Prognostic relevance of molecular subtypes and master regulators in pancreatic ductal adenocarcinoma

Regulation of pancreatic cancer cells by suppressing KIN17 through the PI3K/AKT/mTOR signaling pathway

Pancreatic cancer is an aggressive tumor, which is often associated with a poor clinical prognosis and resistance to conventional chemotherapy. Therefore, there is a need to identify new therapeutic markers for pancreatic cancer. Although KIN17 is a highly expressed DNA‑ and RNA‑binding protein in a number of types of human cancer, its role in pancreatic cancer development, especially in relation to progression, is currently unknown. The present study verified the upregulation of KIN17 in pancreatic cancer using The Cancer Genome Atlas and Gene Expression Omnibus databases (GSE15471, GSE71989 and GSE62165), and identified an association between the PI3K/Akt/mTOR pathway and patient prognosis using publicly available datasets (Gene Expression Profiling Interactive Analysis). Immunohistochemistry was performed to determine the association between KIN17 and the pathological features of clinical pancreatic cancer samples. Furthermore, knockdown of KIN17 was shown to inhibit the migration and invasion of pancreatic cancer cells, and to reverse epithelial‑mesenchymal transition in pancreatic cancer cells through downregulation of Vimentin and N‑cadherin, and upregulation of E‑cadherin. Through various cellular experiments, the role of KIIN17 was explored in PI3K/AKT/mTOR activity. KIN17 inhibition was shown to suppress the migration and invasion of pancreatic cancer cells through PI3K/AKT/mTOR‑mediated autophagy. Furthermore, combined with mTOR inhibition, dual inhibition could enhance autophagy, leading to anti‑migratory and anti‑invasion effects in pancreatic cancer. In conclusion, the present study indicated that KIN17 may have a role in carcinogenesis and could serve as a prognostic biomarker of pancreatic cancer, owing to its high expression. In addition, KIN17 may be considered a potential therapeutic target with its knockdown having an inhibitory effect on pancreatic cancer.

Integrated analysis of cell cycle and p53 signaling pathways related genes in breast, colorectal, lung, and pancreatic cancers: implications for prognosis and drug sensitivity for therapeutic potential

Cancer, a leading cause of death worldwide, is projected to increase by 76.6% in new cases and 89.7% in mortality by 2050 (WHO 2022). Among various types, lung cancer is the most prevalent with high morbidity, while breast, colorectal, and pancreatic cancers also show high mortality rates. Cancer progression often involves disruption in cell cycle regulation and signaling pathways, with mutations in genes like TP53, EGFR, and K-RAS playing significant roles. In this study, we analyzed gene expression datasets to identify common molecular signatures across breast, colorectal, lung and pancreatic cancers. Our focus was on genes related to cell cycle regulation and p53 signaling pathway, intending to discover potential biomarkers for improved diagnosis and treatment strategies. The study analyzed GEO datasets; GSE45827, GSE9348, GSE30219, and GSE62165 for breast, colorectal, lung, and pancreatic cancers respectively. Differentially expressed genes (DEGs) were identified using GEO2R, and functional annotation and pathway analysis were performed using WebGestalt. Common cell cycle and p53 signaling genes were acquired from MSigDB using GSEA. A protein-protein interaction network was constructed using STRING and Cytoscape, identifying top hub genes. Validation of hub genes at mRNA and protein levels was done via GEPIA2 and Human Protein Atlas. Survival analysis was conducted using TCGA data by GEPIA2 and LASSO, and drug sensitivity was analyzed with the GSCA drug bank database, highlighting potential therapeutic targets. The study identified 411 common DEGs among these four cancers. Pathway and functional enrichment revealed key biological processes and pathways like p53 signaling, and cell cycle. The intersection of these DEGs with genes involved in cell cycle and p53 signaling, identified 23 common genes that were used for constructing a PPI network. The top 10 hub genes were validated both for mRNA and protein expression, revealing they are significantly overexpressed in all studied cancers. Prognostic relevance showed that MCM4, MCM6, CCNA2, CDC20, and CHEK1 are associated with survival. Additionally, drug sensitivity analysis highlighted key gene-drug interactions, suggesting potential targets for therapeutic intervention.

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, and a notably low five-year survival rate, underscoring the critical need for early detection methods and more effective therapeutic approaches. This research rigorously investigates the molecular mechanisms underlying PDAC, with a focus on the identification of pivotal genes and pathways that may hold therapeutic relevance and prognostic value. Through the construction of a protein-protein interaction (PPI) network and the examination of differentially expressed genes (DEGs), the study uncovers key hub genes such as CDK1, KIF11, and BUB1, demonstrating their substantial role in the pathogenesis of PDAC. Notably, the dysregulation of these genes is consistent across a spectrum of cancers, positing them as potential targets for wide-ranging cancer therapeutics. This study also brings to the fore significant genes encoding intrinsically disordered proteins, in particular GPRC5A and KRT7, unveiling promising new pathways for therapeutic intervention. Advanced machine learning techniques were harnessed to classify PDAC patients with high accuracy, utilizing the key genetic markers as a dataset. The Support Vector Machine (SVM) model leveraged the hub genes to achieve a sensitivity of 91 % and a specificity of 85 %, while the RandomForest model notched a sensitivity of 91 % and specificity of 92.5 %. Crucially, when the identified genes were cross-referenced with TCGA-PAAD clinical datasets, a tangible correlation with patient survival rates was discovered, reinforcing the potential of these genes as prognostic biomarkers and their viability as targets for therapeutic intervention. This study's findings serve as a potent testament to the value of molecular analysis in enhancing the understanding of PDAC and in advancing the pursuit for more effective diagnostic and treatment strategies.

SIN3B Loss Heats up Cold Tumor Microenvironment to Boost Immunotherapy in Pancreatic Cancer

Despite progress significant advances in immunotherapy for some solid tumors, pancreatic ductal adenocarcinoma (PDAC) remains unresponsive poorly responsive to such interventions, largely due to its highly immunosuppressive tumor microenvironment (TME) with limited CD8+ T cell infiltration. This study explores the role of the epigenetic factor Sin3B in the PDAC TME. Using murine PDAC models, we found that tumor cell-intrinsic Sin3B loss reshapes the TME, increasing CD8+ T cell infiltration and cytotoxicity, thus impeding tumor progression and enhancing sensitivity to anti-PD1 treatment. Sin3B-deficient tumor cells exhibited amplified CXCL9/10 secretion in response to Interferon-gamma (IFNγ), creating a positive feedback loop via the CXCL9/10-CXCR3 axis, thereby intensifying the anti-tumor immune response against PDAC. Mechanistically, extensive epigenetic regulation is uncovered by Sin3B loss, particularly enhanced H3K27Ac distribution on genes related to immune responses in PDAC cells. Consistent with the murine model findings, analysis of human PDAC samples revealed a significant inverse correlation between SIN3B levels and both CD8+ T cell infiltration and CXCL9/10 expression. Notebly, PDAC patients with lower SIN3B expression showed a more favorable response to anti-PD1 therapy. The findings suggest that targeting SIN3B can enhance cytotoxic T cell infiltration into the tumor site and improve immunotherapy efficacy in PDAC, offering potential avenues for therapeutic biomarker or target in this challenging disease.

The Peptidoglycan Recognition Protein 1 confers immune evasive properties on pancreatic cancer stem cells

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) has limited therapeutic options, particularly with immune checkpoint inhibitors. Highly chemoresistant 'stem-like' cells, known as cancer stem cells (CSCs), are implicated in PDAC aggressiveness. Thus, comprehending how this subset of cells evades the immune system is crucial for advancing novel therapies.

DESIGN

We used the KPC mouse model (LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre) and primary tumour cell lines to investigate putative CSC populations. Transcriptomic analyses were conducted to pinpoint new genes involved in immune evasion. Overexpressing and knockout cell lines were established with lentiviral vectors. Subsequent in vitro coculture assays, in vivo mouse and zebrafish tumorigenesis studies, and in silico database approaches were performed.

RESULTS

Using the KPC mouse model, we functionally confirmed a population of cells marked by EpCAM, Sca-1 and CD133 as authentic CSCs and investigated their transcriptional profile. Immune evasion signatures/genes, notably the gene peptidoglycan recognition protein 1 (PGLYRP1), were significantly overexpressed in these CSCs. Modulating PGLYRP1 impacted CSC immune evasion, affecting their resistance to macrophage-mediated and T-cell-mediated killing and their tumourigenesis in immunocompetent mice. Mechanistically, tumour necrosis factor alpha (TNFα)-regulated PGLYRP1 expression interferes with the immune tumour microenvironment (TME) landscape, promoting myeloid cell-derived immunosuppression and activated T-cell death. Importantly, these findings were not only replicated in human models, but clinically, secreted PGLYRP1 levels were significantly elevated in patients with PDAC.

CONCLUSIONS

This study establishes PGLYRP1 as a novel CSC-associated marker crucial for immune evasion, particularly against macrophage phagocytosis and T-cell killing, presenting it as a promising target for PDAC immunotherapy.

Genetic and other risk factors for pancreatic ductal adenocarcinoma (PDAC)

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at an advanced stage, resulting in poor prognosis and low 5-year survival rates. While early evidence suggests increased long-term survival in those with screen-detected resectable cancers, surveillance imaging is currently only recommended for individuals with a lifetime risk of PDAC ≥ 5%. Identification of risk factors for PDAC provides opportunities for early detection, risk reducing interventions, and targeted therapies, thus potentially improving patient outcomes. Here, we summarize modifiable and non-modifiable risk factors for PDAC. We review hereditary cancer syndromes associated with risk for PDAC and their implications for patients and their relatives. In addition, other biologically relevant pathways and environmental and lifestyle risk factors are discussed. Future work may focus on elucidating additional genetic, environmental, and lifestyle risk factors that may modify PDAC risk to continue to identify individuals at increased risk for PDAC who may benefit from surveillance and risk reducing interventions.

Meta-analysis of adjuvant chemotherapy versus no adjuvant chemotherapy for resected stage I pancreatic cancer

BACKGROUND

To evaluate comparative outcomes of pancreatic cancer resection with or without adjuvant chemotherapy in patients with stage I pancreatic cancer.

METHODS

A systematic search of MEDLINE, CENTRAL, and Web of Science and bibliographic reference lists were conducted. All comparative studies reporting outcomes of pancreatic cancer resection for stage I cancer with or without adjuvant chemotherapy were included, and their risk of bias was assessed using the Risk Of Bias In Non-randomized Studies-of Interventions tool. Survival outcomes were analyzed using the hazard ratio and odds ratio for the time-to-event and dichotomous outcomes, respectively.

RESULTS

We included 6 comparative studies reporting a total of 6,874 patients with resected stage 1 pancreatic cancer, of whom 3,951 patients had no adjuvant chemotherapy, and the remaining 2,923 patients received adjuvant chemotherapy. The use of adjuvant chemotherapy was associated with significantly higher overall survival (hazard ratio 0.71, 95% confidence interval 0.62-0.82, P < .00001) and 2-year survival (65.1% vs 57.4%, odds ratio 1.99; 95% confidence interval 1.01-1.41, P = .04) compared to no use of adjuvant chemotherapy. However, there was no statistically significant difference in 1-year (86.8% vs 78.4%, odds ratio 1.60; 95% confidence interval 0.72-3.57, P = .25), 3-year (46.0% vs 44.0%, odds ratio 1.07; 95% confidence interval 0.90-1.29, P = .43), or 5-year survival (24.8% vs 23.3%, odds ratio 1.03; 95% confidence interval 0.80-1.33, P = .81) between the 2 groups.

CONCLUSION

Meta-analysis of best available evidence (level 2a with low to moderate certainty) demonstrates that adjuvant chemotherapy may confer survival benefits for stage I pancreatic cancer when compared to the use of surgery alone. Randomized control trials are required to escalate the level of evidence and confirm these findings with consideration of contemporary chemotherapy agents and regimens.

Transcriptomic-Based Microenvironment Classification Reveals Precision Medicine Strategies for Pancreatic Ductal Adenocarcinoma

BACKGROUND & AIMS

The complex tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) has hindered the development of reliable predictive biomarkers for targeted therapy and immunomodulatory strategies. A comprehensive characterization of the TME is necessary to advance precision therapeutics in PDAC.

METHODS

A transcriptomic profiling platform for TME classification based on functional gene signatures was applied to 14 publicly available PDAC datasets (n = 1657) and validated in a clinically annotated independent cohort of patients with PDAC (n = 79). Four distinct subtypes were identified using unsupervised clustering and assessed to evaluate predictive and prognostic utility.

RESULTS

TME classification using transcriptomic profiling identified 4 biologically distinct subtypes based on their TME immune composition: immune enriched (IE); immune enriched, fibrotic (IE/F); fibrotic (F); and immune depleted (D). The IE and IE/F subtypes demonstrated a more favorable prognosis and potential for response to immunotherapy compared with the F and D subtypes. Most lung metastases and liver metastases were subtypes IE and D, respectively, indicating the role of clonal phenotype and immune milieu in developing personalized therapeutic strategies. In addition, distinct TMEs with potential therapeutic implications were identified in treatment-naive primary tumors compared with tumors that underwent neoadjuvant therapy.

CONCLUSIONS

This novel approach defines a distinct subgroup of PADC patients that may benefit from immunotherapeutic strategies based on their TME subtype and provides a framework to select patients for prospective clinical trials investigating precision immunotherapy in PDAC. Further, the predictive utility and real-world clinical applicability espoused by this transcriptomic-based TME classification approach will accelerate the advancement of precision medicine in PDAC.

MicroRNA-130b Suppresses Malignant Behaviours and Inhibits the Activation of the PI3K/Akt Signaling Pathway by Targeting MET in Pancreatic Cancer

There has been interested in the microRNAs' roles in pancreatic cancer (PC) cell biology, particularly in regulating pathways related to tumorigenesis. The study aimed to explore the hub miRNAs in PC and underlying mechanisms by bioinformatics and fundamental experiments. RNA datasets collected from the Gene Expression Omnibus were analysed to find out differentially expressed RNAs (DERNAs). The miRNA-mRNA and protein-protein interaction (PPI) networks were built. The clinicopathological features and expressions of hub miRNAs and hub mRNAs were explored. Dual-luciferase reporter gene assay was performed to assess the interaction between microRNA and target gene. RT-qPCR and western blot were employed to explore RNA expression. The roles of RNA were detected by CCK-8 test, wound healing, transwell, and flow cytometry experiment. We verified 40 DEmiRNAs and 1613 DEmRNAs, then detected a total of 69 final functional mRNAs (FmRNAs) and 23 DEmiRNAs. In the miRNA-mRNA networks, microRNA-130b (miR-130b) was the hub RNA with highest degrees. Clinical analysis revealed that miR-130b was considerably lower expressed in cancerous tissues than in healthy ones, and patients with higher-expressed miR-130b had a better prognosis. Mechanically, miR-130b directly targeted MET in PC cells. Cell functional experiments verified that miR-130b suppressed cell proliferation, migration, promoted apoptosis, and inhibited the PI3K/Akt pathway by targeting MET in PC cells. Our findings illustrated the specific molecular mechanism of miR-130b regulating PC progress. The miR-130b/MET axis may be an alternative target in the therapeutic intervention of PC and provide an opportunity to deepen our understanding of the pathogenesis of PC.

Caprin-1 influences autophagy-induced tumor growth and immune modulation in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is characterized by rapid progression and poor prognosis. Understanding the genetic mechanisms that affect cancer properties and reprogram tumor immune microenvironment will develop new strategies to maximize the benefits for cancer therapies.

METHODS

Gene signatures and biological processes associated with advanced cancer and unfavorable outcome were profiled using bulk RNA sequencing and spatial transcriptome sequencing, Caprin-1 was identified as an oncogenesis to expedite pancreatic cancer growth by activating autophagy. The mechanism of Caprin-1 inducing autophagy activation was further explored in vitro and in vivo. In addition, higher level of Caprin-1 was found to manipulate immune responses and inflammatory-related pathways. The immune profiles associated with increased levels of Caprin-1 were identified in human PDAC samples. The roles of CD4+T cells, CD8+T cells and tumor associated macrophages (TAMs) on clinical outcomes prediction were investigated.

RESULTS

Caprin-1 was significantly upregulated in advanced PDAC and correlated with poor prognosis. Caprin-1 interacted with both ULK1 and STK38, and manipulated ULK1 phosphorylation which activated autophagy and exerted pro-tumorigenic phenotypes. Additionally, the infiltrated CD4+T cells and tumor associated macrophages (TAMs) were increased in Caprin-1High tissues. The extensive CD4+T cells determined poor clinical outcome in Caprin-1high patients, arguing that highly expressed Caprin-1 may assist cancer cells to escape from immune surveillance.

CONCLUSIONS

Our findings establish causal links between the upregulated expression of Caprin-1 and autophagy activation, which may manipulate immune responses in PDAC development. Our study provides insights into considering Caprin-1 as potential therapeutic target for PDAC treatment.

Eukaryotic translation initiation factor 2α kinase 2 in pancreatic cancer: An approach towards managing clinical prognosis and molecular immunological characterization

Most patients with pancreatic cancer are already in the late stages of the disease when they are diagnosed, and pancreatic cancer is a deadly disease with a poor prognosis. With the advancement of research, immunotherapy has become a new focus in the treatment of tumors. To the best of our knowledge, there is currently no reliable diagnostic or prognostic marker for pancreatic cancer; therefore, the present study investigated the potential of eukaryotic translation initiation factor 2α kinase 2 (EIF2AK2) as a predictive and diagnostic marker for pancreatic cancer. Immunohistochemical staining of clinical samples independently verified that EIF2AK2 expression was significantly higher in clinically operated pancreatic cancer tissues than in adjacent pancreatic tissues., and EIF2AK2 expression and differentially expressed genes (DEGs) were identified using downloadable RNA sequencing data from The Cancer Genome Atlas and Genomic Tumor Expression Atlas. In addition, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analyses and immune cell infiltration were used for functional enrichment analysis of EIF2AK2-associated DEGs. The clinical importance of EIF2AK2 was also determined using Kaplan-Meier survival, Cox regression and time-dependent survival receiver operating characteristic curve analyses, and a predictive nomogram model was generated. Finally, the functional role of EIF2AK2 was assessed in PANC-1 cells using a short hairpin RNA-EIF2AK2 knockdown approach, including CCK-8, wound healing assay, cell cycle and apoptosis assays. The findings suggested that EIF2AK2 may have potential as a diagnostic and prognostic biomarker for patients with pancreatic cancer. Furthermore, EIF2AK2 may provide a new therapeutic target for patients with pancreatic cancer.

Unveiling the role of regulatory T cells in the tumor microenvironment of pancreatic cancer through single-cell transcriptomics and in vitro experiments

Background

In order to investigate the impact of Treg cell infiltration on the immune response against pancreatic cancer within the tumor microenvironment (TME), and identify crucial mRNA markers associated with Treg cells in pancreatic cancer, our study aims to delve into the role of Treg cells in the anti-tumor immune response of pancreatic cancer.

Methods

The ordinary transcriptome data for this study was sourced from the GEO and TCGA databases. It was analyzed using single-cell sequencing analysis and machine learning. To assess the infiltration level of Treg cells in pancreatic cancer tissues, we employed the CIBERSORT method. The identification of genes most closely associated with Treg cells was accomplished through the implementation of weighted gene co-expression network analysis (WGCNA). Our analysis of single-cell sequencing data involved various quality control methods, followed by annotation and advanced analyses such as cell trajectory analysis and cell communication analysis to elucidate the role of Treg cells within the pancreatic cancer microenvironment. Additionally, we categorized the Treg cells into two subsets: Treg1 associated with favorable prognosis, and Treg2 associated with poor prognosis, based on the enrichment scores of the key genes. Employing the hdWGCNA method, we analyzed these two subsets to identify the critical signaling pathways governing their mutual transformation. Finally, we conducted PCR and immunofluorescence staining in vitro to validate the identified key genes.

Results

Based on the results of immune infiltration analysis, we observed significant infiltration of Treg cells in the pancreatic cancer microenvironment. Subsequently, utilizing the WGCNA and machine learning algorithms, we ultimately identified four Treg cell-related genes (TRGs), among which four genes exhibited significant correlations with the occurrence and progression of pancreatic cancer. Among them, CASP4, TOB1, and CLEC2B were associated with poorer prognosis in pancreatic cancer patients, while FYN showed a correlation with better prognosis. Notably, significant differences were found in the HIF-1 signaling pathway between Treg1 and Treg2 cells identified by the four genes. These conclusions were further validated through in vitro experiments.

Conclusion

Treg cells played a crucial role in the pancreatic cancer microenvironment, and their presence held a dual significance. Recognizing this characteristic was vital for understanding the limitations of Treg cell-targeted therapies. CASP4, FYN, TOB1, and CLEC2B exhibited close associations with infiltrating Treg cells in pancreatic cancer, suggesting their involvement in Treg cell functions. Further investigation was warranted to uncover the mechanisms underlying these associations. Notably, the HIF-1 signaling pathway emerged as a significant pathway contributing to the duality of Treg cells. Targeting this pathway could potentially revolutionize the existing treatment approaches for pancreatic cancer.

NFIC regulates ribosomal biology and ER stress in pancreatic acinar cells and restrains PDAC initiation

Pancreatic acinar cells rely on PTF1 and other transcription factors to deploy their transcriptional program. We identify NFIC as a NR5A2 interactor and regulator of acinar differentiation. NFIC binding sites are enriched in NR5A2 ChIP-Sequencing peaks. Nfic knockout mice have a smaller, histologically normal, pancreas with reduced acinar gene expression. NFIC binds and regulates the promoters of acinar genes and those involved in RNA/protein metabolism, and Nfic knockout pancreata show defective ribosomal RNA maturation. NFIC dampens the endoplasmic reticulum stress program through binding to gene promoters and is required for resolution of Tunicamycin-mediated stress. NFIC is down-regulated during caerulein pancreatitis and is required for recovery after damage. Normal human pancreata with low levels of NFIC transcripts display reduced expression of genes down-regulated in Nfic knockout mice. NFIC expression is down-regulated in mouse and human pancreatic ductal adenocarcinoma. Consistently, Nfic knockout mice develop a higher number of mutant Kras-driven pre-neoplastic lesions.

Human pancreatic cancer patients with Epithelial-to-Mesenchymal Transition and an aggressive phenotype show a disturbed balance in Protein Phosphatase Type 2A expression and functionality

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a low survival, its incidence is rising and little therapeutic improvements are expected in the near future. It has been observed that Epithelial-to-Mesenchymal transition (EMT) contributes (including in PDAC) to a more aggressive cancer phenotype. Additionally, largely unexplored, studies indicate a mechanistic interplay between Protein Phosphatase Type 2A (PP2A) enzymes and EMT that could offer treatment opportunities. The aim was to investigate the relation of a PP2A expression signature (encompassing all PP2A subunits, endogenous inhibitors and activators) with EMT and aggressive pancreatic cancer, and to discuss possible implications.

METHODS

We retrieved different PDAC expression datasets from NCBI to capture the variation in patients, and analyzed these using datamining, survival analysis, differential gene and protein expression. We determined genes highly associated with aggressive PDAC. For in vitro evaluation, Panc-1 cells were treated with the pharmacologic PP2A inhibitor Okadaic Acid (OA). Additionally, two OA-resistant Panc-1 clones were developed and characterized.

RESULTS

In patients, there is a strong correlation between EMT and aggressive PDAC, and between aggressive PDAC and PP2A, with a significant upregulation of PP2A inhibitor genes. Several PP2A genes significantly correlated with decreased survival. In vitro, short-term exposure to OA induced EMT in Panc-1 cells. This shift towards EMT was further pronounced in the OA-resistant Panc-1 clones, morphologically and by pathway analysis. Proteomic analysis and gene sequencing showed that the advanced OA-resistant model most resembles the clinical PDAC presentation (with EMT signature, and with several specific PP2A genes upregulated, and others downregulated).

CONCLUSIONS

We demonstrated a strong association between EMT, altered PP2A expression and aggressive PDAC in patients. Also, in vitro, PP2A inhibition induces EMT. Overall, statistics suggests the mechanistic importance of PP2A dysregulation for PDAC progression. Translationally, our observations indicate that pharmacologic restoration of PP2A activity could be an attractive therapeutic strategy to block or reverse progression.

Microarchitectural mimicking of stroma-induced vasculature compression in pancreatic tumors using a 3D engineered model

Fibrotic tumors, such as pancreatic ductal adenocarcinoma (PDAC), are characterized for high desmoplastic reaction, which results in high intra-tumoral solid stress leading to the compression of blood vessels. These microarchitectural alterations cause loss of blood flow and poor intra-tumoral delivery of therapeutics. Currently, there is a lack of relevant in vitro models capable of replicating these mechanical characteristics and to test anti-desmoplastic compounds. Here, a multi-layered vascularized 3D PDAC model consisting of primary human pancreatic stellate cells (PSCs) embedded in collagen/fibrinogen (Col/Fib), mimicking tumor tissue within adjunct healthy tissue, is presented to study the fibrosis-induced compression of vasculature in PDAC. It is demonstrated how the mechanical and biological stimulation induce PSC activation, extracellular matrix production and eventually vessel compression. The clinical relevance is confirmed by correlating with patient transcriptomic data. Furthermore, the effects of gradual vessel compression on the fluid dynamics occurring within the channel is evaluated in silico. Finally, it is demonstrated how cancer-associated fibroblast (CAF)-modulatory therapeutics can inhibit the cell-mediated compression of blood vessels in PDAC in vitro, in silico and in vivo. It is envisioned that this 3D model is used to improve the understanding of mechanical characteristics in tumors and for evaluating novel anti-desmoplastic therapeutics.

Macrophages direct cancer cells through a LOXL2-mediated metastatic cascade in pancreatic ductal adenocarcinoma

OBJECTIVE

The lysyl oxidase-like protein 2 (LOXL2) contributes to tumour progression and metastasis in different tumour entities, but its role in pancreatic ductal adenocarcinoma (PDAC) has not been evaluated in immunocompetent in vivo PDAC models.

DESIGN

Towards this end, we used PDAC patient data sets, patient-derived xenograft in vivo and in vitro models, and four conditional genetically-engineered mouse models (GEMMS) to dissect the role of LOXL2 in PDAC. For GEMM-based studies, K-Ras +/LSL-G12D;Trp53 LSL-R172H;Pdx1-Cre mice (KPC) and the K-Ras +/LSL-G12D;Pdx1-Cre mice (KC) were crossed with Loxl2 allele floxed mice (Loxl2Exon2 fl/fl) or conditional Loxl2 overexpressing mice (R26Loxl2 KI/KI) to generate KPCL2KO or KCL2KO and KPCL2KI or KCL2KI mice, which were used to study overall survival; tumour incidence, burden and differentiation; metastases; epithelial to mesenchymal transition (EMT); stemness and extracellular collagen matrix (ECM) organisation.

RESULTS

Using these PDAC mouse models, we show that while Loxl2 ablation had little effect on primary tumour development and growth, its loss significantly decreased metastasis and increased overall survival. We attribute this effect to non-cell autonomous factors, primarily ECM remodelling. Loxl2 overexpression, on the other hand, promoted primary and metastatic tumour growth and decreased overall survival, which could be linked to increased EMT and stemness. We also identified tumour-associated macrophage-secreted oncostatin M (OSM) as an inducer of LOXL2 expression, and show that targeting macrophages in vivo affects Osm and Loxl2 expression and collagen fibre alignment.

CONCLUSION

Taken together, our findings establish novel pathophysiological roles and functions for LOXL2 in PDAC, which could be potentially exploited to treat metastatic disease.

Elevated FSP1 protects KRAS-mutated cells from ferroptosis during tumor initiation

Oncogenic KRAS is the key driver oncogene for several of the most aggressive human cancers. One key feature of oncogenic KRAS expression is an early increase in cellular reactive oxygen species (ROS) which promotes cellular transformation if cells manage to escape cell death, mechanisms of which remain incompletely understood. Here, we identify that expression of oncogenic as compared to WT KRAS in isogenic cellular systems renders cells more resistant to ferroptosis, a recently described type of regulated necrosis. Mechanistically, we find that cells with mutant KRAS show a specific lack of ferroptosis-induced lipid peroxidation. Interestingly, KRAS-mutant cells upregulate expression of ferroptosis suppressor protein 1 (FSP1). Indeed, elevated levels of FSP1 in KRAS-mutant cells are responsible for mediating ferroptosis resistance and FSP1 is upregulated as a consequence of MAPK and NRF2 pathway activation downstream of KRAS. Strikingly, FSP1 activity promotes cellular transformation in soft agar and its overexpression is sufficient to promote spheroid growth in 3D in KRAS WT cells. Moreover, FSP1 expression and its activity in ferroptosis inhibition accelerates tumor onset of KRAS WT cells in the absence of oncogenic KRAS in vivo. Consequently, we find that pharmacological induction of ferroptosis in pancreatic organoids derived from the LsL-KRAS^G12D expressing mouse model is only effective in combination with FSP1 inhibition. Lastly, FSP1 is upregulated in non-small cell lung cancer (NSCLC), colorectal cancer (CRC) and pancreatic ductal adenocarcinoma (PDAC) as compared to the respective normal tissue of origin and correlates with NRF2 expression in PDAC patient datasets. Based on these data, we propose that KRAS-mutant cells must navigate a ferroptosis checkpoint by upregulating FSP1 during tumor establishment. Consequently, ferroptosis-inducing therapy should be combined with FSP1 inhibitors for efficient therapy of KRAS-mutant cancers.

The Landscape of HNF1B Deficiency: A Syndrome Not Yet Fully Explored

The hepatocyte nuclear factor 1β (HNF1B) gene is involved in the development of specialized epithelia of several organs during the early and late phases of embryogenesis, performing its function mainly by regulating the cell cycle and apoptosis pathways. The first pathogenic variant of HNF1B (namely, R177X) was reported in 1997 and is associated with the maturity-onset diabetes of the young. Since then, more than 230 different HNF1B variants have been reported, revealing a multifaceted syndrome with complex and heterogenous genetic, pathologic, and clinical profiles, mainly affecting the pediatric population. The pancreas and kidneys are the most frequently affected organs, resulting in diabetes, renal cysts, and a decrease in renal function, leading, in 2001, to the definition of HNF1B deficiency syndrome, including renal cysts and diabetes. However, several other organs and systems have since emerged as being affected by HNF1B defect, while diabetes and renal cysts are not always present. Especially, liver involvement has generally been overlooked but recently emerged as particularly relevant (mostly showing chronically elevated liver enzymes) and with a putative relation with tumor development, thus requiring a more granular analysis. Nowadays, HNF1B-associated disease has been recognized as a clinical entity with a broader and more variable multisystem phenotype, but the reasons for the phenotypic heterogeneity are still poorly understood. In this review, we aimed to describe the multifaceted nature of HNF1B deficiency in the pediatric and adult populations: we analyzed the genetic, phenotypic, and clinical features of this complex and misdiagnosed syndrome, covering the most frequent, unusual, and recently identified traits.

C/EBP-Family Redundancy Determines Patient Survival and Lymph Node Involvement in PDAC

Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease with a poor clinical prognosis and unsatisfactory treatment options. We previously found that the transcription factor CCAAT/Enhancer-Binding Protein Delta (C/EBPδ) is lowly expressed in PDAC compared to healthy pancreas duct cells, and that patient survival and lymph node involvement in PDAC is correlated with the expression of C/EBPδ in primary tumor cells. C/EBPδ shares a homologous DNA-binding sequence with other C/EBP-proteins, leading to the presumption that other C/EBP-family members might act redundantly and compensate for the loss of C/EBPδ. This implies that patient stratification could be improved when expression levels of multiple C/EBP-family members are considered simultaneously. In this study, we assessed whether the quantification of C/EBPβ or C/EBPγ in addition to that of C/EBPδ might improve the prediction of patient survival and lymph node involvement using a cohort of 68 resectable PDAC patients. Using Kaplan-Meier analyses of patient groups with different C/EBP-expression levels, we found that both C/EBPβ and C/EBPγ can partially compensate for low C/EBPδ and improve patient survival. Further, we uncovered C/EBPβ as a novel predictor of a decreased likelihood of lymph node involvement in PDAC, and found that C/EBPβ and C/EBPδ can compensate for the lack of each other in order to reduce the risk of lymph node involvement. C/EBPγ, on the other hand, appears to promote lymph node involvement in the absence of C/EBPδ. Altogether, our results show that the redundancy of C/EBP-family members might have a profound influence on clinical prognoses and that the expression of both C/EPBβ and C/EBPγ should be taken into account when dichotomizing patients according to C/EBPδ expression.

Metastatic phenotype and immunosuppressive tumour microenvironment in pancreatic ductal adenocarcinoma: Key role of the urokinase plasminogen activator (PLAU)

Background

Previous studies have revealed the role of dysregulated urokinase plasminogen activator (encoded by PLAU) expression and activity in several pathways associated with cancer progression. However, systematic investigation into the association of PLAU expression with factors that modulate PDAC (pancreatic ductal adenocarcinoma) progression is lacking, such as those affecting stromal (pancreatic stellate cell, PSC)-cancer cell interactions, tumour immunity, PDAC subtypes and clinical outcomes from potential PLAU inhibition.

Methods

This study used an integrated bioinformatics approach to identify prognostic markers correlated with PLAU expression using different transcriptomics, proteomics, and clinical data sets. We then determined the association of dysregulated PLAU and correlated signatures with oncogenic pathways, metastatic phenotypes, stroma, immunosuppressive tumour microenvironment (TME) and clinical outcome. Finally, using an in vivo orthotopic model of pancreatic cancer, we confirmed the predicted effect of inhibiting PLAU on tumour growth and metastasis.

Results

Our analyses revealed that PLAU upregulation is not only associated with numerous other prognostic markers but also associated with the activation of various oncogenic signalling pathways, aggressive phenotypes relevant to PDAC growth and metastasis, such as proliferation, epithelial-mesenchymal transition (EMT), stemness, hypoxia, extracellular cell matrix (ECM) degradation, upregulation of stromal signatures, and immune suppression in the tumour microenvironment (TME). Moreover, the upregulation of PLAU was directly connected with signalling pathways known to mediate PSC-cancer cell interactions. Furthermore, PLAU upregulation was associated with the aggressive basal/squamous phenotype of PDAC and significantly reduced overall survival, indicating that this subset of patients may benefit from therapeutic interventions to inhibit PLAU activity. Our studies with a clinically relevant orthotopic pancreatic model showed that even short-term PLAU inhibition is sufficient to significantly halt tumour growth and, importantly, eliminate visible metastasis.

Conclusion

Elevated PLAU correlates with increased aggressive phenotypes, stromal score, and immune suppression in PDAC. PLAU upregulation is also closely associated with the basal subtype type of PDAC; patients with this subtype are at high risk of mortality from the disease and may benefit from therapeutic targeting of PLAU.

LAMC2 marks a tumor-initiating cell population with an aggressive signature in pancreatic cancer

BACKGROUND

Tumor-initiating cells (TIC), also known as cancer stem cells, are considered a specific subpopulation of cells necessary for cancer initiation and metastasis; however, the mechanisms by which they acquire metastatic traits are not well understood.

METHODS

LAMC2 transcriptional levels were evaluated using publicly available transcriptome data sets, and LAMC2 immunohistochemistry was performed using a tissue microarray composed of PDAC and normal pancreas tissues. Silencing and tracing of LAMC2 was performed using lentiviral shRNA constructs and CRISPR/Cas9-mediated homologous recombination, respectively. The contribution of LAMC2 to PDAC tumorigenicity was explored in vitro by tumor cell invasion, migration, sphere-forming and organoids assays, and in vivo by tumor growth and metastatic assays. mRNA sequencing was performed to identify key cellular pathways upregulated in LAMC2 expressing cells. Metastatic spreading induced by LAMC2- expressing cells was blocked by pharmacological inhibition of transforming growth factor beta (TGF-β) signaling.

RESULTS

We report a LAMC2-expressing cell population, which is endowed with enhanced self-renewal capacity, and is sufficient for tumor initiation and differentiation, and drives metastasis. mRNA profiling of these cells indicates a prominent squamous signature, and differentially activated pathways critical for tumor growth and metastasis, including deregulation of the TGF-β signaling pathway. Treatment with Vactosertib, a new small molecule inhibitor of the TGF-β type I receptor (activin receptor-like kinase-5, ALK5), completely abrogated lung metastasis, primarily originating from LAMC2-expressing cells.

CONCLUSIONS

We have identified a highly metastatic subpopulation of TICs marked by LAMC2. Strategies aimed at targeting the LAMC2 population may be effective in reducing tumor aggressiveness in PDAC patients. Our results prompt further study of this TIC population in pancreatic cancer and exploration as a potential therapeutic target and/or biomarker.

The limits of molecular signatures for pancreatic ductal adenocarcinoma subtyping

Molecular signatures have been suggested as biomarkers to classify pancreatic ductal adenocarcinoma (PDAC) into two, three, four or five subtypes. Since the robustness of existing signatures is controversial, we performed a systematic evaluation of four established signatures for PDAC stratification across nine publicly available datasets. Clustering revealed inconsistency of subtypes across independent datasets and in some cases a different number of PDAC subgroups than in the original study, casting doubt on the actual number of existing subtypes. Next, we built sixteen classification models to investigate the ability of the signatures for tumor subtype prediction. The overall classification performance ranged from ∼35% to ∼90% accuracy, suggesting instability of the signatures. Notably, permuted subtypes and random gene sets achieved very similar performance. Cellular decomposition and functional pathway enrichment analysis revealed strong tissue-specificity of the predicted classes. Our study highlights severe limitations and inconsistencies that can be attributed to technical biases in sample preparation and tumor purity, suggesting that PDAC molecular signatures do not generalize across datasets. How stromal heterogeneity and immune compartment interplay in the diverging development of PDAC is still unclear. Therefore, a more mechanistic or a cross-platform multi-omic approach seems necessary to extract more robust and clinically exploitable insights.

Impact of classical and basal-like molecular subtypes on overall survival in resected pancreatic cancer in the SPACIOUS-2 multicentre study

BACKGROUND

The recently identified classical and basal-like molecular subtypes of pancreatic cancer impact on overall survival (OS). However, the added value of routine subtyping in both clinical practice and randomized trials is still unclear, as most studies do not consider clinicopathological parameters. This study examined the clinical prognostic value of molecular subtyping in patients with resected pancreatic cancer.

METHODS

Subtypes were determined on fresh-frozen resected pancreatic cancer samples from three Dutch centres using the Purity Independent Subtyping of Tumours classification. Patient, treatment, and histopathological variables were compared between subtypes. The prognostic value of subtyping in (simulated) pre- and postoperative settings was assessed using Kaplan-Meier and Cox regression analyses.

RESULTS

Of 199 patients with resected pancreatic cancer, 164 (82.4 per cent) were classified as the classical and 35 (17.6 per cent) as the basal-like subtype. Patients with a basal-like subtype had worse OS (11 versus 16 months (HR 1.49, 95 per cent c.i. 1.03 to 2.15; P = 0.035)) than patients with a classical subtype. In multivariable Cox regression analysis, including only clinical variables, the basal-like subtype was a statistically significant predictor for poor OS (HR 1.61, 95 per cent c.i. 1.11 to 2.34; P = 0.013). When histopathological variables were added to this model, the prognostic value of subtyping decreased (HR 1.49, 95 per cent c.i. 1.01 to 2.19; P = 0.045).

CONCLUSION

The basal-like subtype was associated with worse OS in patients with resected pancreatic cancer. Adding molecular classification to inform on tumor biology may be used in patient stratification.

Comprehensive molecular profiling of pancreatic ductal adenocarcinoma in FNA, biopsy, and resection specimens

BACKGROUND

Molecular testing to identify molecular alterations in pancreatic ductal adenocarcinoma (PDAC) has been increasingly requested because of potential therapeutic implications. In this study, we compared the performance of PDAC fine-needle aspiration (FNA), fine-needle biopsy (FNB), and resection specimens for comprehensive molecular analysis.

METHODS

A next-generation sequencing-based Oncomine Comprehensive Assay (OCA) was used to analyze molecular alterations in FNA, FNB, or resection specimens. We examined adequacy and success rates for completion of molecular testing and catalogued molecular alterations in these specimen types.

RESULTS

The cohort included 23 FNA, 20 FNB, and 27 resection cases. Gene mutation or amplification analysis was successful in 18 (78%) FNA and 16 (80%) FNB specimens, whereas gene fusion assessment succeeded in 12 (52%) FNA and 12 (60%) FNB samples. All 27 (100%) resection specimens were adequate for complete OCA. There were significant differences in success rates for mutation and amplification analysis between resection and FNA or FNB specimens (P < .01) but not between FNA and FNB samples (P > .05). Manual microdissection was less likely to be performed for FNA specimens than FNB or resection specimens (P < .01). KRAS mutation was the most common mutation identified (90%), followed by mutations in TP53 (64%), CDKN2A (25%), and SMAD4 (15%) genes.

CONCLUSIONS

Our study demonstrated similar success rates for comprehensive molecular analysis using FNA and FNB specimens of PDAC, suggesting that FNA material could serve as an alternative source for comprehensive molecular testing. The molecular alterations identified in these specimens may have potential diagnostic and therapeutic implications.

Machine learning-featured Secretogranin V is a circulating diagnostic biomarker for pancreatic adenocarcinomas associated with adipopenia

Background

Pancreatic cancer is one of the most fatal malignancies of the gastrointestinal cancer, with a challenging early diagnosis due to lack of distinctive symptoms and specific biomarkers. The exact etiology of pancreatic cancer is unknown, making the development of reliable biomarkers difficult. The accumulation of patient-derived omics data along with technological advances in artificial intelligence is giving way to a new era in the discovery of suitable biomarkers.

Methods

We performed machine learning (ML)-based modeling using four independent transcriptomic datasets, including GSE16515, GSE62165, GSE71729, and the pancreatic adenocarcinoma (PAC) dataset of the Cancer Genome Atlas. To find candidates for circulating biomarkers, we exported expression profiles of 1,703 genes encoding secretory proteins. Integrating three transcriptomic datasets into either a training or test set, ML-based modeling distinguishing PAC from normal was carried out. Another ML-model classifying long-lived and short-lived patients with PAC was also built to select prognosis-associated features. Finally, circulating level of SCG5 in the plasma was determined from the independent cohort (non-tumor = 25 and pancreatic cancer = 25). We also investigated the impact of SCG5 on adipocyte biology using recombinant protein.

Results

Three distinctive ML-classifiers selected 29-, 64- and 18-featured genes, recognizing the only common gene, SCG5. As per the prediction of ML-models, the SCG5 transcripts was significantly reduced in PAC and decreased further with the progression of the tumor, indicating its potential as a diagnostic as well as prognostic marker for PAC. External validation of SCG5 using plasma samples from patients with PAC confirmed that SCG5 was reduced significantly in patients with PAC when compared to controls. Interestingly, plasma SCG5 levels were correlated with the body mass index and age of donors, implying pancreas-originated SCG5 could regulate energy metabolism systemically. Additionally, analyses using publicly available Genotype-Tissue Expression datasets, including adipose tissue histology and pancreatic SCG5 expression, further validated the association between pancreatic SCG5 expression and the size of subcutaneous adipocytes in humans. However, we could not observe any definite effect of rSCG5 on the cultured adipocyte, in 2D in vitro culture.

Conclusion

Circulating SCG5, which may be associated with adipopenia, is a promising diagnostic biomarker for PAC.

Construction of immune-related signature and identification of S100A14 determining immune-suppressive microenvironment in pancreatic cancer

Pancreatic cancer (PC) is a highly lethal and aggressive disease with its incidence and mortality quite discouraging. A robust prognostic signature and novel biomarkers are urgently needed for accurate stratification of the patients and optimization of clinical decision-making. Since the critical role of immune microenvironment in the progression of PC, a prognostic signature based on seven immune-related genes was established, which was validated in The Cancer Genome Atlas (TCGA) training set, TCGA testing set, TCGA entire set and GSE71729 set. Furthermore, S100A14 (S100 Calcium Binding Protein A14) was identified as the gene occupying the most paramount position in risk signature. According to the GSEA, CIBERSORT and ESTIMATE algorithm, S100A14 was mainly associated with lower proportion of CD8 + T cells and higher proportion of M0 macrophages in PC tissue. Meanwhile, analysis of single-cell dataset CRA001160 revealed a significant negative correlation between S100A14 expression in PC cells and CD8 + T cell infiltration, which was further confirmed by tissue microenvironment landscape imaging and machine learning-based analysis in our own PUMCH cohort. Additionally, analysis of a pan-pancreatic cancer cell line illustrated that S100A14 might inhibit CD8 + T cell activation via the upregulation of PD-L1 expression in PC cells, which was also verified by the immunohistochemical results of PUMCH cohort. Finally, tumor mutation burden analysis and immunophenoscore algorithm revealed that patients with high S100A14 expression had a higher probability of responding to immunotherapy. In conclusion, our study established an efficient immune-related prediction model and identified the potential role of S100A14 in regulating the immune microenvironment and serving as a biomarker for immunotherapy efficacy prediction.

Discovery Proteomics Analysis Determines That Driver Oncogenes Suppress Antiviral Defense Pathways Through Reduction in Interferon-β Autocrine Stimulation

Since the discovery of oncogenes, there has been tremendous interest to understand their mechanistic basis and to develop broadly actionable therapeutics. Some of the most frequently activated oncogenes driving diverse cancers are c-MYC, EGFR, HER2, AKT, KRAS, BRAF, and MEK. Using a reductionist approach, we explored how cellular proteomes are remodeled in isogenic cell lines engineered with or without these driver oncogenes. The most striking discovery for all oncogenic models was the systematic downregulation of scores of antiviral proteins regulated by type 1 interferon. These findings extended to cancer cell lines and patient-derived xenograft models of highly refractory pancreatic cancer and osteosarcoma driven by KRAS and MYC oncogenes. The oncogenes reduced basal expression of and autocrine stimulation by type 1 interferon causing remarkable convergence on common phenotypic and functional profiles. In particular, there was dramatically lower expression of dsRNA sensors including DDX58 (RIG-I) and OAS proteins, which resulted in attenuated functional responses when the oncogenic cells were treated with the dsRNA mimetic, polyI:C, and increased susceptibility to infection with an RNA virus shown using SARS-CoV-2. Our reductionist approach provides molecular and functional insights connected to immune evasion hallmarks in cancers and suggests therapeutic opportunities.

Integrated bioinformatics analysis of potential biomarkers for pancreatic cancer

BACKGROUND

Pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDA), is an aggressive malignancy associated with a low 5-year survival rate. Poor outcomes associated with PDA are attributable to late detection and inoperability. Most patients with PDA are diagnosed with locally advanced and metastatic disease. Such cases are primarily treated with chemotherapy and radiotherapy. Because of the lack of effective molecular targets, early diagnosis and successful therapies are limited. The purpose of this study was to screen key candidate genes for PDA using a bioinformatic approach and to research their potential functional, pathway mechanisms associated with PDA progression. It may help to understand the role of associated genes in the development and progression of PDA and identify relevant molecular markers with value for early diagnosis and targeted therapy.

MATERIALS AND METHODS

To identify novel genes associated with carcinogenesis and progression of PDA, we analyzed the microarray datasets GSE62165, GSE125158, and GSE71989 from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and the Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A protein-protein interaction (PPI) network was constructed using STRING, and module analysis was performed using Cytoscape. Gene Expression Profiling Interactive Analysis (GEPIA) was used to evaluate the differential expression of hub genes in patients with PDA. In addition, we verified the expression of these genes in PDA cell lines and normal pancreatic epithelial cells.

RESULTS

A total of 202 DEGs were identified and these were found to be enriched for various functions and pathways, including cell adhesion, leukocyte migration, extracellular matrix organization, extracellular region, collagen trimer, membrane raft, fibronectin-binding, integrin binding, protein digestion, and absorption, and focal adhesion. Among these DEGs, 12 hub genes with high degrees of connectivity were selected. Survival analysis showed that the hub genes (HMMR, CEP55, CDK1, UHRF1, ASPM, RAD51AP1, DLGAP5, KIF11, SHCBP1, PBK, and HMGB2) may be involved in the tumorigenesis and development of PDA, highlighting their potential as diagnostic and therapeutic factors in PDA.

CONCLUSIONS

In summary, the DEGs and hub genes identified in the present study not only contribute to a better understanding of the molecular mechanisms underlying the carcinogenesis and progression of PDA but may also serve as potential new biomarkers and targets for PDA.

Investigating the interference of single nucleotide polymorphisms with miRNA mediated gene regulation in pancreatic ductal adenocarcinoma: An in silico approach

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a strong genetic component and single nucleotide polymorphisms (SNPs) in key genes have been found to modulate the susceptibility of the individuals to the disease. SNPs in 3'-UTR of the target genes or in miRNA seed region has gained much importance as this may lead to impairment of miRNA-mRNA interaction. Not much information about this phenomenon is available with respect to PDAC and we wanted to predict such SNPs which could affect miRNA function in the disease using bioinformatics tools.

METHODS

After identifying the deregulated miRNAs and genes in PDAC, we determined how many of those altered genes are among experimentally validated targets of those miRNAs. Subsequently, SNPs which could alter these miRNA-mRNA interactions were detected using multiple webtools following high stringent conditions. Disease relevance of the SNPs were also evaluated.

RESULTS

We identified a total of 2492 experimentally validated target genes for 303 miRNAs deregulated in PDAC. Our meta-analysis from 363 PDAC patients and 162 control individuals resulted in a set of differentially expressed genes in pancreatic cancer, which was further compared with the miRNA target genes to get targets differentially expressed in pancreatic cancer. We further detected SNPs either in 'seed' region of miRNAs or 'seed-match' sequence of mRNAs either having disruption or creation of miRNA binding site, correlated the expression for each miRNA-SNP-mRNA interaction. Selected SNPs were found to be in LD with important GWAS identified SNPs.

CONCLUSION

Our study, hereby, explores the probable effects of SNPs on miRNA-target mRNA interactions. Through stringent analytical methods, we have identified 3 common variants and 13other rare variants possibly interfering with miRNA mediated gene regulation in PDAC.

MNX1-HNF1B Axis Is Indispensable for Intraductal Papillary Mucinous Neoplasm Lineages

BACKGROUND & AIMS

Chromatin architecture governs cell lineages by regulating the specific gene expression; however, its role in the diversity of cancer development remains unknown. Among pancreatic cancers, pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasms (IPMN) with an associated invasive carcinoma (IPMNinv) arise from 2 distinct precursors, and their fundamental differences remain obscure. Here, we aimed to assess the difference of chromatin architecture regulating the transcriptional signatures or biological features in pancreatic cancers.

METHODS

We established 28 human organoids from distinct subtypes of pancreatic tumors, including IPMN, IPMNinv, and PDAC. We performed exome sequencing (seq), RNA-seq, assay for transposase-accessible chromatin-seq, chromatin immunoprecipitation-seq, high-throughput chromosome conformation capture, and phenotypic analyses with short hairpin RNA or clustered regularly interspaced short palindromic repeats interference.

RESULTS

Established organoids successfully reproduced the histology of primary tumors. IPMN and IPMNinv organoids harbored GNAS, RNF43, or KLF4 mutations and showed the distinct expression profiles compared with PDAC. Chromatin accessibility profiles revealed the gain of stomach-specific open regions in IPMN and the pattern of diverse gastrointestinal tissues in IPMNinv. In contrast, PDAC presented an impressive loss of accessible regions compared with normal pancreatic ducts. Transcription factor footprint analysis and functional assays identified that MNX1 and HNF1B were biologically indispensable for IPMN lineages. The upregulation of MNX1 was specifically marked in the human IPMN lineage tissues. The MNX1-HNF1B axis governed a set of genes, including MYC, SOX9, and OLFM4, which are known to be essential for gastrointestinal stem cells. High-throughput chromosome conformation capture analysis suggested the HNF1B target genes to be 3-dimensionally connected in the genome of IPMNinv.

CONCLUSIONS

Our organoid analyses identified the MNX1-HNF1B axis to be biologically significant in IPMN lineages.

The expression and survival significance of sodium glucose transporters in pancreatic cancer

Background

Sodium glucose transporters (SGLTs) play vital roles in glucose uptake in many solid cancers, including pancreatic cancer (PC). However, their expression profile in pancreatic cancer and correlation with prognosis are not clear. Thus, we aimed to analyse the expression profile and prognostic significance of SGLT-1 and SGLT-2 in PC.

Methods

Eighty-eight patients with pancreatic ductal adenocarcinoma (PDAC) undergoing surgery in Huashan Hospital, Fudan University, from July 2017 to June 2020 were enrolled in the study. Specimens for immunohistochemistry were obtained through surgical resection. Bioinformatics analysis was performed based on the Gene Expression Omnibus (GEO), Oncomine and The Cancer Genome Atlas (TCGA) databases. The statistics were calculated using IBM SPSS Statistics, version 20 and R 4.1.1. P values lower than 0.05 were considered to indicate statistical significance.

Results

SGLT-1 but not SGLT-2 was significantly overexpressed in PDAC. Survival analysis showed that the median overall survival (OS) and progression-free survival (PFS) of patients with high SGLT-1 expression were significantly longer than that of patients with low SGLT-1 expression. Cox regression indicated that high SGLT-1 expression was an independent predictor for a better prognosis, while residual tumour status (R1 and R2) was an independent risk factor for a poor prognosis. Finally, PDZK1-interacting protein 1 (PDZK1IP1), a protein participating in the generation of reactive oxygen species, was overexpressed in PDAC and its expression was significantly correlated with SGLT-1.

Conclusions

SGLT-1 but not SGLT-2 was overexpressed in PDAC, and the overexpression of SGLT-1 could be a predictor of a better prognosis. Residual tumour status (R1 and R2) was a risk factor for poor prognosis and disease progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09060-4.

Comprehensive quantitative analysis of alternative splicing variants reveals the HNF1B mRNA splicing pattern in various tumour and non-tumour tissues

Hepatocyte nuclear factor-1-beta (HNF1B) is a transcription factor and putative biomarker of solid tumours. Recently, we have revealed a variety of HNF1B mRNA alternative splicing variants (ASVs) with unknown, but potentially regulatory, functions. The aim of our work was to quantify the most common variants and compare their expression in tumour and non-tumour tissues of the large intestine, prostate, and kidney. The HNF1B mRNA variants 3p, Δ7, Δ7–8, and Δ8 were expressed across all the analysed tissues in 28.2–33.5%, 1.5–2%, 0.8–1.7%, and 2.3–6.9% of overall HNF1B mRNA expression, respectively, and occurred individually or in combination. The quantitative changes of ASVs between tumour and non-tumour tissue were observed for the large intestine (3p, Δ7–8), prostate (3p), and kidney samples (Δ7). Decreased expression of the overall HNF1B mRNA in the large intestine and prostate cancer samples compared with the corresponding non-tumour samples was observed (p = 0.019 and p = 0.047, respectively). The decreased mRNA expression correlated with decreased protein expression in large intestine carcinomas (p < 0.001). The qualitative and quantitative pattern of the ASVs studied by droplet digital PCR was confirmed by next-generation sequencing, which suggests the significance of the NGS approach for further massive evaluation of the splicing patterns in a variety of genes.

Pancreatic Cancer Patient-Derived Organoid Platforms: A Clinical Tool to Study Cell- and Non-Cell-Autonomous Mechanisms of Treatment Response

For many years, cell lines and animal models have been essential to improve our understanding of the basis of cell metabolism, signaling, and genetics. They also provided an essential boost to cancer drug discovery. Nevertheless, these model systems failed to reproduce the tumor heterogeneity and the complex biological interactions between cancer cells and human hosts, making a high priority search for alternative methods that are able to export results from model systems to humans, which has become a major bottleneck in the drug development. The emergent human in vitro 3D cell culture technologies have attracted widespread attention because they seem to have the potential to overcome these limitations. Organoids are unique 3D culture models with the ability to self-organize in contained structures. Their versatility has offered an exceptional window of opportunity to approach human cancers. Pancreatic cancers (PCs) patient-derived-organoids (PDOs) preserve histological, genomic, and molecular features of neoplasms they originate from and therefore retain their heterogeneity. Patient-derived organoids can be established with a high success rate from minimal tissue core specimens acquired with endoscopic-ultrasound-guided techniques and assembled into platforms, representing tens to hundreds of cancers each conserving specific features, expanding the types of patient samples that can be propagated and analyzed in the laboratory. Because of their nature, PDO platforms are multipurpose systems that can be easily adapted in co-culture settings to perform a wide spectrum of studies, ranging from drug discovery to immune response evaluation to tumor-stroma interaction. This possibility to increase the complexity of organoids creating a hybrid culture with non-epithelial cells increases the interest in organoid-based platforms giving a pragmatic way to deeply study biological interactions in vitro. In this view, implementing organoid models in co-clinical trials to compare drug responses may represent the next step toward even more personalized medicine. In the present review, we discuss how PDO platforms are shaping modern-day oncology aiding to unravel the most complex aspects of PC.

Identification of Key Deregulated RNA-Binding Proteins in Pancreatic Cancer by Meta-Analysis and Prediction of Their Role as Modulators of Oncogenesis

RNA-binding proteins (RBPs) play a significant role in multiple cellular processes with their deregulations strongly associated with cancer. However, there are not adequate evidences regarding global alteration and functions of RBPs in pancreatic cancer, interrogated in a systematic manner. In this study, we have prepared an exhaustive list of RBPs from multiple sources, downloaded gene expression microarray data from a total of 241 pancreatic tumors and 124 normal pancreatic tissues, performed a meta-analysis, and obtained differentially expressed RBPs (DE-RBPs) using the Limma package of R Bioconductor. The results were validated in microarray datasets and the Cancer Genome Atlas (TCGA) RNA sequencing dataset for pancreatic adenocarcinoma (PAAD). Pathway enrichment analysis was performed using DE-RBPs, and we also constructed the protein-protein interaction (PPI) network to detect key modules and hub-RBPs. Coding and noncoding targets for top altered and hub RBPs were identified, and altered pathways modulated by these targets were also investigated. Our meta-analysis identified 45 upregulated and 15 downregulated RBPs as differentially expressed in pancreatic cancer, and pathway enrichment analysis demonstrated their important contribution in tumor development. As a result of PPI network analysis, 26 hub RBPs were detected and coding and noncoding targets for all these RBPs were categorized. Functional exploration characterized the pathways related to epithelial-to-mesenchymal transition (EMT), cell migration, and metastasis to emerge as major pathways interfered by the targets of these RBPs. Our study identified a unique meta-signature of 26 hub-RBPs to primarily modulate pancreatic tumor cell migration and metastasis in pancreatic cancer. IGF2BP3, ISG20, NIP7, PRDX1, RCC2, RUVBL1, SNRPD1, PAIP2B, and SIDT2 were found to play the most prominent role in the regulation of EMT in the process. The findings not only contribute to understand the biology of RBPs in pancreatic cancer but also to evaluate their candidature as possible therapeutic targets.

S100A2 Is a Prognostic Biomarker Involved in Immune Infiltration and Predict Immunotherapy Response in Pancreatic Cancer

Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. It is of great significance to construct an effective prognostic signature of PC and find the novel biomarker for the optimization of the clinical decision-making. Due to the crucial role of immunity in tumor development, a prognostic model based on nine immune-related genes was constructed, which was proved to be effective in The Cancer Genome Atlas (TCGA) training set, TCGA testing set, TCGA entire set, GSE78229 set, and GSE62452 set. Furthermore, S100A2 (S100 Calcium Binding Protein A2) was identified as the gene occupying the most paramount position in risk model. Gene set enrichment analysis (GSEA), ESTIMATE and CIBERSORT algorithm revealed that S100A2 was closely associated with the immune status in PC microenvironment, mainly related to lower proportion of CD8+T cells and activated NK cells and higher proportion of M0 macrophages. Meanwhile, patients with high S100A2 expression might get more benefit from immunotherapy according to immunophenoscore algorithm. Afterwards, our independent cohort was also used to demonstrate S100A2 was an unfavorable marker of PC, as well as its remarkably positive correlation with the expression of PD-L1. In conclusion, our results demonstrate S100A2 might be responsible for the preservation of immune-suppressive status in PC microenvironment, which was identified with significant potentiality in predicting prognosis and immunotherapy response in PC patients.

A personalized approach to pancreatic ductal adenocarcinoma and its application in surgical practice

Pancreatic duct adenocarcinoma is an aggressive tumor which constitutes the fourth leading cause of cancer-related mortality in the USA. Despite the fact that surgery is an integral part of treatment, 5-year survival rates remain unfavorable, partly because of the complex genetic background, delayed diagnosis and also the absence of effective therapeutic approaches. To optimize surgery's results in recent years, the use of patients' genetic profile has been implemented through classification into subtypes; subtypes based on mutations which could efficiently lead oncologists to the path of targeted novel neoadjuvant regimens. This approach aims to achieve the most effective selection of patients undergoing surgery, to increase the number of potentially resectable tumors and also control micro-metastases, aiming to extend overall survival.

RUNX2 and LAMC2: promising pancreatic cancer biomarkers identified by an integrative data mining of pancreatic adenocarcinoma tissues

Pancreatic carcinoma (PC) is a severe disease associated with high mortality. Although strategies for cancer therapy have made great progress, outcomes of pancreatic carcinoma patients remain extremely poor. Therefore, it is urgent to find novel biomarkers and therapeutic targets. To identify biomarkers for early diagnosis and therapy, three mRNA microarray datasets and two miRNA datasets were selected, and combinative analysis was performed by GEO2R. Functional and pathway enrichment analysis were performed using DAVID database. MiRTarBase, miRWalk and Diana Tools were used to get key genes. TCGA, HPA and western blotting were used to verify diagnostic and prognostic value of key genes. By integrating mRNA and miRNA expression profiles, we identified 114 differentially expressed genes and 114 differentially expressed miRNAs, respectively. Then, three overlapping key genes, RUNX2, LAMC2 and FBXO32, were found. Their protein levels in pancreatic tissue from PC patients and normal people were analyzed by immunohistochemical staining and western blotting. RUNX2 showed a potential property to identify PC. Aberrant over-expression of LAMC2 was associated with poor prognosis of PC patients, tumor status and subtypes. In summary, our current study identified that RUNX2 and LAMC2 may be promising targets for early diagnosis and therapy of PC patients.

Genomic Heterogeneity of Pancreatic Ductal Adenocarcinoma and Its Clinical Impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer death due to limited advances in recent years in early diagnosis and personalized therapy capable of overcoming tumor resistance to chemotherapy. In the last decades, significant advances have been achieved in the identification of recurrent genetic and molecular alterations of PDAC including those involving the KRAS, CDKN2A, SMAD4, and TP53 driver genes. Despite these common genetic traits, PDAC are highly heterogeneous tumors at both the inter- and intra-tumoral genomic level, which might contribute to distinct tumor behavior and response to therapy, with variable patient outcomes. Despite this, genetic and genomic data on PDAC has had a limited impact on the clinical management of patients. Integration of genomic data for classification of PDAC into clinically defined entities-i.e., classical vs. squamous subtypes of PDAC-leading to different treatment approaches has the potential for significantly improving patient outcomes. In this review, we summarize current knowledge about the most relevant genomic subtypes of PDAC including the impact of distinct patterns of intra-tumoral genomic heterogeneity on the classification and clinical and therapeutic management of PDAC.

GSK2126458 has the potential to inhibit the proliferation of pancreatic cancer uncovered by bioinformatics analysis and pharmacological experiments

BACKGROUND

Pancreatic cancer is one of the most serious digestive malignancies. At present, there is an extreme lack of effective strategies in clinical treatment. The purpose of this study is to identify key genes and pathways in the development of pancreatic cancer and provide targets for the treatment of pancreatic cancer.

METHODS

GSE15471 and GSE62165 were used to screen differentially expressed genes by GEO2R tool. Hub genes prognostic potential assessed using the GEPIA and Kaplan-Meier plotter databases. The drug susceptibility data of pan-cancer cell lines is provided by The Genomics of Drug Sensitivity in Cancer Project (GDSC). Finally, the effects of PI3K-Akt signaling pathway inhibitors on cell viability of pancreatic cancer cells were detected by cell proliferation and invasion assays.

RESULTS

A total of 609 differentially expressed genes were screened and enriched in the focal adhesion, phagosome and PI3K-Akt signaling pathway. Of the 15 hub genes we found, four were primarily associated with the PI3K-Akt signaling pathway, including COL3A1, EGF, FN1 and ITGA2. GDSC analysis showed that mTOR inhibitors are very sensitive to pancreatic cancer cells with mutations in EWSR1.FLI1 and RNF43. Cell proliferation and invasion results showed that mTOR inhibitors (GSK2126458) can inhibit the proliferation of pancreatic cancer cells.

CONCLUSIONS

This study suggested that the PI3K-Akt signaling pathway may be a key pathway for pancreatic cancer, our study uncovered the potential therapeutic potential of GSK2126458, a specific mTOR inhibitor, for pancreatic cancer.

The Expression and Survival Significance of Glucose Transporter-1 in Pancreatic Cancer: Meta-Analysis, Bioinformatics Analysis and Retrospective Study

To explore the expression profile and prognostic relevance of GLUT-1 in pancreatic cancer, a meta-analysis, bioinformatics analysis based on Gene Expression Omnibus (GEO), Oncomine dataset and The Cancer Genome Atlas (TCGA) database, and immunohistochemistry in tumor and normal tissue from 88 pancreatic ductal adenocarcinoma (PDAC) patients were performed. GLUT-1 was significantly overexpressed in pancreatic cancer but it could not be a significant biomarker for prognosis. TNM stage and pathological grade could be biomarker of poor prognosis of patients with pancreatic cancer.

ITGA2, LAMB3, and LAMC2 may be the potential therapeutic targets in pancreatic ductal adenocarcinoma: an integrated bioinformatics analysis

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer with an abysmal prognosis rate over the last few decades. Early diagnosis and prevention could effectively combat this malignancy. Therefore, it is crucial to discover potential biomarkers to identify asymptomatic premalignant or early malignant tumors of PDAC. Gene expression analysis is a powerful technique to identify candidate biomarkers involved in disease progression. In the present study, five independent gene expression datasets, including 321 PDAC tissues and 208 adjacent non-cancerous tissue samples, were subjected to statistical and bioinformatics analysis. A total of 20 differentially expressed genes (DEGs) were identified in PDAC tissues compared to non-cancerous tissue samples. Gene ontology and pathway enrichment analysis showed that DEGs were mainly enriched in extracellular matrix (ECM), cell adhesion, ECM-receptor interaction, and focal adhesion signaling. The protein-protein interaction network was constructed, and the hub genes were evaluated. Collagen type XII alpha 1 chain (COL12A1), fibronectin 1 (FN1), integrin subunit alpha 2 (ITGA2), laminin subunit beta 3 (LAMB3), laminin subunit gamma 2 (LAMC2), thrombospondin 2 (THBS2), and versican (VCAN) were identified as hub genes. The correlation analysis revealed that identified hub genes were significantly interconnected. Wherein COL12A1, FN1, ITGA2, LAMB3, LAMC2, and THBS2 were significantly associated with PDAC pathological stages. The Kaplan-Meier survival plots revealed that ITGA2, LAMB3, and LAMC2 expression were inversely correlated with a prolonged patient survival period. Furthermore, the Human Protein Atlas database was used to validate the expression and cellular origins of hub genes encoded proteins. The protein expression of hub genes was higher in pancreatic cancer tissue than in normal pancreatic tissue samples, wherein ITGA2, LAMB3, and LAMC2 were exclusively expressed in pancreatic cancer cells. Pancreatic cancer cell-specific expression of these three proteins may play pleiotropic roles in cancer progression. Our results collectively suggest that ITGA2, LAMB3, and LAMC2 could provide deep insights into pancreatic carcinogenesis molecular mechanisms and provide attractive therapeutic targets.

Insights into the etiology and physiopathology of MODY5/HNF1B pancreatic phenotype with a mouse model of the human disease

Maturity-onset diabetes of the young type 5 (MODY5) is due to heterozygous mutations or deletion of HNF1B. No mouse models are currently available to recapitulate the human MODY5 disease. Here, we investigate the pancreatic phenotype of a unique MODY5 mouse model generated by heterozygous insertion of a human HNF1B splicing mutation at the intron-2 splice donor site in the mouse genome. This Hnf1bsp2/+ model generated with targeted mutation of Hnf1b mimicking the c.544+1G>T (T) mutation identified in humans, results in alternative transcripts and a 38% decrease of native Hnf1b transcript levels. As a clinical feature of MODY5 patients, the hypomorphic mouse model Hnf1bsp2/+ displays glucose intolerance. Whereas Hnf1bsp2/+ isolated islets showed no altered insulin secretion, we found a 65% decrease in pancreatic insulin content associated with a 30% decrease in total large islet volume and a 20% decrease in total β-cell volume. These defects were associated with a 30% decrease in expression of the pro-endocrine gene Neurog3 that we previously identified as a direct target of Hnf1b, showing a developmental etiology. As another clinical feature of MODY5 patients, the Hnf1bsp2/+ pancreases display exocrine dysfunction with hypoplasia. We observed chronic pancreatitis with loss of acinar cells, acinar-to-ductal metaplasia, and lipomatosis, with upregulation of signaling pathways and impaired acinar cell regeneration. This was associated with ductal cell deficiency characterized by shortened primary cilia. Importantly, the Hnf1bsp2/+ mouse model reproduces the pancreatic features of the human MODY5/HNF1B disease, providing a unique in vivo tool for molecular studies of the endocrine and exocrine defects and to advance basic and translational research. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Pancreatitis initiated pancreatic ductal adenocarcinoma: Pathophysiology explaining clinical evidence

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant lethal disease due to its asymptomatic at its early lesion of the disease and drug resistance. Target therapy associated with molecular pathways so far seems not to produce reasonable outcomes. Understanding of the molecular mechanisms underlying inflammation-initiated tumorigenesis may be helpful for development of an effective therapy of the disease. A line of studies showed that pancreatic tumorigenesis was resulted from pancreatitis, which was caused synergistically by various pancreatic cells. This review focuses on those players and their possible clinic implications, such as exocrine acinar cells, ductal cells, and various stromal cells, including pancreatic stellate cells (PSCs), macrophages, lymphocytes, neutrophils, mast cells, adipocytes and endothelial cells, working together with each other in an inflammation-mediated microenvironment governed by a myriad of cellular signaling networks towards PDAC.

TMPRSS4 Promotes Cell Proliferation and Inhibits Apoptosis in Pancreatic Ductal Adenocarcinoma by Activating ERK1/2 Signaling Pathway

Transmembrane protease serine 4 (TMPRSS4) is upregulated in various kinds of human cancers, including pancreatic cancer. However, its biological function in pancreatic ductal adenocarcinoma (PDAC) remains unclear. In the current study, real-time qPCR, immunohistochemical staining, Western blotting, and database (Cancer Genome Atlas and Gene Expression) analysis revealed remarkable overexpression of TMPRSS4 in PDAC tissue as compared to non-tumor tissue. The TMPRSS4 overexpression was associated with poor prognosis of PDAC patients. Moreover, multivariate analysis revealed that TMPRSS4 serves as an independent risk factor in PDAC. We performed gain-and loss-of-function analysis and found that TMPRSS4 promotes cellular proliferation and inhibits apoptosis of PDAC cells both in vitro and in vivo. Furthermore, we showed that TMPRSS4 might promote cell proliferation and inhibit apoptosis through activating ERK1/2 signaling pathway in pancreatic cancer cells. These findings were validated by using ERK1/2 phosphorylation inhibitor SCH772984 both in vitro and in vivo. Taken together, this study suggests that TMPRSS4 is a proto-oncogene, which promotes initiation and progression of PDAC by controlling cell proliferation and apoptosis. Our findings indicate that TMPRSS4 could be a promising prognostic biomarker and a therapeutic target for the treatment of pancreatic cancer.

Utility of HNF-1B and a panel of lineage-specific biomarkers to optimize the diagnosis of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) represents one of the most common cancers with dismal prognosis. Definitive diagnosis of PDAC remains challenging due to the lack of specific biomarkers. A transcription factor essential for pancreatic development named HNF-1B can be a potential biomarker for PDAC. However, HNF-1B was not entirely specific for PDAC and can be expressed in cancers of Müllerian tract, kidney, lung, bladder and prostate. To solve this issue, we investigated the expression of a panel of well-established lineage-specific biomarkers for non-pancreatic origins, including TTF1 and Napsin A for lung, RCC for kidney, ER and PR for breast, NKX3.1 for prostate, PAX8 for Müllerian tract, GATA3 for breast and bladder, and keratin CK7 and CK20 in 149 PDACs, using immunohistochemistry and tissue microarray. A two-tier scoring system for HNF-1B expression in tumor cells was used. Chi-square and Fisher's exact tests were performed using SAS software version 9.4 to test the association between HNF-1B expression and tumor morphology and differentiation. The results showed that PAX8 was focally positive in 6 cases (4.0%). GATA3 was focally positive in 5 cases (3.4%). Napsin A was all negative except for 1 case with focal weak staining. All other lineage-specific markers such as TTF1, RCC, ER, PR and NKX3.1 were completely negative in all PDACs. Consistent with our previous result, the majority of PDACs (88.6%) was positive for HNF-1B, including 78 cases (59.1%) with "strong" and 54 cases (40.9%) with "weak" staining pattern. There was no significant association between HNF-1B expression and cytoplasmic clearing morphology. Addition of keratins may further aid the diagnosis of PDAC since the majority of PDACs (84.6%) was CK7+/CK20-, only a minority of PDACs (11.4%) was CK7+/CK20+, 2.7% were CK-/CK20-, and 1.3% were CK7-/CK20+. In conclusion, HNF-1B can serve as a useful biomarker to aid the diagnosis of PDAC when combined with other lineage-specific biomarkers to exclude the other origins.

Hepatocyte nuclear factor 1 beta: A perspective in cancer

Hepatocyte nuclear factor 1 beta (HNF1 β/B) exists as a homeobox transcription factor having a vital role in the embryonic development of organs mainly liver, kidney and pancreas. Initially described as a gene causing maturity‐onset diabetes of the young (MODY), HNF1β expression deregulation and single nucleotide polymorphisms in HNF1β have now been associated with several tumours including endometrial, prostate, ovarian, hepatocellular, renal and colorectal cancers. Its function has been studied either as homodimer or heterodimer with HNF1α. In this review, the role of HNF1B in different cancers will be discussed along with the role of its splice variants, and its emerging role as a potential biomarker in cancer.

High Expression of COL17A1 Predicts Poor Prognosis and Promotes the Tumor Progression via NF-κB Pathway in Pancreatic Adenocarcinoma

COL17A1 (collagen type XVII alpha 1 chain) is known to be upregulated and has a prognostic role in many malignancies, as well as contributing to cell proliferation, apoptosis, and invasion. However, little knowledge is available on the expression and prognostic value of COL17A1 in pancreatic adenocarcinoma (PDAC). In our study, we searched the public database and found that mRNA and protein levels of COL17A1 are commonly upregulated in PDAC tissues. The immunohistochemical analysis conducted by us revealed enhanced expression of COL17A1 protein in 169 PDAC samples compared with that in 67 adjacent normal tissues. We also observed a significantly positive correlation between COL17A1 expression and lymph node metastasis (p < 0.0001), TNM clinical stage (p < 0.0001), and pathology differentiation (p < 0.01). The KM-plot results indicated that PDAC patients with a high COL17A1 expression have a poorer overall survival (p < 0.001) than those with a low COL17A1 expression. The result of the Cox regression analysis of multivariate data suggested COL17A1 is an independent prognostic indicator of PDAC patients' overall survival. CCK-8, wound healing, and transwell assays suggested that COL17A1 knockdown markedly inhibited tumor proliferation and invasion in PDAC cells, and cells with COL17A1 overexpression had a prominently higher proliferative and invasive capacity. Knockdown of COL17A1 significantly upregulated the apoptosis rate. We deduce that upregulated COL17A1 activated the NF-κB pathway in PDAC cells. In summary, our studies showed the prognostic value of COL17A1 in PDAC and that COL17A1 may act as a molecular therapeutic target for PDAC treatment.

Identifying MMP14 and COL12A1 as a potential combination of prognostic biomarkers in pancreatic ductal adenocarcinoma using integrated bioinformatics analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant neoplasm. It is necessary to improve the understanding of the underlying molecular mechanisms and identify the key genes and signaling pathways involved in PDAC.

Methods

The microarray datasets GSE28735, GSE62165, and GSE91035 were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis, including protein-protein interaction (PPI) network, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The PPI network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. GO functional annotation and KEGG pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Hub genes were validated via the Gene Expression Profiling Interactive Analysis tool (GEPIA) and the Human Protein Atlas (HPA) website.

Results

A total of 263 DEGs (167 upregulated and 96 downregulated) were common to the three datasets. We used STRING and Cytoscape software to establish the PPI network and then identified key modules. From the PPI network, 225 nodes and 803 edges were selected. The most significant module, which comprised 11 DEGs, was identified using the Molecular Complex Detection plugin. The top 20 hub genes, which were filtered by the CytoHubba plugin, comprised FN1, COL1A1, COL3A1, BGN, POSTN, FBN1, COL5A2, COL12A1, THBS2, COL6A3, VCAN, CDH11, MMP14, LTBP1, IGFBP5, ALB, CXCL12, FAP, MATN3, and COL8A1. These genes were validated using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, and the encoded proteins were subsequently validated using the HPA website. The GO analysis results showed that the most significantly enriched biological process, cellular component, and molecular function terms among the 20 hub genes were cell adhesion, proteinaceous extracellular matrix, and calcium ion binding, respectively. The KEGG pathway analysis showed that the 20 hub genes were mainly enriched in ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and protein digestion and absorption. These findings indicated that FBN1 and COL8A1 appear to be involved in the progression of PDAC. Moreover, patient survival analysis performed via the GEPIA using TCGA and GTEx databases demonstrated that the expression levels of COL12A1 and MMP14 were correlated with a poor prognosis in PDAC patients (p < 0.05).

Conclusions

The results demonstrated that upregulation of MMP14 and COL12A1 is associated with poor overall survival, and these might be a combination of prognostic biomarkers in PDAC.

Autophagy Regulatory Genes MET and RIPK2 Play a Prognostic Role in Pancreatic Ductal Adenocarcinoma: A Bioinformatic Analysis Based on GEO and TCGA

Pancreatic ductal adenocarcinoma is a common malignant tumor with a poor prognosis. Autophagy activity changes in both cancer cells and microenvironment and affects the progression of pancreatic ductal adenocarcinoma. The purpose of this study was to predict the prognostic autophagy regulatory genes and their role in the regulation of autophagy in pancreatic ductal adenocarcinoma. We draw conclusions based on gene expression data from different platforms: GSE62165 and GSE85916 from the array platform, TCGA from the bulk RNA-seq platform, and GSE111672 from the single-cell RNA-seq platform. At first, we detected differentially expressed genes in pancreatic ductal adenocarcinoma compared with normal pancreatic tissue based on GSE62165. Then, we screened prognostic genes based on GSE85916 and TCGA. Furthermore, we constructed a risk signature composed of the prognostic differentially expressed genes. Finally, we predicted the probable role of these genes in regulating autophagy and the types of cell expressing these genes. According to our screening criteria, there were only two genes: MET and RIPK2, selected into the development of the risk signature. However, evaluated by log-rank tests, receiver operating characteristic curves, and calibration curves, the risk signature was worth considering its clinical application because of good sensitivity, specificity, and stability. Besides, we predicted that both MET and RIPK2 promote autophagy in pancreatic ductal adenocarcinoma by gene set enrichment analysis. Analysis of single-cell RNA-seq data from GSE111672 revealed that both MET and RIPK2 were expressed in cancer cells while RIPK2 was also expressed in monocytes and neutrophils. After comprehensive analysis, we found that both MET and RIPK2 are related to the prognosis of pancreatic ductal adenocarcinoma and provided some associated clues for clinical application and basic experiment research.

Identification of Spindle and Kinetochore-Associated Family Genes as Therapeutic Targets and Prognostic Biomarkers in Pancreas Ductal Adenocarcinoma Microenvironment

Aim

The role of spindle and kinetochore-associated (SKA) genes in tumorigenesis and cancer progression has been widely studied. However, so far, the oncogenic involvement of SKA family genes in pancreatic cancer and their prognostic potential remain unknown.

Methods

Here, we carried out a meta-analysis of the differential expression of SKA genes in normal and tumor tissue. Univariate and multivariate survival analyses were done to evaluate the correlation between SKA family gene expression and pancreas ductal adenocarcinoma (PDAC) prognosis. Joint-effect and stratified survival analysis as well as nomogram analysis were used to estimate the prognostic value of genes. The underlying regulatory and biological mechanisms were identified by Gene set enrichment analysis. Interaction between SKA prognosis-related genes and immune cell infiltration was assessed using the Tumor Immune Estimation Resource tool.

Results

We find that SKA1-3 are highly expressed in PDAC tissues relative to non-cancer tissues. Survival analysis revealed that high expression of SKA1 and SKA3 independently indicate poor prognosis but they are not associated with relapse-free survival. The prognostic value of SKA1 and SKA3 was further confirmed by the nomogram, joint-effect, and stratified survival analysis. Analysis of underlying mechanisms reveals that these genes influence cancer-related signaling pathways, kinases, miRNA, and E2F family genes. Notably, prognosis-related genes are inversely correlated with several immune cells infiltrating levels.

Conclusion

We find that SKA1 and SKA3 expression correlates with prognosis and immune cell infiltration in PDAC, highlighting their potential as pancreatic cancer prognostic biomarkers.