls. We found marked concordance between cfDNA hydroxymethylome and the aberrant transcriptome of the underlying gliomas. Functional analysis also revealed overrepresentation of the differentially hydroxymethylated genes (DhmGs) in oncogenic and neural pathways. After splitting our dataset into training and test cohort, we showed that a penalized logistic model constructed with training set DhmGs could distinguish glioma patients from healthy controls in both our test set (AUC = 0.962) and an independent dataset (AUC = 0.930) consisting of 111 gliomas and 111 controls. Additionally, the DhmGs between gliomas with mutant and wild-type isocitrate dehydrogenase (IDH) could be used to train a cfDNA predictor of the IDH mutation status of the underlying tumor (AUC = 0.816), and patients with predicted IDH mutant gliomas had significantly better outcome (P = .01). These results indicate that our plasma cfDNA 5hmC sequencing method could obtain glioma-specific signals, which may be used to noninvasively detect these patients and predict the aggressiveness of their tumors.

EBS-seq: enrichment-based method for accurate analysis of 5-hydroxymethylcytosine at single-base resolution

BACKGROUND

A growing body of research has emphasized 5-hydroxymethylcytosine (5hmC) as an important epigenetic mark. High-resolution methods to detect 5hmC require high sequencing depth and are therefore expensive. Many studies have used enrichment-based methods to detect 5hmC; however, conventional enrichment-based methods have limited resolution. To overcome these limitations, we developed EBS-seq, a cost-efficient method for 5hmC detection with single-base resolution that combines the advantages of high-resolution methods and enrichment-based methods.

RESULTS

EBS-seq uses selective labeling of 5hmC, deamination of cytosine and 5-methylcytosine, pull-down of labeled 5hmC, and C-to-T conversion during DNA amplification. Using this method, we profiled 5hmC in HEK293T cells and two colorectal cancer samples. Compared with conventional enrichment-based 5hmC detection, EBS-seq improved 5hmC signals by localizing them at single-base resolution. Furthermore, EBS-seq was able to determine 5hmC levels in CpG-dense regions where distortion of signals can occur, such as CpG islands and CpG shores. Comparing EBS-seq and conventional high-resolution 5hmC detection by ACE-seq, we showed that EBS-seq is more effective at finding 5hmC sites. Using EBS-seq, we found strong associations between gene expression and gene-body 5hmC content in both HEK293T cells and colorectal cancer samples.

CONCLUSIONS

EBS-seq is a reliable and cost-efficient method for 5hmC detection because it simultaneously enriches 5hmC-containing DNA fragments and localizes 5hmC signals at single-base resolution. This method is a promising choice for 5hmC detection in challenging clinical samples with low 5hmC levels, such as cancer tissues.

GATA4 and GATA6 loss-of-expression is associated with extinction of the classical programme and poor outcome in pancreatic ductal adenocarcinoma

OBJECTIVE

GATA6 is a key regulator of the classical phenotype in pancreatic ductal adenocarcinoma (PDAC). Low GATA6 expression associates with poor patient outcome. GATA4 is the second most expressed GATA factor in the pancreas. We assessed whether, and how, GATA4 contributes to PDAC phenotype and analysed the association of expression with outcome and response to chemotherapy.

DESIGN

We analysed PDAC transcriptomic data, stratifying cases according to GATA4 and GATA6 expression and identified differentially expressed genes and pathways. The genome-wide distribution of GATA4 was assessed, as well as the effects of GATA4 knockdown. A multicentre tissue microarray study to assess GATA4 and GATA6 expression in samples (n=745) from patients with resectable was performed. GATA4 and GATA6 levels were dichotomised into high/low categorical variables; association with outcome was assessed using univariable and multivariable Cox regression models.

RESULTS

GATA4 messenger RNA is enriched in classical, compared with basal-like tumours. We classified samples in 4 groups as high/low for GATA4 and GATA6. Reduced expression of GATA4 had a minor transcriptional impact but low expression of GATA4 enhanced the effects of GATA6 low expression. GATA4 and GATA6 display a partially overlapping genome-wide distribution, mainly at promoters. Reduced expression of both proteins in tumours was associated with the worst patient survival. GATA4 and GATA6 expression significantly decreased in metastases and negatively correlated with basal markers.

CONCLUSIONS

GATA4 and GATA6 cooperate to maintain the classical phenotype. Our findings provide compelling rationale to assess their expression as biomarkers of poor prognosis and therapeutic response.

Circulating tumor-associated autoantibodies as novel diagnostic biomarkers in pancreatic adenocarcinoma

To develop a superior diagnostic approach for pancreatic adenocarcinoma (PAAC), the present study prospectively included 338 PAAC patients, 294 normal healthy volunteers (NHV), 122 chronic pancreatitis (CP) patients and 100 patients with non-PAAC malignancies. In the identification phase, HuProt Human Proteome Microarray, comprising 21 065 proteins, was used to identify serum tumor-associated autoantibodies (TAAbs) candidates differentiating PAAC (n = 30) from NHV (n = 30). A PAAC-focused array containing 165 differentially expressed TAAbs identified was subsequently adopted in the validation phase (n = 712) for specificity and sensitivities. The multivariate TAAbs signature for differentiation PAAC from controls (NHV + CP) identified five candidates, namely the IgG-type TAAbs against CLDN17, KCNN3, SLAMF7, SLC22A11 and OR51F2. Multivariate logistic performance model of y = (22.893 × CA19-9 + 0.68 × CLDN17 - 4.012) showed a significant better diagnostic accuracy than that of CA19-9 and CLDN17 in differentiating PAAC from controls (NHV + CP) (AUC = 0.97, 0.92 and 0.82, respectively, P-value < .0001). We further tested the autoantigen level of CLDN17 by ELISA in 82 sera samples from PAAC (n = 42), CP (n = 24) and NHV (n = 16). Similarly, the model showed superior diagnostic performance than that of CA19-9 and CLDN17 (AUC = 0.93, 0.83 and 0.81, respectively, P-value < .0001) in differentiating PAAC from controls. In conclusion, our study is the first to characterize the circulating TAAbs signatures in PAAC. The results showed that CLDN17 combined with CA19-9 provided potentially clinical value and may serve as noninvasive novel biomarkers for PAAC diagnosis.

Unintrusive multi-cancer detection by circulating cell-free DNA methylation sequencing (THUNDER): development and independent validation studies

BACKGROUND

Early detection of cancer offers the opportunity to identify candidates when curative treatments are achievable. The THUNDER study (THe UNintrusive Detection of EaRly-stage cancers, NCT04820868) aimed to evaluate the performance of ELSA-seq, a previously described cfDNA methylation-based technology, in the early detection and localization of six types of cancers in the colorectum, esophagus, liver, lung, ovary and pancreas.

PATIENTS AND METHODS

A customized panel of 161,984 CpG sites was constructed and validated by public and in-house (cancer: n=249; non-cancer: n=288) methylome data, respectively. The cfDNA samples from 1,693 participants (cancer: n=735; non-cancer: n=958) were retrospectively collected to train and validate two multi-cancer detection blood test models (MCDBT-1/2) for different clinical scenarios. The models were validated on a prospective and independent cohort of age-matched 1,010 participants (cancer: n=505; non-cancer: n=505). Simulation using the cancer incidence in China was applied to infer stage-shift and survival benefits to demonstrate the potential utility of the models in the real world.

RESULTS

MCDBT-1 yielded a sensitivity of 69.1% (64.8%‒73.3%), a specificity of 98.9% (97.6%‒99.7%) and tissue origin accuracy of 83.2% (78.7%‒87.1%) in the independent validation set. For early stage (I‒III) patients, the sensitivity of MCDBT-1 was 59.8% (54.4%‒65.0%). In the real-world simulation, MCDBT-1 achieved the sensitivity of 70.6% in detecting the six cancers, thus decreasing late-stage incidence by 38.7%‒46.4%, and increasing 5-year survival rate by 33.1%‒40.4%, respectively. In parallel, MCDBT-2 was generated at a slightly low specificity of 95.1% (92.8%-96.9%) but a higher sensitivity of 75.1% (71.9%-79.8%) than MCDBT-1 for populations at relatively high risk of cancers, and also had ideal performance.

CONCLUSION

In this large-scale clinical validation study, MCDBT-1/2 models showed a high sensitivity, specificity, and accuracy of predicted origin in detecting six types of cancers.

Universal Design of Luciferase Fusion Proteins for Epigenetic Modifications Detection Based on Bioluminescence Resonance Energy Transfer

Global hypomethylation and promoter hypermethylation of tumor-suppressor genes are the hallmarks of cancer. We previously reported a global DNA methylation level sensing system based on dual-color bioluminescence resonance energy transfer (BRET) using methyl-CpG binding domain (MBD)-fused firefly luciferase (Fluc) and unmethyl-CpG binding domain (CXXC)-fused Oplophorus luciferase (Oluc). Moreover, BRET-based hydroxymethylation and hemi-methylation level sensing systems have been developed using hydroxymethyl-CpG and hemi-methyl-CpG binding domain-fused Fluc. These studies suggest that target epigenetic modifications can be simultaneously quantified using target-modification-binding protein-fused luciferases. In this study, we focused on the SnoopTag (SnT)/SnoopCatcher (SnC) protein ligation system to establish a universal design for fusion protein construction for any combination. SnT spontaneously forms an isopeptide bond with SnC; therefore, any kind of fusion protein would be constructed by the SnT/SnC system. To establish the proof of concept, MBD-SnT, CXXC-SnT, and SnC-Oluc were prepared and ligated MBD-SnT or CXXC-SnT to SnC-Oluc. The ligation products of MBD-SnT-SnC-Oluc and CXXC-SnT-SnC-Oluc showed luciferase activity and specific binding activity to methyl-CpG and unmethyl-CpG, respectively. The BRET signal using MBD-SnT-SnC-Oluc and CXXC-SnT-SnC-Oluc increased the amount of methyl-CpG and unmethyl-CpG in genomic DNA, respectively. There was a significant negative correlation between the BRET signals; therefore, the global DNA methylation level was quantified using the BRET signals (R² = 0.99, and R.S.D. <3.5%). These results indicate that the SnT/SnC protein ligation system can be utilized to construct target modification-binding protein-fused luciferases in any combination that detects target modifications in genomic DNA based on BRET.

Advances in Liquid Biopsy Technology and Implications for Pancreatic Cancer

Pancreatic cancer is a highly aggressive malignancy with a climbing incidence. The majority of cases are detected late, with incurable locally advanced or metastatic disease. Even in individuals who undergo resection, recurrence is unfortunately very common. There is no universally accepted screening modality for the general population and diagnosis, evaluation of treatment response, and detection of recurrence relies primarily on the use of imaging. Identification of minimally invasive techniques to help diagnose, prognosticate, predict response or resistance to therapy, and detect recurrence are desperately needed. Liquid biopsies represent an emerging group of technologies which allow for non-invasive serial sampling of tumor material. Although not yet approved for routine use in pancreatic cancer, the increasing sensitivity and specificity of contemporary liquid biopsy platforms will likely change clinical practice in the near future. In this review, we discuss the recent technological advances in liquid biopsy, focusing on circulating tumor DNA, exosomes, microRNAs, and circulating tumor cells.

Role of epigenetics in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, associated with poor survival outcomes. Lack of early diagnosis, resistance to conventional therapeutic treatments (including immunotherapy) and recurrence are some of the major hurdles in PDAC and contribute to its poor survival rate. While the risk of genetic predisposition to cancers is widely acknowledged and understood, recent advances in whole-genome and next-generation sequencing techniques have led to the acknowledgment of the role played by epigenetics, especially in PDAC. Epigenetic changes are heritable genetic modifications that influence gene expression without altering the DNA sequence. Epigenetic mechanisms (e.g., DNA methylation, post-translational modification of histone complexes and ncRNA) that result in reversible changes in gene expression are increasingly understood to be responsible for tumor initiation, development and even escape from immune surveillance. Our review seeks to highlight the various components of the epigenetic machinery that are known to be implicated in PDAC initiation and development and the feasibility of targeting these components to identify novel pharmacological strategies that could potentially lead to breakthroughs in PDAC treatment.

Screening for pancreatic cancer has the potential to save lives, but is it practical?

INTRODUCTION

Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers.

AREAS COVERED

This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms.

EXPERT OPINION

From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease.

SIGNIFICANCE

In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.

5-Hydroxymethylcytosines in circulating cell-free DNA reveal a diagnostic biomarker for glioma

Gliomas typically have unfavorable prognosis, due to late detection and interventions. However, effective biomarkers for early glioma diagnosis based on 5-hydroxymethylcytosines (5 hm C) in circulating cell-free DNA (cfDNA) are not currently available. 5 hm C profiles in GSE132118 set were subjected for establishment of diagnostic model using the LASSO (least absolute shrinkage and selection operator) algorithm. The 5 hm C-based models demonstrated great potency in differentiating healthy subjects from gliomas, with area under the curves (AUCs) > 0.91 in the training and validation sets. Moreover, the indicator performed well in combination with clinicopathological characteristics to differentiate glioblastomas (GBMs) from lower grade glioma (LGGs). Enrichment analysis on 5 hm C profiles displayed great correlation with glioma pathophysiology. The 5 hm C-derived biomarker might act as an effective and non-invasive measure in glioma screening.

Hydroxymethylation profile of cell-free DNA is a biomarker for early colorectal cancer

Early detection of cancer will improve survival rates. The blood biomarker 5-hydroxymethylcytosine has been shown to discriminate cancer. In a large covariate-controlled study of over two thousand individual blood samples, we created, tested and explored the properties of a 5-hydroxymethylcytosine-based classifier to detect colorectal cancer (CRC). In an independent validation sample set, the classifier discriminated CRC samples from controls with an area under the receiver operating characteristic curve (AUC) of 90% (95% CI [87, 93]). Sensitivity was 55% at 95% specificity. Performance was similar for early stage 1 (AUC 89%; 95% CI [83, 94]) and late stage 4 CRC (AUC 94%; 95% CI [89, 98]). The classifier could detect CRC even when the proportion of tumor DNA in blood was undetectable by other methods. Expanding the classifier to include information about cell-free DNA fragment size and abundance across the genome led to gains in sensitivity (63% at 95% specificity), with similar overall performance (AUC 91%; 95% CI [89, 94]). We confirm that 5-hydroxymethylcytosine can be used to detect CRC, even in early-stage disease. Therefore, the inclusion of 5-hydroxymethylcytosine in multianalyte testing could improve sensitivity for the detection of early-stage cancer.

Regional gain and global loss of 5-hydroxymethylcytosine coexist in genitourinary cancers and regulate different oncogenic pathways

BACKGROUND

DNA 5-hydroxymethylcytosine (5hmC) is produced by dynamic 5mC oxidation process contributing to tissue specification, and loss of 5hmC has been reported in multiple cancers including genitourinary cancers. However, 5hmC is also cell-type specific, and its variability may exist between differentiated tumor cells and cancer stem cells. Thus, cancer-associated changes in 5hmC may be contributed by distinct sets of tumor cells within the tumor tissues.

RESULTS

Here, we applied a sensitive immunoprecipitation-based method (hMeDIP-seq) to analyze 5hmC changes during genitourinary carcinogenesis (including prostate, urothelial and kidney). We confirmed the tissue-specific distribution of 5hmC in genitourinary tissues and identified regional gain and global loss of 5hmC coexisting in genitourinary cancers. The genes with gain of 5hmC during tumorigenesis were functionally enriched in regulating stemness and hypoxia, whereas were associated with poor clinical prognosis irrespective of their differences in tumor type. We identified that gain of 5hmC occurred in soft fibrin gel-induced 3D tumor spheres with a tumor-repopulating phenotype in two prostate cancer cell lines, 22RV1 and PC3, compared with conventional two-dimensional (2D) rigid dishes. Then, we defined a malignant signature derived from the differentially hydroxymethylated regions affected genes of cancer stem-like cells, which could predict a worse clinical outcome and identified phenotypically malignant populations of cells from prostate cancer tumors. Notably, an oxidation-resistant vitamin C derivative, ascorbyl phosphate magnesium, restored 5hmC and killed the cancer stem cell-like cells leading to apoptosis in prostate cancer cell lines.

CONCLUSIONS

Collectively, our study dissects the regional gain of 5hmC in maintaining cancer stem-like cells and related to poor prognosis, which provides proof of concept for an epigenetic differentiation therapy with vitamin C by 5hmC reprogramming.

Role of DNA De-methylation intermediate '5-hydroxymethylcytosine' in ovarian cancer management: A comprehensive review

Ovarian cancer remains the most eminent silent killer, with high morbidity and mortality among all gynaecological cancers. The advanced-stage patient's diagnosis has a low survival rate caused by its asymptomatic progression and diverse histopathological sub-types, wherefore in poor prognosis and highly recurring malignancy with multidrug resistance towards chemotherapy. Epigenetic biomarkers open promising avenues of intriguing research to combat OC malignancy, furthermore a tool for its early diagnosis. 5-hydroxymethycytosine (5-hmC), alias the sixth base of the genome, is an intermediate formed during the recently established DNA demethylation process and catalysed via ten-eleven translocation (TET) family of enzymes. It plays a significant role in regulating gene expression and has sparked interest in various cancer types. This review summarizes the role of active DNA demethylation process, its enzymes and intermediate 5-hmC in epigenetic landscape of ovarian cancer as a potent biomarker for clinical translation in identification of therapeutic targets, diagnostic and prognostic evaluation.

Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing

Nanopore sequencing has brought the technology to the next generation in the science of sequencing. This is achieved through research advancing on: pore efficiency, creating mechanisms to control DNA translocation, enhancing signal-to-noise ratio, and expanding to long-read ranges. Heterogeneity regarding epigenetics would be broad as mutations in the epigenome are sensitive to cause new challenges in cancer research. Epigenetic enzymes which catalyze DNA methylation and histone modification are dysregulated in cancer cells and cause numerous heterogeneous clones to evolve. Detection of this heterogeneity in these clones plays an indispensable role in the treatment of various cancer types. With single-cell profiling, the nanopore sequencing technology could provide a simple sequence at long reads and is expected to be used soon at the bedside or doctor's office. Here, we review the advancements of nanopore sequencing and its use in the detection of epigenetic heterogeneity in cancer.

Tracing the Origin of Cell-Free DNA Molecules through Tissue-Specific Epigenetic Signatures

All cell and tissue types constantly release DNA fragments into human body fluids by various mechanisms including programmed cell death, accidental cell degradation and active extrusion. Particularly, cell-free DNA (cfDNA) in plasma or serum has been utilized for minimally invasive molecular diagnostics. Disease onset or pathological conditions that lead to increased cell death alter the contribution of different tissues to the total pool of cfDNA. Because cfDNA molecules retain cell-type specific epigenetic features, it is possible to infer tissue-of-origin from epigenetic characteristics. Recent research efforts demonstrated that analysis of, e.g., methylation patterns, nucleosome occupancy, and fragmentomics determined the cell- or tissue-of-origin of individual cfDNA molecules. This novel tissue-of origin-analysis enables to estimate the contributions of different tissues to the total cfDNA pool in body fluids and find tissues with increased cell death (pathologic condition), expanding the portfolio of liquid biopsies towards a wide range of pathologies and early diagnosis. In this review, we summarize the currently available tissue-of-origin approaches and point out the next steps towards clinical implementation.

Cell-free DNA 5-hydroxymethylcytosine is an emerging marker of acute myeloid leukemia

Aberrant changes in 5-hydroxymethylcytosine (5hmC) are a unique epigenetic feature in many cancers including acute myeloid leukemia (AML). However, genome-wide analysis of 5hmC in plasma cell-free DNA (cfDNA) remains unexploited in AML patients. We used a highly sensitive and robust nano-5hmC-Seal technology and profiled genome-wide 5hmC distribution in 239 plasma cfDNA samples from 103 AML patients and 81 non-cancer controls. We developed a 5hmC diagnostic model that precisely differentiates AML patients from controls with high sensitivity and specificity. We also developed a 5hmC prognostic model that accurately predicts prognosis in AML patients. High weighted prognostic scores (wp-scores) in AML patients were significantly associated with adverse overall survival (OS) in both training (P = 3.31e-05) and validation (P = 0.000464) sets. The wp-score was also significantly associated with genetic risk stratification and displayed dynamic changes with varied disease burden. Moreover, we found that high wp-scores in a single gene, BMS1 and GEMIN5 predicted OS in AML patients in both the training set (P = 0.023 and 0.031, respectively) and validation set (P = 9.66e-05 and 0.011, respectively). Lastly, our study demonstrated the genome-wide landscape of DNA hydroxymethylation in AML and revealed critical genes and pathways related to AML diagnosis and prognosis. Our data reveal plasma cfDNA 5hmC signatures as sensitive and accurate markers for AML diagnosis and prognosis. Plasma cfDNA 5hmC analysis will be an effective and minimally invasive tool for AML management.

Is Cell-Free DNA Testing in Pancreatic Ductal Adenocarcinoma Ready for Prime Time?

Simple Summary

Pancreatic cancer is a deadly cancer with limited treatment options. It is often detected in most people at stages where cure is not possible. There is no good test to know if a person will respond to treatment or if there is any disease beyond what can be seen by available imaging tests. Genetic material from the tumor is expected to float in the blood. Studying the alterations in the genetic material could help detect the tumor early, give an idea about its aggressiveness and response to available treatments, and facilitate the discovery of newer therapies. The focus of the studies so far has been on only one kind of genetic aberration, mutations, which has not given us great results. There is a need to explore another type of change known as methylation that could hold answers for managing pancreatic cancers better.

Abstract

Cell-free DNA (cfDNA) testing currently does not have a significant role in PDA management: it is insufficient to diagnose PDA, and its use is primarily restricted to identifying targetable mutations (if tissue is insufficient or unavailable). cfDNA testing has the potential to address critical needs in PDA management, such as pre-operative risk stratification (POR), prognostication, and predicting (and monitoring) treatment response. Prior studies have focused primarily on somatic mutations, specifically KRAS variants, and have shown limited success in addressing prognosis and POR. Recent studies have demonstrated the importance of other less prevalent mutations (ERBB2 and TP53), but no studies have provided reliable mutation panels for clinical use. Methylation aberrations in cfDNA (epigenetic markers) in PDA have been relatively less explored. However, early evidence has suggested they offer diagnostic and, to some extent, prognostic value. The inclusion of epigenetic markers of cfDNA adds another dimension to genomic testing and may open new therapeutic avenues beyond addressing critical areas of need in PDA treatment. For cfDNA to substantially influence PDA management, concerted efforts are required to include less frequent mutations and epigenetic markers. Furthermore, relying on KRAS mutations for PDA management will always be inadequate.