AUTHOR=Feng Tingze , Wu Tianzhi , Zhang Yanxia , Zhou Lang , Liu Shanshan , Li Lin , Li Ming , Hu Erqiang , Wang Qianwen , Fu Xiaocong , Zhan Li , Xie Zijing , Xie Wenqin , Huang Xianying , Shang Xuan , Yu Guangchuang 

TITLE=Stemness Analysis Uncovers That The Peroxisome Proliferator-Activated Receptor Signaling Pathway Can Mediate Fatty Acid Homeostasis In Sorafenib-Resistant Hepatocellular Carcinoma Cells

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.912694

DOI=10.3389/fonc.2022.912694

ISSN=2234-943X

ABSTRACT=Aim: Hepatocellular carcinoma stem cells are regarded as an important part of individualized HCC treatment and sorafenib resistance. However, there is lacking systematic assessment of stem-like indices and associations with response of Sorafenib in HCC. Our study thus aimed to evaluate the status of tumor dedifferentiation for HCC and further identify the regulatory mechanisms under condition of resistance to Sorafenib. 
Methods: Three datasets of HCC, including mRNA expression, somatic mutation and clinical information were collected. The mRNA expression-based stemness index (mRNAsi), which can represent degrees of dedifferentiation of HCC samples, was calculated to predict drug response of sorafenib therapy and prognosis. Next, unsupervised cluster analysis was conducted to distinguish mRNAsi-based subgroups and gene/geneset functional enrichment analysis were employed to identify key sorafenib resistance-related pathways. We also combined with other omics data to discuss and verify the regulations of key genes identified in this study. 
Results and Conclusion: Our study demonstrates that stemness index obtained from transcriptomic is a promising biomarker to predict the response of Sorafenib therapy and the prognosis in HCC. We reveal fatty acid metabolic-related PPAR signaling pathway is a potential sorafenib resistance pathway that doesn’t have been reported before. By analyzing the core regulatory genes of PPAR pathway, we identified four candidate targets gene, RXRB, NR1H3, CYP8B1 and SCD, as a signature to distinguish the response of sorafenib. We propose a mechanistic hypothesis and suggest the combined use of SCD inhibitors and sorafenib may be a promising therapeutic approach.