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High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype

Background: Gastric cancer is the fourth most common cause of cancer-related death. Currently, it is broadly accepted that the molecular complexity and heterogeneity of gastric cancer, both inter- and intra-tumor, display important barriers for finding specific biomarkers for the early detection and...

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Autores principales: Machlowska, Julita, Kapusta, Przemysław, Baj, Jacek, Morsink, Folkert H. M., Wołkow, Paweł, Maciejewski, Ryszard, Offerhaus, G. Johan A., Sitarz, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7409326/
https://www.ncbi.nlm.nih.gov/pubmed/32708070
http://dx.doi.org/10.3390/cancers12071981
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author Machlowska, Julita
Kapusta, Przemysław
Baj, Jacek
Morsink, Folkert H. M.
Wołkow, Paweł
Maciejewski, Ryszard
Offerhaus, G. Johan A.
Sitarz, Robert
author_facet Machlowska, Julita
Kapusta, Przemysław
Baj, Jacek
Morsink, Folkert H. M.
Wołkow, Paweł
Maciejewski, Ryszard
Offerhaus, G. Johan A.
Sitarz, Robert
author_sort Machlowska, Julita
collection PubMed
description Background: Gastric cancer is the fourth most common cause of cancer-related death. Currently, it is broadly accepted that the molecular complexity and heterogeneity of gastric cancer, both inter- and intra-tumor, display important barriers for finding specific biomarkers for the early detection and diagnosis of this malignancy. Early-onset gastric cancer is not as prevalent as conventional gastric carcinoma, but it is a preferable model for studying the genetic background, as young patients are less exposed to environmental factors, which influence cancer development. Aim: The main objective of this study was to reveal age-dependent genotypic characteristics of gastric cancer subtypes, as well as conduct mutation profiling for the most frequent alterations in gastric cancer development, using targeted next-generation sequencing technology. Patients and methods: The study group included 53 patients, consisting of 18 patients with conventional gastric cancer and 35 with an early-onset subtype. The DNA of all index cases was used for next-generation sequencing, employing a panel of 94 genes and 284 single nucleotide polymorphisms (SNPs) (TruSight Cancer Panel, Illumina), which is characteristic for common and rare types of cancer. Results: From among the 53 samples processed for sequencing, we were able to identify seven candidate genes (STK11, RET, FANCM, SLX4, WRN, MEN1, and KIT) and nine variants among them: one splice_acceptor, four synonymous, and four missense variants. These were selected for the age-dependent differentiation of gastric cancer subtypes. We found four variants with C-Score ≥ 10, as 10% of the most deleterious substitutions: rs1800862 (RET), rs10138997 (FANCM), rs2230009 (WRN), and rs2959656 (MEN1). We identified 36 different variants, among 24 different genes, which were the most frequent genetic alterations among study subjects. We found 16 different variants among the genes that were present in 100% of the total cohort: SDHB (rs2746462), ALK (rs1670283), XPC (rs2958057), RECQL4 (rs4925828; rs11342077, rs398010167; rs2721190), DDB2 (rs326212), MEN1 (rs540012), AIP (rs4930199), ATM (rs659243), HNF1A (rs1169305), BRCA2 (rs206075; rs169547), ERCC5 (rs9514066; rs9514067), and FANCI (rs7183618). Conclusions: The technology of next-generation sequencing is a useful tool for studying the development and progression of gastric carcinoma in a high-throughput way. Our study revealed that early-onset gastric cancer has a different mutation frequency profile in certain genes compared to conventional subtype.
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spelling pubmed-74093262020-08-25 High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype Machlowska, Julita Kapusta, Przemysław Baj, Jacek Morsink, Folkert H. M. Wołkow, Paweł Maciejewski, Ryszard Offerhaus, G. Johan A. Sitarz, Robert Cancers (Basel) Article Background: Gastric cancer is the fourth most common cause of cancer-related death. Currently, it is broadly accepted that the molecular complexity and heterogeneity of gastric cancer, both inter- and intra-tumor, display important barriers for finding specific biomarkers for the early detection and diagnosis of this malignancy. Early-onset gastric cancer is not as prevalent as conventional gastric carcinoma, but it is a preferable model for studying the genetic background, as young patients are less exposed to environmental factors, which influence cancer development. Aim: The main objective of this study was to reveal age-dependent genotypic characteristics of gastric cancer subtypes, as well as conduct mutation profiling for the most frequent alterations in gastric cancer development, using targeted next-generation sequencing technology. Patients and methods: The study group included 53 patients, consisting of 18 patients with conventional gastric cancer and 35 with an early-onset subtype. The DNA of all index cases was used for next-generation sequencing, employing a panel of 94 genes and 284 single nucleotide polymorphisms (SNPs) (TruSight Cancer Panel, Illumina), which is characteristic for common and rare types of cancer. Results: From among the 53 samples processed for sequencing, we were able to identify seven candidate genes (STK11, RET, FANCM, SLX4, WRN, MEN1, and KIT) and nine variants among them: one splice_acceptor, four synonymous, and four missense variants. These were selected for the age-dependent differentiation of gastric cancer subtypes. We found four variants with C-Score ≥ 10, as 10% of the most deleterious substitutions: rs1800862 (RET), rs10138997 (FANCM), rs2230009 (WRN), and rs2959656 (MEN1). We identified 36 different variants, among 24 different genes, which were the most frequent genetic alterations among study subjects. We found 16 different variants among the genes that were present in 100% of the total cohort: SDHB (rs2746462), ALK (rs1670283), XPC (rs2958057), RECQL4 (rs4925828; rs11342077, rs398010167; rs2721190), DDB2 (rs326212), MEN1 (rs540012), AIP (rs4930199), ATM (rs659243), HNF1A (rs1169305), BRCA2 (rs206075; rs169547), ERCC5 (rs9514066; rs9514067), and FANCI (rs7183618). Conclusions: The technology of next-generation sequencing is a useful tool for studying the development and progression of gastric carcinoma in a high-throughput way. Our study revealed that early-onset gastric cancer has a different mutation frequency profile in certain genes compared to conventional subtype. MDPI 2020-07-21 /pmc/articles/PMC7409326/ /pubmed/32708070 http://dx.doi.org/10.3390/cancers12071981 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Machlowska, Julita
Kapusta, Przemysław
Baj, Jacek
Morsink, Folkert H. M.
Wołkow, Paweł
Maciejewski, Ryszard
Offerhaus, G. Johan A.
Sitarz, Robert
High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype
title High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype
title_full High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype
title_fullStr High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype
title_full_unstemmed High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype
title_short High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype
title_sort high-throughput sequencing of gastric cancer patients: unravelling genetic predispositions towards an early-onset subtype
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7409326/
https://www.ncbi.nlm.nih.gov/pubmed/32708070
http://dx.doi.org/10.3390/cancers12071981
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