Abstract
BackgroundLung cancer is one of most common cancers worldwide, with a 5-year survival rate of less than 20%, which is mainly due to late-stage diagnosis. Noninvasive methods using 5-hydroxymethylation of cytosine (5hmC) modifications and fragmentation profiles from 5hmC cell-free DNA (cfDNA) sequencing provide an opportunity for lung cancer detection and management.ResultsA total of 157 lung cancer patients were recruited to generate the largest lung cancer cfDNA 5hmC dataset, which mainly consisted of 62 lung adenocarcinoma (LUAD), 48 lung squamous cell carcinoma (LUSC) and 25 small cell lung cancer (SCLC) patients, with most patients (131, 83.44%) at advanced tumor stages. A 37-feature 5hmC model was constructed and validated to distinguish lung cancer patients from healthy controls, with areas under the curve (AUCs) of 0.8938 and 0.8476 (sensitivity = 87.50% and 72.73%, specificity = 83.87% and 80.60%) in two distinct validation sets. Furthermore, fragment profiles of cfDNA 5hmC datasets were first explored to develop a 48-feature fragmentation model with good performance (AUC = 0.9257 and 0.822, sensitivity = 87.50% and 78.79%, specificity = 80.65% and 76.12%) in the two validation sets. Another diagnostic model integrating 5hmC signals and fragment profiles improved AUC to 0.9432 and 0.8639 (sensitivity = 87.50% and 83.33%, specificity = 90.30% and 77.61%) in the two validation sets, better than models based on either of them alone and performing well in different stages and lung cancer subtypes. Several 5hmC markers were found to be associated with overall survival (OS) and disease-free survival (DFS) based on gene expression data from The Cancer Genome Atlas (TCGA).ConclusionsBoth the 5hmC signal and fragmentation profiles in 5hmC cfDNA data are sensitive and effective in lung cancer detection and could be incorporated into the diagnostic model to achieve good performance, promoting research focused on clinical diagnostic models based on cfDNA 5hmC data.Graphical abstract
Highlights
Lung cancer is one of most common cancers worldwide, with a 5-year survival rate of less than 20%, which is mainly due to late-stage diagnosis
Corresponding genes of several 5-hydroxymethylation of cytosine (5hmC) markers were found to be associated with overall survival (OS) and disease-free survival (DFS) in gene expression data from The Cancer Genome Atlas (TCGA)
Characteristics of samples and cell-free DNA (cfDNA) 5hmC sequencing data To gain a comprehensive understanding of genome-wide 5hmC modifications and fragmentation related to lung cancer, we recruited 189 healthy individuals and 157 Chinese-descent lung cancer patients in our study (Fig. 1a, Table 1), which mainly included 62 lung adenocarcinoma (LUAD), 48 lung squamous cell carcinoma (LUSC), and 25 small cell lung cancer (SCLC) patients
Summary
Lung cancer is one of most common cancers worldwide, with a 5-year survival rate of less than 20%, which is mainly due to late-stage diagnosis. Noninvasive methods using 5-hydroxymethylation of cytosine (5hmC) modifications and fragmentation profiles from 5hmC cell-free DNA (cfDNA) sequencing provide an opportunity for lung cancer detection and management. Lung cancer is the most common cause of cancer death worldwide [1], causing approximately 1.6 million deaths annually, with a low five-year survival rate of approximately 15.9% due to difficult diagnosis at an early stage [2]. Several studies have investigated proteins, gene expression levels or microRNAs [8,9,10,11,12] as promising biomarkers in early detection, but few have been approved for routine clinical screening due to the high false-positive rate [2, 13]. There is an urgent clinical need for the development of noninvasive approaches to improve SCLC early detection and the general population. The potency and reliability of cell-free 5hmC as a diagnostic biomarker for SCLC remain elusive
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