Multi-omics analysis reveals cancer stemness function and establishes a predictive model for thyroid cancer prognosis and immunotherapy.

多组学分析揭示了癌症干细胞功能,并建立了甲状腺癌预后和免疫治疗的预测模型

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作者:Feng Zhanrong, Xu Yue, Ding Ying, Sun Xiaoxiao, Zhao Qian, Zhu Jingjing, Chen Qiang, Zhang Yang, Zhang Yilai
Cancer stem cells (CSCs) play a crucial role in the progression of tumors, resistance to immunotherapy, and the development of thyroid carcinoma (THCA). However, the precise mechanisms involved remain poorly understood. In this study, 26 mRNAs linked to cancer stemness were identified through an analysis of 13 publicly available THCA transcriptomic datasets alongside a CRISPR dataset for thyroid cancer cell lines. Notably, we revealed an inverse relationship between the stemness of cancer cells and the efficacy of immunotherapy. Utilizing multiple machine learning approaches, we created and confirmed a model for tumor stemness cells (TSC), which included genes associated with cancer stemness. This model successfully forecasted patient outcomes and responses to treatment with Cytotoxic T-Lymphocyte Associated Protein 4 (CTLA4) immune checkpoint inhibitors (ICIs) across different types of cancer. Additionally, chromosomal amplifications in regions 1q and 8p were identified as intrinsic contributors to the onset of thyroid cancer. Specifically, based on single cell dataset, the amplification of CKS1B on chromosome 1q was revealed to advance the progression of thyroid cancer cells by boosting their proliferation. Furthermore, experimental results revealed that the heightened expression of CKS1B considerably enhanced the proliferation and invasion capabilities of THCA, suggesting it could serve as a possible therapeutic target for this condition. In summary, our study sheds light on the relationship between the traits of cancer stem cells and the efficacy of immunotherapy, providing a novel model for predicting the prognosis and individual responses to immunotherapy in patients with THCA.

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