研究动态
Articles below are published ahead of final publication in an issue. Please cite articles in the following format: authors, (year), title, journal, DOI.

启动子突变无关的 TERT 表达与甲状腺乳头状癌中免疫丰富的环境有关。

Promoter mutation-independent TERT expression is related to immune-enriched milieu in papillary thyroid cancer.

发表日期:2024 Aug 01
作者: Dong Hyun Seo, Seul Gi Lee, Soon Min Choi, Ha Yan Kim, Sunmi Park, Sang Geun Jung, Young Suk Jo, Jandee Lee
来源: ENDOCRINE-RELATED CANCER

摘要:

端粒酶逆转录酶启动子突变(pTERT MT)通过端粒酶逆转录酶(TERT)的异常表达促进人类致癌。然而,尽管提出了多种 TERT 机制,但独立于 pTERT MT 的 TERT 表达的致瘤影响仍不清楚。为了解决这个问题,我们采用综合生物信息学来评估不同 TERT 表达机制之间注意到的生物变异。带有 pTERT MT (pTERT MT PTC) 的乳头状甲状腺癌 (PTC) 表现出侵袭性的临床行为,并表现出与细胞永生性和基因组不稳定性相关的生物学特征。具有 TERT 表达但不具有 pTERT MT (TERT ( ) PTC) 的 PTC 也表现出较差的临床病理特征,并且富含免疫反应。相应地,c-MYC/E2F 和核因子 kappa B (NFκB) 分别是 pTERT MT PTC 和 TERT ( ) PTC 中的主要转录因子。值得注意的是,我们发现 TERT 高甲基化肿瘤区域 (THOR) 是 TERT ( ) PTC 患者潜在的 TERT 表达机制。此外,结合基于机器学习的评分系统,破译了甲状腺乳头状癌的三种独特亚型。我们提出的评分系统具有临床意义,特别是在微小癌预测生存结果和推断放射性碘治疗的治疗反应方面。最后,我们的分析扩展到内分泌相关癌症,揭示了 TERT 的各种调节机制,但临床结果和生物学行为较差。
Telomerase reverse transcriptase promoter mutation (pTERT MT) promotes human carcinogenesis via aberrant expression of telomerase reverse transcriptase (TERT). However, the tumorigenic impact of TERT expression independent of pTERT MT remains unclear despite numerous mechanisms of TERT being suggested. To tackle this issue, we employed comprehensive bioinformatics to assess biological variations noticed among different TERT expression mechanisms. Papillary thyroid cancer (PTC) with pTERT MT (pTERT MT PTC) presented aggressive clinical behavior and exhibited biological profiles associated with cellular immortality and genomic instability. PTC with TERT expression, but without pTERT MT (TERT (+) PTC), also exhibited poor clinicopathological characteristics and was enriched with immune responses. In accordance, c-MYC/E2F and nuclear factor kappa B (NFκB) were dominant transcription factors in pTERT MT PTC and TERT (+) PTC, respectively. Notably, we revealed TERT hypermethylated oncological region (THOR) as potential TERT expressing mechanism in TERT (+) PTC patients. Furthermore, three unique subtypes of papillary thyroid cancer were deciphered using combination of machine learning based scoring systems. Our proposed scoring system was clinically significant especially in microcarcinoma predicting survival outcomes and inferring therapeutic responses of radioactive iodine therapy. Finally, our analysis was expanded to endocrine-related cancers, unveiling various regulatory mechanisms of TERT with poor clinical outcomes and biological behaviors.