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Cell free DNA 5-hydroxymethylcytosine as an emerging marker of acute myeloid leukemia

ABSTRACT: Cell free DNA 5-hydroxymethylcytosine as an emerging marker of acute myeloid leukemia

PROVIDER: PRJNA687749 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13304200_1.fastq.gz	Fastqsanger.gz
	SRR13304200_2.fastq.gz	Fastqsanger.gz
	SRR13304201_1.fastq.gz	Fastqsanger.gz
	SRR13304201_2.fastq.gz	Fastqsanger.gz
	SRR13304202_1.fastq.gz	Fastqsanger.gz

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Cell free DNA 5-hydroxymethylcytosine as an emerging marker of acute myeloid leukemia

Project description:Aberrant changes in 5-hydroxymethylcytosine (5hmC) are a unique epigenetic feature in many cancers including acute myeloid leukemia (AML). However, genome-wide analysis of 5hmC in plasma cell-free DNA (cfDNA) remains unexploited in AML patients. We used a highly sensitive and robust nano-5hmC-Seal technology and profiled genome-wide 5hmC distribution in 239 plasma cfDNA samples from 103 AML patients and 81 non-cancer controls. We developed a 5hmC diagnostic model that precisely differentiates AML patients from controls with high sensitivity and specificity. We also developed a 5hmC prognostic model that accurately predicts prognosis in AML patients. High weighted prognostic scores (wp-scores) in AML patients were significantly associated with adverse overall survival (OS) in both training (P = 3.31e-05) and validation (P = .000464) sets. The wp-score was also significantly associated with genetic risk stratification and displayed dynamic changes with varied disease burden. Moreover, we found that high wp-scores in a single gene, BMS1 and GEMIN5 predicted OS in AML patients in both the training set (P =.023 and .031, respectively) and validation set (P = 9.66e-05 and 0.011, respectively). Lastly, our study demonstrated the genome-wide landscape of DNA hydroxymethylation in AML and revealed critical genes and pathways related to AML diagnosis and prognosis. Our data reveal plasma cfDNA 5hmC signatures as sensitive and accurate markers for AML diagnosis and prognosis. Plasma cfDNA 5hmC analysis will be an effective and minimally invasive tool for AML management.

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Cell-free DNA 5-hydroxymethylcytosine is an emerging marker of acute myeloid leukemia.

Project description:Aberrant changes in 5-hydroxymethylcytosine (5hmC) are a unique epigenetic feature in many cancers including acute myeloid leukemia (AML). However, genome-wide analysis of 5hmC in plasma cell-free DNA (cfDNA) remains unexploited in AML patients. We used a highly sensitive and robust nano-5hmC-Seal technology and profiled genome-wide 5hmC distribution in 239 plasma cfDNA samples from 103 AML patients and 81 non-cancer controls. We developed a 5hmC diagnostic model that precisely differentiates AML patients from controls with high sensitivity and specificity. We also developed a 5hmC prognostic model that accurately predicts prognosis in AML patients. High weighted prognostic scores (wp-scores) in AML patients were significantly associated with adverse overall survival (OS) in both training (P = 3.31e-05) and validation (P = 0.000464) sets. The wp-score was also significantly associated with genetic risk stratification and displayed dynamic changes with varied disease burden. Moreover, we found that high wp-scores in a single gene, BMS1 and GEMIN5 predicted OS in AML patients in both the training set (P = 0.023 and 0.031, respectively) and validation set (P = 9.66e-05 and 0.011, respectively). Lastly, our study demonstrated the genome-wide landscape of DNA hydroxymethylation in AML and revealed critical genes and pathways related to AML diagnosis and prognosis. Our data reveal plasma cfDNA 5hmC signatures as sensitive and accurate markers for AML diagnosis and prognosis. Plasma cfDNA 5hmC analysis will be an effective and minimally invasive tool for AML management.

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Project description:Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurate prediction of individual patient responses to ICIs remains a challenge. We performed a genome-wide analysis of 5-hydroxymethylcytosine (5hmC) in plasma cell-free DNA (cfDNA) samples from 83 lung cancer patients. Using machine learning approaches, we developed a 5hmC signature to predict ICI treatment response and calculated a weighted-predictive score (wp-score) based on the 5hmC levels of signature genes in each sample. A low wp-score was significantly correlated with longer progression-free survival across three independent patient sample sets, and demonstrated superior predictive capability to tumor programmed death-ligand 1. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. Our study suggests that cfDNA 5hmC analysis is a minimally invasive, innovative strategy for guiding treatment selection in lung cancer patients.

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