Coyle Krysta M, Dreval Kostiantyn, Hodson Daniel J, Morin Ryan D
Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada.
Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada.
Blood Adv. 2025 Apr 22;9(8):2019-2031. doi: 10.1182/bloodadvances.2022009461.
Comprehensive genetic analysis of tumors with exome or whole-genome sequencing has enabled the identification of the genes that are recurrently mutated in cancer. This has stimulated a series of exciting advances over the past 15 years, guiding us to new molecular biomarkers and therapeutic targets among the common mature B-cell neoplasms. In particular, diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and Burkitt lymphoma (BL) have each been the subject of considerable attention in this field. Currently, >850 genes have been reported as targets of protein-coding mutations in at least 1 of these entities. To reduce this to a manageable size, we describe a systematic approach to prioritize and categorize these genes, based on the quality and type of supporting data. For each entity, we provide a list of candidate driver genes categorized into Tier 1 (high-confidence genes), Tier 2 (candidate driver genes), or Tier 3 (lowest-confidence genes). Collectively, this reduces the number of high-confidence genes for these 3 lymphomas to a mere 144. This further affirms the substantial overlap between the genes relevant in DLBCL and each of FL and BL. These highly curated and annotated gene lists will continue to be maintained as a resource to the community. These results emphasize the extent of the knowledge gap regarding the role of each of these genes in lymphomagenesis. We offer our perspective on how to accelerate the experimental confirmation of drivers using a variety of model systems, using these lists as a guide for prioritizing genes.
通过外显子组测序或全基因组测序对肿瘤进行全面的基因分析，已能够鉴定出在癌症中反复发生突变的基因。在过去15年里，这推动了一系列令人兴奋的进展，在常见的成熟B细胞肿瘤中为我们指引了新的分子生物标志物和治疗靶点。特别是弥漫性大B细胞淋巴瘤（DLBCL）、滤泡性淋巴瘤（FL）和伯基特淋巴瘤（BL），在该领域均受到了相当多的关注。目前，已有超过850个基因被报道为这些实体中至少一种的蛋白质编码突变靶点。为了将其缩减到易于管理的规模，我们描述了一种基于支持数据的质量和类型对这些基因进行优先级排序和分类的系统方法。对于每个实体，我们提供了一份候选驱动基因列表，分为1级（高可信度基因）、2级（候选驱动基因）或3级（最低可信度基因）。总体而言，这将这3种淋巴瘤的高可信度基因数量减少到仅144个。这进一步证实了DLBCL与FL和BL各自相关基因之间存在大量重叠。这些经过高度整理和注释的基因列表将继续作为社区资源予以维护。这些结果强调了关于这些基因在淋巴瘤发生中作用的知识差距程度。我们就如何利用各种模型系统加速对驱动基因的实验验证提出了我们的观点，并将这些列表作为基因优先级排序的指南。
