Identification of PPAR-related differentially expressed genes liver hepatocellular carcinoma and construction of a prognostic model based on data analysis and molecular docking

Liver hepatocellular carcinoma (LIHC) is a significant global health issue with limited treatment options. In this study, single-cell RNA sequencing (scRNA-seq) data were used to explore the molecular mechanisms of LIHC development and identify potential targets for therapy. The expression of peroxisome proliferator-activated receptors (PPAR)-related genes was analysed in LIHC samples, and primary cell populations, including natural killer cells, T cells, B cells, myeloid cells, endothelial cells, fibroblasts and hepatocytes, were identified. Analysis of the differentially expressed genes (DEGs) between normal and tumour tissues revealed significant changes in gene expression in various cell populations. PPAR activity was evaluated using the 'AUCell' R software, which indicated higher scores in the normal versus the malignant hepatocytes. Furthermore, the DEGs showed significant enrichment of pathways related to lipid and glucose metabolism, cell development, differentiation and inflammation. A prognostic model was then constructed using 8 PPARs-related genes, including FABP5, LPL, ACAA1, PPARD, FABP4, PLIN1, HMGCS2 and CYP7A1, identified using least absolute shrinkage and selection operator-Cox regression analysis, and validated in the TCGA-LIHC, ICGI-LIRI and GSE14520 datasets. Patients with low-risk scores had better prognosis in all cohorts. Based on the expression of the eight model genes, two clusters of patients were identified by ConsensusCluster analysis. We also predicted small-molecule drugs targeting the model genes, and identified perfluorohexanesulfonic acid, triflumizole and perfluorononanoic acid as potential candidates. Finally, wound healing assay confirmed that PPARD can promote the migration of liver cancer cells. Overall, our study offers novel perspectives on the molecular mechanisms of LIHC and potential areas for therapeutic intervention, which may facilitate the development of more effective treatment regimens.

Brain Metastases Are Regulated by Immuno-inflammatory Signaling Pathways Governed by STAT3, MAPK and Tumor Suppressor p53 Status: Possible Therapeutic Targets

BACKGROUND/AIM

Brain metastasis (BM) is a complex multi-step process involving various immune checkpoint proteins. Mitogen-activated protein kinase (MAPK), extracellular signal-regulated kinases 1/2 (ERK1/2), and signal transducer and activator of transcription 3 (STAT3) are implicated in tumorigenesis and are critical upstream regulators of Programmed Death Ligand 1 (PD-L1), an immunotherapy target. Tumor suppressor p53, dysregulated in cancers, regulates STAT3 and ERK1/2 signaling. This study examined the roles of STAT3, MAPK and p53 status in BM initiation and maintenance.

MATERIALS AND METHODS

Twenty-six BM, with various primary malignancies, were used (IRB-approved) to determine mutant p53 (p53mt), pSTAT3Tyr705, pERK1/2Thr202/Tyr204, and PD-L1 expression using immunohistochemistry. cDNA microarray was used for gene expression analysis. Brain-metastatic breast cancer cells (MDA-MB-231) were treated with STAT3 (NSC74859) or MAPK/ERK1/2 (U0126) inhibitors in regular or astrocytic media. ERK1/2 pathway was assessed using western blotting, and cell proliferation and migration were determined using MTT and scratch-wound assays, respectively.

RESULTS

pSTAT3Tyr705 and pERK1/2Thr202/Tyr204 were expressed at tumor margins, whereas p53mt and PD-L1 were uniformly expressed, with significant overlap between expression of these proteins. Gene expression analysis identified alterations in 18 p53- and 32 STAT3- or MAPK-associated genes contributing to dysregulated immune responses and cell cycle regulation. U0126 and NSC74859 reduced pERK1/2Thr202/Tyr204 expression. Cell proliferation decreased following each treatment (p≤0.01). Migration stagnated following U0126 treatment in astrocytic media (p≤0.01).

CONCLUSION

Activation of STAT3 and ERK1/2 promotes BM and provides compelling evidence for use of STAT3, ERK1/2 and p53 status as potential immunotherapeutic targets in BM.

RNA-sequencing based first choice of treatment and determination of risk in multiple myeloma

Background

Immunotherapeutic targets in multiple myeloma (MM) have variable expression height and are partly expressed in subfractions of patients only. With increasing numbers of available compounds, strategies for appropriate choice of targets (combinations) are warranted. Simultaneously, risk assessment is advisable as patient's life expectancy varies between months and decades.

Methods

We first assess feasibility of RNA-sequencing in a multicenter trial (GMMG-MM5, n=604 patients). Next, we use a clinical routine cohort of untreated symptomatic myeloma patients undergoing autologous stem cell transplantation (n=535, median follow-up (FU) 64 months) to perform RNA-sequencing, gene expression profiling (GEP), and iFISH by ten-probe panel on CD138-purified malignant plasma cells. We subsequently compare target expression to plasma cell precursors, MGUS (n=59), asymptomatic (n=142) and relapsed (n=69) myeloma patients, myeloma cell lines (n=26), and between longitudinal samples (MM vs. relapsed MM). Data are validated using the independent MMRF CoMMpass-cohort (n=767, FU 31 months).

Results

RNA-sequencing is feasible in 90.8% of patients (GMMG-MM5). Actionable immune-oncological targets (n=19) can be divided in those expressed in all normal and >99% of MM-patients (CD38, SLAMF7, BCMA, GPRC5D, FCRH5, TACI, CD74, CD44, CD37, CD79B), those with expression loss in subfractions of MM-patients (BAFF-R [81.3%], CD19 [57.9%], CD20 [82.8%], CD22 [28.4%]), aberrantly expressed in MM (NY-ESO1/2 [12%], MUC1 [12.7%], CD30 [4.9%], mutated BRAF V600E/K [2.1%]), and resistance-conveying target-mutations e.g., against part but not all BCMA-directed treatments. Risk is assessable regarding proliferation, translated GEP- (UAMS70-, SKY92-, RS-score) and de novo (LfM-HRS) defined risk scores. LfM-HRS delineates three groups of 40%, 38%, and 22% of patients with 5-year and 12-year survival rates of 84% (49%), 67% (18%), and 32% (0%). R-ISS and RNA-sequencing identify partially overlapping patient populations, with R-ISS missing, e.g., 30% (22/72) of highly proliferative myeloma.

Conclusion

RNA-sequencing based assessment of risk and targets for first choice treatment is possible in clinical routine.

CNN3 in glioma: The prognostic factor and a potential immunotherapeutic target

BACKGROUND

Gliomas are the most intrinsic type of primary intracranial tumors. The protein encoded by The calponin 3 (CNN3) has been proven to be a member of the calponin family. Its relationships with cervical cancer, colorectal cancer, gastric cancer, and colon cancer have been emphasized by several studies. Our research aims to explore the prognosis value and immunotherapeutic targetability of CNN3 in glioma patients using bioinformatics approach.

METHODS

CNN3 expression in glioma was analyzed based on GEO and TCGA datasets. Gene expression profiling with clinical information was employed to investigate the correlation between clinicopathological features of glioma patients and relative CNN3 expression levels. Survival analysis was conducted using Kaplan-Meier analysis and the Cox proportional-hazards regression model. Gene set enrichment analysis was conducted to select the pathways significantly enriched for CNN3 associations. Correlations between inflammatory activities, immune checkpoint molecules and CNN3 were probed by gene set variation analysis, correlograms, and correlation analysis.

RESULTS

CNN3 was enriched in gliomas, and high expression of CNN3 correlated with worse clinicopathological features and prognosis. Associations between CNN3 and several immune-related pathways were confirmed using a bioinformatics approach. Correlation analysis revealed that CNN3 was associated with inflammatory and immune activities, tumor microenvironment, and immune checkpoint molecules.

CONCLUSION

Our results indicate that high CNN3 expression levels predict poor prognosis, and CNN3 may be a promising immunotherapy target.

Prognostic Biomarkers and Immunotherapeutic Targets Among CXC Chemokines in Pancreatic Adenocarcinoma

Background

Pancreatic cancer is one of the principal causes of tumor-related death worldwide. CXC chemokines, a subfamily of functional chemotactic peptides, affect the initiation of tumor cells and clinical outcomes in several human malignant tumors. However, the specific biological functions and clinical significance of CXC chemokines in pancreatic cancer have not been clarified.

Methods

Bioinformatics analysis tools and databases, including ONCOMINE, GEPIA2, the Human Protein Atlas, DAVID, GeneMANIA, cBioPortal, STRING, DGidb, MethSurv, TRRUST, SurvExpress, SurvivalMeth, and TIMER, were utilized to clarify the clinical significance and biological functions of CXC chemokine in pancreatic cancer.

Results

Except for CXCL11/12, the transcriptional levels of other CXC chemokines in PAAD tissues were significantly elevated, and the expression level of CXCL16 was the highest among these CXC chemokines. Our findings also suggested that all of the CXC chemokines were linked to tumor-immune dysfunction involving the abundance of immune cell infiltration, and the Cox proportional hazard model confirmed that dendritic and CXCL3/5/7/8/11/17 were significantly associated with the clinical outcome of PAAD patients. Furthermore, increasing expressions of CXCL5/9/10/11/17 were related to unfavorable overall survival (OS), and only CXCL17 was a prognostic factor for disease-free survival (DFS) in PAAD patients. The expression pattern and prognostic power of CXC chemokines were further validated in the independent GSE62452 dataset. For the prognostic value of single CpG of DNA methylation of CXC chemokines in patients with PAAD, we identified 3 CpGs of CXCL1, 2 CpGs of CXCL2, 2 CpGs of CXCL3, 3 CpGs of CXCL4, 10 CpGs of CXCL5, 1 CpG of CXCL6, 1 CpG of CXCL7, 3 CpGs of CXCL12, 3 CpGs of CXCL14, and 5 CpGs of CXCL17 that were significantly associated with prognosis in PAAD patients. Moreover, the prognostic value of CXC chemokine signature in PAAD was explored and tested in two independent cohort, and results indicated that the patients in the low-risk group had a better OS compared with the high-risk group. Survival analysis of the DNA methylation of CXC chemokine signature demonstrated that PAAD patients in the high-risk group had longer survival times.

Conclusions

These findings reveal the novel insights into CXC chemokine expression and their biological functions in the pancreatic cancers, which might serve as accurate prognostic biomarkers and suitable immunotherapeutic targets for patients with pancreatic cancer.

WGCNA identification of TLR7 as a novel diagnostic biomarker, progression and prognostic indicator, and immunotherapeutic target for stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is a malignant tumor with high histological heterogeneity. However, the potential mechanism of STAD tumorigenesis remains to be elucidated. The purpose of our research was to identify candidate genes associated with the diagnosis, progression, prognosis, and immunotherapeutic targets of STAD. Based on tumor samples from the GSE28541 dataset, weighted gene co-expression network analysis revealed 16 modules related to STAD stage and grade. The salmon module emerged as the most relevant module (cor = 0.34), and functional enrichment analysis showed that the genes in the salmon were primarily related to major histocompatibility complex, immune response, and cell differentiation. Toll-like receptor 7 (TLR7) was recognized as the real hub gene in the salmon module. Compared to normal stomach tissues, the transcriptional and translational levels of TLR7 were significantly elevated in STAD. Receiver operating characteristic curves verified that TLR7 displayed remarkable sensitivity and specificity for the diagnosis of STAD. The functions of TLR7 were primarily enriched in the regulation of Toll-like receptor signaling pathway, pattern recognition receptor signaling pathway, and innate immune response. Overexpression of TLR7 tended to indicate more advanced STAD, higher degree of STAD, and poorer prognosis of STAD. In addition, TLR7 expression was positively correlated with immune cell infiltration and immune checkpoint expression. Somatic copy number alteration of TLR7 was also significantly related to immune cell infiltration. In conclusion, this study revealed the crucial role of TLR7 in STAD and provided new perspectives for the selection of biomarkers, progression and prognosis indicators, and immunotherapeutic targets for STAD.

Molecular and clinical characterization of PARP9 in gliomas: A potential immunotherapeutic target

BACKGROUND

Glioma is a primary malignancy of the central nervous system (CNS). As biomedicine advances, an efficient molecular target is urgently needed for the diagnosis and treatment of glioma. Meanwhile, several studies have demonstrated that glioma development is closely related to immunity. PARP9 is an inactive mono-ADP-ribosyltransferase belonging to the poly-ADP ribosyltransferase (ARTD) family. In this article, we aimed to reveal the relationship between PARP9 and glioma and explore the potential prognostic value and immunotherapeutic targetability of PARP9 in glioma.

METHODS

PARP9 transcript levels were analyzed with TCGA and GEO databases. The clinicopathological information of patients with glioma in the TCGA database and gene expression profiles were analyzed to determine the relationship between the expression of PARP9 and clinicopathologic characteristics. Kaplan-Meier survival analysis, univariate Cox regression analysis, and multivariate Cox regression analysis were used for survival analysis. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used for bioinformatics analysis. Correlation analysis explored the relationships between PARP9, infiltrating inflammatory immune cells, and immune checkpoint molecules.

RESULTS

PARP9 is highly expressed in glioma, and high expression of PARP9 is associated with poor prognosis and advanced clinicopathological features. Bioinformatics analysis showed that some immune-related pathways were closely associated with high expression of PARP9. Correlation analysis indicated that PARP9 was closely related to inflammatory and immune responses, high immune cell infiltration, and immune checkpoint molecules.

CONCLUSIONS

PARP9 may serve as an unfavorable prognosis predictor for glioma and a potential immunotherapeutic target.