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A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer

BACKGROUND: Currently, pathological examination of gastroscopy biopsy specimens is the gold standard for gastric cancer (GC) diagnosis. However, it has a false-negative rate of 10–20% due to inaccurate sampling locations and/or insufficient sampling amount. A signature should be developed to aid the...

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Autores principales: Yan, Haidan, Li, Meifeng, Cao, Longlong, Chen, Haifeng, Lai, Hungming, Guan, Qingzhou, Chen, Huxing, Zhou, Wenbin, Zheng, Baotong, Guo, Zheng, Zheng, Chaohui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394047/
https://www.ncbi.nlm.nih.gov/pubmed/30819200
http://dx.doi.org/10.1186/s12967-019-1816-4
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author Yan, Haidan
Li, Meifeng
Cao, Longlong
Chen, Haifeng
Lai, Hungming
Guan, Qingzhou
Chen, Huxing
Zhou, Wenbin
Zheng, Baotong
Guo, Zheng
Zheng, Chaohui
author_facet Yan, Haidan
Li, Meifeng
Cao, Longlong
Chen, Haifeng
Lai, Hungming
Guan, Qingzhou
Chen, Huxing
Zhou, Wenbin
Zheng, Baotong
Guo, Zheng
Zheng, Chaohui
author_sort Yan, Haidan
collection PubMed
description BACKGROUND: Currently, pathological examination of gastroscopy biopsy specimens is the gold standard for gastric cancer (GC) diagnosis. However, it has a false-negative rate of 10–20% due to inaccurate sampling locations and/or insufficient sampling amount. A signature should be developed to aid the early diagnosis of GC using biopsy specimens even when they are sampled from inaccurate locations. METHODS: We extracted a robust qualitative transcriptional signature, based on the within-sample relative expression orderings (REOs) of gene pairs, to discriminate both GC tissues and adjacent-normal tissues from non-GC gastritis, intestinal metaplasia and normal gastric tissues. RESULTS: A signature consisting of two gene pairs for GC diagnosis was identified and validated in data of both biopsy specimens and surgical resection specimens pooled from publicly available datasets measured by different laboratories with different platforms. For gastroscopy biopsy specimens, 96.20% of 79 non-GC tissues were correctly identified as non-GC, and 96.84% of 158 GC tissues and six of seven adjacent-normal tissues were correctly identified as GC. For surgical resection specimens, 98.37% of 2560 GC tissues and 97.28% of 221 adjacent-normal tissues were correctly identified as GC. Especially, 97.67% of the 257 GC patients at stage I were exactly diagnosed as GC. We additionally measured 21 GC tissues from seven different GC patients, each with three specimens sampled from three tumor locations with different proportions of the tumor epithelial cell. All these GC tissues were correctly identified as GC, even when the proportion of the tumor epithelial cell was as low as 14%. CONCLUSIONS: The qualitative transcriptional signature can distinguish both GC and adjacent-normal tissues from normal, gastritis and intestinal metaplasia tissues of non-GC patients even using inaccurately sampled biopsy specimens, which can be applied robustly at the individual level to aid the early GC diagnosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1816-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-63940472019-03-11 A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer Yan, Haidan Li, Meifeng Cao, Longlong Chen, Haifeng Lai, Hungming Guan, Qingzhou Chen, Huxing Zhou, Wenbin Zheng, Baotong Guo, Zheng Zheng, Chaohui J Transl Med Research BACKGROUND: Currently, pathological examination of gastroscopy biopsy specimens is the gold standard for gastric cancer (GC) diagnosis. However, it has a false-negative rate of 10–20% due to inaccurate sampling locations and/or insufficient sampling amount. A signature should be developed to aid the early diagnosis of GC using biopsy specimens even when they are sampled from inaccurate locations. METHODS: We extracted a robust qualitative transcriptional signature, based on the within-sample relative expression orderings (REOs) of gene pairs, to discriminate both GC tissues and adjacent-normal tissues from non-GC gastritis, intestinal metaplasia and normal gastric tissues. RESULTS: A signature consisting of two gene pairs for GC diagnosis was identified and validated in data of both biopsy specimens and surgical resection specimens pooled from publicly available datasets measured by different laboratories with different platforms. For gastroscopy biopsy specimens, 96.20% of 79 non-GC tissues were correctly identified as non-GC, and 96.84% of 158 GC tissues and six of seven adjacent-normal tissues were correctly identified as GC. For surgical resection specimens, 98.37% of 2560 GC tissues and 97.28% of 221 adjacent-normal tissues were correctly identified as GC. Especially, 97.67% of the 257 GC patients at stage I were exactly diagnosed as GC. We additionally measured 21 GC tissues from seven different GC patients, each with three specimens sampled from three tumor locations with different proportions of the tumor epithelial cell. All these GC tissues were correctly identified as GC, even when the proportion of the tumor epithelial cell was as low as 14%. CONCLUSIONS: The qualitative transcriptional signature can distinguish both GC and adjacent-normal tissues from normal, gastritis and intestinal metaplasia tissues of non-GC patients even using inaccurately sampled biopsy specimens, which can be applied robustly at the individual level to aid the early GC diagnosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1816-4) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-28 /pmc/articles/PMC6394047/ /pubmed/30819200 http://dx.doi.org/10.1186/s12967-019-1816-4 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Yan, Haidan
Li, Meifeng
Cao, Longlong
Chen, Haifeng
Lai, Hungming
Guan, Qingzhou
Chen, Huxing
Zhou, Wenbin
Zheng, Baotong
Guo, Zheng
Zheng, Chaohui
A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
title A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
title_full A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
title_fullStr A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
title_full_unstemmed A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
title_short A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
title_sort robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394047/
https://www.ncbi.nlm.nih.gov/pubmed/30819200
http://dx.doi.org/10.1186/s12967-019-1816-4
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