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.

A consultation and work-up diagnosis protocol for a multicancer early detection test: a case series study.

The emergence of multicancer early detection (MCED) tests holds promise for improving early cancer detection and public health outcomes. However, positive MCED test results require confirmation through recommended cancer diagnostic imaging modalities. To address these challenges, we have developed a consultation and work-up protocol for definitive diagnostic results post MCED testing, named SPOT-MAS. Developed through circulating tumor DNA (ctDNA) analysis and in line with professional guidelines and advisory board consensus, this protocol standardizes information to aid general practitioners in accessing, interpreting and managing SPOT-MAS results. Clinical effectiveness is demonstrated through a series of identified cancer cases. Our research indicates that the protocol could empower healthcare professionals to confidently interpret circulating tumor DNA test results for 5 common types of cancer, thereby facilitating the clinical integration of MCED tests.

New tests can now screen for multiple types of cancer early, offering hope for better health outcomes. If one of these tests shows a positive result, doctors need to confirm it with imaging tests. We have developed a guide to help doctors understand and confirm these results. This guide could help healthcare professionals interpret results for five common types of cancer, making it easier to use these tests in regular medical practice.

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.

Insight into heavy metal chemical fractions in ash collected from municipal and industrial waste incinerators in northern Vietnam.

This investigation involved the collection of fly ash and bottom ash specimens from seven waste incinerators situated in the northern provinces of Vietnam, aimed at assessing the composition and distribution patterns of five chemical fractions of heavy metals (Pb, Cr, As, Cd Cu, and Zn) present in incinerator waste ash. The outcomes reveal that fly ash exhibited a relatively elevated concentration of industrial waste metals (25-66%) such as As, Cd, and Pb primarily in exchangeable (F1) and carbonate fractions (F2), which are mobile forms susceptible to environmental dissolution and consequential bioaccumulation posing health risks to humans. The predominant states of the metals Cr, Cu, and Zn were identified as residual, Fe-Mn oxide, and carbonate, respectively, with their relative proportions showing minimal variation. Conversely, heavy metals were predominantly present in residual residue and Fe-Mn bound form (F3) in bottom ash derived from both residential and commercial waste incineration operations. The non-carcinogenic hazard indices (HI) associated with the examined metals, ranked for both adults and children, were as follows: Pb > Cr > As > Cd > Cu > Zn. Notably, the HI values for Pb, Cr, and As exceeded the permissible threshold (HI > 1) for children. However, the risk of As, Cd, and Pb-related cancer via exposure pathways remained within acceptable limits for both age groups. Conversely, the probability of carcinogenic effects attributable to Cr surpassed the permissible threshold (>10-4), indicating significant health concerns associated with heavy metals in waste incinerators for humans, particularly children.

RNA therapeutics history and future perspectives.

Ribonucleic acid (RNA) therapeutics have significantly used RNA-based drugs to the prevention and treatment of diseases as effective messenger RNA-based vaccines in response to the COVID-19 pandemic. The RNA therapeutics with five classes including antisense oligonucleotide, small interfering RNA, microRNA, APTAMER and messenger RNAs are being quickly developed to treat various human diseases as neurological disease, cardiovascular disease, genetic and rare disease, cancer disease, coronavirus disease… which cannot be treated by other conventional drugs as small molecule-based drugs and antibodies. Therefore, the discovery of these RNA therapeutics created a new avenue for treatment of various human diseases. This chapter demonstrates the history of important discoveries in RNA biology and their impact on key developments in RNA therapeutics as well as the advantages of RNA therapeutics; RNA therapeutics describes the action mechanisms and examples of RNA-based drugs approved for treatment of various disease; and RNA therapeutics discusses delivery methods for RNA therapeutics to target organs and cells. In conclusion, this chapter is designed to offer an updated important development and advance of RNA therapeutics for the prevention and treatment of various human diseases.

Five undescribed aryltetralin lignans with cytotoxic activities from the fruits of Cleistanthus eberhardtii.

Five undescribed lignans, cleiseberharnins A-D (1-4), cleiseberharside A (5) were isolated from the fruits of Cleistanthus eberhartii (Phyllanthaceae), together with six known aryltetralin lignans, cleistantoxin (6), picroburseranin (7), neocleistantoxin (8), 7-hydroxypicropolygamain (9), cleisindoside D (10), and cleisindoside A (11). Their structures and relative configurations were established by analysis of HRESIMS and NMR data, and quantum chemical calculations of JH,H coupling constants. The absolute configurations of 1-5 were determined by analysis of their experimental CD spectra and comparison with calculated electronic circular dichroism (ECD) spectra. All compounds (1-11) were evaluated for their cytotoxicity against KB, MCF-7, HepG-2, and Lu-1 human cancer cell lines. Among the tested compounds, compounds 6 and 7 showed strong activity against KB, MCF7, HepG2 and Lu-1 cell lines with IC50 values in the range of 0.02-0.62 µM. Compound 1 showed activity against three cancer cell lines KB, HepG2, and Lu-1 with IC50 values of 6.98, 7.61 and 11.75 µM, respectively. Compound 2 exhibited a selective inhibition with moderate cytotoxicity against Lu-1 with IC50 value of 15.30 µM. Compounds 4, 5 and 9 showed moderate activity against the three cancer cell lines with IC50 values in the range of 8.73-19.70 µM.

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.

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.

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.

Survey-based cancer mortality in the Lao PDR, 2007-08.

BACKGROUND: The Lao PDR is a landlocked country with 5,920,000 inhabitants for which very few epidemiological studies on cancer have been performed. The aim of the present study was to examine cancer mortality in 2007-2008. METHODS: A descriptive cancer epidemiology protocol was designed with a data collection form and guideline for both demographics and list of all deaths from all 757 local Health Centers of 17 provinces/ cities. Five indicators, name, age, sex, date of death and the cause of death (ICD-10), were collected for each case. The age-specific cancer mortality rate and ASRs per 100,000 were estimated. RESULTS: There were 448 cancer cases reported from Health Centers within 7 of 17 provinces/cities. Number of person-years was 654,459 for the two-year period. Cancer mortality rates of all sites (ASR) were 116.7 and 97.2 per 100,000 in males and females, respectively. The five most common cancers causing mortality per 100,000 were liver (52.2), followed by colorectal (19.0), lung (17.3), stomach (6.9), and leukemia-lymphoma (7.2) in males and liver (28.4); followed by colorectal (19.0), lung (14.0), cervical uteri (9.2) and stomach (7.1) in females. CONCLUSIONS: Liver and colorectal cancers were the first and second most common, respectively, in both males and female.

A TNF region haplotype offers protection from typhoid fever in Vietnamese patients.

The genomic region surrounding the TNF locus on human chromosome 6 has previously been associated with typhoid fever in Vietnam (Dunstan et al. in J Infect Dis 183:261-268, 2001). We used a haplotypic approach to understand this association further. Eighty single nucleotide polymorphisms (SNPs) spanning a 150 kb region were genotyped in 95 Vietnamese individuals (typhoid case/mother/father trios). A subset of data from 33 SNPs with a minor allele frequency of >4.3% was used to construct haplotypes. Fifteen SNPs, which tagged the 42 constructed haplotypes were selected. The haplotype tagging SNPs (T1-T15) were genotyped in 380 confirmed typhoid cases and 380 Vietnamese ethnically matched controls. Allelic frequencies of seven SNPs (T1, T2, T3, T5, T6, T7, T8) were significantly different between typhoid cases and controls. Logistic regression results support the hypothesis that there is just one signal associated with disease at this locus. Haplotype-based analysis of the tag SNPs provided positive evidence of association with typhoid (posterior probability 0.821). The analysis highlighted a low-risk cluster of haplotypes that each carry the minor allele of T1 or T7, but not both, and otherwise carry the combination of alleles *12122*1111 at T1-T11, further supporting the one associated signal hypothesis. Finally, individuals that carry the typhoid fever protective haplotype *12122*1111 also produce a relatively low TNF-alpha response to LPS.