Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics

Screening of common genomic biomarkers to explore common drugs for the treatment of pancreatic and kidney cancers with type-2 diabetes through bioinformatics analysis

Type 2 diabetes (T2D) is a crucial risk factor for both pancreatic cancer (PC) and kidney cancer (KC). However, effective common drugs for treating PC and/or KC patients who are also suffering from T2D are currently lacking, despite the probability of their co-occurrence. Taking disease-specific multiple drugs during the co-existence of multiple diseases may lead to adverse side effects or toxicity to the patients due to drug-drug interactions. This study aimed to identify T2D-, PC and KC-causing common genomic biomarkers (cGBs) highlighting their pathogenetic mechanisms to explore effective drugs as their common treatment. We analyzed transcriptomic profile datasets, applying weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis approaches to identify T2D-, PC-, and KC-causing cGBs. We then disclosed common pathogenetic mechanisms through gene ontology (GO) terms, KEGG pathways, regulatory networks, and DNA methylation of these cGBs. Initially, we identified 78 common differentially expressed genes (cDEGs) that could distinguish T2D, PC, and KC samples from controls based on their transcriptomic profiles. From these, six top-ranked cDEGs (TOP2A, BIRC5, RRM2, ALB, MUC1, and E2F7) were selected as cGBs and considered targets for exploring common drug molecules for each of three diseases. Functional enrichment analyses, including GO terms, KEGG pathways, and regulatory network analyses involving transcription factors (TFs) and microRNAs, along with DNA methylation and immune infiltration studies, revealed critical common molecular mechanisms linked to PC, KC, and T2D. Finally, we identified six top-ranked drug molecules (NVP.BHG712, Irinotecan, Olaparib, Imatinib, RG-4733, and Linsitinib) as potential common treatments for PC, KC and T2D during their co-existence, supported by the literature reviews. Thus, this bioinformatics study provides valuable insights and resources for developing a genome-guided common treatment strategy for PC and/or KC patients who are also suffering from T2D.

Epigenetic silencing ZSCAN23 promotes pancreatic cancer growth by activating Wnt signaling

Pancreatic ductal adenocarcinoma (PDAC) is the most malignant tumor. Zinc finger and SCAN domain-containing protein 23 (ZSCAN23) is a new member of the SCAN domain family. The expression regulation and biological function remain to be elucidated. In this study, we explored the epigenetic regulation and the function of ZSCAN23 in PDAC. ZSCAN23 was methylated in 60.21% (171/284) of PDAC and its expression was regulated by promoter region methylation. The expression of ZSCAN23 inhibited cell proliferation, colony formation, migration, invasion, and induced apoptosis and G1/S phase arrest. ZSCAN23 suppressed Panc10.05 cell xenograft growth in mice. Mechanistically, ZSCAN23 inhibited Wnt signaling by interacting with myosin heavy chain 9 (MYH9) in pancreatic cancer cells. ZSCAN23 is frequently methylated in PDAC and may serve as a detective marker. ZSCAN23 suppresses PDAC cell growth both in vitro and in vivo.

Targeted inhibition of CHKα and mTOR in models of pancreatic ductal adenocarcinoma: A novel regimen for metastasis

Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic malignancy for which there are currently no effective anti-metastatic therapies. Herein, we employed single-cell RNA sequencing and metabolomics analysis to demonstrate that metastatic cells highly express focal adhesion kinase (FAK), which promotes metastasis by remodeling choline kinase α (CHKα)-dependent choline metabolism. We designed a novel CHKα inhibitor, CHKI-03, and verified its efficacy in inhibiting metastasis in multiple preclinical models. Classical and newly synthesized small-molecule inhibitors have previously been used to assess the therapeutic potential of targeting mTOR and CHKα in various animal models. Mechanistically, FAK activated mTOR and its downstream HIF-1α, thereby elevating CHKα expression and promoting the proliferation, migration, and invasion of PDAC cells, as well as tumor growth and metastasis. Consistently, high expression levels of both FAK and CHKα are correlated with poor prognosis in patients with PDAC. Notably, CHK1-03 inhibited CHKα expression and also suppressed mTORC1 phosphorylation, disrupting the mTORC1-CHKα positive feedback loop. In addition, the combination of CHKI-03 and the mTORC1 inhibitor rapamycin synergistically inhibited tumor growth and metastasis in PDX models. The combination of CHKI-03 and rapamycin demonstrates considerable therapeutic efficacy in PDO models resistant to gemcitabine. Our findings reveal a pivotal mechanism underlying PDAC metastasis regulated by mTORC1-CHKα loop-dependent choline metabolism reprogramming, highlighting the therapeutic potential of this novel regimen for treating PDAC metastasis.

Activatable Fluorescence and Bio/Chemiluminescence Probes for Aminopeptidases: From Design to Biomedical Applications

Aminopeptidases are exopeptidases that catalyze the cleavage of amino acid residues from the N-terminal fragment of protein or peptide substrates. Owing to their function, they play important roles in protein maturation, signal transduction, cell-cycle control, and various disease mechanisms, notably in cancer pathology. To gain better insights into their function, molecular imaging assisted by fluorescence and bio/chemiluminescence probes has become an indispensable method to their superiorities, including excellent sensitivity, selectivity, and real-time and noninvasive imaging. Numerous efforts are made to develop activatable probes that can effectively enhance efficiency and accuracy as well as minimize the side effects. This review is classified according to the type of aminopeptidases, summarizing some recent works on the design, work mechanism, and sensing, imaging, and theranostic performance of their activatable probe. Finally, the current challenges are outlined in developing activatable probes for aminopeptidases and provide possible solutions for future advancements.

A Four-Gene Panel for the Prediction of Prognosis and Immune Cell Enrichment in Gliomas

BACKGROUNDS

Gliomas is a deadly disease without effective therapy. Although immunotherapy has provided novel choices for glioma treatment, the curative efficacy is unsatisfactory due to the complex immune micro-environment and the heterogeneity of the disease. Therefore, it is urgent to identify effective biomarkers and therapeutic targets.

METHODS

Overall survival, gene ontology (GO), Kyoto Encyclopedia of Genes, and Genomes (KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and immune infiltration were analyzed by bioinformatics software with The Cancer Genome Atlas (TCGA) database.

RESULTS

Based on the TCGA database and protein-protein interaction (PPI) analysis revealed a four-gene panels [DNA topoisomerase II alpha (TOP2A); ribonucleotide reductase regulatory subunit M2 (RRM2); kinesin family member 20 A (KIF20A) and DLG associated protein 5 (DLGAP5)], which correlated with poor prognosis, including overall survival (OS), disease specific survival (DSS) and progress free interval (PFI), mitosis, cell cycle, Th2 cells and macrophages enrichment. The four-gene panels correlates with the biomarkers of Th2 cells, macrophages tumor-associated macrophages (TAMs) and the immune checkpoint molecules in gliomas.

CONCLUSION

The four-gene panels represented a novel prognostic indicator and potential therapeutic target for the treatment of glioma. In addition, the four-gene panels might contribute to enhance the efficacy of immunotherapy in glioma.

Anti-tumor target screening of sea cucumber saponin Frondoside A: a bioinformatics and molecular docking analysis

Cancer remains the leading cause of death worldwide. In spite of significant advances in targeted and immunotherapeutic approaches, clinical outcomes for cancer remain poor. The aim of the present study was to investigate the potential mechanisms and therapeutic targets of Frondoside A for the treatment of liver, pancreatic, and bladder cancers. The data presented in our study demonstrated that Frondoside A reduced the viability and migration of HepG2, Panc02, and UM-UC-3 cancer cell in vitro. Moreover, we utilized the GEO database to screen and identify for differentially expressed genes (DEGs) in liver, pancreatic, and bladder cancers, which resulted in the identification of 714, 357, and 101 DEGs, respectively. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation were performed using the Metascape database for DEGs that were significantly associated with cancer development. The protein-protein interaction (PPI) networks of the identified DEGs in liver, pancreatic, and bladder cancers were analyzed using Cytoscape 3.9.0 software, and subsequently identified potential key genes that were associated with these networks. Subsequently, their prognostic values were assessed by gene expression level analysis and Kaplan-Meier survival analysis (GEPIA). Furthermore, we utilized TIMER 2.0 to investigate the correlation between the expression of the identified key gene and cancer immune infiltration. Finally, molecular docking simulations were performed to assess the affinity of Frondoside A and key genes. Our results showed a significant correlation between these DEGs and cancer progression. Combined, these analyses revealed that Frondoside A involves in the regulation of multiple pathways, such as drug metabolism, cell cycle in liver cancer by inhibiting the expression of CDK1, TOP2A, CDC20, and KIF20A, and regulates protein digestion and absorption, receptor interaction in pancreatic cancer by down-regulation of ASPM, TOP2A, DLGAP5, TPX2, KIF23, MELK, LAMA3, and ANLN. While in bladder cancer, Frondoside A regulates muscle contraction, complement and coagulation cascade by increase FLNC expression. In conclusion, the present study offers valuable insights into the molecular mechanism underlying the anticancer effects of Frondoside A, and suggests that Frondoside A can be used as a functional food supplement or further developed as a natural anti-cancer drug.

A Novel HOXA10-Associated 5-Gene-Based Prognostic Signature for Stratification of Short-term Survivors of Pancreatic Ductal Adenocarcinoma

PURPOSE

Despite the significant association of molecular subtypes with poor prognosis in patients with pancreatic ductal adenocarcinoma (PDAC), few efforts have been made to identify the underlying pathway(s) responsible for this prognosis. Identifying a clinically relevant prognosis-based gene signature may be the key to improving patient outcomes.

EXPERIMENTAL DESIGN

We analyzed the transcriptomic profiles of treatment-naïve surgically resected short-term survivor (STS) and long-term survivor (LTS) tumors (GSE62452) for expression and survival, followed by validation in several datasets. These results were corroborated by IHC analysis of PDAC-resected STS and LTS tumors. The mechanism of this differential survival was investigated using CIBERSORT and pathway analyses.

RESULTS

We identified a short-surviving prognostic subtype of PDAC with a high degree of significance (P = 0.018). One hundred thirty genes in this novel subtype were found to be regulated by a master regulator, homeobox gene HOXA10, and a 5-gene signature derived from these genes, including BANF1, EIF4G1, MRPS10, PDIA4, and TYMS, exhibited differential expression in STSs and a strong association with poor survival. This signature was further associated with the proportion of T cells and macrophages found in STSs and LTSs, demonstrating a potential role in PDAC immunosuppression. Pathway analyses corroborated these findings, revealing that this HOXA10-driven prognostic signature is associated with immune suppression and enhanced tumorigenesis.

CONCLUSIONS

Overall, these findings reveal the presence of a HOXA10-associated prognostic subtype that can be used to differentiate between STS and LTS patients of PDAC and inform on the molecular interactions that play a role in this poor prognosis.

Targeting DNA topoisomerase IIα (TOP2A) in the hypoxic tumour microenvironment using unidirectional hypoxia-activated prodrugs (uHAPs)

The hypoxic tumour microenvironment (hTME), arising from inadequate and chaotic vascularity, can present a major obstacle for the treatment of solid tumours. Hypoxic tumour cells compromise responses to treatment since they can generate resistance to radiotherapy, chemotherapy and immunotherapy. The hTME impairs the delivery of a range of anti-cancer drugs, creates routes for metastasis and exerts selection pressures for aggressive phenotypes; these changes potentially occur within an immunosuppressed environment. Therapeutic strategies aimed at the hTME include targeting the molecular changes associated with hypoxia. An alternative approach is to exploit the prevailing lack of oxygen as a principle for the selective activation of prodrugs to target cellular components within the hTME. This review focuses on the design concepts and rationale for the use of unidirectional Hypoxia-Activated Prodrugs (uHAPs) to target the hTME as exemplified by the uHAPs AQ4N and OCT1002. These agents undergo irreversible reduction in a hypoxic environment to active forms that target DNA topoisomerase IIα (TOP2A). This nuclear enzyme is essential for cell division and is a recognised chemotherapeutic target. An activated uHAP interacts with the enzyme-DNA complex to induce DNA damage, cell cycle arrest and tumour cell death. uHAPs are designed to overcome the shortcomings of conventional HAPs and offer unique pharmacodynamic properties for effective targeting of TOP2A in the hTME. uHAP therapy in combination with standard of care treatments has the potential to enhance outcomes by co-addressing the therapeutic challenge presented by the hTME.

Integrated analysis of Dendrobium nobile extract Dendrobin A against pancreatic ductal adenocarcinoma based on network pharmacology, bioinformatics, and validation experiments

Background: Dendrobium nobile (D. nobile), a traditional Chinese medicine, has received attention as an anti-tumor drug, but its mechanism is still unclear. In this study, we applied network pharmacology, bioinformatics, and in vitro experiments to explore the effect and mechanism of Dendrobin A, the active ingredient of D. nobile, against pancreatic ductal adenocarcinoma (PDAC). Methods: The databases of SwissTargetPrediction and PharmMapper were used to obtain the potential targets of Dendrobin A, and the differentially expressed genes (DEGs) between PDAC and normal pancreatic tissues were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. The protein-protein interaction (PPI) network for Dendrobin A anti-PDAC targets was constructed based on the STRING database. Molecular docking was used to assess Dendrobin A anti-PDAC targets. PLAU, one of the key targets of Dendrobin A anti-PDAC, was immunohistochemically stained in clinical tissue arrays. Finally, in vitro experiments were used to validate the effects of Dendrobin A on PLAU expression and the proliferation, apoptosis, cell cycle, migration, and invasion of PDAC cells. Results: A total of 90 genes for Dendrobin A anti-PDAC were screened, and a PPI network for Dendrobin A anti-PDAC targets was constructed. Notably, a scale-free module with 19 genes in the PPI indicated that the PPI is highly credible. Among these 19 genes, PLAU was positively correlated with the cachexia status while negatively correlated with the overall survival of PDAC patients. Through molecular docking, Dendrobin A was found to bind to PLAU, and the Dendrobin A treatment led to an attenuated PLAU expression in PDAC cells. Based on clinical tissue arrays, PLAU protein was highly expressed in PDAC cells compared to normal controls, and PLAU protein levels were associated with the differentiation and lymph node metastatic status of PDAC. In vitro experiments further showed that Dendrobin A treatment significantly inhibited the proliferation, migration, and invasion, inducing apoptosis and arresting the cell cycle of PDAC cells at the G2/M phase. Conclusion: Dendrobin A, a representative active ingredient of D. nobile, can effectively fight against PDAC by targeting PLAU. Our results provide the foundation for future PDAC treatment based on D. nobile.

Identification and Validation of Three PDAC Subtypes and Individualized GSVA Immune Pathway-Related Prognostic Risk Score Formula in Pancreatic Ductal Adenocarcinoma Patients

Background

With the progress of precision medicine treatment in pancreatic ductal adenocarcinoma (PDAC), individualized cancer-related medical examination and prediction are of great importance in this high malignant tumor and tumor-immune microenvironment with changed pathways highly enrolled in the carcinogenesis of PDAC.

Methods

High-throughput data of pancreatic ductal adenocarcinoma were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. After batch normalization, the enrichment pathway and relevant scores were identified by the enrichment of immune-related pathway signature using gene set variation analysis (GSVA). Then, cancerous subtype in TCGA and GEO samples was defined through the NMF methods by cancertypes packages in R software, respectively. Subsequently, the significance between the characteristics of each TCGA sample and cancer type and the significant prognosis-related pathway with risk score formula is calculated through t-test and univariate Cox analysis. Next, the prognostic value of gained risk score formula and each significant prognosis-related pathway were validated in TCGA and GEO samples by survival analysis. The pivotal hub genes in the enriched significant prognosis-related pathway are identified and validated, and the TIMER database was used to identify the potential role of hub genes in the PDAC immune environment. The potential role of hub genes is promoting the transdifferentiation of cancer-associated fibroblasts.

Results

The enrichment pathway and relevant scores were identified by GSVA, and 3 subtypes of pancreatic ductal adenocarcinoma were defined in TCGA and GEO samples. The clinical stage, tumor node metastasis classification, and tumor grade are strongly relative to the subtype above in TCGA samples. A risk formula about GSVA significant pathway “GSE45365_WT_VS_IFNAR_KO_CD11B_DC_MCMV_INFECTION_DN ∗ 0.80 + HALLMARK_GLYCOLYSIS ∗ 16.8 + GSE19888_CTRL_VS_T_CELL_MEMBRANES_ACT_MAST_CELL_DN ∗ 14.4” was identified and validated in TCGA and GEO samples through survival analysis with significance. DCN, VCAN, B4GALT7, SDC1, SDC2, B3GALT6, B3GAT3, SDC3, GPC1, and XYLT2 were identified as hub genes in these GSVA significant pathways and validated in silico.

Conclusions

Three pancreatic ductal adenocarcinoma subtypes are identified, and an individualized GSVA immune pathway score-related prognostic risk score formula with 10 hub genes is identified and validated. The predicted function of the 10 upregulated hub genes in tumor-immune microenvironment was promoting the infiltration of cancer-associated fibroblasts. These findings will contribute to the precision medicine of pancreatic ductal adenocarcinoma treatment and tumor immune-related basic research.