根据癌症基因组图谱（The Cancer Genome Atlas，TCGA）亚组，定制设计的下一代 DNA 测序基因面板在分子水平上对子宫内膜癌进行分类的效用。
Utility of a custom designed next generation DNA sequencing gene panel to molecularly classify endometrial cancers according to The Cancer Genome Atlas subgroups.
机构信息
Division of Gynecologic Oncology, Department of Obstetrics and Gynecology and Women's Health, Montefiore Medical Center, Bronx, NY, 10461, USA.
Department of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA.
出版信息
BMC Med Genomics. 2020 Nov 30;13(1):179. doi: 10.1186/s12920-020-00824-8.
BACKGROUND
The Cancer Genome Atlas identified four molecular subgroups of endometrial cancer with survival differences based on whole genome, transcriptomic, and proteomic characterization. Clinically accessible algorithms that reproduce this data are needed. Our aim was to determine if targeted sequencing alone allowed for molecular classification of endometrial cancer.
METHODS
Using a custom-designed 156 gene panel, we analyzed 47 endometrial cancers and matching non-tumor tissue. Variants were annotated for pathogenicity and medical records were reviewed for the clinicopathologic variables. Using molecular characteristics, tumors were classified into four subgroups. Group 1 included patients with > 570 unfiltered somatic variants, > 9 cytosine to adenine nucleotide substitutions per sample, and < 1 cytosine to guanine nucleotide substitution per sample. Group 2 included patients with any somatic mutation in MSH2, MSH6, MLH1, PMS2. Group 3 included patients with TP53 mutations without mutation in mismatch repair genes. Remaining patients were classified as group 4. Analyses were performed using SAS 9.4 (SAS Institute Inc., Cary, North Carolina, USA).
RESULTS
Endometrioid endometrial cancers had more candidate variants of potential pathogenic interest (median 6 IQR 4.13 vs. 2 IQR 2.3; p < 0.01) than uterine serous cancers. PTEN (82% vs. 15%, p < 0.01) and PIK3CA (74% vs. 23%, p < 0.01) mutations were more frequent in endometrioid than serous carcinomas. TP53 (18% vs. 77%, p < 0.01) mutations were more frequent in serous carcinomas. Visual inspection of the number of unfiltered somatic variants per sample identified six grade 3 endometrioid samples with high tumor mutational burden, all of which demonstrated POLE mutations, most commonly P286R and V411L. Of the grade 3 endometrioid carcinomas, those with POLE mutations were less likely to have risk factors necessitating adjuvant treatment than those with low tumor mutational burden. Targeted sequencing was unable to assign samples to microsatellite unstable, copy number low, and copy number high subgroups.
CONCLUSIONS
Targeted sequencing can predict the presence of POLE mutations based on the tumor mutational burden. However, targeted sequencing alone is inadequate to classify endometrial cancers into molecular subgroups identified by The Cancer Genome Atlas.
背景
癌症基因组图谱通过全基因组、转录组和蛋白质组学特征鉴定了具有生存差异的四种子宫内膜癌分子亚型。需要能够重现这些数据的临床可获取算法。我们的目的是确定仅靶向测序是否可以实现子宫内膜癌的分子分类。
方法
使用定制的 156 个基因面板，我们分析了 47 例子宫内膜癌和匹配的非肿瘤组织。对变体进行致病性注释，并审查病历以获取临床病理变量。根据分子特征，将肿瘤分为四个亚组。第 1 组包括具有 >570 个未经滤过的体细胞变体、>每个样本 9 个胞嘧啶到腺嘌呤核苷酸取代和<每个样本 1 个胞嘧啶到鸟嘌呤核苷酸取代的患者。第 2 组包括任何 MSH2、MSH6、MLH1、PMS2 体细胞突变的患者。第 3 组包括无错配修复基因突变的 TP53 突变患者。其余患者被归类为第 4 组。使用 SAS 9.4（SAS Institute Inc.，美国北卡罗来纳州卡里）进行分析。
结果
子宫内膜样子宫内膜癌的候选潜在致病性变体数量更多（中位数 6 IQR 4.13 与 2 IQR 2.3；p<0.01），比子宫浆液性癌多。PTEN（82%与 15%，p<0.01）和 PIK3CA（74%与 23%，p<0.01）突变在子宫内膜样癌中更为常见。TP53（18%与 77%，p<0.01）突变在浆液性癌中更为常见。通过观察每个样本未经滤过的体细胞变体数量，我们发现 6 个高肿瘤突变负担的 3 级子宫内膜样样本，均显示 POLE 突变，最常见的是 P286R 和 V411L。在 3 级子宫内膜样癌中，POLE 突变的肿瘤比低肿瘤突变负担的肿瘤更不可能有需要辅助治疗的危险因素。靶向测序无法将样本分配到微卫星不稳定、拷贝数低和拷贝数高亚组。
结论
靶向测序可以根据肿瘤突变负担预测 POLE 突变的存在。然而，仅靶向测序不足以将子宫内膜癌分类为癌症基因组图谱确定的分子亚型。
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