Cargando…

Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability

Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size...

Descripción completa

Detalles Bibliográficos
Autores principales: Sorokin, Maksim, Rabushko, Elizaveta, Efimov, Victor, Poddubskaya, Elena, Sekacheva, Marina, Simonov, Alexander, Nikitin, Daniil, Drobyshev, Aleksey, Suntsova, Maria, Buzdin, Anton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8650122/
https://www.ncbi.nlm.nih.gov/pubmed/34888350
http://dx.doi.org/10.3389/fmolb.2021.737821
_version_ 1784611142180536320
author Sorokin, Maksim
Rabushko, Elizaveta
Efimov, Victor
Poddubskaya, Elena
Sekacheva, Marina
Simonov, Alexander
Nikitin, Daniil
Drobyshev, Aleksey
Suntsova, Maria
Buzdin, Anton
author_facet Sorokin, Maksim
Rabushko, Elizaveta
Efimov, Victor
Poddubskaya, Elena
Sekacheva, Marina
Simonov, Alexander
Nikitin, Daniil
Drobyshev, Aleksey
Suntsova, Maria
Buzdin, Anton
author_sort Sorokin, Maksim
collection PubMed
description Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94–1 for the experimental CRCs and 0.94–1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91–0.97, whereas the third signature showed a significantly lower AUC of 0.69–0.88. Software for calculating these MSI signatures using RNAseq data is included.
format Online
Article
Text
id pubmed-8650122
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-86501222021-12-08 Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability Sorokin, Maksim Rabushko, Elizaveta Efimov, Victor Poddubskaya, Elena Sekacheva, Marina Simonov, Alexander Nikitin, Daniil Drobyshev, Aleksey Suntsova, Maria Buzdin, Anton Front Mol Biosci Molecular Biosciences Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94–1 for the experimental CRCs and 0.94–1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91–0.97, whereas the third signature showed a significantly lower AUC of 0.69–0.88. Software for calculating these MSI signatures using RNAseq data is included. Frontiers Media S.A. 2021-11-23 /pmc/articles/PMC8650122/ /pubmed/34888350 http://dx.doi.org/10.3389/fmolb.2021.737821 Text en Copyright © 2021 Sorokin, Rabushko, Efimov, Poddubskaya, Sekacheva, Simonov, Nikitin, Drobyshev, Suntsova and Buzdin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Sorokin, Maksim
Rabushko, Elizaveta
Efimov, Victor
Poddubskaya, Elena
Sekacheva, Marina
Simonov, Alexander
Nikitin, Daniil
Drobyshev, Aleksey
Suntsova, Maria
Buzdin, Anton
Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability
title Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability
title_full Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability
title_fullStr Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability
title_full_unstemmed Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability
title_short Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability
title_sort experimental and meta-analytic validation of rna sequencing signatures for predicting status of microsatellite instability
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8650122/
https://www.ncbi.nlm.nih.gov/pubmed/34888350
http://dx.doi.org/10.3389/fmolb.2021.737821
work_keys_str_mv AT sorokinmaksim experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT rabushkoelizaveta experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT efimovvictor experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT poddubskayaelena experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT sekachevamarina experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT simonovalexander experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT nikitindaniil experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT drobyshevaleksey experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT suntsovamaria experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability
AT buzdinanton experimentalandmetaanalyticvalidationofrnasequencingsignaturesforpredictingstatusofmicrosatelliteinstability