A Novel Diagnostic Method For AITL By Detecting RHOA G17V Hotspot Mutation Using Allele-Specific Real-Time PCR
Authors: Nakamoto-Matsubara Rie , Sakata-Yanagimoto Mamiko , Enami Terukazu , Yoshida Kenichi , Shiraishi Yuichi , Muto Hideharu , Kamada Yuhei , Obara Naoshi , Kurita Naoki , Seki Masanori , Yokoyama Yasuhisa , Noguchi Emiko , Izutsu Koji , Ota Yasunori , Sanada Masashi , Chiba Kenichi , Tanaka Hiroko , Shimizu Seiichi , Komeno Takuya , Satou Yuji , Itoh Takayoshi , Suzukawa Kazumi , Hasegawa Yuichi , Takeuchi Kengo , Miyano Satoru , Nakamura Naoya , Ogawa Seishi , Chiba Shigeru 
Published: October 2019

Abstract

Backgrounds
Angioimmunoblastic T-cell lymphoma (AITL) is a distinct subtype of T-cell lymphoma, characterized by generalized lymphadenopathy and frequent autoimmune-like manifestations. The diagnosis of AITL is sometimes challenging for hematopathologists, because the tumor cell content is generally low and relatively large reactive lymphocytes are confused as tumor cells. Possibly because of the low tumor cell frequency, clonal rearrangement of T-cell receptor gene is undetectable in 30% of the cases. We identified recurrent mutations in RHOA at c.G50T, predicting to generate p.G17V in 70% of AITL and PTCL-NOS harboring AITL features, which implies diagnostic properties for AITL (M S-Y and SC, unpublished).

Purpose
To establish a novel cost-effective method to diagnose AITL, we performed allele-specific realtime PCR to detect RHOA G17V mutation.

Methods
Genomic DNA was extracted from 119 AITL and PTCL-NOS samples, which include 47 periodate-lysine-paraformaldehyde (PLP)-fixed, 12 formalin-fixed-paraffin- embedded (FFPE) and 60 frozen tissues. Forty-one out of 60 genomic DNA samples, purified from frozen tissue, were amplified by RepliG kit (QIAGEN). Allele-specific primers for RHOA G17V mutant and wild-type sequences were designed by Wangkumhang's algorithm. The [mut] and [WT] values were individually measured by realtime PCR using each primer set, and the [mut]/([mut]+[WT]) values were calculated.
Mutant allele frequencies were determined by amplicon-based deep sequencing using MiSeq.

Results
The [mut] values were distributed from 1.5×10-7 to 7.6×10-2, and the [WT] values were from 7.9×10-5 to 1.3×10-2. The [mut]/[mut]+[WT] values were distributed from 1.9×10-4 to 8.5×10-1. We set a cut-off value to determine existence of mutation as 2% for MiSeq, and 1.3×10-2 for the [mut]/([mut]+[WT]) value. Then we compared these two methods to detect RHOA G17V mutation.
Forty-three cases were positive for the RHOA mutation in this study cohort by MiSeq, including 32 AITL and 11 PTCL-NOS cases. The [mut]/([mut]+[WT]) values of DNA from FFPE samples tend to be lower than those from other samples, and 4 out of 12 FFPE samples determined as mutation-positive by MiSeq were not detected by our allele-specific realtime PCR. We therefore excluded the FFPE samples and analyzed the data of 107 DNA samples, purified from PLP-fixed and frozen tissues. Rank correlation coefficient was 0.753. Sensitivity was 97.4%, and specificity was 97.1%. Positive concordance rate was 94.9%, and negative concordance rate was 98.6%.

Conclusions
We established a method to detect RHOA G17V hotspot mutation for AITL. It is expected to be highly accurate and cost effective.

Disclosures:
No relevant conflicts of interest to declare.