DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model

Zisheng Chen; Shan Xiong; Jianfu Li; Limin Ou; Caichen Li; Jinsheng Tao; Zeyu Jiang; Jianbing Fan; Jianxing He; Wenhua Liang

doi:10.21037/tlcr.2020.03.13

DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model

Transl Lung Cancer Res. 2020 Apr;9(2):280-287. doi: 10.21037/tlcr.2020.03.13.

Authors

Zisheng Chen^{1

2}, Shan Xiong², Jianfu Li², Limin Ou², Caichen Li², Jinsheng Tao³, Zeyu Jiang³, Jianbing Fan³, Jianxing He², Wenhua Liang²

Affiliations

¹ Department of Respiratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan 511518, China.
² Department of Thoracic Surgery and Oncology, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease and National Clinical Research Centre for Respiratory Disease, Guangzhou 510120, China.
³ AnchorDx Medical Co. Ltd., Guangzhou 510300, China.

Abstract

Background: Lymph node (LN) metastasis status is the most important prognostic factor and determines treatment strategy. Methylation alteration is an optimal candidate to trace the signal from early stage tumors due to its early existence, multiple loci and stability in blood. We built a diagnostic tool to screen and identify a set of plasma methylation markers in early stage occult LN metastasis.

Methods: High-throughput targeted methylation sequencing was performed on tissue and matched plasma samples from a cohort of 119 non-small cell lung cancer (NSCLC) patients with a primary lesion of less than 3.0 cm in diameter. The methylation profiles were compared between patients with and without occult LN metastases. We carried out a set of machine-learning analyses on our discovery cohort to evaluate the utility of cell free DNA methylation profiles in early detection of LN metastasis. Two preliminary prognostic models predictive of LN metastasis were built by random forest with differentially methylated markers shared by plasma and tissue samples and markers present either in plasma or tissue samples respectively. The performance of these models was then evaluated using receiver operating characteristic (ROC) statistics derived from ten-fold cross validation repeated ten times.

Results: Within this cohort, 27 cases (27/119, 22.7%) were found to have occult LN metastases found by pathological examination. Compared with those without metastases, 878 and 52 genes were differentially methylated in terms of tissue (MTA3, MIR548H4, HIST3H2A, etc.) and plasma (CIRBP, CHGB, FCHO1, etc.) respectively. 19 of these genes (ICAM1, EPH4, COCH, etc.) were overlapped. We selected 22 pairs of cases with or without occult LN metastasis by matching gender, age, smoking history and tumor histology to build and test the plasma model. The AUC of the preliminary prediction model using markers shared by plasma and tissue samples and markers present either in plasma or tissue samples is 88.6% (95% CI, 87.8-89.4%) and 74.9% (95% CI, 72.2-77.6%) respectively.

Conclusions: We identified a set of specific plasma methylation markers for early occult LN metastasis of NSCLC and established a preliminary non-invasive blood diagnostic tool.

Keywords: Occult lymph node metastasis; methylation; non-small cell lung cancer (NSCLC); plasma cell-free DNA.