Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma

Abstract Introduction Targeted therapies are based on specific gene alterations. Various specimen types have been used to determine gene alterations, however, no systemic comparisons have yet been made. Herein, we assessed alterations in selected cancer‐associated genes across varying sample sites i...

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Main Authors: Yuwei Liao, Zhaokui Ma, Yu Zhang, Dan Li, Dekang Lv, Zhisheng Chen, Peiying Li, Aisha AI‐Dherasi, Feng Zheng, Jichao Tian, Kun Zou, Yue Wang, Dongxia Wang, Miguel Cordova, Huan Zhou, Xiuhua Li, Dan Liu, Ruofei Yu, Qingzheng Zhang, Xiaolong Zhang, Jian Zhang, Xuehong Zhang, Xia Zhang, Yulong Li, Yanyan Shao, Luyao Song, Ruimei Liu, Yichen Wang, Sufiyan Sufiyan, Quentin Liu, Gareth I. Owen, Zhiguang Li, Jun Chen
Format: Article
Language:English
Published: Wiley 2019-09-01
Series:Cancer Medicine
Subjects:
Online Access:https://doi.org/10.1002/cam4.2458
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language English
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author Yuwei Liao
Zhaokui Ma
Yu Zhang
Dan Li
Dekang Lv
Zhisheng Chen
Peiying Li
Aisha AI‐Dherasi
Feng Zheng
Jichao Tian
Kun Zou
Yue Wang
Dongxia Wang
Miguel Cordova
Huan Zhou
Xiuhua Li
Dan Liu
Ruofei Yu
Qingzheng Zhang
Xiaolong Zhang
Jian Zhang
Xuehong Zhang
Xia Zhang
Yulong Li
Yanyan Shao
Luyao Song
Ruimei Liu
Yichen Wang
Sufiyan Sufiyan
Quentin Liu
Gareth I. Owen
Zhiguang Li
Jun Chen
spellingShingle Yuwei Liao
Zhaokui Ma
Yu Zhang
Dan Li
Dekang Lv
Zhisheng Chen
Peiying Li
Aisha AI‐Dherasi
Feng Zheng
Jichao Tian
Kun Zou
Yue Wang
Dongxia Wang
Miguel Cordova
Huan Zhou
Xiuhua Li
Dan Liu
Ruofei Yu
Qingzheng Zhang
Xiaolong Zhang
Jian Zhang
Xuehong Zhang
Xia Zhang
Yulong Li
Yanyan Shao
Luyao Song
Ruimei Liu
Yichen Wang
Sufiyan Sufiyan
Quentin Liu
Gareth I. Owen
Zhiguang Li
Jun Chen
Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma
Cancer Medicine
lung cancer
next‐generation sequencing
NOTCH1
plasma
pleural effusion
author_facet Yuwei Liao
Zhaokui Ma
Yu Zhang
Dan Li
Dekang Lv
Zhisheng Chen
Peiying Li
Aisha AI‐Dherasi
Feng Zheng
Jichao Tian
Kun Zou
Yue Wang
Dongxia Wang
Miguel Cordova
Huan Zhou
Xiuhua Li
Dan Liu
Ruofei Yu
Qingzheng Zhang
Xiaolong Zhang
Jian Zhang
Xuehong Zhang
Xia Zhang
Yulong Li
Yanyan Shao
Luyao Song
Ruimei Liu
Yichen Wang
Sufiyan Sufiyan
Quentin Liu
Gareth I. Owen
Zhiguang Li
Jun Chen
author_sort Yuwei Liao
title Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma
title_short Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma
title_full Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma
title_fullStr Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma
title_full_unstemmed Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma
title_sort targeted deep sequencing from multiple sources demonstrates increased notch1 alterations in lung cancer patient plasma
publisher Wiley
series Cancer Medicine
issn 2045-7634
publishDate 2019-09-01
description Abstract Introduction Targeted therapies are based on specific gene alterations. Various specimen types have been used to determine gene alterations, however, no systemic comparisons have yet been made. Herein, we assessed alterations in selected cancer‐associated genes across varying sample sites in lung cancer patients. Materials and Methods Targeted deep sequencing for 48 tumor‐related genes was applied to 153 samples from 55 lung cancer patients obtained from six sources: Formalin‐fixed paraffin‐embedded (FFPE) tumor tissues, pleural effusion supernatant (PES) and pleural effusion cell sediments (PEC), white blood cells (WBCs), oral epithelial cells (OECs), and plasma. Results Mutations were detected in 96% (53/55) of the patients and in 83% (40/48) of the selected genes. Each sample type exhibited a characteristic mutational pattern. As anticipated, TP53 was the most affected sequence (54.5% patients), however this was followed by NOTCH1 (36%, across all sample types). EGFR was altered in patient samples at a frequency of 32.7% and KRAS 10.9%. This high EGFR/ low KRAS frequency is in accordance with other TCGA cohorts of Asian origin but differs from the Caucasian population where KRAS is the more dominant mutation. Additionally, 66% (31/47) of PEC samples had copy number variants (CNVs) in at least one gene. Unlike the concurrent loss and gain in most genes, herein NOTCH1 loss was identified in 21% patients, with no gain observed. Based on the relative prevalence of mutations and CNVs, we divided lung cancer patients into SNV‐dominated, CNV‐dominated, and codominated groups. Conclusions Our results confirm previous reports that EGFR mutations are more prevalent than KRAS in Chinese lung cancer patients. NOTCH1 gene alterations are more common than previously reported and reveals a role of NOTCH1 modifications in tumor metastasis. Furthermore, genetic material from malignant pleural effusion cell sediments may be a noninvasive manner to identify CNV and participate in treatment decisions.
topic lung cancer
next‐generation sequencing
NOTCH1
plasma
pleural effusion
url https://doi.org/10.1002/cam4.2458
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spelling doaj-6f26b75592cd42e5bff856217eb2dd782020-11-25T02:04:19ZengWileyCancer Medicine2045-76342019-09-018125673568610.1002/cam4.2458Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasmaYuwei Liao0Zhaokui Ma1Yu Zhang2Dan Li3Dekang Lv4Zhisheng Chen5Peiying Li6Aisha AI‐Dherasi7Feng Zheng8Jichao Tian9Kun Zou10Yue Wang11Dongxia Wang12Miguel Cordova13Huan Zhou14Xiuhua Li15Dan Liu16Ruofei Yu17Qingzheng Zhang18Xiaolong Zhang19Jian Zhang20Xuehong Zhang21Xia Zhang22Yulong Li23Yanyan Shao24Luyao Song25Ruimei Liu26Yichen Wang27Sufiyan Sufiyan28Quentin Liu29Gareth I. Owen30Zhiguang Li31Jun Chen32The Second Hospital of Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaAdvanced Institute for Medical Sciences Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaThe First Affiliated Hospital of Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaFaculty of Biological Sciences Pontificia Universidad Católica de Chile Santiago ChileThe Second Hospital of Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaFaculty of Biological Sciences Pontificia Universidad Católica de Chile Santiago ChileCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell Dalian Medical University Dalian ChinaThe Second Hospital of Dalian Medical University Dalian ChinaAbstract Introduction Targeted therapies are based on specific gene alterations. Various specimen types have been used to determine gene alterations, however, no systemic comparisons have yet been made. Herein, we assessed alterations in selected cancer‐associated genes across varying sample sites in lung cancer patients. Materials and Methods Targeted deep sequencing for 48 tumor‐related genes was applied to 153 samples from 55 lung cancer patients obtained from six sources: Formalin‐fixed paraffin‐embedded (FFPE) tumor tissues, pleural effusion supernatant (PES) and pleural effusion cell sediments (PEC), white blood cells (WBCs), oral epithelial cells (OECs), and plasma. Results Mutations were detected in 96% (53/55) of the patients and in 83% (40/48) of the selected genes. Each sample type exhibited a characteristic mutational pattern. As anticipated, TP53 was the most affected sequence (54.5% patients), however this was followed by NOTCH1 (36%, across all sample types). EGFR was altered in patient samples at a frequency of 32.7% and KRAS 10.9%. This high EGFR/ low KRAS frequency is in accordance with other TCGA cohorts of Asian origin but differs from the Caucasian population where KRAS is the more dominant mutation. Additionally, 66% (31/47) of PEC samples had copy number variants (CNVs) in at least one gene. Unlike the concurrent loss and gain in most genes, herein NOTCH1 loss was identified in 21% patients, with no gain observed. Based on the relative prevalence of mutations and CNVs, we divided lung cancer patients into SNV‐dominated, CNV‐dominated, and codominated groups. Conclusions Our results confirm previous reports that EGFR mutations are more prevalent than KRAS in Chinese lung cancer patients. NOTCH1 gene alterations are more common than previously reported and reveals a role of NOTCH1 modifications in tumor metastasis. Furthermore, genetic material from malignant pleural effusion cell sediments may be a noninvasive manner to identify CNV and participate in treatment decisions.https://doi.org/10.1002/cam4.2458lung cancernext‐generation sequencingNOTCH1plasmapleural effusion