Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
Canada's Michael Smith Genome Sciences Centre, Vancouver, BC, Canada.
J Pathol Clin Res. 2022 Jul;8(4):395-407. doi: 10.1002/cjp2.265. Epub 2022 Mar 8.
In this study, we evaluate the impact of whole genome and transcriptome analysis (WGTA) on predictive molecular profiling and histologic diagnosis in a cohort of advanced malignancies. WGTA was used to generate reports including molecular alterations and site/tissue of origin prediction. Two reviewers analyzed genomic reports, clinical history, and tumor pathology. We used National Comprehensive Cancer Network (NCCN) consensus guidelines, Food and Drug Administration (FDA) approvals, and provincially reimbursed treatments to define genomic biomarkers associated with approved targeted therapeutic options (TTOs). Tumor tissue/site of origin was reassessed for most cases using genomic analysis, including a machine learning algorithm (Supervised Cancer Origin Prediction Using Expression [SCOPE]) trained on The Cancer Genome Atlas data. WGTA was performed on 652 cases, including a range of primary tumor types/tumor sites and 15 malignant tumors of uncertain histogenesis (MTUH). At the time WGTA was performed, alterations associated with an approved TTO were identified in 39 (6%) cases; 3 of these were not identified through routine pathology workup. In seven (1%) cases, the pathology workup either failed, was not performed, or gave a different result from the WGTA. Approved TTOs identified by WGTA increased to 103 (16%) when applying 2021 guidelines. The histopathologic diagnosis was reviewed in 389 cases and agreed with the diagnostic consensus after WGTA in 94% of non-MTUH cases (n = 374). The remainder included situations where the morphologic diagnosis was changed based on WGTA and clinical data (0.5%), or where the WGTA was non-contributory (5%). The 15 MTUH were all diagnosed as specific tumor types by WGTA. Tumor board reviews including WGTA agreed with almost all initial predictive molecular profile and histopathologic diagnoses. WGTA was a powerful tool to assign site/tissue of origin in MTUH. Current efforts focus on improving therapeutic predictive power and decreasing cost to enhance use of WGTA data as a routine clinical test.
在这项研究中,我们评估了全基因组和转录组分析(WGTA)对晚期恶性肿瘤预测分子分析和组织学诊断的影响。WGTA 用于生成包括分子改变和起源部位/组织预测的报告。两位评审员分析了基因组报告、临床病史和肿瘤病理学。我们使用国家综合癌症网络(NCCN)共识指南、食品和药物管理局(FDA)批准的药物和省级报销的治疗方法来定义与批准的靶向治疗方案(TTO)相关的基因组生物标志物。对于大多数病例,使用基因组分析重新评估肿瘤组织/起源部位,包括使用基于癌症基因组图谱数据训练的机器学习算法(Supervised Cancer Origin Prediction Using Expression [SCOPE])。在进行 WGTA 时,对 652 例病例进行了分析,包括一系列原发性肿瘤类型/肿瘤部位和 15 例组织来源不明的恶性肿瘤(MTUH)。在进行 WGTA 时,确定了 39 例(6%)与批准的 TTO 相关的改变;其中 3 例未通过常规病理学检查发现。在 7 例(1%)病例中,病理学检查要么失败,要么未进行,要么与 WGTA 的结果不同。当应用 2021 年指南时,通过 WGTA 确定的批准 TTO 增加到 103 例(16%)。对 389 例病例进行了组织病理学诊断回顾,在非 MTUH 病例中,94%(n=374)的病例在 WGTA 后与诊断共识一致。其余包括基于 WGTA 和临床数据改变形态学诊断的情况(0.5%),或 WGTA 无贡献的情况(5%)。15 例 MTUH 均通过 WGTA 诊断为特定肿瘤类型。包括 WGTA 的肿瘤委员会审查几乎与所有初始预测分子谱和组织病理学诊断一致。WGTA 是为 MTUH 分配起源部位/组织的有力工具。目前的工作重点是提高治疗预测能力和降低成本,以增强 WGTA 数据作为常规临床检测的使用。