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. 2021 May-Jun;18(3):285-294.
doi: 10.21873/cgp.20259.

Clinical Utility of Functional RNA Analysis for the Reclassification of Splicing Gene Variants in Hereditary Cancer

Konstantinos Agiannitopoulos  1 , Georgia Pepe  2 , Eirini Papadopoulou  2 , Georgios N Tsaousis  2 , Stavroula Kampouri  2 , Sonia Maravelaki  2 , Athanassios Fassas  3 , Christos Christodoulou  4 , Rodoniki Iosifidou  5 , Sofia Karageorgopoulou  4 , Christos Markopoulos  6 , Ioannis Natsiopoulos  7 , Konstantinos Papazisis  8 , Maria Vasilaki-Antonatou  4 , Vassileios Venizelos  4 , Vahit Ozmen  9 , Sualp Tansan  10 , Kerim Kaban  11 , Dan Tudor Eniu  12 , Angelica Chiorean  12 , George Nasioulas  2
Affiliations

Clinical Utility of Functional RNA Analysis for the Reclassification of Splicing Gene Variants in Hereditary Cancer

Konstantinos Agiannitopoulos et al. Cancer Genomics Proteomics. 2021 May-Jun.

Abstract

Background: Classification of splicing variants (SVs) in genes associated with hereditary cancer is often challenging. The aim of this study was to investigate the occurrence of SVs in hereditary cancer genes and the clinical utility of RNA analysis.

Material and methods: 1518 individuals were tested for cancer predisposition, using a Next Generation Sequencing (NGS) panel of 36 genes. Splicing variant analysis was performed using RT-PCR and Sanger Sequencing.

Results: In total, 34 different SVs were identified, 53% of which were classified as pathogenic or likely pathogenic. The remaining 16 variants were initially classified as Variant of Uncertain Significance (VUS). RNA analysis was performed for 3 novel variants.

Conclusion: The RNA analysis assisted in the reclassification of 20% of splicing variants from VUS to pathogenic. RNA analysis is essential in the case of uncharacterized splicing variants, for proper classification and personalized management of these patients.

Keywords: NGS; RNA analysis; Splicing variant; cancer genes.

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Conflict of interest statement

There are no conflicts to declare.

Figures

Figure 1
Figure 1. Variant classification results for splicing variants identified in the 36 genes tested in this study. A. Classification of splicing variants according to their clinical significance. B. The number and frequency of Pathogenic/Likely Pathogenic and VUS splicing variants among genes.
Figure 2
Figure 2. Analysis of ATM c.2125-1G>T. A. Pedigree of the proband with the c.2125-1G>T variant in ATM. B. RNA analysis of the variant revealed the deletion of 11 bases (r.2125del), resulting in a frameshift deletion, p.(Ile709Phefs*22) (the second and third chromatograms) compared to the analysis of a wild type sample (top chromatogram).
Figure 3
Figure 3. Analysis of ATM c.2464_2466+2delTTAGT. A. Pedigree of the proband with the c.2464_2466+2delTTAGT variant in ATM. B. RNA analysis of the variant revealed a deletion of 5 bases (r.2466del), resulting in a frameshift deletion, p.(Ser821Serfs*8) (bottom panel) compared to the analysis of a wild type sample (top panel).
Figure 4
Figure 4. Analysis of MSH2 c.1510+1_1510+2dupGT. A. Pedigree of the proband with the c.1510+1_1510+2dupGT variant in MSH2. B. RNA analysis of the variant revealed the insertion of 2 bases (r.1510dup) causing a frameshift insertion, p.(Gly5040Glyfs*39) (second and third chromatograms) compared to the analysis of a wild type sample (top chromatogram).
See this image and copyright information in PMC

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