DNA methylation and miR-92a-3p-mediated repression of HIP1R promotes pancreatic cancer progression by activating the PI3K/AKT pathway.

Pancreatic cancer (PAAD) is a highly malignant tumour characterized of high mortality and poor prognosis. Huntingtin-interacting protein 1-related (HIP1R) has been recognized as a tumour suppressor in gastric cancer, while its biological function in PAAD remains to be elucidated. In this study, we reported the downregulation of HIP1R in PAAD tissues and cell lines, and the overexpression of HIP1R suppressed the proliferation, migration and invasion of PAAD cells, while silencing HIP1R showed the opposite effects. DNA methylation analysis revealed that the promoter region of HIP1R was heavily methylated in PAAD cell lines when compared to the normal pancreatic duct epithelial cells. A DNA methylation inhibitor 5-AZA increased the expression of HIP1R in PAAD cells. 5-AZA treatment also inhibited the proliferation, migration and invasion, and induced apoptosis in PAAD cell lines, which could be attenuated by HIP1R silencing. We further demonstrated that HIP1R was negatively regulated by miR-92a-3p, which modulates the malignant phenotype of PAAD cells in vitro and the tumorigenesis in vivo. The miR-92a-3p/HIP1R axis could regulate PI3K/AKT pathway in PAAD cells. Taken together, our data suggest that targeting DNA methylation and miR-92a-3p-mediated repression of HIP1R could serve as novel therapeutic strategies for PAAD treatment.

Construction of a pancreatic cancer prediction model for oxidative stress-related lncRNA.

Long non-coding RNAs (lncRNAs) may play a role in oxidative stress by altering the tumor microenvironment, thereby affecting pancreatic cancer progression. There is currently limited information on oxidative stress-related lncRNAs as novel prognostic markers of pancreatic cancer. Gene expression and clinical data of patients with pancreatic cancer were downloaded from The Cancer Genome Atlas (TCGA-PAAD) and the International Cancer Genome Consortium (ICGC-PACA) database. A weighted gene co-expression network analysis (WGCNA) was constructed to identify genes that were differentially expressed between normal and tumor samples. Based on the TCGA-PAAD cohort, a prediction model was established using lasso regression and Cox regression. The TCGA-PAAD and ICGC-PACA cohorts were used for internal and external validation, respectively. Furthermore, a nomogram based on clinical characteristics was used to predict mortality of patients. Differences in mutational status and tumor-infiltrating immune cells between risk subgroups were also explored and model-based lncRNAs were analyzed for potential immune-related therapeutic drugs. A prediction model for 6-lncRNA was established using lasso regression and Cox regression. Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves indicated that patients with lower risk scores had a better prognosis. Combined with Cox regression analysis of clinical features, risk score was an independent factor predicting overall survival of patients with pancreatic cancer in both the TCGA-PAAD and ICGC-PACA cohorts. Mutation status and immune-related analysis indicated that the high-risk group had a significantly higher gene mutation rate and a higher possibility of immune escape, respectively. Furthermore, the model genes showed a strong correlation with immune-related therapeutic drugs. A pancreatic cancer prediction model based on oxidative stress-related lncRNA was established, which may be used as a biomarker related to the prognosis of pancreatic cancer to evaluate the prognosis of pancreatic cancer patients.

Construction of a novel signature based on immune-related lncRNA to identify high and low risk pancreatic adenocarcinoma patients.

BACKGROUND: Pancreatic adenocarcinoma is one of the most lethal tumors in the world with a poor prognosis. Thus, an accurate prediction model, which identify patients within high risk of pancreatic adenocarcinoma is needed to adjust the treatment and elevate the prognosis of these patients. METHODS: We obtained RNAseq data of The Cancer Genome Atlas (TCGA) pancreatic adenocarcinoma (PAAD) from UCSC Xena database, identified immune-related lncRNAs (irlncRNAs) by correlation analysis, and identified differential expressed irlncRNAs (DEirlncRNAs) between pancreatic adenocarcinoma tissues from TCGA and normal pancreatic tissues from TCGA and Genotype-Tissue Expression (GTEx). Further univariate and lasso regression analysis were performed to construct prognostic signature model. Then, we calculated the areas under curve and identified the best cut-off value to identify high- and low-risk patients with pancreatic adenocarcinoma. The clinical characteristics, immune cell infiltration, immunosuppressive microenvironment, and chemoresistance were compared between high- and low-risk patients with pancreatic adenocarcinoma. RESULTS: We identified 20 DEirlncRNA pairs and grouped the patients by the best cut-off value. We proved that our prognostic signature model possesses a remarkable efficiency to predict prognosis of PAAD patients. The AUC for ROC curve was 0.905 for 1-year prediction, 0.942 for 2-year prediction, and 0.966 for 3-year prediction. Patients in high-risk group have poor survival rate and worse clinical characteristics. We also proved that patients in high-risk groups were in immunosuppressive status and may be resistant to immunotherapy. Anti-cancer drug evaluation was performed based on in-silico predated tool, such as paclitaxel, sorafenib, and erlotinib, may be suitable for PAAD patients in high-risk group. CONCLUSIONS: Overall, our study constructed a novel prognostic risk model based on pairing irlncRNAs, exhibited a promising prediction value in patients with pancreatic adenocarcinoma. Our prognostic risk model may help distinguish PAAD patients suitable for medical treatments.

Knockdown of NF-κB activating protein promotes pancreatic cancer growth and metastasis through mTOR signaling pathway.

BACKGROUND: NF-κB activating protein (NKAP) acts as a transcriptional suppressor in the Notch signaling pathway, It plays a role in hematopoiesis maintenance, immune cell development, maturation, and functional competency acquisition. NKAP has been found to act as an oncogene in many tumors, but it has not been reported in PAAD.The purpose of this study was to investigate the effect of NKAP on the growth and metastasis of pancreatic adenocarcinoma(PAAD). METHODS AND RESULTS: In this study, western blot and qRT-PCR showed that highly expressed NKAP was found in PAAD cell lines, and small interfering RNA (siRNA) was employed to reduce the expression of NKAP in PAAD cell lines. The results of CCK-8, clony formation, Transwell and flow cytometry showed that knockdown of NKAP significantly inhibited biological function of PAAD cells, and increased cell apoptosis. Study also observed that knockdown of NKAP inhibited the expression levels of apoptosis proteins and cyclin in PAAD cells. In addition, mTOR's degree of phosphorylation and the expression of its downstream target p70S6K can both be activated by NKAP. This effect was also confirmed in salvage experiments performed with Rapamycin(RaPa), an inhibitor of mTOR. At the end of the experiment, It was investigated how NKAP affected the drug sensitivity of gemcitabine used to treat PAAD. The results showed that knocking down NKAP could increase the drug sensitivity of gemcitabine. CONCLUSIONS: NKAP as an oncogene regulates the development of PAAD cells. The research found that the mTOR signaling pathway is engaged in the oncogenic role of NKAP in PAAD for the first time.

NQO1/CPT1A promotes the progression of pancreatic adenocarcinoma via fatty acid oxidation.

NQO1, a cytosolic enzyme, is closely related to the progression of cancers and poor outcome of cancer patients. However, the molecular biological mechanism of NQO1 tumorigenicity in pancreatic adenocarcinoma (PAAD) has not been clearly understood. In this study, we demonstrate the molecular mechanism of NQO1 in PAAD proliferation, metastasis and fatty acid oxidation (FAO). Multiple databases and western blot analysis show that NQO1 is overexpressed in PAAD and associated with lymph node metastasis and shorter survival. Furthermore, in vitro and in vivo experiments reveal that overexpression of NQO1 improves tumor growth, metastasis and FAO in PAAD. Mechanistically, NQO1 is able to bind to carnitine palmitoyltransferase 1A (CPT1A), a key enzyme controlling FAO. Therefore, Co-IP and a series of rescue experiments demonstrate that NQO1 promotes PAAD progression via CPT1A-mediated FAO. Our findings identify CPT1A-dependent FAO as an essential metabolic pathway for NQO1 to promote the PAAD process. Targeting the NQO1/CPT1A/FAO axis in PAAD to attenuate proliferation and dissemination is a potential approach to promote a better antitumour effect and improve patient outcomes.

Overexpression of CENPL mRNA potentially regulated by miR-340-3p predicts the prognosis of pancreatic cancer patients.

BACKGROUND: In our previous study it was found that CENPL was overexpressed in hepatocellular carcinoma and significantly predicted patient's prognosis. However, the expression and prognostic value of CENPL in other gastrointestinal tumors remain unknown. Therefore, we investigated the expression and prognostic value of CENPL in esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), pancreatic adenocarcinoma (PAAD), colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ). METHODS: In this study, Oncomine, GEPIA, OncoLnc, TIMER, cBioPortal, miRWalk and ENCORI databases were used to analyze the level of CENPL mRNA, prognostic value and potential regulatory mechanism of CENPL mRNA in tumors. The CENPL expression and clinicopathological data regarding PAAD were from the UCSC Xena database and univariate and multivariate Cox regression analyses were performed using R (Version 3.6.3). Immunohistochemical staining was used to verify the expression of CENPL protein in clinical specimens. Cytoscape (Version: 3.7.2) was used to visualize microRNA (miRNA) that potentially regulates CENPL. RESULTS: Gene differential expression analysis showed that CENPL mRNA was significantly overexpressed in ESCA, STAD, PAAD, COAD and READ (p < 0.01). The overexpression of CENPL mRNA was significantly correlated with the poor prognosis of PAAD patients (p < 0.05). However, there was no significant correlation between the level of CENPL mRNA and the prognosis of ESCA, STAD, COAD and READ patients (p > 0.05). Univariate and multivariate Cox regression analyses suggested that CENPL was a prognostic risk factor for PAAD. The mutation rate of CENPL in PAAD was 2.2% (17/850). There was no significant correlation between the CENPL expression and the infiltration levels of immune cells in PAAD (|Cor|< 0.5). Immunohistochemical staining showed that CENPL was overexpressed in 42% (11/26) of PAAD specimens, which was significantly higher compared with that in the normal tissues. The expression of miR-340-3p and miR-484 in PAAD were significantly lower than in the normal tissues (p < 0.05) and PAAD patients with lower expression of miR-340-3p had poorer prognosis (p < 0.05). CONCLUSION: CENPL potentially regulated by miR-340-3p, is overexpressed in PAAD and predicts patient's prognosis, suggestive of a diagnostic and prognostic value in PAAD patients.

Development and clinical validation of a novel 9-gene prognostic model based on multi-omics in pancreatic adenocarcinoma.

The prognoses of patients with pancreatic adenocarcinoma (PAAD) remain poor due to the lack of biomarkers for early diagnosis and effective prognosis prediction. RNA sequencing, single nucleotide polymorphism, and copy number variation data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes. GISTIC 2.0 was used to identify significantly amplified or deleted genes, and Mutsig 2.0 was used to analyze the mutation data. The Lasso method was used to construct a risk prediction model. The Rms package was used to evaluate the overall predictive performance of the signature. Finally, Western blot and polymerase chain reaction were performed to evaluate gene expression. A total of 54 candidate genes were obtained after integrating the genomic mutated genes and prognosis-related genes. The Lasso method was used to ascertain 9 characteristic genes, including UNC13B, TSPYL4, MICAL1, KLHDC7B, KLHL32, AIM1, ARHGAP18, DCBLD1, and CACNA2D4. The 9-gene signature model was able to help stratify samples at risk in the training and external validation cohorts. In addition, the overall predictive performance of our model was found to be superior to that of other models. KLHDC7B, AIM1, DCBLD1, TSPYL4, and MICAL1 were significantly highly expressed in tumor tissues compared to normal tissues. ARHGAP18 and CACNA2D4 had no difference in expression between tumor and normal tissues. UNC13B and KLHL32 expression in the normal group was higher than in the tumor group. The 9-gene signature constructed in this study can be used as a novel prognostic marker to predict the survival of patients with pancreatic adenocarcinoma.

LncRNA ZFAS1 promotes pancreatic adenocarcinoma metastasis via the RHOA/ROCK2 pathway by sponging miR-3924.

BACKGROUND: The mortality and morbidity rates of pancreatic adenocarcinoma have been increasing over the past two decades, and an understanding of the mechanisms underlying pancreatic adenocarcinoma progression is urgently needed. The long non-coding RNA ZFAS1 has been demonstrated to be an oncogene in some cancers, but its function and mechanism in pancreatic adenocarcinoma remain unclear. METHODS: The ZFAS1 expression level in pancreatic adenocarcinoma was predicted by bioinformatic analysis, and the expression level of ZFAS1 in pancreatic adenocarcinoma tissue samples and cell lines was further detected by quantitative real-time PCR and in situ hybridization. The functions of ZFAS1 in pancreatic adenocarcinoma in vitro and in vivo were investigated by further bioinformatic analysis. Dual-luciferase reporter assays were used to confirm the binding of ZFAS1/miR-3924 and miR-3924/ROCK2, and rescue assays were performed to further investigate the underlying mechanism. RESULTS: ZFAS1 overexpression in pancreatic adenocarcinoma was predicted and experimentally verified. ZFAS1 silencing inhibited pancreatic adenocarcinoma metastasis in vitro and in vivo. The competing endogenous RNA mechanism of ZFAS1 was also identified. CONCLUSIONS: Our results demonstrated the promotive effect of ZFAS1 on pancreatic adenocarcinoma metastasis and suggested its potential role as a novel regulator of ROCK2.

Good or not good: Role of miR-18a in cancer biology.

miR-18a is a member of primary transcript called miR-17-92a (C13orf25 or MIR17HG) which also contains five other miRNAs: miR-17, miR-19a, miR-20a, miR-19b and miR-92a. This cluster as a whole shows specific characteristics, where miR-18a seems to be unique. In contrast to the other members, the expression of miR-18a is additionally controlled and probably functions as its own internal controller of the cluster. miR-18a regulates many genes involved in proliferation, cell cycle, apoptosis, response to different kinds of stress, autophagy and differentiation. The disturbances of miR-18a expression are observed in cancer as well as in different diseases or pathological states. The miR-17-92a cluster is commonly described as oncogenic and it is known as 'oncomiR-1', but this statement is a simplification because miR-18a can act both as an oncogene and a suppressor. In this review we summarize the current knowledge about miR-18a focusing on its regulation, role in cancer biology and utility as a potential biomarker.

Systematic review of the association between dietary patterns and perinatal anxiety and depression.

BACKGROUND: Specific dietary factors contribute to greater risks of prenatal and postpartum anxiety and depression. This study aimed to systematically review and assess the evidence regarding the association between dietary patterns and perinatal anxiety and depression (PAAD). METHODS: A systematic search of the Latin American & Caribbean Health Sciences Literature (LILACS), PubMed, and Scopus databases for cross-sectional and cohort studies through April 2019 was conducted. The methodological quality of the studies was assessed using the Newcastle-Ottawa scale (NOS) and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework was used to assess the quality of evidence. RESULTS: Ten studies (six cohort and four cross-sectional) were included. All studies had good methodological quality. In these studies, the Western (n = 10), healthy (n = 9), and traditional (n = 7) dietary patterns were examined. The healthy pattern was inversely associated with prenatal and postpartum anxiety and prenatal depression. The traditional Japanese dietary pattern, the traditional Indian-confinement dietary pattern, the United Kingdom traditional dietary and the traditional Brazilian dietary pattern were associated with a lower risk of prenatal depression, postpartum depression, prenatal anxiety and postpartum anxiety, respectively. There was no significant association between a Western dietary pattern and PAAD. The GRADE assessment suggested that the quality of the evidence was very low to low across all outcomes owing to the design, risk of bias, and small sample size. CONCLUSIONS: There is no definitive evidence about the relationship between Western dietary patterns and perinatal anxiety and depression. However, it found an inverse association among the healthy dietary pattern and PAAD. Future studies will be required to better evaluate associations between meal patterns and PAAD. Such studies may provide new insights and assist in the development of new prevention and treatment strategies.

Comprehensive multi-omics analysis and prognostic significance of fibroblast growth factor binding protein 1 (FGFBP1) in pancreatic adenocarcinoma.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) is a highly aggressive cancer with poor prognosis and limited therapeutic options. Identifying molecular markers and understanding their role in PAAD pathogenesis is crucial for developing targeted therapies. This study integrates bioinformatics and molecular experiments to investigate the diagnostic, prognostic, and therapeutic significance of FGFBP1 in PAAD. METHODS: UALCAN, TNMplot, OncoDB, GEPIA2, HPA, GSCA, KM Plotter, TISIDB, TISCH2, CancerSEA, STRING, DAVID, cell culture, RT-qPCR analysis, western blot analysis, colony formation, cell proliferation, and wound healing assays. RESULTS: Expression analyses revealed a significantly elevated FGFBP1 levels in PAAD tissues compared to normal samples. Promoter methylation analysis indicated lower methylation levels in PAAD, inversely correlated with FGFBP1 expression, suggesting epigenetic regulation. Genetic alteration analysis showed that FGFBP1 is not significantly affected by single nucleotide variants, but copy number variations are present without impacting mRNA expression. Survival analysis using KM plotter demonstrated that high FGFBP1 expression is associated with poor overall and disease-free survival. A Cox regression-based prognostic model confirmed the negative impact of elevated FGFBP1 on patient outcomes. Correlation analysis with immune-related factors indicated that FGFBP1 may contribute to an immunosuppressive tumor microenvironment, affecting immune cell infiltration and function. Single-cell analysis highlighted FGFBP1 expression in malignant, endothelial, and fibroblast cells within the tumor microenvironment. Gene enrichment analysis revealed FGFBP1's involvement in various biological processes and pathways related to cancer progression. Experimental validation using RT-qPCR confirmed high FGFBP1 expression in PAAD cell lines. FGFBP1 knockdown in HEK293T cells significantly reduced cell proliferation, colony formation, and migration. CONCLUSION: These findings suggest that FGFBP1 plays a critical role in PAAD pathogenesis and could serve as a potential therapeutic target for improving patient outcomes.

Potential impact of epithelial splicing regulatory protein 1 (ESRP1) associated with tumor immunity in pancreatic adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is a prevalent and highly malignant gastrointestinal tumor. Therefore, exploring the mechanisms of drug resistance and immune pathways in PAAD is crucial for clinical treatment. In this study, a total of 497 differentially expressed genes (DEGs) were identified between normal and PAAD samples, and which were enriched to 117 GO terms and 7 functional pathways. Subsequently, 5 overall survival-related DEGs (ESRP1, KRT6A, H2BC11, H2BC4 and KLK) was generated using Cox hazards regression analysis in TCGA dataset. Furthermore, the weighted gene co-expression network analysis revealed a strong association between ESRP1 and PAAD among 5 survival-related DEGs. Patients were divided into two clusters based on ESRP1 expression levels, and low ESRP1 expression existed stronger immune infiltration and higher expression of immunomodulatory targets than high ESRP1 expression by single-sample gene set enrichment analysis, which indicated that low ESRP1 expression was associated with longer survival compared to high ESRP1 expression. Finally, our study also found that immune cells distribution and immunomodulatory targets gene expression in the GEO dataset were similar to the TCGA cohort. Overall, our findings suggest that ESRP1 may play a role in influencing immune contexture and regulating immune function of PAAD patients by integrating data from various databases. SIGNIFICANCE: Utilizing TCGA and GEO datasets, this study uncovers the significant impact of epithelial splicing regulatory protein 1 (ESRP1) on PAAD. ESRP1 emerges as a key regulator of immune function, influencing tumor microenvironment and immune cell infiltration. Cluster analysis shows that low ESRP1 expression correlates with enhanced immune activity, predicting better prognosis. This discovery suggests that ESRP1 can serve as a potential biomarker for the prognosis of PAAD, offering new insights into personalized immunotherapy by influencing immune regulation and tumor progression.

A prognostic model for anoikis-related genes in pancreatic cancer.

Anoikis, a distinct form of programmed cell death, is crucial for both organismal development and maintaining tissue equilibrium. Its role extends to the proliferation and progression of cancer cells. This study aimed to establish an anoikis-related prognostic model to predict the prognosis of pancreatic cancer (PC) patients. Gene expression data and patient clinical profiles were sourced from The Cancer Genome Atlas (TCGA-PAAD: Pancreatic Adenocarcinoma) and the International Cancer Genome Consortium (ICGC-PACA: Pancreatic Ductal Adenocarcinoma). Non-cancerous pancreatic tissue gene expression data were obtained from the Genotype-Tissue Expression (GTEx) project. The R package was used to construct anoikis-related PC prognostic models, which were later validated with the ICGC-PACA database. Survival analyses demonstrated a poorer prognosis for patients in the high-risk group, consistent across both TCGA-PAAD and ICGC-PACA datasets. A nomogram was designed as a predictive tool to estimate patient mortality. The study also analyzed tumor mutations and immune infiltration across various risk groups, uncovering notable differences in tumor mutation patterns and immune landscapes between high- and low-risk groups. In conclusion, this research successfully developed a prognostic model centered on anoikis-related genes, offering a novel tool for predicting the clinical trajectory of PC patients.

Identification of pancreatic adenocarcinoma immune subtype associated with tumor neoantigen from aberrant alternative splicing.

Background: Pancreatic adenocarcinoma (PAAD) is referred to as an immunologically "cold" tumor that responds poorly to immunotherapy. A fundamental theory that explains the low immunogenicity of PAAD is the dramatically low tumor mutation burden (TMB) of PAAD tumors, which fails to induce sufficient immune response. Alternative splicing of pre-mRNA, which could alter the proteomic diversity of many cancers, has been reported to be involved in neoantigen production. Therefore, we aim to identify novel PAAD antigens and immune subtypes through systematic bioinformatics research. Methods: Data for splicing analysis were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq database. Among the available algorithms, we chose CIBERSORT to evaluate the immune cell distribution among PAADs. The TCGA-PAAD expression matrix was used to construct a co-expression network. Single-cell analysis was performed based on the Seurat workflow. Results: Integrated analysis of aberrantly upregulated genes, alternatively spliced genes, genes associated with nonsense-mediated RNA decay (NMD) factors, antigen presentation and overall survival (OS) in TCGA-PAAD revealed that PLEC is a promising neoantigen for PAAD-targeted therapy. We identified a C2 TCGA-PAAD subtype that had better prognosis and more CD8+ T-cell infiltration. We propose a novel immune subtyping system for PAAD to indicate patient prognosis and opportunities for immunotherapy, such as immune checkpoint (ICP) inhibitors. Conclusions: In conclusion, the present study used a transcriptome-guided approach to screen neoantigen candidates based on alternative splicing, NMD factors, and antigen-presenting signatures for PAAD. A prognosis model with guidance of immunotherapy will aid in patient selection for appropriate treatment.

Modeling of new markers for the diagnosis and prognosis of pancreatic cancer based on the transition from inflammation to cancer.

Background: Pancreatic adenocarcinoma (PAAD) is a lethal disease with a poor prognosis. Genes involved in acute pancreatitis (AP) or chronic pancreatitis (CP) might be important for PAAD development. This study sought to identify potential PAAD diagnosis markers and to establish a PAAD prognosis prediction model based on AP- and CP-related genes. Methods: The significantly differentially expressed genes in both AP or CP and PAAD were obtained by a bioinformatics analysis. A risk-score model for predicting survival was constructed based on The Cancer Genome Atlas (TCGA) data and validated using an International Cancer Genome Consortium (ICGC) cohort. Protein expression and the effects of the genes in the risk models were validated by immunohistochemistry, or Cell Counting Kit-8 (CCK-8) and transwell assays. The study sample data included six AP tissue samples and five normal pancreatic tissue samples, six CP tissue samples and six normal pancreatic tissue samples from the Gene Expression Omnibus (GEO) expression profiling microarrays GSE109227 and GSE41418 data sets, respectively, and fragments per kilobase per million mapped fragments (FPKM) data from four normal controls and 150 PAAD cases from TCGA database, and 182 cancer patient samples with complete survival prognostic data from the ICGC database. Results: In total, 508 significantly differentially expressed genes were found in both AP or CP and PAAD. Trefoil factor 2 (TFF2), tubulointerstitial nephritis antigen (TINAG), trefoil factor 1 (TFF1), aquaporin 5 (AQP5), SAM pointed domain containing ETS transcription factor (SPDEF), anterior gradient protein 2 (AGR2), apolipoprotein B messenger RNA editing enzyme catalytic subunit 1 (APOBEC1), kallikrein-related peptidase 6 (KLK6), dopa decarboxylase (DDC), mucin 13 (MUC13), claudin 18 (CLDN18), annexin A10 (ANXA10), and tetraspanin 1 (TSPAN1) were found to be present in PAAD and had the largest fold change. A risk-score model, comprising 19 genes, was constructed for prognostic prediction. A high-risk score indicated a poor prognosis. TINAG, DDC, SPDEF, and APOBEC1 proteins were increased in PAAD, while TINAG and DDC were correlated with the pathologic grade. Decreased TINAG, APOBEC1, transmembrane protein 94 (TMEM94), and kelch like family member 36 (KLHL36) expression inhibited PAAD cell proliferation, while decreased SPDEF, TMEM94, and KLHL36 expression significantly inhibited PAAD cell migration. Conclusions: The AP and CP co-related genes were significantly correlated with PAAD. TINAG, DDC, SPDEF, and APOBEC1 could serve as new PAAD predictors. The risk model developed in this study could be used to predict the prognosis of PAAD patients.

A study on the role of Taxifolin in inducing apoptosis of pancreatic cancer cells: screening results using weighted gene co-expression network analysis.

Pancreatic adenocarcinoma (PAAD) is a frequent malignant tumor in the pancreas. The incomplete understanding of cancer etiology and pathogenesis, as well as the limitations in early detection and diagnostic methods, have created an urgent need for the discovery of new therapeutic targets and drugs to control this disease. As a result, the current therapeutic options are limited. In this study, the weighted gene co-expression network analysis (WGCNA) method was employed to identify key genes associated with the progression and prognosis of pancreatic adenocarcinoma (PAAD) patients in the Gene Expression Profiling Interactive Analysis (GEPIA) database. To identify small molecule drugs with potential in the treatment of pancreatic adenocarcinoma (PAAD), we compared key genes to the reference dataset in the CMAP database. First, we analyzed the antitumor properties of small molecule drugs using cell counting kit-8 (CCK-8), AO/EB and Transwell assays. Subsequently, we integrated network pharmacology with molecular docking to explore the potential mechanisms of the identified molecules' anti-tumor effects. Our findings indicated that the progression and prognosis of PAAD patients in pancreatic cancer were associated with 11 genes, namely, DKK1, S100A2, CDA, KRT6A, ITGA3, GPR87, IL20RB, ZBED2, PMEPA1, CST6, and MUC16. These genes were filtered based on their therapeutic potential through comparing them with the reference dataset in the CMAP database. Taxifolin, a natural small molecule drug with the potential for treating PAAD, was screened by comparing it with the reference dataset in the CMAP database. Cell-based experiments have validated the potential of Taxifolin to facilitate apoptosis in pancreatic cancer cells while restraining their invasion and metastasis. This outcome is believed to be achieved via the HIF-1 signaling pathway. In conclusion, this study provided a theoretical basis for screening genes related to the progression of pancreatic cancer and discovered potentially active small molecule drugs. The experimental results confirm that Taxifolin has the ability to promote apoptosis in pancreatic cancer cells.

LDHA as a predictive biomarker and its association with the infiltration of immune cells in pancreatic adenocarcinoma.

Background: Lactate dehydrogenase A (LDHA) plays a crucial role in the final step of anaerobic glycolysis, converting L-lactate and NAD+ to pyruvate and nicotinamide adenine dinucleotide (NADH). Its high expression has been linked to tumorigenesis and patient survival in various human cancers. However, the full implications of LDHA's role and its correlation with clinicopathological features in pancreatic adenocarcinoma (PAAD) remain to be fully understood. This study was thus conducted to elucidate the specific functions of LDHA in PAAD, with the aim of providing more robust evidence for clinical diagnosis and treatment. Methods: In an extensive systems analysis, we searched through numerous databases, including The Cancer Genome Atlas (TCGA) and Oncomine. Our objective was to clarify the clinical implications and functional role of LDHA in PAAD. Bioinformatics was used to identify the biological function of LDHA expression and its correlation with tumor immune status. Results: Our analysis revealed that the LDHA gene is overexpressed in PAAD and that this upregulation was associated with a worse patient prognosis. Through gene set enrichment analysis, we found that LDHA's influence on PAAD is linked to signaling pathways involving Kirsten rat sarcoma viral oncogene homolog (K-Ras), transforming growth factor-ß (TGF-ß), and hypoxia inducible factor-1 (HIF-1). Mutation of K-Ras could upregulate its own expression and was positively correlated with LDHA expression. Moreover, our data demonstrated that LDHA expression was linked to immune infiltration and poor prognosis in PAAD, indicating its role in disease pathogenesis. Overexpression of LDHA may suppress tumor immunity, suggesting it as a potential target for the diagnosis and treatment of PAAD, thus providing new insights into managing this aggressive cancer. Conclusions: Overall, our results showed that LDHA as a prognostic biomarker could serve as a novel target for future PAAD immunotherapy.

Analyzing the role of TM4SF1 expression in pancreatic adenocarcinoma: understanding prognostic implications and therapeutic opportunities.

Background: Pancreatic adenocarcinoma (PAAD) is a highly lethal malignancy characterized by aggressive growth and poor prognosis. Understanding the molecular mechanisms underlying PAAD is crucial for developing effective therapies. This study aimed to explore the role of TM4SF1 and other key genes in PAAD progression, their prognostic implications, and therapeutic opportunities. Methods: Differential gene expression analysis was performed using PAAD and normal tissue samples to identify upregulated genes, with TM4SF1 emerging as significantly elevated in PAAD. Functional enrichment analysis elucidated associated signaling pathways. A prognostic model comprising BPIFB4, PLEKHN1, CPTP, DVL1, and DDR1 was developed using least absolute shrinkage and selection operator (LASSO) regression and validated in an independent cohort. Genetic mutation analysis provided insights into the functional significance of identified genes. Pharmacogenomic analysis examined associations between gene expression and drug sensitivity. Experimental validation included quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot analyses to confirm gene expression patterns and protein levels. Results: Lower TM4SF1 expression correlated with enhanced anti-tumor immune activity in PAAD, suggesting a complex interplay between genetic expression and immune response. The prognostic model showed robust associations with patient survival outcomes, validated across diverse patient cohorts. Genetic mutation analysis highlighted potential therapeutic targets. Pharmacogenomic analysis revealed correlations between gene expression profiles and drug responsiveness, suggesting personalized treatment strategies. Experimental validation confirmed elevated TM4SF1 levels in tumor tissues and demonstrated its role in promoting cancer cell proliferation and colony formation. Conclusions: This study advances understanding of the molecular landscape of PAAD, emphasizing TM4SF1 as a key regulator and potential therapeutic target. The integration of genetic expression, immune response dynamics, and pharmacogenomics offers a multifaceted approach to personalized treatment strategies for PAAD, paving the way for improved patient outcomes and novel therapeutic interventions. Further research is warranted to elucidate the clinical utility of targeting TM4SF1 and other identified genes in PAAD management.

MMP11 as a prognostic biomarker correlated with immune infiltrates in pancreatic adenocarcinoma.

Background: Matrix metalloproteinase 11 (MMP11) plays a vital role in cell proliferation, apoptosis, tumor angiogenesis, migration, and other basic processes. Currently, few studies have examined the value of MMP11 in pancreatic cancer in relation to prognostic risk, diagnostic indicators, and immunotherapy. This study aims to explore the association between MMP11 and the tumor immune microenvironment in pancreatic adenocarcinoma (PAAD). Methods: We selected clinical samples and data downloaded from The Cancer Genome Atlas and Genotype-Tissue Expression, in addition, we use other online data for further analysis. Through a comprehensive bioinformatics investigation, we systematically analyzed the clinical significance and expression level of MMP11 in pancreatic cancer. Results: MMP11 was overexpressed in many cancers, and a higher expression of MMP11 was associated with a poorer prognosis in pancreatic cancer. Conversely, the hypermethylation of MMP11 was associated with better overall survival. The MMP11 expression network had widespread effects on the prognosis and immune activation of PAAD. The expression of MMP11 was significantly associated with a variety of tumor-infiltrating immune cells. An association was also found between MMP11 expression and chemokines in PAAD. High MMP11 expression might be involved in immune cell migration to the tumor microenvironment. Conclusions: MMP11 is a prognostic biomarker for patients in pancreatic cancer and may regulate the tumor immune microenvironment. The potential effects and mechanisms of MMP11 in PAAD require further exploring.