Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.

BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. METHODS: We constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. RESULTS: Our final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. CONCLUSIONS: In conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples.

Evaluation of a multimodal ctDNA-based assay for detection of aggressive cancers lacking standard screening tests.

Aim: Cancers lacking standard screening (LSS) options account for approximately 70% of cancer-related deaths due to late-stage diagnosis. Circulating tumor DNA (ctDNA) is a promising biomarker for multi-cancer early detection. We previously developed SPOT-MAS, a multimodal ctDNA-based assay analyzing methylation and fragmentomic profiles, effective in detecting common cancers (breast, colorectal, liver, lung and gastric). This study extends the analysis to five LSS cancers: endometrial, esophageal, head and neck, ovarian and pancreatic.Methods: SPOT-MAS was applied to profile cfDNA methylation and fragmentomic patterns in 739 healthy individuals and 135 LSS cancer patients.Results: We identified 347 differentially methylated regions and observed genome-wide hypomethylation across all five LSS cancers. Esophageal and head and neck cancers showed an enrichment of short cfDNA fragments (<150 bp). Eleven 4-mer end motifs were consistently altered in cfDNA fragments across all LSS cancers. Many significant signatures were consistent with previous observations in common cancers. Notably, SPOT-MAS achieved 96.2% specificity and 74.8% overall sensitivity, with a lower sensitivity of 60.7% in early-stage cancers.Conclusion: This proof-of-concept study demonstrates that SPOT-MAS a non-invasive test trained on five common cancer types, could detect a number of LSS cancer cases, potentially complementing existing screening programs.

Many cancers do not have standard tests, so they are often found too late, which leads to about 70% of cancer deaths. We've created a blood test that can help find cancer early. This test has already worked well for common cancers like breast and lung cancer, and now we're testing it on five harder-to-detect cancers: endometrial, esophageal, head and neck, ovarian and pancreatic cancers. In our study, we tested our blood test on 739 healthy people and 135 patients with these difficult cancers. Our method correctly identified healthy people 96.2% of the time and found cancer cases 74.8% of the time. This new test could help with screening for types of cancer that do not have good tests right now.

Clinical validation of a ctDNA-Based Assay for Multi-Cancer Detection: An Interim Report from a Vietnamese Longitudinal Prospective Cohort Study of 2795 Participants.

The SPOT-MAS assay "Screening for the Presence Of Tumor by Methylation And Size" detects the five most common cancers in Vietnam by evaluating circulating tumor DNA in the blood. Here, we validated its performance in a prospective multi-center clinical trial, K-DETEK. Our analysis of 2795 participants from 14 sites across Vietnam demonstrates its ability to detect cancers in asymptomatic individuals with a positive predictive value of 60%, with 83.3% accuracy in detecting tumor location. We present a case report to support further using SPOT-MAS as a complementary method to achieve early cancer detection and provide the opportunity for early treatment.

Fragment length profiles of cancer mutations enhance detection of circulating tumor DNA in patients with early-stage hepatocellular carcinoma.

BACKGROUND: Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. METHODS: Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. RESULTS: Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. CONCLUSIONS: Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Spatial metapopulation dynamics with local and global colonization.

We revisit a spatial metapopulation model on continuous space as a stochastic point pattern dynamics. In the model, local patches as points are distributed with a certain spatial configuration and status of each patch changes stochastically between occupied and empty: an occupied patch becomes empty by local extinction and an empty patch becomes occupied both by local and global colonization. We carry out simulation analysis and derive an analytical model in terms of singlet, pair and triplet probabilities that describe the stochastic dynamics. Using a simple closure that approximates triplet probabilities by singlet and pair probabilities, we show that equilibrium singlet and pair probabilities can be analytically derived. The derived equilibrium properties successfully describe simulation results under a certain condition where the range of local colonization and the proportion of global colonization play key roles. Our model is an extension of the classical non-spatial Levins model to a spatially explicit metapopulation model. We appeal the advantage of point pattern approach to study spatial dynamics in general ecology and call for the need to deepen our understanding of mathematical tools to explore point pattern dynamics.

Ultra-Deep Sequencing of Plasma-Circulating DNA for the Detection of Tumor- Derived Mutations in Patients with Nonmetastatic Colorectal Cancer.

Identification of tumor-derived mutation (TDM) in liquid biopsies (LB), especially in early-stage patients, faces several challenges, including low variant-allele frequencies, interference by white blood cell (WBC)-derived mutations (WDM), benign somatic mutations and tumor heterogeneity. Here, we addressed the above-mentioned challenges in a cohort of 50 nonmetastatic colorectal cancer patients, via a workflow involving parallel sequencing of paired WBC- and tumor-gDNA. After excluding potential false positive mutations, we detected at least one TDM in LB of 56% (28/50) of patients, with the majority showing low-patient coverage, except for one TDM mapped to KMT2D that recurred in 30% (15/30) of patients.

Multimodal analysis of ctDNA methylation and fragmentomic profiles enhances detection of nonmetastatic colorectal cancer.

Aims: Early detection of colorectal cancer (CRC) provides substantially better survival rates. This study aimed to develop a blood-based screening assay named SPOT-MAS ('screen for the presence of tumor by DNA methylation and size') for early CRC detection with high accuracy. Methods: Plasma cell-free DNA samples from 159 patients with nonmetastatic CRC and 158 healthy controls were simultaneously analyzed for fragment length and methylation profiles. We then employed a deep neural network with fragment length and methylation signatures to build a classification model. Results: The model achieved an area under the curve of 0.989 and a sensitivity of 96.8% at 97% specificity in detecting CRC. External validation of our model showed comparable performance, with an area under the curve of 0.96. Conclusion: SPOT-MAS based on integration of cancer-specific methylation and fragmentomic signatures could provide high accuracy for early-stage CRC detection.

A novel blood test for early detection of colorectal cancer. Colorectal cancer is a cancer of the colon or rectum, located at the lower end of the digestive tract. The early detection of colorectal cancer can help people with the disease have a higher chance of survival and a better quality of life. Current screening methods can be invasive, cause discomfort or have low accuracy; therefore newer screening methods are needed. In this study we developed a new screening method, called SPOT-MAS, which works by measuring the signals of cancer DNA in the blood. By combining different characteristics of cancer DNA, SPOT-MAS could distinguish blood samples of people with colorectal cancer from those of healthy individuals with high accuracy.

Circulating DNA methylation profile improves the accuracy of serum biomarkers for the detection of nonmetastatic hepatocellular carcinoma.

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, µTASWako®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

The early detection of liver cancer in high-risk populations can help people with the disease have a higher chance of survival and better quality of life. However, this is still a healthcare challenge. Current commercial blood tests measuring protein signatures in the blood have low accuracy due to increased levels of these proteins being detected in both liver cancer patients and patients with chronic liver diseases. In this study, we identified a set of signatures in DNA released by cancer cells into the bloodstream and used them as biomarkers to distinguish liver cancer patients from high-risk patients. We also demonstrated that adding those signatures to a commercial blood test currently used in clinics could improve the accuracy in detecting liver cancer patients.

Competition or cooperation in transboundary fish stocks management: Insight from a dynamical model.

An idealized system of a shared fish stock associated with different exclusive economic zones (EEZ) is modelled. Parameters were estimated for the case of the small pelagic fisheries shared between Southern Morocco, Mauritania and the Senegambia. Two models of fishing effort distribution were explored. The first one considers independent national fisheries in each EEZ, with a cost per unit of fishing effort that depends on local fishery policy. The second one considers the case of a fully cooperative fishery performed by an international fleet freely moving across the borders. Both models are based on a set of six ordinary differential equations describing the time evolution of the fish biomass and the fishing effort. We take advantage of the two time scales to obtain a reduced model governing the total fish biomass of the system and fishing efforts in each zone. At the fast equilibrium, the fish distribution follows the ideal free distribution according to the carrying capacity in each area. Different equilibria can be reached according to management choices. When fishing fleets are independent and national fishery policies are not harmonized, in the general case, competition leads after a few decades to a scenario where only one fishery remains sustainable. In the case of sub-regional agreement acting on the adjustment of cost per unit of fishing effort in each EEZ, we found that a large number of equilibria exists. In this last case the initial distribution of fishing effort strongly impact the optimal equilibrium that can be reached. Lastly, the country with the highest carrying capacity density may get less landings when collaborating with other countries than if it minimises its fishing costs. The second fully cooperative model shows that a single international fishing fleet moving freely in the fishing areas leads to a sustainable equilibrium. Such findings should foster regional fisheries organizations to get potential new ways for neighbouring fish stock management.

Multimodal analysis of genome-wide methylation, copy number aberrations, and end motif signatures enhances detection of early-stage breast cancer.

Introduction: Breast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes. Methods: Here, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects. Results: We identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity. Discussion: Our findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Kinetics of Organic Biodegradation and Biogas Production in the Pilot-Scale Moving Bed Biofilm Reactor (MBBR) for Piggery Wastewater Treatment.

In this research, the kinetics of COD biodegradation and biogas production in a moving bed biofilm reactor (MBBR) at pilot scale (10 m3) for piggery wastewater treatment were investigated. Polyethylene (PE) was used as a carrying material, with organic loading rates (OLRs) of 10, 15, and 18 kgCOD/m3 day in accordance to hydraulic retention times (HRTs) of 0.56, 0.37, and 0.3 day. The results showed that a high COD removal efficiency was obtained in the range of 68-78% with the influent COD of 5.2-5.8 g/L at all 3 HRTs. About COD degradation kinetics, in comparison to the first- and second-order kinetics and the Monod model, Stover-Kincannon model showed the best fit with R 2 0.98 and a saturation value constant (K B ) and a maximum utilization rate (U max) of 52.40 g/L day and 82.65 g/L day, respectively. The first- and second-order kinetics with all 3 HRTs and Monod model with the HRT of 0.56 day also obtained high R 2 values. Therefore, these kinetics and models can be further considered to be used for predicting the kinetic characteristics of the MBBR system in piggery wastewater treatment process. The result of a 6-month operation of the MBBR was that biogas production was mostly in the operating period of days 17 to 80, around 0.2 to 0.3 and 0.15-0.20 L/gCODconverted, respectively, and then reduction at an OLR of 18 kgCOD/m3. After the start-up stage, day 35 biogas cumulative volume fluctuated from 20 to 30 m3/day and reached approximately 3500 m3 for 178 days during the whole digestive process. Methane is accounted for about 65-70% of biogas with concentration around 400 mg/L.

The transfer and decay of maternal antibody against Shigella sonnei in a longitudinal cohort of Vietnamese infants.

BACKGROUND: Shigella sonnei is an emergent and major diarrheal pathogen for which there is currently no vaccine. We aimed to quantify duration of maternal antibody against S. sonnei and investigate transplacental IgG transfer in a birth cohort in southern Vietnam. METHODS AND RESULTS: Over 500-paired maternal/infant plasma samples were evaluated for presence of anti-S. sonnei-O IgG and IgM. Longitudinal plasma samples allowed for the estimation of the median half-life of maternal anti-S. sonnei-O IgG, which was 43 days (95% confidence interval: 41-45 days). Additionally, half of infants lacked a detectable titer by 19 weeks of age. Lower cord titers were associated with greater increases in S. sonnei IgG over the first year of life, and the incidence of S. sonnei seroconversion was estimated to be 4/100 infant years. Maternal IgG titer, the ratio of antibody transfer, the season of birth and gestational age were significantly associated with cord titer. CONCLUSIONS: Maternal anti-S. sonnei-O IgG is efficiently transferred across the placenta and anti-S. sonnei-O maternal IgG declines rapidly after birth and is undetectable after 5 months in the majority of children. Preterm neonates and children born to mothers with low IgG titers have lower cord titers and therefore may be at greater risk of seroconversion in infancy.

Seroprevalence of antibodies against human papillomavirus (HPV) types 16 and 18 in four continents: the International Agency for Research on Cancer HPV Prevalence Surveys.

BACKGROUND: Few human papillomavirus (HPV) seroprevalence studies have been carried out in women from low-resource countries. METHODS: Seroprevalence of antibodies against HPV16 and HPV18 was assessed in 7,074 women ≥15 years of age (median 44 years) from eight world areas. Serum antibodies against HPV16 and HPV18 were tested for using enzyme-linked immunosorbent assay. HPV DNA was assessed using a general primer GP5+/6+-mediated PCR. RESULTS: HPV16 and HPV18 seroprevalence both ranged from <1% (Hanoi, Vietnam) to >or=25% (Nigeria). Of women who were HPV16 or HPV18 DNA-positive, seropositivity for the same type was 39.8% and 23.2%, respectively. Seropositivity for either type was directly associated with markers of sexual behavior. HPV16 and/or 18 (HPV16/18)-seropositive women had an increased risk of having cytologic abnormalities only if they were also HPV DNA-positive. A high international correlation was found between HPV16/18 seroprevalence and overall HPV DNA prevalence (r = 0.81; P = 0.022). However, HPV16/18 seroprevalence was substantially higher than the corresponding DNA prevalence in all study areas (although to different extents) and, contrary to DNA, tended to increase from young to middle age, and then decline or remain fairly constant. In all study areas, the vast majority of the information on the burden of exposure to HPV16/18 derived from serology. CONCLUSIONS: The correlation between HPV DNA and HPV serology was not very good at an individual woman level, but high at a population level. IMPACT: HPV serology is a poor marker of current infection or related lesions, but it can contribute, together with DNA, in evaluating the variations in the burden of HPV infection worldwide.

Human papillomavirus infection among women in South and North Vietnam.

The incidence rate of invasive cervical carcinoma (ICC) is 4-fold higher in Ho Chi Minh City, in the South of Vietnam, than in Hanoi, in the North. Thus, we explored the prevalence of and the risk factors for human papillomavirus (HPV) infection in these 2 areas. A population-based random sample of married women aged 15-69 years were interviewed and had a gynaecological examination in the urban district of Ho Chi Minh City and in a peri-urban district in Hanoi. HPV DNA detection was performed using a GP5+/6+ primer-mediated PCR enzyme immunoassay. A total of 922 women from Ho Chi Minh and 994 from Hanoi, for whom a Pap smear and HPV-status were available, were evaluated. HPV DNA was detected among 10.9% of women in Ho Chi Minh City and 2.0% in Hanoi (age standardized prevalence, world standard population: 10.6% and 2.3%, respectively). In the 2 areas combined, 30 different HPV types were found, the most common being HPV 16 (in 14 single and 18 multiple infections), followed by HPV 58, 18 and 56. A peak of HPV DNA detection in women younger than age 25 was found in Ho Chi Minh City (22.3%) but not in Hanoi. Major risk factors for HPV DNA detection were indicators of sexual habits, most notably the presence of HSV-2 antibodies, nulliparity and the current use of oral contraceptives. Women in Hanoi showed the lowest HPV prevalence ever reported so far, suggesting that HPV has not spread widely in this population. As expected, HPV prevalence in a population seemed to be closely correlated with ICC incidence rates.