Advanced NGS analysis of cell-free tumor DNA supports clonal relation to primary high-grade B-cell lymphoma lesion and CNS relapse despite MRI negativity.

IF 2.3 3区 医学 Q2 PATHOLOGY Diagnostic Pathology Pub Date : 2025-02-04 DOI:10.1186/s13000-025-01609-2
Veronika Navrkalova, Andrea Mareckova, Jakub Porc, Samuel Hricko, Viera Hrabcakova, Jarmila Kissova, Sona Kundova, Marie Jarosova, Sarka Pospisilova, Jana Kotaskova, Andrea Janikova
{"title":"Advanced NGS analysis of cell-free tumor DNA supports clonal relation to primary high-grade B-cell lymphoma lesion and CNS relapse despite MRI negativity.","authors":"Veronika Navrkalova, Andrea Mareckova, Jakub Porc, Samuel Hricko, Viera Hrabcakova, Jarmila Kissova, Sona Kundova, Marie Jarosova, Sarka Pospisilova, Jana Kotaskova, Andrea Janikova","doi":"10.1186/s13000-025-01609-2","DOIUrl":null,"url":null,"abstract":"<p><p>High-grade B-cell lymphomas (HGBCLs) are aggressive blood cancers with a severe disease course, especially when the central nervous system (CNS) is involved. Standard histological examination depends on tissue availability and is currently supplemented with molecular tests, as the status of MYC, BCL2, or BCL6 gene rearrangements is required for proper lymphoma classification. This case report demonstrates the relevance of cerebrospinal fluid (CSF) cell-free DNA testing by integrative next-generation sequencing (NGS) panel. The benefit of this approach resided in tumor genotyping alongside the proof of CNS progression despite MRI negativity, revealing a clonal relationship with the primary tumor lesion. In addition, our strategy allowed us to classify the tumor as DLBCL/HGBL-MYC/BCL2 entity. In clinical practice, such a minimally invasive approach provides a more sensitive tool than standard imaging and cell analyzing techniques, enabling more accurate disease monitoring and relapse prediction in particular cases.</p>","PeriodicalId":11237,"journal":{"name":"Diagnostic Pathology","volume":"20 1","pages":"14"},"PeriodicalIF":2.3000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11792325/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnostic Pathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13000-025-01609-2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

High-grade B-cell lymphomas (HGBCLs) are aggressive blood cancers with a severe disease course, especially when the central nervous system (CNS) is involved. Standard histological examination depends on tissue availability and is currently supplemented with molecular tests, as the status of MYC, BCL2, or BCL6 gene rearrangements is required for proper lymphoma classification. This case report demonstrates the relevance of cerebrospinal fluid (CSF) cell-free DNA testing by integrative next-generation sequencing (NGS) panel. The benefit of this approach resided in tumor genotyping alongside the proof of CNS progression despite MRI negativity, revealing a clonal relationship with the primary tumor lesion. In addition, our strategy allowed us to classify the tumor as DLBCL/HGBL-MYC/BCL2 entity. In clinical practice, such a minimally invasive approach provides a more sensitive tool than standard imaging and cell analyzing techniques, enabling more accurate disease monitoring and relapse prediction in particular cases.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
无细胞肿瘤DNA的先进NGS分析支持原发性高级别b细胞淋巴瘤病变和中枢神经系统复发的克隆关系,尽管MRI阴性。
高级别B细胞淋巴瘤(HGBCL)是一种侵袭性血癌,病程严重,尤其是累及中枢神经系统(CNS)时。标准组织学检查取决于组织的可用性,目前还辅以分子检测,因为正确的淋巴瘤分类需要MYC、BCL2或BCL6基因重排的状态。本病例报告展示了通过整合性新一代测序(NGS)面板进行脑脊液(CSF)无细胞 DNA 检测的重要性。这种方法的优势在于,尽管核磁共振成像呈阴性,但肿瘤基因分型和中枢神经系统进展的证据揭示了与原发肿瘤病灶的克隆关系。此外,我们的策略还能将肿瘤归类为 DLBCL/HGBL-MYC/BCL2 实体。在临床实践中,这种微创方法提供了比标准成像和细胞分析技术更灵敏的工具,使我们能够对特定病例进行更准确的疾病监测和复发预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Diagnostic Pathology
Diagnostic Pathology 医学-病理学
CiteScore
4.60
自引率
0.00%
发文量
93
审稿时长
1 months
期刊介绍: Diagnostic Pathology is an open access, peer-reviewed, online journal that considers research in surgical and clinical pathology, immunology, and biology, with a special focus on cutting-edge approaches in diagnostic pathology and tissue-based therapy. The journal covers all aspects of surgical pathology, including classic diagnostic pathology, prognosis-related diagnosis (tumor stages, prognosis markers, such as MIB-percentage, hormone receptors, etc.), and therapy-related findings. The journal also focuses on the technological aspects of pathology, including molecular biology techniques, morphometry aspects (stereology, DNA analysis, syntactic structure analysis), communication aspects (telecommunication, virtual microscopy, virtual pathology institutions, etc.), and electronic education and quality assurance (for example interactive publication, on-line references with automated updating, etc.).
期刊最新文献
Construction of an integrated diagnostic-therapeutic model for prostate cancer using rapid multiplex immunohistochemistry. Case report: a case of primary cutaneous diffuse large B-cell lymphoma, leg type with TdT positive in an elderly woman. Detection of collagen band-associated regions in H&E-stained colonic biopsies of collagenous colitis patients using superpixel-based feature extraction and neural network classification. Adenocarcinoma admixed with neuroendocrine carcinoma of the cervix: a clinicopathological diagnostic study and molecular features. Calcifying fibrous tumors of the thoracic cavity: a clinicopathological series of seven solitary cases.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1