Project description:We used a highly sensitive nano-5hmC-Seal method and profiled the genome-wide distribution of 5-hydroxymethylcytosine (5hmC) in plasma cell-free DNA (cfDNA) from 384 patients with bladder, breast, colorectal, kidney, lung, or prostate cancer and 221 controls. We used machine learning and developed plasma cfDNA 5hmC signatures that are highly sensitive for cancer detection and cancer origin determination. We also identified genes and signaling pathways with aberrant DNA hydroxymethylation in six cancers.
Project description:aCGH experiment on cell-free DNA collected from the plasma of patients with castration-resistant prostate cancer. No replicates. castration-resistant prostate cancer vs male reference DNA
Project description:5-Hydroxymethylcytosine (5hmC) is an important mammalian DNA epigenetic modification that has been linked to gene regulation and cancer pathogenesis. Here we explored the diagnostic potential of 5hmC in cell-free DNA (cfDNA), the circulating DNA found in human plasma which represents a noninvasive window into the health status of the body. We showed that the genome-wide 5hmC distribution in cfDNA can be reliably sequenced by chemical labeling-based 5hmC enrichment. We sequenced cell-free 5hmC from 49 patients of seven different cancer types and found distinct features that can be used for monitoring disease status and progression. Specifically, we discovered that lung cancer leads to a stage-dependent hypohydroxymethlation in cfDNA, whereas hepatocellular carcinoma (HCC) and pancreatic cancer lead to disease-specific changes in the cell-free hydroxymethylome. Our results demonstrate that cell-free 5hmC can be used not only to track the stage of cancer but also to identify tissue of origin in some solid tumors.
Project description:The epigenome of plasma cell-free DNA (cfDNA) has demonstrated promise as both a prognostic and predictive cancer biomarker in liquid biopsies. Currently, it remains unknown whether and why cfDNA 5-hydroxymethylcytosine (5hmC) can identify disease state for non-small cell lung cancer (NSCLC). We profiled 5-hydroxymethylomes using the plasma cfDNA of 302 EGFR-mutant NSCLC patients with different disease states. We found NSCLCs were epigenetically heterogeneous among individuals, especially for cfDNA 5hmC on gene EGFR. The diversity of age, sex, race, smoking status, EGFR-mutation of patients increased the epigenetic heterogeneity of NSCLC, however, only smoking status shaped disease state-associated cfDNA 5hmC. More importantly, disease state-dependent and patients’ characteristics-independent cfDNA 5hmC can be linked to lung function and regulatory elements in human lung cells. Interestingly, although 5-hydroxymethylome heterogeneity of plasma cfDNA among NSCLC patients were detected substantially, cfDNA-5hmC-based machine learning model can accurately predict different disease state in NSCLC.
Project description:Prostate cancer is the second most occurring cancer in men worldwide, and with the advances made with screening for prostate-specific antigen, it has been prone to early diagnosis and over-treatment. To better understand the mechanisms of tumorigenesis and possible treatment responses, we developed a mathematical model of prostate cancer which considers the major signalling pathways known to be deregulated. The model includes pathways such as androgen receptor, MAPK, Wnt, NFkB, PI3K/AKT, MAPK, mTOR, SHH, the cell cycle, the epithelial-mesenchymal transition (EMT), apoptosis and DNA damage pathways. The final model accounts for 133 nodes and 449 edges. We applied a methodology to personalise this Boolean model to molecular data to reflect the heterogeneity and specific response to perturbations of cancer patients, using TCGA and GDSC datasets.
2022-06-22 | MODEL2106070001 | BioModels
Project description:cell-free DNA sequencing of plasma
| PRJNA687910 | ENA
Project description:Cell free plasma DNA sequenced for T-cell Lymphoma patients