Expression Analysis and Mutational Status of Histone Methyltransferase KMT2D at Different Upper Tract Urothelial Carcinoma Locations.

Abstract

The gene coding for histone methyltransferase KMT2D is found among the top mutated genes in upper tract urothelial carcinoma (UTUC); however, there is a lack of data regarding its association with clinicopathologic features as well as survival outcomes. Therefore, we aimed to investigate KMT2D expression, mutation patterns, and their utility as prognostic biomarkers in patients with UTUC. A single-center study was conducted on tumor specimens from 51 patients treated with radical nephroureterectomy (RNU). Analysis of KMT2D protein expression was performed using immunohistochemistry (IHC). Customized next-generation sequencing (NGS) was used to assess alterations in KMT2D exons. Cox regression was used to assess the relationship of KMT2D protein expression and mutational status with survival outcomes. KMT2D expression was increased in patients with a previous history of bladder cancer (25% vs. 0%, p = 0.02). The NGS analysis of KMT2D exons in 27 UTUC tumors revealed a significant association between pathogenic KMT2D variants and tumor location (p = 0.02). Pathogenic KMT2D variants were predominantly found in patients with non-pelvic or multifocal tumors (60% vs. 14%), while the majority of patients with a pelvic tumor location (81% vs. 20%) did not harbor pathogenic KMT2D alterations. Both IHC and NGS analyses of KMT2D failed to detect a statistically significant association between KMT2D protein or KMT2D gene alteration status and clinical variables such as stage/grade of the disease or survival outcomes (all p > 0.05). KMT2D alterations and protein expression were associated with UTUC features such as multifocality, ureteral location, and previous bladder cancer. While KMT2D protein expression and KMT2D mutational status do not seem to have prognostic value in UTUC, they appear to add information to improve clinical decision-making regarding the type of therapy.

• Authors: Ekaterina Laukhtina, Ursula Lemberger, Andreas Bruchbacher, Dafina Ilijazi, Stephan Korn, Florian Berndl, David D'Andrea, Martin Susani, Dmitry Enikeev, Eva Compérat, Shahrokh F Shariat, Melanie R Hassler
• Journal: Journal of personalized medicine (J Pers Med) Vol. 11 Issue 11 (Nov 04 2021) ISSN: 2075-4426 [Print] Switzerland
• PMID: 34834500 (Publication Type: Journal Article)