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DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7225136/ https://www.ncbi.nlm.nih.gov/pubmed/32420067 http://dx.doi.org/10.21037/tlcr.2020.03.13 |
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author | Chen, Zisheng Xiong, Shan Li, Jianfu Ou, Limin Li, Caichen Tao, Jinsheng Jiang, Zeyu Fan, Jianbing He, Jianxing Liang, Wenhua |
author_facet | Chen, Zisheng Xiong, Shan Li, Jianfu Ou, Limin Li, Caichen Tao, Jinsheng Jiang, Zeyu Fan, Jianbing He, Jianxing Liang, Wenhua |
author_sort | Chen, Zisheng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7225136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-72251362020-05-15 DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model Chen, Zisheng Xiong, Shan Li, Jianfu Ou, Limin Li, Caichen Tao, Jinsheng Jiang, Zeyu Fan, Jianbing He, Jianxing Liang, Wenhua Transl Lung Cancer Res Original Article 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. AME Publishing Company 2020-04 /pmc/articles/PMC7225136/ /pubmed/32420067 http://dx.doi.org/10.21037/tlcr.2020.03.13 Text en 2020 Translational Lung Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Chen, Zisheng Xiong, Shan Li, Jianfu Ou, Limin Li, Caichen Tao, Jinsheng Jiang, Zeyu Fan, Jianbing He, Jianxing Liang, Wenhua DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
title | DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
title_full | DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
title_fullStr | DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
title_full_unstemmed | DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
title_short | DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
title_sort | dna methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7225136/ https://www.ncbi.nlm.nih.gov/pubmed/32420067 http://dx.doi.org/10.21037/tlcr.2020.03.13 |
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