Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.
Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey, USA.
Clin Transl Med. 2023 Jun;13(6):e1298. doi: 10.1002/ctm2.1298.
Differentiated thyroid cancer (DTC) affects thousands of lives worldwide each year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis. Unfortunately, thyroidectomy and/or radioiodine therapy often worsen(s) quality of life and might be unnecessary in indolent DTC cases. On the other hand, the lack of biomarkers indicating a potential metastatic thyroid cancer imposes an additional challenge to managing and treating patients with this disease.
The presented clinical setting highlights the unmet need for a precise molecular diagnosis of DTC and potential metastatic disease, which should dictate appropriate therapy.
In this article, we present a differential multi-omics model approach, including metabolomics, genomics, and bioinformatic models, to distinguish normal glands from thyroid tumours. Additionally, we are proposing biomarkers that could indicate potential metastatic diseases in papillary thyroid cancer (PTC), a sub-class of DTC.
Normal and tumour thyroid tissue from DTC patients had a distinct yet well-defined metabolic profile with high levels of anabolic metabolites and/or other metabolites associated with the energy maintenance of tumour cells. The consistency of the DTC metabolic profile allowed us to build a bioinformatic classification model capable of clearly distinguishing normal from tumor thyroid tissues, which might help diagnose thyroid cancer. Moreover, based on PTC patient samples, our data suggest that elevated nuclear and mitochondrial DNA mutational burden, intra-tumour heterogeneity, shortened telomere length, and altered metabolic profile reflect the potential for metastatic disease.
Altogether, this work indicates that a differential and integrated multi-omics approach might improve DTC management, perhaps preventing unnecessary thyroid gland removal and/or radioiodine therapy.
Well-designed, prospective translational clinical trials will ultimately show the value of this integrated multi-omics approach and early diagnosis of DTC and potential metastatic PTC.
分化型甲状腺癌（DTC）每年在全球影响数千人的生命。通常，DTC 是一种可治疗的疾病，预后良好。然而，一些患者需要接受部分或全部甲状腺切除术和放射性碘治疗，以防止局部疾病复发和转移。不幸的是，甲状腺切除术和/或放射性碘治疗往往会降低生活质量，并且在惰性 DTC 病例中可能是不必要的。另一方面，缺乏表明潜在转移性甲状腺癌的生物标志物给管理和治疗此类疾病的患者带来了额外的挑战。
所呈现的临床背景强调了对 DTC 和潜在转移性疾病进行精确分子诊断的未满足需求，这应该决定适当的治疗方法。
在本文中，我们提出了一种差异化的多组学模型方法，包括代谢组学、基因组学和生物信息模型，以区分正常腺体和甲状腺肿瘤。此外，我们提出了可能表明甲状腺乳头状癌（PTC）中潜在转移性疾病的生物标志物，PTC 是 DTC 的一个亚类。
DTC 患者的正常和肿瘤甲状腺组织具有独特但定义明确的代谢特征，具有高水平的合成代谢代谢物和/或其他与肿瘤细胞能量维持相关的代谢物。DTC 代谢特征的一致性使我们能够构建一种能够清楚地区分正常和肿瘤甲状腺组织的生物信息分类模型，这可能有助于诊断甲状腺癌。此外，基于 PTC 患者样本，我们的数据表明，核和线粒体 DNA 突变负担增加、肿瘤内异质性、端粒缩短和代谢特征改变反映了转移性疾病的潜力。
总的来说，这项工作表明，差异化和综合的多组学方法可能改善 DTC 的管理，也许可以防止不必要的甲状腺切除和/或放射性碘治疗。
精心设计的前瞻性转化临床试验最终将显示这种综合多组学方法和早期诊断 DTC 和潜在转移性 PTC 的价值。
