Identification of an Autophagy-Related Pair Signature for Predicting Prognoses and Immune Activity in Pancreatic Adenocarcinoma

The hsa_circ_0082152 maintains NF-κB mRNA stability by binding to MTDH to promote anti-tuberculosis drug-induced liver injury

Anti-tuberculosis drug-induced liver injury (ADLI) is a common adverse reaction during anti-tuberculosis treatment and often leads to treatment interruptions. Circular RNAs (circRNAs) have been identified as key modulators in liver diseases. CircRNAs is a special class of noncoding RNAs that have been found to have significant impacts on the progression of inflammation via various mechanisms. In the serum of ADLI patients, upregulation of the circular RNA hsa_circ_0082152 (derived from the host gene snd1) was observed, along with increased ALT and AST levels, as well as alterations in the levels of inflammation-related factors such as NF-κB, IL-1β and TNF-α. To elucidate the underlying mechanisms, we established an HL-7702-ADLI cell model and confirmed similar upregulation of hsa_circ_0082152. Downregulation of hsa_circ_0082152 significantly inhibited inflammatory injury in ADLI cells, while upregulation had the opposite effect. RNA immunoprecipitation showed that hsa_circ_0082152 functions by interacting with metadherin (MTDH). Our study further verified that the interaction of hsa_circ_0082152 with the MTDH protein binding to NF-κB mRNA to maintain NF-κB mRNA stability, which increases the expression of NF-κB and its targets IL-1β and TNF-α. Conversely, depletion of MTDH rescued the promotive effect of hsa_circ_0082152 overexpression on ADLI inflammation. Therefore, hsa_circ_0082152 overexpression promotes ADLI progression via the MTDH/NF-κB axis.

Predicting potential therapeutic targets and small molecule drugs for early-stage lung adenocarcinoma

Lung cancer is a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) constituting the majority, and its main subtype being lung adenocarcinoma (LUAD). Despite substantial advances in LUAD diagnosis and treatment, early diagnostic biomarkers inadequately fulfill clinical requirements. Thus, we conducted bioinformatics analysis to identify potential biomarkers and corresponding therapeutic drugs for early-stage LUAD patients. Here we identified a total of 10 differentially expressed genes (DEGs) with survival significance through the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Subsequently, we identified a promising small molecule drug, Aminopurvalanol A, based on the 10 key genes using the L1000FWD application, which was validated by molecular docking followed by in vivo and in vitro experiments. The results highlighted TOP2A, CDH3, ASPM, CENPF, SLC2A1, and PRC1 as potential detection biomarkers for early LUAD. We confirmed the efficacy and safety of Aminopurvalanol A, providing valuable insights for the clinical management of LUAD.

Identification of a PANoptosis-related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer

Breast cancer (BC) is the most prevalent malignancy among women worldwide. Mounting evidence suggests that PANoptosis participates in cancer development and therapy. However, the role of PANoptosis in BC remains unclear. In this study, we identified ten PANoptosis-related genes using Cox regression analysis, random forest (RF) algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. A PANoptosis-related score (PRS) was calculated based on the coefficient of LASSO. Notably, we divided the patients into high- and low-risk groups according to the PRS and revealed a negative correlation between PRS and overall survival. Next, a nomogram model was constructed and validated to improve the clinical application of PRS. Functional enrichment analyses and the Bayesian network demonstrated that differentially expressed genes between high- and low-risk groups were mainly enriched in immune-related pathways. Besides, we found significant differences in tumor mutation burden and tumor immune microenvironment between patients in these two groups using bulk-RNA and single-cell RNA sequencing data. Furthermore, charged multivesicular body protein 2B (CHMP2B) was identified as the hub gene by combining LASSO, weighted gene co-expression network analysis, RF and eXtreme Gradient Boosting. Importantly, using immunohistochemistry analysis based on our tissue microarray, we found that CHMP2B was highly expressed in tumor tissue, and CD4 and CD8 were more likely to be positive in the CHMP2B-negative group. Survival analyses revealed that CHMP2B adversely impacted the survival of BC patients. In conclusion, we not only constructed a highly accurate predictive model based on PRS, but also revealed the importance of PANoptosis-related gene signature in the modulation of the tumor microenvironment and drug sensitivity in BC.

Molecular Targets and Mechanisms of Hedyotis diffusa Willd. for Esophageal Adenocarcinoma Treatment Based on Network Pharmacology and Weighted Gene Co-expression Network Analysis

BACKGROUND

Hedyotis diffusa Willd. (HDW) is a common anticancer herbal medicine in China, and its therapeutic effectiveness has been demonstrated in a range of cancer patients. There is no consensus about the therapeutic targets and molecular mechanisms of HDW, which contains many active ingredients.

AIM

To clarify the mechanism of HDW for esophageal adenocarcinoma (EAC), we utilized network pharmacology and weighted gene co-expression network analysis methods (WGCNA).

METHODS

The gene modules that were linked with the clinical features of EAC were obtained through the WGCNA method. Then, the potential target genes were retrieved through the network pharmacology method in order to determine the targets of the active components. After enrichment analysis, a variety of signaling pathways with significant ratios of target genes were found, including regulation of trans-synaptic signaling, neuroactive ligand-receptor interaction and modulation of chemical synaptic transmission. By means of protein-protein interaction (PPI) network analysis, we have successfully identified the hub genes, which were AR, CNR1, GRIK1, MAPK10, MAPT, PGR and PIK3R1.

RESULT

Our study employed molecular docking simulations to evaluate the binding affinity of the active components with the hub gene. The identified active anticancer constituents in HDW are scopoletol, quercetin, ferulic acid, coumarin, and trans-4-methoxycinnamyl alcohol.

CONCLUSION

Our findings shed light on the molecular underpinnings of HDW in the treatment of EAC and hold great promise for the identification of potential HDW compounds and biomarkers for EAC therapy.

Smoking induces WEE1 expression to promote docetaxel resistance in esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) patients have poor clinical outcomes, with an overall 5-year survival rate of 20%. Smoking is a significant risk factor for EAC. The role of WEE1, a nuclear kinase that negatively regulates the cell cycle in normal conditions, in EAC tumorigenesis and drug resistance is not fully understood. Immunohistochemistry staining shows significant WEE1 overexpression in human EAC tissues. Nicotine, nicotine-derived nitrosamine ketone, or 2% cigarette smoke extract treatment induces WEE1 protein expression in EAC, detected by western blot and immunofluorescence staining. qRT-PCR and reporter assay indicates that smoking induces WEE1 expression through miR-195-5p downregulation in EAC. ATP-Glo cell viability and clonogenic assay confirmed that WEE1 inhibition sensitizes EAC cells to docetaxel treatment in vitro. A TE-10 smoking machine with EAC patient-derived xenograft mouse model demonstrated that smoking induces WEE1 protein expression and resistance to docetaxel in vivo. MK-1775 and docetaxel combined treatment improves EAC patient-derived xenograft mouse survival in vivo. Our findings demonstrate, for the first time, that smoking-induced WEE1 overexpression through miRNA dysregulation in EAC plays an essential role in EAC drug resistance. WEE1 inhibition is a promising therapeutic method to overcome drug resistance and target treatment refractory cancer cells.

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

Background

Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients' prognoses.

Methods

The URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool.

Results

The URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes.

Conclusion

The URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.

Paired protein kinases PRKCI-RIPK2 promote pancreatic cancer growth and metastasis via enhancing NF-κB/JNK/ERK phosphorylation

BACKGROUND

Protein kinases play a pivotal role in the malignant evolution of pancreatic cancer (PC) through mediating phosphorylation. Many kinase inhibitors have been developed and translated into clinical use, while the complex pathology of PC confounds their clinical efficacy and warrants the discovery of more effective therapeutic targets.

METHODS

Here, we used the Gene Expression Omnibus (GEO) database and protein kinase datasets to map the PC-related protein kinase-encoding genes. Then, applying Gene Expression and Profiling Interactive Analysis (GEPIA), GEO and Human Protein Atlas, we evaluated gene correlation, gene expression at protein and mRNA levels, as well as survival significance. In addition, we performed protein kinase RIPK2 knockout and overexpression to observe effects of its expression on PC cell proliferation, migration and invasion in vitro, as well as cell apoptosis, reactive oxygen species (ROS) production and autophagy. We established PC subcutaneous xenograft and liver metastasis models to investigate the effects of RIPK2 knockout on PC growth and metastasis. Co-immunoprecipitation and immunofluorescence were utilized to explore the interaction between protein kinases RIPK2 and PRKCI. Polymerase chain reaction and immunoblotting were used to evaluate gene expression and protein phosphorylation level.

RESULTS

We found fourteen kinases aberrantly expressed in human PC and nine kinases with prognosis significance. Among them, RIPK2 with both serine/threonine and tyrosine activities were validated to promote PC cells proliferation, migration and invasion. RIPK2 knockout could inhibit subcutaneous tumor growth and liver metastasis of PC. In addition, RIPK2 knockout suppressed autophagosome formation, increased ROS production and PC cell apoptosis. Importantly, another oncogenic kinase PRKCI could interact with RIPK2 to enhance the phosphorylation of downstream NF-κB, JNK and ERK.

CONCLUSION

Paired protein kinases PRKCI-RIPK2 with multiple phosphorylation activities represent a new pathological mechanism in PC and could provide potential targets for PC therapy.

A Novel Cuproptosis-Associated Gene Signature to Predict Prognosis in Patients with Pancreatic Cancer

Background

Pancreatic cancer (PAAD) is a malignant tumor with a poor prognosis and lacks sensitive biomarkers for diagnosis and targeted therapy. Cuproptosis, a recently proposed form of cell death based on cellular copper ion concentration, plays a key role in cancer biology. This study is aimed at constructing a risk model for predicting the prognosis of PAAD patients based on cuproptosis-related genes.

Methods

Pancreatic-related data from UCSC-TCGA and UCSC-GTEx databases were extracted for analysis, and TCGA-PAAD samples were randomly divided into the training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes coexpressed with 19 copper death genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of the Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis.

Results

The Cox risk model has an eight prognostic cuproptosis-related gene signature. Kaplan-Meier survival curves demonstrated that the high-risk group had a shorter survival time. The ROC curve of the risk score was well created to predict one-, three-, and five-year survival rates, and AUC of the risk score was higher than other clinical characteristics. Cox regression analysis revealed that the risk score has an independent prognostic value for PAAD. GSEA reveals specific tumor pathways associated with the risk model (Myc targets v1, mTORC1 signaling, and E2F targets).

Conclusions

We constructed a prognostic model containing eight cuproptosis-related genes (AKR1B10, KLHL29, PROM2, PIP5K1C, KIF18B, AMIGO2, MRPL3, and PI4KB) that can accurately predict the prognosis of PAAD patients. The results will provide new perspectives for individualized outcome prediction and new therapy development for PAAD patients.

Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy

Background: CAMP response element binding protein 3-like 1 (CREB3L1) has been indicated as a critical biomarker and can modulate multifaced behaviors of tumor cells in diverse cancers. However, a systematic assessment of CREB3L1 in pan-cancer is of absence, and the predictive value of CREB3L1 in cancer prognosis, the tumor immune microenvironment and the efficacy of immunotherapy remains unexplored.

Methods: CREB3L1 expression in 33 different cancer types was investigated using RNAseq data from The Cancer Genome Atlas (TCGA) database. The characteristics of CREB3L1 alternations were illustrated in cBioPortal database. The prognostic and clinicopathological value of CREB3L1 was analyzed through clinical data downloaded from the TCGA database. The potential role of CREB3L1 in the tumor immune microenvironment was illustrated by utilizing CIBERSORT and ESTIMATE algorithms, and TISIDB online database. The associations between CREB3L1 expression and tumor mutation burden (TMB), and microsatellite instability (MSI) were assessed by spearman’s rank correlation coefficient. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. The correlations of CREB3L1 expression with PD-1/PD-L1 inhibitors efficacy and drug sensitivity were also investigated.

Results: The expression of CREB3L1 was abnormally high or low in several different cancer types, and was also strictly associated with the prognosis of cancer patients. CREB3L1 expression levels have a strong relationship with infiltrating immune cells, including regulatory T cells, CD8+ T cells, macrophages, B naïve cells, dendritic cells and mast cells. CREB3L1 expression was also correlated with the expression of multiple immune-related biomolecules, TMB, and MSI in several cancers. Moreover, CREB3L1 had promising applications in predicting the immunotherapeutic benefits and drug sensitivity in cancer management.

Conclusions: Our results highlight the value of CREB3L1 as a predictive biomarker for the prognosis and immunotherapy efficacy in multiple cancers, and CREB3L1 seems to play key roles in the tumor immune microenvironment, suggesting the role of CREB3L1 as a promising biomarker for predicting the prognosis and immune-related signatures in diverse cancers.

Keratin 8 Is an Inflammation-Induced and Prognosis-Related Marker for Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the highest-grade malignancies in the world. More effective biomarkers and treatment plans are necessary to improve the diagnosis rate and clinical outcome. The oncogenesis of PDAC is influenced by several factors, including chronic pancreatitis (CP). Keratin 8 (KRT8) is an important member of the keratin protein family and plays a role in regulating the cellular response to stress stimuli and mediating inflammatory reactions. However, the role of KRT8 in pancreatitis and PDAC is still poorly understood. Here we assessed the differentially expressed genes (DEGs) by bioinformatic methods with expression profiles available online for a caerulein-induced mouse model and human PDAC tissue. The prognostic value was evaluated by Kaplan–Meier analysis and Cox regression analysis. The diagnostic value was evaluated by Receiver Operating Characteristic analysis (ROC). The function of the genes was predicted by protein-protein interaction analysis, correlation analysis, and GO analysis. The conclusion was further validated in rat pancreatitis model, human tissue, and PDAC cell lines, including immunohistochemical staining (IHC), CCK-8 assay, wound healing assay, and flow cytometry. KRT8 was found to be upregulated in murine pancreatitis tissue, human CP tissue, and human PDAC tissue. High expression of KRT8 had a negative impact on the prognosis of PDAC patients. KRT8 was predicted to be involved in the regulation of the migration and viability of PDAC cells, which was validated in PDAC cell lines. Knockdown of KRT8 impaired the migration and proliferation and induced apoptosis in PDAC cell lines. In conclusion, keratin 8 is an inflammation-induced molecule and could serve as a diagnostic and prognostic marker for PDAC patients. More studies are needed for further validation from the perspective of precision and individualized medicine.

Identification of an autophagy-related gene signature for predicting prognosis and immune activity in pancreatic adenocarcinoma

Adenocarcinoma of the pancreas (PAAD) is a cancerous growth that deteriorates rapidly and has a poor prognosis. Researchers are investigating autophagy in PAAD to identify a new biomarker and treatment target. An autophagy-related gene (ARG) model for overall survival (OS) was constructed using multivariate Cox regression analyses. A cohort of the Cancer Genome Atlas (TCGA)-PAAD was used as the training group as a basis for model construction. This prediction model was validated with several external datasets. To evaluate model performance, the analysis with receiver operating characteristic curves (ROC) was performed. The Human Protein Atlas (HPA) and Cancer Cell Line Encyclopedia (CCLE) were investigated to validate the effects of ARGs expression on cancer cells. Comparing the levels of immune infiltration between high-risk and low-risk groups was finished through the use of CIBERSORT. The differentially expressed genes (DEGs) between the low-/high-risk groups were analyzed further via Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, which were used to identify potential small-molecule compounds in Connectivity Map (CMap), followed by half-maximal inhibitory concentration (IC50) examination with PANC-1 cells. The risk score was finally calculated as follows: BAK1 × 0.34 + ITGA3 × 0.38 + BAG3 × 0.35 + APOL1 × 0.26-RAB24 × 0.67519. ITGA3 and RAB24 both emerged as independent prognostic factors in multivariate Cox regression. Each PAAD cohort had a significantly shorter OS in the high-risk group than in the low-risk group. The high-risk group exhibited infiltration of several immune cell types, including naive B cells (p = 0.003), plasma cells (p = 0.044), and CD8 T cells (nearly significant, p = 0.080). Higher infiltration levels of NK cells (p = 0.025), resting macrophages (p = 0.020), and mast cells (p = 0.007) were found in the high-risk group than the low-risk group. The in vitro and in vivo expression of signature ARGs was consistent in the CCLE and HPA databases. The top 3 enriched Gene Ontology biological processes (GO-BPs) were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were MAPK, cAMP, and cell adhesion molecules. Four potential small-molecule compounds (piperacetazine, vinburnine, withaferin A and hecogenin) that target ARGs were also identified. Taking the results together, our research shows that the ARG signature may serve as a useful prognostic indicator and reveal potential therapeutic targets in patients with PAAD.

In Pancreatic Adenocarcinoma Alpha-Synuclein Increases and Marks Peri-Neural Infiltration

α-Synuclein (α-syn) is a protein involved in neuronal degeneration. However, the family of synucleins has recently been demonstrated to be involved in the mechanisms of oncogenesis by selectively accelerating cellular processes leading to cancer. Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers, with a specifically high neurotropism. The molecular bases of this biological behavior are currently poorly understood. Here, α-synuclein was analyzed concerning the protein expression in PDAC and the potential association with PDAC neurotropism. Tumor (PDAC) and extra-tumor (extra-PDAC) samples from 20 patients affected by PDAC following pancreatic resections were collected at the General Surgery Unit, University of Pisa. All patients were affected by moderately or poorly differentiated PDAC. The amount of α-syn was compared between tumor and extra-tumor specimen (sampled from non-affected neighboring pancreatic areas) by using in situ immuno-staining with peroxidase anti-α-syn immunohistochemistry, α-syn detection by using Western blotting, and electron microscopy by using α-syn-conjugated immuno-gold particles. All the methods consistently indicate that each PDAC sample possesses a higher amount of α-syn compared with extra-PDAC tissue. Moreover, the expression of α-syn was much higher in those PDAC samples from tumors with perineural infiltration compared with tumors without perineural infiltration.