Yin Yi, Xu Zi-Yuan, Liu Yuan-Jie, Huang Wei, Zhang Qian, Li Jie-Pin, Zou Xi
Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.
No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China.
J Hepatocell Carcinoma. 2022 Aug 27;9:885-900. doi: 10.2147/JHC.S378175. eCollection 2022.
Helicases have been classified as a class of enzymes that determine the stability of the cellular genome. There is growing evidence that helicases can help tumor cells resist drug killing by repairing Deoxyribose Nucleic Acid (DNA) or stabilizing transcription, which may contribute to the understanding of drug resistance. Currently, identifying cancer biomarkers among helicases and stratifying patients according to helicase activity will be able to guide treatment well.
We clustered 371 hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) by consensus clustering based on helicase expression profiles to identify potential molecular subtypes. The Multiscale Embedded Gene Co-Expression Network Analysis (MEGENA) algorithm was used to find core differential gene modules between different molecular subtypes, and single-cell analysis was utlized to explore the potential function of hub gene. Immunohistochemical (IHC) staining was used to verify the diagnostic value of DDX56 and its ability to reflect the proliferation efficiency of cancer cells.
We identified two subtypes associated with helicase. High helicase subtype was associated with poor clinical outcome, massive M0 macrophage infiltration, and highly active cell proliferation features. In addition, we identified a new biomarker, , which has not been reported in HCC, was highly expressed in HCC tissues, associated with poor prognosis, and was also shown to be associated with high cell proliferative activity.
In conclusion, based on helicase expression profiles, we have developed a new classification system for HCC, which is a proliferation-related system, and has clinical significance in evaluating prognosis and treating HCC patients, including immunotherapy and chemotherapy. In addition, we identified a new biomarker, , which is overexpressed in HCC tissues, predicts a poor prognosis and is a validated index of tumor cell proliferation.
解旋酶已被归类为一类决定细胞基因组稳定性的酶。越来越多的证据表明，解旋酶可通过修复脱氧核糖核酸（DNA）或稳定转录来帮助肿瘤细胞抵抗药物杀伤，这可能有助于理解耐药性。目前，在解旋酶中识别癌症生物标志物并根据解旋酶活性对患者进行分层将能够很好地指导治疗。
我们基于解旋酶表达谱，通过一致性聚类对来自癌症基因组图谱（TCGA）的371例肝细胞癌（HCC）患者进行聚类，以识别潜在的分子亚型。使用多尺度嵌入式基因共表达网络分析（MEGENA）算法来寻找不同分子亚型之间的核心差异基因模块，并利用单细胞分析来探索枢纽基因的潜在功能。免疫组织化学（IHC）染色用于验证DDX56的诊断价值及其反映癌细胞增殖效率的能力。
我们识别出与解旋酶相关的两种亚型。高解旋酶亚型与不良临床结局、大量M0巨噬细胞浸润和高活性细胞增殖特征相关。此外，我们识别出一种新的生物标志物，该标志物在HCC中尚未见报道，在HCC组织中高表达，与预后不良相关，并且还显示与高细胞增殖活性相关。
总之，基于解旋酶表达谱，我们开发了一种新的HCC分类系统，这是一种与增殖相关的系统，在评估HCC患者的预后和治疗方面具有临床意义，包括免疫治疗和化疗。此外，我们识别出一种新的生物标志物，该标志物在HCC组织中过表达，预测预后不良，并且是肿瘤细胞增殖的有效指标。
