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

Hepatocellular carcinoma (HCC) 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 a 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 the condition of resistance to sorafenib. Datasets of HCC, including messenger RNAs (mRNAs) 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 was employed to identify key sorafenib resistance-related pathways. In addition, we analyzed and confirmed the regulation of key genes discovered in this study by combining other omics data. Finally, Luciferase reporter assays were performed to validate their regulation. Our study demonstrated that the stemness index obtained from transcriptomic is a promising biomarker to predict the response of sorafenib therapy and the prognosis in HCC. We revealed the peroxisome proliferator-activated receptor signaling pathway (the PPAR signaling pathway), related to fatty acid biosynthesis, that was a potential sorafenib resistance pathway that had not been reported before. By analyzing the core regulatory genes of the PPAR signaling pathway, we identified four candidate target genes, retinoid X receptor beta (RXRB), nuclear receptor subfamily 1 group H member 3 (NR1H3), cytochrome P450 family 8 subfamily B member 1 (CYP8B1) and stearoyl-CoA desaturase (SCD), as a signature to distinguish the response of sorafenib. We proposed and validated that the RXRB and NR1H3 could directly regulate NR1H3 and SCD, respectively. Our results suggest that the combined use of SCD inhibitors and sorafenib may be a promising therapeutic approach.

clusterProfiler 4.0: A universal enrichment tool for interpreting omics data.

Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.

ggtreeExtra: Compact Visualization of Richly Annotated Phylogenetic Data.

We present the ggtreeExtra package for visualizing heterogeneous data with a phylogenetic tree in a circular or rectangular layout (https://www.bioconductor.org/packages/ggtreeExtra). The package supports more data types and visualization methods than other tools. It supports using the grammar of graphics syntax to present data on a tree with richly annotated layers and allows evolutionary statistics inferred by commonly used software to be integrated and visualized with external data. GgtreeExtra is a universal tool for tree data visualization. It extends the applications of the phylogenetic tree in different disciplines by making more domain-specific data to be available to visualize and interpret in the evolutionary context.

CTLA-4 immunotherapy exposes differences in immune response along with different tumor progression in colorectal cancer.

Tumor growth is accompanied by a changing tumor microenvironment and mutations that increase the resistance to therapy. Here, we used syngeneic models to evaluate the drug response of tumors of the same type of different sizes. We used the in vivo efficacy and Ki-67 immunohistochemistry (IHC) assay to assess the difference in responses in response to treatment with the same concentration of anti-CTLA-4. Flow cytometry analysis revealed changes in the immune subpopulations changes the spleen, peripheral blood, lymph node, and tumor tissue across different tumor growth phases. For example, naive CD4+T, CD4+TCM, CD8+TEM, T, B, Treg, CD8+TCM exhibited different percentages depending on the specific immune organ. To further expose the changes in the immune microenvironment, the level of expression of PD-1 and CTLA-4 showed statistically significant difference in related subsets for each four immune tissues in different tumor sizes. In addition, the ratios of CD4 + Teff/ CD4 + Treg and CD8 + T/Treg in corresponding immune tissue were also associated with statistically significant differences alongside tumor growth in different animal models. These results reveal the ongoing changes in the immune microenvironment during tumor progression and anti-CTLA-4 antibody immunotherapy effect depends on the expression level of immune factors.

Subcutaneous inoculation position affects the immune environment in CT26 carcinomas.

Comprehensive knowledge on the murine CT26 colon carcinoma line is a classic model used in the pharmacodynamic experiments involving IDO-1 inhibitors, immune-related checkpoint antibodies and immune related mechanisms. In this study, we determined the impact of different subcutaneous inoculation locations on tumor growth and immune factor expression. CT26 cells were treated with the IDO-1 inhibitor, INCB024360, following INF-γ stimulation and analyzed for kynurenine concentration. Female Balb/c mice were inoculated with CT26 cells in either or both the right upper flank or the right lower flank. Isolated tumors were evaluated for changes in tumor volume following treatment with anti-PD-1, anti-CTLA-4, or no treatment. Isolated tumors were also evaluated for changes in immune cell subpopulations and expression of key immune factors using FACS. Treatment of two CT26 cell lines with INCB024360 produced similar results. IC50 values were 222.5 and 276.0, and the peak inhibitory rates were 97.99% and 91.85% respectively. Analysis of tumor growth revealed that tumor volumes were larger (1925 mm3 vs. 767 mm3), and the anti-tumor effects of both anti-PD-1 and anti-CTLA-4 were different in mice inoculated in the right lower flank than in those inoculated in the upper flank. FACS analysis revealed that the CD8+T subpopulation in the right upper flank was higher than that in the lower flank (*P < 0.05). By contrast, the myeloid cell populations was lower in the right upper flank than it was in the right lower flank (*P < 0.05). The INF-γ populations in CD8+T (*P < 0.05) and regulatory T (Treg) cell subpopulation (*P < 0.05) were also more abundant in the right upper flank than in the right lower flank. In contrast to the uniform of the results from the in vitro experiment, the anti-CTLA-4 and anti-PD-1 antibodies had different efficacies depending on the location of the subcutaneous inoculation of CT26 in mice. The differences in the percentages of CD8+T, myeloid cells, INF-γ in CD8+T, and Treg subpopulations indicated that the tumor microenvironment was affected by inoculation position. Taken together, these results suggest that tumors isolated from same cell line with different inoculation positions are different enough to be considered different models.