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

Roles of peroxisome proliferator-activated receptors in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the main pathological type of liver cancer, is linked to risk factors such as viral hepatitis, alcohol intake and non-alcoholic fatty liver disease (NAFLD). Recent advances have greatly improved our understanding that NAFLD is playing a major risk factor for HCC. Peroxisome proliferator-activated receptors (PPARs) are a class of transcription factors divided into three subtypes: PPARα (PPARA), PPARδ/β (PPARD) and PPARγ (PPARG). As important nuclear receptors, PPARs are involved in many physiological processes, and PPARs can improve NAFLD by regulating lipid metabolism, accelerating fatty acid oxidation and inhibiting inflammation. In recent years, some studies have shown that PPARs can participate in the occurrence and development of HCC by regulating metabolic pathways. In addition, PPAR modulators have been reported to inhibit the proliferation and metastasis of HCC cells and can enhance the curative effect of conventional treatments. This article reviews the role of PPARs in the occurrence and development of HCC, as well as its value in the diagnosis, treatment and prognosis of HCC, in order to provide directions for future research.

Identification of Novel Stemness-based Subtypes and Construction of a Prognostic Risk Model for Patients with Lung Squamous Cell Carcinoma

BACKGROUND

Although cancer stem cells (CSCs) contribute to tumorigenesis, progression, and drug resistance, stemness-based classification and prognostic signatures of lung squamous cell carcinoma (LUSC) remain unclarified. This study attempted to identify stemness-based subtypes and develop a prognostic risk model for LUSC.

METHODS

Based on RNA-seq data from The Cancer Genome Atlas (TCGA), Gene-Expression Omnibus (GEO) and Progenitor Cell Biology Consortium (PCBC), mRNA expression-based stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR) algorithm. A weighted gene coexpression network (WGCNA) was employed to identify stemness subtypes. Differences in mutation, clinical characteristics, immune cell infiltration, and antitumor therapy responses were determined. We constructed a prognostic risk model, followed by validations in GEO cohort, pan-cancer and immunotherapy datasets.

RESULTS

LUSC patients with subtype C2 had a better prognosis, manifested by higher mRNAsi, higher tumor protein 53 (TP53) and Titin (TTN) mutation frequencies, lower immune scores and decreased immune checkpoints. Patients with subtype C2 were more sensitive to Imatinib, Pyrimethamine, and Paclitaxel therapy, whereas those with subtype C1 were more sensitive to Sunitinib, Saracatinib, and Dasatinib. Moreover, we constructed stemness-based signatures using seven genes (BMI1, CCDC51, CTNS, EIF1AX, FAM43A, THBD, and TRIM68) and found high-risk patients had a poorer prognosis in the TCGA cohort. Similar results were found in the GEO cohort. We verified the good performance of risk scores in prognosis prediction and therapy responses.

CONCLUSION

The stemness-based subtypes shed novel insights into the potential roles of LUSC-stemness in tumor heterogeneity, and our prognostic signatures offer a promising tool for prognosis prediction and guide therapeutic decisions in LUSC.

Identification and validation of a fatty acid metabolism gene signature for the promotion of metastasis in liver cancer

Metastasis is a fatal status for liver cancer, and the identification of an effective prediction model and promising therapeutic target is essential. Given the known relationship between fatty acid (FA) metabolism and the liver, the present study aimed to investigate dysregulation of genes associated with FA metabolism in liver cancer. Bioinformatics analyses were performed on data from patients with hepatocellular carcinoma (HCC) obtained from The Cancer Genome Atlas database using R software packages. Online public tools such as the Human Protein Atlas, Tumor Immune Single-Cell Hub and the University of Alabama at Birmingham Cancer Data Analysis portal were also utilized. Some essential results were further verified using in vitro experiments using HepG2 liver cancer cells. A signature consisting of three genes associated with the progression and prognosis of HCC and FA metabolism was identified. When samples were scored based on the expression of these genes and divided according to the median value, the higher score group showed a worse outcome and repressive immune microenvironment than the lower score group. Downstream pathways such as hypoxia, IL6/JAK/STAT3 and epithelial-mesenchymal transition were found to be significantly activated in the higher score group. As the core factor in the signature, mitochondrial ribosomal protein L35 (MRPL35) was found to be upregulated in HCC and to have certain impacts on the dysregulation of effective immunity. Further investigations and in vitro experiments indicated that MRPL35 facilitates the migration and invasion abilities of liver cancer, and the resistance of HCC to treatment. These findings have important implications regarding the characteristics and mechanisms of metastasis in liver cancer, and provide a promising signature based on FA metabolism-related genes that may be used to predict outcomes and explored as a novel therapeutic target in liver cancer.

Lipid metabolism of hepatocellular carcinoma impacts targeted therapy and immunotherapy

Hepatocellular carcinoma (HCC) is a common malignant tumor that affecting many people's lives globally. The common risk factors for HCC include being overweight and obese. The liver is the center of lipid metabolism, synthesizing most cholesterol and fatty acids. Abnormal lipid metabolism is a significant feature of metabolic reprogramming in HCC and affects the prognosis of HCC patients by regulating inflammatory responses and changing the immune microenvironment. Targeted therapy and immunotherapy are being explored as the primary treatment strategies for HCC patients with unresectable tumors. Here, we detail the specific changes of lipid metabolism in HCC and its impact on both these therapies for HCC. HCC treatment strategies aimed at targeting lipid metabolism and how to integrate them with targeted therapy or immunotherapy rationally are also presented.