Oon Ming Liang, Lim Jing Quan, Lee Bernett, Leong Sai Mun, Soon Gwyneth Shook-Ting, Wong Zi Wei, Lim Evelyn Huizi, Li Zhenhua, Yeoh Allen Eng Juh, Chen Shangying, Ban Kenneth Hon Kim, Chung Tae-Hoon, Tan Soo-Yong, Chuang Shih-Sung, Kato Seiichi, Nakamura Shigeo, Takahashi Emiko, Ho Yong-Howe, Khoury Joseph D, Au-Yeung Rex K H, Cheng Chee-Leong, Lim Soon-Thye, Chng Wee-Joo, Tripodo Claudio, Rotzschke Olaf, Ong Choon Kiat, Ng Siok-Bian
Department of Pathology, National University Hospital, National University Health System, Singapore 119074, Singapore.
Lymphoma Genomic Translational Research Laboratory, Division of Cellular and Molecular Research, National Cancer Centre Singapore, Singapore 169610, Singapore.
Cancers (Basel). 2021 Jan 19;13(2):340. doi: 10.3390/cancers13020340.
T-cell lymphomas arise from a single neoplastic clone and exhibit identical patterns of deletions in T-cell receptor (TCR) genes. Whole genome sequencing (WGS) data represent a treasure trove of information for the development of novel clinical applications. However, the use of WGS to identify clonal T-cell proliferations has not been systematically studied. In this study, based on WGS data, we identified monoclonal rearrangements (MRs) of T-cell receptors (TCR) genes using a novel segmentation algorithm and copy number computation. We evaluated the feasibility of this technique as a marker of T-cell clonality using T-cell lymphomas (TCL, = 44) and extranodal NK/T-cell lymphomas (ENKTLs, = 20), and identified 98% of TCLs with one or more TCR gene MRs, against 91% detected using PCR. TCR MRs were absent in all ENKTLs and NK cell lines. Sensitivity-wise, this platform is sufficiently competent, with MRs detected in the majority of samples with tumor content under 25% and it can also distinguish monoallelic from biallelic MRs. Understanding the copy number landscape of TCR using WGS data may engender new diagnostic applications in hematolymphoid pathology, which can be readily adapted to the analysis of B-cell receptor loci for B-cell clonality determination.
T细胞淋巴瘤起源于单个肿瘤克隆，在T细胞受体（TCR）基因中呈现相同的缺失模式。全基因组测序（WGS）数据是开发新型临床应用的信息宝库。然而，利用WGS来识别克隆性T细胞增殖尚未得到系统研究。在本研究中，基于WGS数据，我们使用一种新型分割算法和拷贝数计算方法识别T细胞受体（TCR）基因的单克隆重排（MRs）。我们使用T细胞淋巴瘤（TCL，n = 44）和结外NK/T细胞淋巴瘤（ENKTLs，n = 20）评估了该技术作为T细胞克隆性标志物的可行性，发现98%的TCL存在一个或多个TCR基因MRs，而使用PCR检测到的比例为91%。所有ENKTL和NK细胞系均未检测到TCR MRs。在敏感性方面，该平台能力足够，在大多数肿瘤含量低于25%的样本中检测到了MRs，并且还能区分单等位基因MRs和双等位基因MRs。利用WGS数据了解TCR的拷贝数情况可能会在血液淋巴病理学中产生新的诊断应用，并且可以很容易地应用于分析B细胞受体基因座以确定B细胞克隆性。
