Identifying Optimal Loci for the Molecular Diagnosis of Microsatellite Instability.
cancer
immunotherapy
microsatellite instability
mismatch repair
next-generation DNA sequencing
screening
Journal
Clinical chemistry
ISSN: 1530-8561
Titre abrégé: Clin Chem
Pays: England
ID NLM: 9421549
Informations de publication
Date de publication:
01 10 2020
01 10 2020
Historique:
received:
29
04
2020
accepted:
09
07
2020
entrez:
1
10
2020
pubmed:
2
10
2020
medline:
25
5
2021
Statut:
ppublish
Résumé
Microsatellite instability (MSI) predicts oncological response to checkpoint blockade immunotherapies. Although microsatellite mutation is pathognomonic for the condition, loci have unequal diagnostic value for predicting MSI within and across cancer types. To better inform molecular diagnosis of MSI, we examined 9438 tumor-normal exome pairs and 901 whole genome sequence pairs from 32 different cancer types and cataloged genome-wide microsatellite instability events. Using a statistical framework, we identified microsatellite mutations that were predictive of MSI within and across cancer types. The diagnostic accuracy of different subsets of maximally informative markers was estimated computationally using a dedicated validation set. Twenty-five cancer types exhibited hypermutated states consistent with MSI. Recurrently mutated microsatellites associated with MSI were identifiable in 15 cancer types, but were largely specific to individual cancer types. Cancer-specific microsatellite panels of 1 to 7 loci were needed to attain ≥95% diagnostic sensitivity and specificity for 11 cancer types, and in 8 of the cancer types, 100% sensitivity and specificity were achieved. Breast cancer required 800 loci to achieve comparable performance. We were unable to identify recurrent microsatellite mutations supporting reliable MSI diagnosis in ovarian tumors. Features associated with informative microsatellites were cataloged. Most microsatellites informative for MSI are specific to particular cancer types, requiring the use of tissue-specific loci for optimal diagnosis. Limited numbers of markers are needed to provide accurate MSI diagnosis in most tumor types, but it is challenging to diagnose breast and ovarian cancers using predefined microsatellite locus panels.
Sections du résumé
BACKGROUND
Microsatellite instability (MSI) predicts oncological response to checkpoint blockade immunotherapies. Although microsatellite mutation is pathognomonic for the condition, loci have unequal diagnostic value for predicting MSI within and across cancer types.
METHODS
To better inform molecular diagnosis of MSI, we examined 9438 tumor-normal exome pairs and 901 whole genome sequence pairs from 32 different cancer types and cataloged genome-wide microsatellite instability events. Using a statistical framework, we identified microsatellite mutations that were predictive of MSI within and across cancer types. The diagnostic accuracy of different subsets of maximally informative markers was estimated computationally using a dedicated validation set.
RESULTS
Twenty-five cancer types exhibited hypermutated states consistent with MSI. Recurrently mutated microsatellites associated with MSI were identifiable in 15 cancer types, but were largely specific to individual cancer types. Cancer-specific microsatellite panels of 1 to 7 loci were needed to attain ≥95% diagnostic sensitivity and specificity for 11 cancer types, and in 8 of the cancer types, 100% sensitivity and specificity were achieved. Breast cancer required 800 loci to achieve comparable performance. We were unable to identify recurrent microsatellite mutations supporting reliable MSI diagnosis in ovarian tumors. Features associated with informative microsatellites were cataloged.
CONCLUSIONS
Most microsatellites informative for MSI are specific to particular cancer types, requiring the use of tissue-specific loci for optimal diagnosis. Limited numbers of markers are needed to provide accurate MSI diagnosis in most tumor types, but it is challenging to diagnose breast and ovarian cancers using predefined microsatellite locus panels.
Identifiants
pubmed: 33001187
pii: 5910777
doi: 10.1093/clinchem/hvaa177
pmc: PMC7528407
doi:
Substances chimiques
Biomarkers, Tumor
0
DNA
9007-49-2
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1310-1318Subventions
Organisme : NCI NIH HHS
ID : R33 CA222344
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM086270
Pays : United States
Informations de copyright
© American Association for Clinical Chemistry 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Références
Proc Natl Acad Sci U S A. 2016 Nov 29;113(48):E7769-E7777
pubmed: 27837027
Bioinformatics. 2017 Aug 15;33(16):2583-2585
pubmed: 28398459
N Engl J Med. 2015 Jun 25;372(26):2509-20
pubmed: 26028255
JCO Precis Oncol. 2017;2017:
pubmed: 29850653
Dis Markers. 2004;20(4-5):237-50
pubmed: 15528789
Cancer Res. 2006 Aug 1;66(15):7810-7
pubmed: 16885385
Nucleic Acids Res. 2010 Sep;38(16):e164
pubmed: 20601685
Appl Immunohistochem Mol Morphol. 2018 Feb;26(2):e15-e21
pubmed: 28877075
Clin Chem. 2014 Sep;60(9):1192-9
pubmed: 24987110
Nature. 2017 Nov 23;551(7681):517-520
pubmed: 29132144
JCO Precis Oncol. 2017;2017:
pubmed: 30211344
N Engl J Med. 2003 Jul 17;349(3):247-57
pubmed: 12867608
Nat Commun. 2017 Jun 06;8:15180
pubmed: 28585546
J Mol Diagn. 2015 Nov;17(6):705-14
pubmed: 26322950
Clin Cancer Res. 2019 Dec 1;25(23):7035-7045
pubmed: 31383735
J Clin Oncol. 2012 Apr 1;30(10):1058-63
pubmed: 22355048
Transl Lung Cancer Res. 2018 Dec;7(Suppl 4):S358-S361
pubmed: 30705855
J Mol Diagn. 2008 Jul;10(4):301-7
pubmed: 18556776
Science. 2015 Oct 9;350(6257):207-211
pubmed: 26359337
Oncotarget. 2017 Jan 31;8(5):7452-7463
pubmed: 27980218
Sci Rep. 2015 Aug 26;5:13321
pubmed: 26306458
J Mol Diagn. 2006 Jul;8(3):305-11
pubmed: 16825502
J Mol Diagn. 2019 Nov;21(6):1053-1066
pubmed: 31445211
Front Oncol. 2018 Dec 12;8:621
pubmed: 30631754
Science. 2019 May 3;364(6439):485-491
pubmed: 31048490
J Clin Oncol. 2010 Jul 10;28(20):3380-7
pubmed: 20516444
Genet Med. 2009 Jan;11(1):35-41
pubmed: 19125126
Cancer Med. 2018 Mar;7(3):746-756
pubmed: 29436178
Genome Med. 2017 Apr 19;9(1):34
pubmed: 28420421
Oncotarget. 2018 Apr 17;9(29):20304-20322
pubmed: 29755653
Genome Res. 2014 May;24(5):743-50
pubmed: 24782321
Clin Chem. 2018 Jun;64(6):950-958
pubmed: 29632127
Br J Haematol. 2004 Jan;124(2):160-5
pubmed: 14687025
Bioinformatics. 2014 Apr 1;30(7):1015-6
pubmed: 24371154
Nucleic Acids Res. 2013 Sep;41(16):e158
pubmed: 23861444
Science. 2017 Jul 28;357(6349):409-413
pubmed: 28596308
Genome Med. 2016 Dec 22;8(1):136
pubmed: 28007036
Nat Med. 2016 Nov;22(11):1342-1350
pubmed: 27694933
Nat Biotechnol. 2017 Oct;35(10):951-959
pubmed: 28892075
Nat Rev Clin Oncol. 2010 Mar;7(3):153-62
pubmed: 20142816