Kim Hyunho, Joo Min Wook, Yoon Joohee, Park Hong Sik, Kim June Hyuk, Lee Joo Hwan, Kim Sung Hwan, Lee Seul Ki, Chung Yang-Guk, Cho Yoon Joo
Division of Medical Oncology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Department of Orthopedic Surgery, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Clin Orthop Relat Res. 2024 Mar 22;482(6):1028-37. doi: 10.1097/CORR.0000000000003041.
A clear classification of the subtype and grade of soft tissue sarcoma is important for predicting prognosis and establishing treatment strategies. However, the rarity and heterogeneity of these tumors often make diagnosis difficult. In addition, it remains challenging to predict the response to chemotherapy and prognosis. Thus, we need a new method to help diagnose soft tissue sarcomas and determine treatment strategies in conjunction with traditional methods. Genetic alterations can be found in some subtypes of soft tissue sarcoma, but many other types show dysregulated gene expression attributed to epigenetic changes, such as DNA methylation status. However, research on DNA methylation profiles in soft tissue sarcoma is still insufficient to provide information to assist in diagnosis and therapeutic decisions.
QUESTIONS/PURPOSES: (1) Do DNA methylation profiles differ between normal tissue and soft tissue sarcoma? (2) Do DNA methylation profiles vary between different histologic subtypes of soft tissue sarcoma? (3) Do DNA methylation profiles differ based on tumor grade?
Between January 2019 and December 2022, we treated 85 patients for soft tissue sarcomas. We considered patients whose specimens were approved for pilot research by the Human Biobank of St. Vincent's Hospital, The Catholic University of Korea, as potentially eligible. Based on this, 41% (35 patients) were eligible; 1% (one patient) was excluded because of gender mismatch between clinical and genetic data after controlling for data quality. Finally, 39 specimens (34 soft tissue sarcomas and five normal samples) were included from 34 patients who had clinical data. All tissue samples were collected intraoperatively. The five normal tissue samples were from muscle tissues. There were 20 female patients and 14 male patients, with a median age of 58 years (range 19 to 82 years). Genomic DNA was extracted from frozen tissue, and DNA methylation profiles were obtained. Genomic annotation of DNA methylation sites and hierarchical cluster analysis were performed to interpret results from DNA methylation profiling. A t-test was used to analyze different methylation probes. Benjamini-Hochberg-adjusted p value calculations were used to account for bias resulting from evaluating thousands of methylation sites.
The most common histologic subtypes were liposarcoma (n = 10) and leiomyosarcoma (n = 9). The tumor grade was Fédération Nationale des Centres de Lutte Contre Le Cancer Grades 1, 2, and 3 in 3, 15, and 16 patients, respectively. DNA methylation profiling demonstrated differences between soft tissue sarcoma and normal tissue as 21,188 cytosine-phosphate-guanine sites. Despite the small number of samples, 72 of these sites showed an adjusted p value of < 0.000001, suggesting a low probability of statistical errors. Among the 72 sites, 70 exhibited a hypermethylation pattern in soft tissue sarcoma, with only two sites showing a hypomethylation pattern. Thirty of 34 soft tissue sarcomas were distinguished from normal samples using hierarchical cluster analysis. There was a different methylation pattern between leiomyosarcoma and liposarcoma at 7445 sites. Using the data, hierarchical clustering analysis showed that liposarcoma was distinguished from leiomyosarcoma. When we used the same approach and included other subtypes with three or more samples, only leiomyosarcoma and myxofibrosarcoma were separated from the other subtypes, while liposarcoma and alveolar soft-part sarcoma were mixed with the others. When comparing DNA methylation profiles between low-grade (Grade 1) and high-grade (Grades 2 and 3) soft tissue sarcomas, a difference in methylation pattern was observed at 144 cytosine-phosphate-guanine sites. Among these, 132 cytosine-phosphate-guanine sites exhibited hypermethylation in the high-grade group compared with the low-grade group. Hierarchical clustering analysis showed a division into two groups, with most high-grade sarcomas (28 of 31) separated from the low-grade group and few (3 out of 31) clustered together with the low-grade group. However, three high-grade soft tissue sarcomas were grouped with the Grade 1 cluster, and all of these sarcomas were Grade 2. When comparing Grades 1 and 2 to Grade 3, Grade 3 tumors were separated from Grades 1 and 2.
We observed a different DNA methylation pattern between soft tissue sarcomas and normal tissues. Liposarcoma was distinguished from leiomyosarcoma using methylation profiling. High-grade soft tissue sarcoma samples showed a hypermethylation pattern compared with low-grade ones. Our findings indicate the need for research using methylation profiling to better understand the diverse biological characteristics of soft tissue sarcoma. Such research should include studies with sufficient samples and a variety of subtypes, as well as analyses of the expression and function of related genes. Additionally, efforts to link this research with clinical data related to treatment and prognosis are necessary.
Level III, diagnostic study.
软组织肉瘤亚型和分级的明确分类对于预测预后和制定治疗策略至关重要。然而，这些肿瘤的罕见性和异质性常常使诊断变得困难。此外，预测化疗反应和预后仍然具有挑战性。因此，我们需要一种新方法来辅助诊断软组织肉瘤，并结合传统方法确定治疗策略。在软组织肉瘤的某些亚型中可发现基因改变，但许多其他类型表现出归因于表观遗传变化（如DNA甲基化状态）的基因表达失调。然而，关于软组织肉瘤DNA甲基化谱的研究仍不足以提供有助于诊断和治疗决策的信息。
问题/目的：（1）正常组织与软组织肉瘤的DNA甲基化谱是否不同？（2）软组织肉瘤不同组织学亚型之间的DNA甲基化谱是否存在差异？（3）DNA甲基化谱是否因肿瘤分级而异？
2019年1月至2022年12月期间，我们治疗了85例软组织肉瘤患者。我们认为其标本经韩国天主教大学圣文森特医院人类生物样本库批准用于试点研究的患者具有潜在入选资格。据此，41%（35例患者）符合条件；1%（1例患者）因在控制数据质量后临床和基因数据存在性别不匹配而被排除。最终，纳入了34例有临床数据患者的39份标本（34份软组织肉瘤标本和5份正常样本）。所有组织样本均在术中采集。5份正常组织样本来自肌肉组织。有20例女性患者和14例男性患者，中位年龄为58岁（范围19至82岁）。从冷冻组织中提取基因组DNA，并获得DNA甲基化谱。对DNA甲基化位点进行基因组注释并进行层次聚类分析，以解释DNA甲基化谱分析结果。采用t检验分析不同的甲基化探针。使用Benjamini-Hochberg校正的p值计算来校正因评估数千个甲基化位点而产生的偏差。
最常见的组织学亚型是脂肪肉瘤（n = 10）和平滑肌肉瘤（n = 9）。肿瘤分级分别为法国国立癌症中心联合会1级、2级和3级的患者有3例、15例和16例。DNA甲基化谱分析显示软组织肉瘤与正常组织之间在21,188个胞嘧啶-磷酸-鸟嘌呤位点存在差异。尽管样本数量较少，但其中72个位点的校正p值<0.000001，表明统计误差概率较低。在这72个位点中，70个在软组织肉瘤中呈现高甲基化模式，只有2个位点呈现低甲基化模式。34例软组织肉瘤中的30例通过层次聚类分析与正常样本区分开来。平滑肌肉瘤和脂肪肉瘤在7445个位点存在不同的甲基化模式。利用这些数据，层次聚类分析显示脂肪肉瘤与平滑肌肉瘤得以区分。当我们采用相同方法并纳入其他有三个或更多样本的亚型时，只有平滑肌肉瘤和黏液纤维肉瘤与其他亚型分开，而脂肪肉瘤和腺泡状软组织肉瘤则与其他亚型混合在一起。比较低级别（1级）和高级别（2级和3级）软组织肉瘤的DNA甲基化谱时，在144个胞嘧啶-磷酸-鸟嘌呤位点观察到甲基化模式差异。其中，与低级别组相比，高级别组中有132个胞嘧啶-磷酸-鸟嘌呤位点呈现高甲基化。层次聚类分析显示分为两组，大多数高级别肉瘤（31例中的28例）与低级别组分开，少数（31例中的3例）与低级别组聚集在一起。然而，有3例高级别软组织肉瘤与1级聚类在一起，所有这些肉瘤均为2级。比较1级和2级与3级时，3级肿瘤与1级和2级分开。
我们观察到软组织肉瘤与正常组织之间存在不同的DNA甲基化模式。利用甲基化谱分析可区分脂肪肉瘤和平滑肌肉瘤。高级别软组织肉瘤样本与低级别样本相比呈现高甲基化模式。我们的研究结果表明需要利用甲基化谱分析进行研究，以更好地了解软组织肉瘤的多种生物学特性。此类研究应包括有足够样本和多种亚型的研究，以及相关基因表达和功能的分析。此外，有必要努力将该研究与治疗和预后相关的临床数据联系起来。
III级，诊断性研究。
