Project description:Background & Aims. Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods. To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results. We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded AUROCs of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Conclusions. 5mC markers derived from cfDNA robustly identify HCC within a cirrhotic liver background indicating that further validation is warranted. Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.

Project description:Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods: To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results: We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded area under the receiver operating characteristic (AUROC) curves of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Validation of a 5-marker panel created from combining hypermethylated and hypomethylated CpGs in an independent cfDNA set by bisulfite pyrosequencing yielded an AUROC of 0.956, compared to the discovery AUROC of 0.996. Conclusion: Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.

Project description:Despite more than a century fighting against tuberculosis, the World Health Organisation has estimated that around 1.7 million people died of tuberculosis in 2016 and over a quarter of the world’s population is infected. One of the critical hurdles for stopping tuberculosis transmission is early and effective diagnosis of patients with the active pulmonary disease. Although important innovations in molecular diagnosis have been recently developed (e.g. Xpert MTB/RIF, Cepheid Inc., USA), there are no suitable tests for population screening at point-of-care. The current tuberculosis diagnosis pipeline presents a highly variable performance and requires access to reference laboratory facilities. A non-sputum based rapid test with high specificity and sensitivity could save ~400,000 lives per year. Therefore, new biomarkers for diagnosis are urgently required for identifying patients with early symptoms and to expedite treatment. Variable sensitivity and specificity can be overcome using a combination of multiple biomarkers (5). Proteins, as ultimate biological effectors, are ideal candidates for diagnostic biomarkers; consequently, proteomic studies are a crucial platform for biomarker discovery in tuberculosis. This work aims to develop a multi-marker panel for tuberculosis diagnosis with high performance capable of differentiating tuberculosis patients from relevant controls. Quantitative Multidimensional Protein Identification Technology (qMudPIT) is applied for biomarker discovery identifying candidates for early diagnosis of tuberculosis. The multidimensional method optimised in this work led to the identification of 5022 plasma proteins and 3577 quantified proteins using iTRAQ labelling. Known and completely novel markers for active tuberculosis in plasma were identified including a peptide derived from Mycobacterium tuberculosis. Complementary statistical and bioinformatic analysis were applied to prioritise candidates for validation in one or two independent cohorts. The plasma proteomic profile here described represents a power strategy for biomarker discovery and the panel proposed has the potential to be translated to a rapid test and which might contribute to tuberculosis control.

Project description:Background: Circular RNA (circRNA) has been reported to be involved in the pathogenesis of cardiovascular disease (CVD), however, it is unclear whether circRNA carried by exosomes (exos) can be used as biomarkers for chronic coronary syndrome (CCS). This study aimed to investigate the expression pattern of exosomal circRNAs in the plasma of CCS patients, and to screen exo-circRNAs that can act as biomarkers for the diagnosis of CCS. Methods: High-throughput sequencing technology was carried out in the plasma exosomal RNA of 15 CCS patients and 15 non-cardiac chest pain patients (NCCP, control group) (sequencing cohort) to screen for differentially expressed circRNAs. Selected differentially expressed exo-circRNAs were further verified by real time polymerase chain reaction (RT-PCR) in a small-sample cohort (derivation cohort) and a large-sample cohort (validation cohort). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of exo-circRNAs for CCS patients. Results: By high-throughput sequencing of circRNAs in 15 CCS patients and 15 NCCP patients, 276 circRNAs differentially expressed in plasma exosomes of CCS patients were screened by using |log2(Fold change) |>1 and q-value<0.001, and 103 were up-regulated and 173 were down-regulated. Among the 103 up-regulated circRNAs, 5 circRNAs with high expression levels and significantly increased in plasma exosomes of CCS patients were selected for validation. Twice RT-PCR validation demonstrated that exo-hsa_circ_0075269 and exo-hsa_circ_0000284 were significantly up-regulated in patients with CCS (P<0.001). Circulating exo-hsa_circ_0075269 and exo-hsa_circ_0000284 yielded the area under the curve (AUC) values of 0.761 (P<0.001, 95%CI=0.669, 0.852) and 0.623 (P=0.015, 95%CI=0.522, 0.724) for CCS, respectively by ROC curve analysis. Moreover, AUC of hsa_circ_0075269 combined with hsa_circ_0000284 for diagnosing CCS was 0.741 (P<0.001, 95%CI=0.667, 0.850). Conclusion: The expression profile of circRNA in plasma exosomes of patients with CCS was significantly different from that of the control group. Plasma exo-hsa_circ_0075269 and exo-hsa_circ_0000284 have the potential to be new biomarkers for CCS diagnosis.

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Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

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