diff --git a/content/04.discussion.md b/content/04.discussion.md
index 5c248e22..f6fefc69 100644
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@@ -13,7 +13,7 @@ As such, uniform clinical molecular subtyping was largely not performed for most
 Since DNA methylation data for these samples were yet available to classify molecular subtypes, we created RNA- and DNA-based subtyping modules aligned with WHO molecularly-defined diagnoses.
 We manually curated any known subtypes from pathology reports and/or free text clinical data fields.
 For unclassified tumors, we worked closely with pathologists and clinicians to assign research-grade integrated diagnoses for 60% of tumors while discovering incorrectly diagnosed or mis-identified samples in the OpenPBTA cohort.
-For example, we subtyped medulloblastoma tumors, of which only 35% (43/122) had prior subtype information from pathology reports, using MMS2 (91%; 39/43) or MedulloClassifier (95%; 41/43) [@doi:10.1186/s13029-016-0053-y; @doi:10.1371/journal.pcbi.1008263] and subsequently applied the consensus of these methods to subtype all medulloblastomas.
+For example, we subtyped medulloblastoma tumors, of which only 35% (43/122) had prior subtype information from pathology reports, using `MMS2` or `MedulloClassifier` [@doi:10.1186/s13029-016-0053-y; @doi:10.1371/journal.pcbi.1008263] and subsequently applied the consensus of these methods to subtype all medulloblastomas.
 
 We advanced the integrative analyses and cross-cohort comparison via a number of validated modules.
 We used an expression classifier to determine whether tumors have dysfunctional _TP53_ [@doi:10.1016/j.celrep.2018.03.076] and the EXTEND algorithm to determine their degree of telomerase activity using a 13-gene signature [@doi:10.1038/s41467-020-20474-9].