scholarly journals epiLiver a novel tumor specific, high throughput and cost-effective blood test for specific detection of liver cancer (HCC)

2021 ◽  
Author(s):  
David Cheishvili ◽  
Chifat Wong ◽  
Mohammad Mahbubul Karim ◽  
Mohammad Golam Kibria ◽  
Nusrat Jahan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Early Detection ◽  
High Throughput ◽  
Cost Effective ◽  
Gene Expression Omnibus ◽  
Morbidity And Mortality ◽  
Data Repository ◽  
Liquid Biopsies ◽  
Data Set ◽  
Normal Tissues

AbstractRobust cost effective and high-throughput tests for early detection of cancer in otherwise healthy people could potentially revolutionize public-health and the heavy personal and public burden of the morbidity and mortality from cancer. Several studies have delineated tumor specific DNA methylation profiles that could serve as biomarkers for early detection of Hepatocellular Carcinoma (HCC) as well as other cancers in liquid biopsies. Several published DNA methylation markers fail to distinguish HCC DNA from DNA from other tissues and other cancers that are potentially present in plasma. We describe a set of DNA methylation signatures in HCC that are “categorically” distinct from normal tissues and blood DNA methylation profiles. We develop a classifier combined of 4 CG sites that is sufficient to detect HCC in TCGA HCC data set at high accuracy. A single CG site at the F12 gene is sufficient to differentiate HCC samples from thousands of other blood samples, normal tissues and 31 tumors in the TCGA and Gene Expression Omnibus (GEO) data repository (n=11,704). A “next generation sequencing”-targeted-multiplexed high-throughput assay was developed, which was used to examine in a clinical study plasma samples from HCC, chronic hepatitis B (CHB) patients and healthy controls (n=398). The sensitivity for HCC detection was 84.5% at a specificity of 95% and AUC of 0.94. Applying this assay for routine follow up of people who are at high risk for developing HCC could have a significant impact on reducing the morbidity and mortality from HCC.

scholarly journals epiLiver a novel tumor specific, high throughput and cost-effective blood test for specific detection of liver cancer (HCC)

2021 ◽  
Author(s):  
David Cheishvili ◽  
Chifat Wong ◽  
Mohammad Karim ◽  
Mohammad Kibria ◽  
Nusrat Jahan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Early Detection ◽  
High Throughput ◽  
Cost Effective ◽  
Gene Expression Omnibus ◽  
Morbidity And Mortality ◽  
Data Repository ◽  
Liquid Biopsies ◽  
Data Set ◽  
Normal Tissues

Abstract Robust cost effective and high-throughput tests for early detection of cancer in otherwise healthy people could potentially revolutionize public-health and the heavy personal and public burden of the morbidity and mortality from cancer. Several studies have delineated tumor specific DNA methylation profiles that could serve as biomarkers for early detection of Hepatocellular Carcinoma (HCC) as well as other cancers in liquid biopsies. Several published DNA methylation markers fail to distinguish HCC DNA from DNA from other tissues and other cancers that are potentially present in plasma. We describe a set of DNA methylation signatures in HCC that are “categorically” distinct from normal tissues and blood DNA methylation profiles. We develop a classifier combined of 4 CG sites that is sufficient to detect HCC in TCGA HCC data set at high accuracy. A single CG site at the F12 gene is sufficient to differentiate HCC samples from thousands of other blood samples, normal tissues and 31 tumors in the TCGA and Gene Expression Omnibus (GEO) data repository (n = 11,704). A “next generation sequencing”-targeted-multiplexed high-throughput assay was developed, which was used to examine in a clinical study plasma samples from HCC, chronic hepatitis B (CHB) patients and healthy controls (n = 398). The sensitivity for HCC detection was 84.5% at a specificity of 95% and AUC of 0.94. Applying this assay for routine follow up of people who are at high risk for developing HCC could have a significant impact on reducing the morbidity and mortality from HCC.

scholarly journals Identification of Methylation Biomarkers for Early Detection of Prostate Cancer

2021 ◽  
Author(s):  
Yiyi Pu ◽  
Chao Li ◽  
Haining Yuan ◽  
Xiaoju Wang
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Early Detection ◽  
Early Diagnosis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prostate Tumors ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
Cancer Types

Abstract Background: DNA methylation has been widely used for development of cancer diagnosis biomarker. However, the clinical translational rate is low. Databases, such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), offer great opportunities for DNA methylation biomarker identification. By taking advantage of the public databases, we aimed to identify cancer specific biomarkers based on DNA methylation level for early detection purpose. Results: We performed a pan-cancer methylation analysis using datasets from TCGA and validated the results using GEO datasets. To identify early-diagnosis biomarkers, we focused on the localized tumors, and identified the biomarkers that can effectively distinguish the localized tumors from normal tissues. After comparing biomarkers for all cancer types, we identified a large group of cancer specific biomarkers. Within all 26 prostate cancer specific biomarkers selected, we confirmed three biomarker sets by multiplex analysis. First, 7 biomarkers (cg26140475, cg24891312, cg24522654, cg21359747, cg03254336, cg12697139, cg19034132) could detect localized prostate tumors from normal tissues (AUC > 0.9). Second, 9 biomarkers (cg17220055, cg26140475, cg24891312, cg09853702, cg22400059, cg16736279, cg27639613, cg06011086, cg00664697) could distinguish between low and high Gleason score prostate tumors (AUC = 0.79). Last, a single biomarker (cg26140475) completely separated prostate tumor from other urinary tumors (AUC = 1). Conclusions: Our study identified and validated a panel of methylation-based biomarkers which could be used for prostate cancer early diagnosis.

scholarly journals High-Throughput Detection of Multiple miRNAs and Methylated DNA by Droplet Digital PCR

2021 ◽  
Vol 11 (5) ◽  
pp. 359
Author(s):  
Ning Li ◽  
Pushpa Dhilipkannah ◽  
Feng Jiang
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Early Detection ◽  
Cancer Patients ◽  
High Throughput ◽  
Digital Pcr ◽  
Droplet Digital Pcr ◽  
Lung Cancer Patients ◽  
Molecular Aberrations ◽  
High Throughput Assay

Altered miRNA expression and DNA methylation have highly active and diverse roles in carcinogenesis. Simultaneous detection of the molecular aberrations may have a synergistic effect on the diagnosis of malignancies. Herein, we develop a high-throughput assay for detecting multiple miRNAs and DNA methylation using droplet digital PCR (ddPCR) coupled with a 96-microwell plate. The microplate-based ddPCR could absolutely and reproducibly quantify 15 miRNAs and 14 DNA methylation sites with a high sensitivity (one copy/µL and 0.1%, respectively). Analyzing sputum and plasma of 40 lung cancer patients and 36 cancer-free smokers by this approach identified an integrated biomarker panel consisting of two sputum miRNAs (miRs-31-5p and 210-3p), one sputum DNA methylation (RASSF1A), and two plasma miRNAs (miR-21-5p and 126) for the diagnosis of lung cancer with higher sensitivity and specificity compared with a single type of biomarker. The diagnostic value of the integrated biomarker panel for the early detection of lung cancer was confirmed in a different cohort of 36 lung cancer patients and 39 cancer-free smokers. The high-throughput assay for quantification of multiple molecular aberrations across sputum and plasma could improve the early detection of lung cancer.

scholarly journals Early detection of the major male cancer types in blood-based liquid biopsies using a DNA methylation panel

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Vera Constâncio ◽  
Sandra P. Nunes ◽  
Catarina Moreira-Barbosa ◽  
Rui Freitas ◽  
Jorge Oliveira ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Early Detection ◽  
Minimally Invasive ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Liquid Biopsies ◽  
Cell Lung Carcinoma ◽  
Cancer Types

Abstract Background Lung (LC), prostate (PCa) and colorectal (CRC) cancers are the most incident in males worldwide. Despite recent advances, optimal population-based cancer screening methods remain an unmet need. Due to its early onset, cancer specificity and accessibility in body fluids, aberrant DNA promoter methylation might be a valuable minimally invasive tool for early cancer detection. Herein, we aimed to develop a minimally invasive methylation-based test for simultaneous early detection of LC, PCa and CRC in males, using liquid biopsies. Results Circulating cell-free DNA was extracted from 102 LC, 121 PCa and 100 CRC patients and 136 asymptomatic donors’ plasma samples. Sodium-bisulfite modification and whole-genome amplification was performed. Promoter methylation levels of APCme, FOXA1me, GSTP1me, HOXD3me, RARβ2me, RASSF1Ame, SEPT9me and SOX17me were assessed by multiplex quantitative methylation-specific PCR. SEPT9me and SOX17me were the only biomarkers shared by all three cancer types, although they detected CRC with limited sensitivity. A “PanCancer” panel (FOXA1me, RARβ2me and RASSF1Ame) detected LC and PCa with 64% sensitivity and 70% specificity, complemented with “CancerType” panel (GSTP1me and SOX17me) which discriminated between LC and PCa with 93% specificity, but with modest sensitivity. Moreover, a HOXD3me and RASSF1Ame panel discriminated small cell lung carcinoma from non-small cell lung carcinoma with 75% sensitivity, 88% specificity, 6.5 LR+ and 0.28 LR–. An APCme and RASSF1Ame panel independently predicted disease-specific mortality in LC patients. Conclusions We concluded that a DNA methylation-based test in liquid biopsies might enable minimally invasive screening of LC and PCa, improving patient compliance and reducing healthcare costs. Moreover, it might assist in LC subtyping and prognostication.

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

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Glenn Rademakers ◽  
Maartje Massen ◽  
Alexander Koch ◽  
Muriel X. Draht ◽  
Nikkie Buekers ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Nervous System ◽  
Gene Ontology ◽  
Early Detection ◽  
Colon Adenocarcinoma ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Methylation Marker ◽  
Diagnostic Potential ◽  
Gene Ontology Enrichment

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

An efficient deep belief network for Detection of Coronavirus Disease COVID-19

2020 ◽  
pp. 05-13
Author(s):  
Shaymaa Adnan Abdulrahma ◽  
◽  
◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Deep Learning ◽  
Early Detection ◽  
Respiratory Diseases ◽  
Medical Images ◽  
Respiratory Viruses ◽  
Data Repository ◽  
Data Set ◽  
Belief Network ◽  
Learning Technique ◽  
Normal Lungs

COVID-19 infection is one of the most dangerous respiratory viruses and the early detection of this disease reduces the speed of its spread among people . The goal of this virus is to infect the lung by creating white patchy shadows inside the lungs. This paper presents an intelligent method based on the deep learning technique to analyze the medical images of respiratory diseases . Two data set was used in this experiment first dataset is normal lungs taken from Kaggle data repository. While abnormal lungs taken from (https://github.com/muhammedtalo/COVID-19) .The results show that the proposed system identifies the COVID-19 cases with an accuracy of 90%.

scholarly journals A machine learning case–control classifier for schizophrenia based on DNA methylation in blood

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chathura J. Gunasekara ◽  
Eilis Hannon ◽  
Harry MacKay ◽  
Cristian Coarfa ◽  
Andrew McQuillin ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Population Based ◽  
Case Control ◽  
Training Data ◽  
Polygenic Risk Score ◽  
Reverse Causality ◽  
Cell Type Specificity ◽  
Data Set ◽  
Human Genomic ◽  
Genomic Regions

AbstractEpigenetic dysregulation is thought to contribute to the etiology of schizophrenia (SZ), but the cell type-specificity of DNA methylation makes population-based epigenetic studies of SZ challenging. To train an SZ case–control classifier based on DNA methylation in blood, therefore, we focused on human genomic regions of systemic interindividual epigenetic variation (CoRSIVs), a subset of which are represented on the Illumina Human Methylation 450K (HM450) array. HM450 DNA methylation data on whole blood of 414 SZ cases and 433 non-psychiatric controls were used as training data for a classification algorithm with built-in feature selection, sparse partial least squares discriminate analysis (SPLS-DA); application of SPLS-DA to HM450 data has not been previously reported. Using the first two SPLS-DA dimensions we calculated a “risk distance” to identify individuals with the highest probability of SZ. The model was then evaluated on an independent HM450 data set on 353 SZ cases and 322 non-psychiatric controls. Our CoRSIV-based model classified 303 individuals as cases with a positive predictive value (PPV) of 80%, far surpassing the performance of a model based on polygenic risk score (PRS). Importantly, risk distance (based on CoRSIV methylation) was not associated with medication use, arguing against reverse causality. Risk distance and PRS were positively correlated (Pearson r = 0.28, P = 1.28 × 10−12), and mediational analysis suggested that genetic effects on SZ are partially mediated by altered methylation at CoRSIVs. Our results indicate two innate dimensions of SZ risk: one based on genetic, and the other on systemic epigenetic variants.

scholarly journals Blood-Based Detection of Colorectal Cancer Using Cancer-Specific DNA Methylation Markers

Diagnostics ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 51
Author(s):  
Nam-Yun Cho ◽  
Ji-Won Park ◽  
Xianyu Wen ◽  
Yun-Joo Shin ◽  
Jun-Kyu Kang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Sensitivity And Specificity ◽  
Stage Iv ◽  
High Sensitivity ◽  
Liquid Biopsies ◽  
Blood Leukocytes ◽  
Marker Panel ◽  
A Genome ◽  
Methylight Assay

Cancer tissues have characteristic DNA methylation profiles compared with their corresponding normal tissues that can be utilized for cancer diagnosis with liquid biopsy. Using a genome-scale DNA methylation approach, we sought to identify a panel of DNA methylation markers specific for cell-free DNA (cfDNA) from patients with colorectal cancer (CRC). By comparing DNA methylomes between CRC and normal mucosal tissues or blood leukocytes, we identified eight cancer-specific methylated loci (ADGRB1, ANKRD13, FAM123A, GLI3, PCDHG, PPP1R16B, SLIT3, and TMEM90B) and developed a five-marker panel (FAM123A, GLI3, PPP1R16B, SLIT3, and TMEM90B) that detected CRC in liquid biopsies with a high sensitivity and specificity with a droplet digital MethyLight assay. In a set of cfDNA samples from CRC patients (n = 117) and healthy volunteers (n = 60), a panel of five markers on the platform of the droplet digital MethyLight assay detected stages I–III and stage IV CRCs with sensitivities of 45.9% and 95.7%, respectively, and a specificity of 95.0%. The number of detected markers was correlated with the cancer stage, perineural invasion, lymphatic emboli, and venous invasion. Our five-marker panel with the droplet digital MethyLight assay showed a high sensitivity and specificity for the detection of CRC with cfDNA samples from patients with metastatic CRC.

Oral Cancer: Raising Awareness of the Importance of Suspicion in Early Detection

2021 ◽  
Vol 10 (1) ◽  
pp. 10-12
Author(s):  
Farooq Ahmed ◽  
Honieh Bolooki ◽  
Senathrajah Ariyaratnam ◽  
Michael N. Pemberton
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cancer ◽  
Early Detection ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Verrucous Carcinoma ◽  
Mucosal Lesion ◽  
Morbidity And Mortality ◽  
Raising Awareness ◽  
Suspicious Lesions

Oral cancer is a significant cause of morbidity and mortality worldwide. In this article we present two cases of potentially innocuous looking lesions, initially thought to be traumatic in origin, but later diagnosed as cancer. The first patient presented with a persistent laceration thought to be caused by an accidental shaving injury, which was subsequently diagnosed as squamous cell carcinoma. The second patient presented with a hyperplastic mucosal lesion, suspected as forming due to denture-clasp irritation, which was subsequently diagnosed as proliferative verrucous carcinoma. The importance of early detection and palpation of suspicious lesions is emphasised in this article.

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