Genes In Pancreatic Ductal Adenocarcinoma Research Articles

Extrahepatic Distal Cholangiocarcinoma vs. Pancreatic Ductal Adenocarcinoma: Histology and Molecular Profiling for Differential Diagnosis and Treatment.

Pancreatic ductal adenocarcinoma (PDAC) and distal cholangiocarcinoma (dCCA) are very aggressive tumors with a high mortality rate. Pancreas and distal bile ducts share a common embryonic development. Hence, PDAC and dCCA exhibit similar histological features that make a differential diagnosis during routine diagnostic practice challenging. However, there are also significant differences, with potential clinical implications. Even if PDAC and dCCA are generally associated with poor survival, patients with dCCA seem to present a better prognosis. Moreover, although precision oncology-based approaches are still limited in both entities, their most important targets are different and include alterations affecting BRCA1/2 and related genes in PDAC, as well as HER2 amplification in dCCA. Along this line, microsatellite instability represents a potential contact point in terms of tailored treatments, but its prevalence is very low in both tumor types. This review aims at defining the most important similarities and differences in terms of clinicopathological and molecular features between these two entities, also discussing the main theranostic implications derived from this challenging differential diagnosis.

Screening of potential pain genes in pancreatic ductal adenocarcinoma (PDAC) based on bioinformatics methods.

We aimed to identify cancer pain genes in pancreatic ductal adenocarcinoma (PDAC) using bioinformatic tools to provide evidence for pain treatment in PDAC patients. The GSE50570 data were obtained from the high-throughput Gene Expression Omnibus (GEO) database and subsequently analyzed. A volcano map, principal component analysis (PCA) map, box plot, and heat map were drawn, and a Venn diagram was constructed by comparison with human secreted histone genes. The differentially expressed secreted histone genes in PDAC were obtained. Then, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, followed by protein-protein interaction (PPI) network analysis and key genetic screening. In comparison to normal samples, the expression of 81 secreted protein-related genes was downregulated, and the expression of 12 secreted protein-related genes was upregulated in PDAC. According to the GO and KEGG enrichment analysis results, these differentially expressed genes are mainly involved in the PI3K-Akt signaling pathway, protein digestion and absorption, extracellular matrix (ECM) receptor interaction, AGE-RAGE (advanced glycation endproducts-the Receptor of Advanced Glycation Endproducts) signaling pathway, relaxin signaling pathway, interleukin-17 (IL-17) signaling pathway, and transforming growth factor-β (TGF-β) signaling pathway, affecting the different manifestations of PDAC cancer pain. We used Cytoscape software to construct a protein interaction network of common differentially expressed genes and obtained three clusters with high scores. Our literature review found that several genes, including PTGS2, VCAN, and CCL2, were directly related to cancer pain occurrence. By data mining the PDAC tumor expression, dozens of differentially expressed genes were identified in this study, several of which have been associated with the frequency and severity of cancer pain. This study provides an important foundation for the pain treatment of PDAC tumor patients.

Development of a basement membrane gene signature and identification of the potential candidate therapeutic targets for pancreatic cancer.

Pancreatic cancer is a deadly cancer with a poor prognosis. In light of mounting evidence that basement membrane genes (BMGs) play a role in the development of cancer, we sought to examine the prognostic importance and role of BMGs in pancreatic ductal adenocarcinoma (PDAC) patients. BMGs were obtained from previous top research studies. The clinical and messenger ribonucleic acid expression data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets, respectively. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used for the PDAC risk modeling and gene identification. The Kaplan-Meier method was used to compare outcomes between the low- and high-risk groups. Finally, we analyzed small-molecule drugs that could be used to target BMGs for treatment using the Enrichr data set and validated the function of the tubulointerstitial nephritis antigen (TINAG) in pancreatic cancer. We successfully constructed and validated a 7 BMG-based model to predict PDAC patient outcomes. Additionally, we discovered that 7 BMG-based model was an independent predictive factor for PDAC. According to our functional analysis, the majority of the signaling pathways enriched in BMGs were those connected to malignancy. Immune cell infiltration and immunological checkpoints were also linked to the BMG-based model. Further, we identified 5 small-molecule drugs that may be useful in treating PDAC patients. We also found that TINAG promoted cell proliferation in pancreatic cancer. Our study extended understandings of how BMGs work in PDAC. We identified a credible predictive biomarker for PDAC patients' survival.

Abstract B030: The quadruplex-binding compound QN-302 targets the S100P gene in PDAC

Abstract The compound QN-302, a tetra-substituted naphthalene diimide derivative has been previously disclosed to have single-digit nM anti-proliferative activity in a panel of human pancreatic ductal adenocarcinoma (PDAC) cell lines (Ahmed et al., ACS Med Chem Lett, 2020, 11, 1634-1644). It also has significant anti-tumor activity in the MIA-PACA2 xenograft model for PDAC as well as in the more demanding KPC model. Its novel mode of action involves the targeting of quadruplex (G4)-forming motifs in promoter regions of cancer-associated genes, where their prevalence is over-represented compared to other genes. The presence of a promoter G4 motif, stabilized by a ligand, presents an effective block to transcription. Transcriptome analyses of QN-302 in MIA-PACA2 cells has validated this concept, with the disclosure of a pattern of down-regulated genes involved in cancer-associated pathways and carrying G4 motifs in their promoters. We have also previously shown using RT-PCR and Western blots that a sub-set of these genes and their gene products are down-regulated in the MIA-PACA2 xenograft model following QN-302 treatment. We have now examined cellular changes in the expression of the 229 gene set associated with PDAC and compared these with data from cells and xenografts treated with QN-302. We find that expression of the key gene S100P, a prominent and well-authenticated marker of PDAC disease and progression, is highly down-regulated in QN-302 treated cells. The S100P gene contains 31 putative G4 motifs, including a classic G4 site in the S100P promoter, just upstream of the transcription start site. Transcriptome analyses have also been performed on tumor material from human patients, comprising a panel of poorly differentiated as well as more highly differentiated tumors, and has been compared with normal pancreas expression data. The S100P gene is statistically significantly highly over-expressed (especially in the poorly differentiated tumors), giving added confidence to the concept that the S100P gene is a therapeutic target and may also be useful as a marker of QN-302 response in future clinical use. We also find that the anti-tumor effect of QN-302 treatment in PDAC xenografts results in a high level of apoptosis, which is consistent with earlier reports that S100P in tumors binds to and suppresses p53 activity. The suppression of S100P transcription by QN-302 would thus be expected to remove this roadblock to apoptosis and cell death, in accordance with our observations. QN-302 is bio-available at therapeutic doses and is well tolerated at these levels in these animal models. It is being developed for clinical evaluation by Qualigen Therapeutics Inc and is currently at the pre-IND stage. Citation Format: Ahmed Ahmed, William Greenhalf, Tariq Arshad, Stephen S. Neidle. The quadruplex-binding compound QN-302 targets the S100P gene in PDAC [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B030.

Abstract B017: MICAL2 promotes pancreatic cancer growth and metastasis independent of MRTF-A signaling

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer in large part due to its propensity for early metastasis. We used ChIP-seq to identify differentially tagged super-enhancer associated genes in PDAC and identified MICAL2 as a gene of interest. MICAL (molecule interacting with CasL) proteins are flavin monooyxgenases that induce actin depolymerization. MICAL2 canonically modulates nuclear actin to regulate SRF/MRTF-A (myocardin related transcription factor) mediated transcription to drive EMT (epithelial-mesenchymal transition) and fibrosis. In this study, we sought to determine the impact of MICAL2 on PDAC progression and its dependence on SRF/MRTF-A signaling. Methods: Studies were performed in human and murine PDAC models. MICAL2 and MRTF-A were knocked down with shRNA and gene expression quantitated with qPCR. In vitro cell viability was assessed by MTT colorimetric assay. Cell migration was tested with in vitro wound scratch assays. Cell cycle analysis was done with flow cytometry-based DNA content measurement. Subcutaneous, orthotopic, and intrasplenic injections of PDAC cells were performed to assess in vivo growth and metastasis. Protein expression was measured with Western blotting. Student’s t-test was used to confirm statistical significance of experimental results. Results: In human PDAC cell lines, MICAL2 knockdown decreased cell viability, reduced cell migration and wound healing, and induced cell cycle arrest at G0/G1. MICAL2 inhibition was associated with decreased p-AKT, c-Myc, and increased p27 by Western blot. Orthotopic and subcutaneous injections of KPC46 shMICAL2 cells were performed in syngeneic mice; orthotopic injections of shMICAL2 cells led to decreased tumor growth compared to control (0.26 gm vs. 1 gm, p = 0.008), not observed with shMRTF-A (1.032 gm vs. 1 gm, p = 0.95). Subcutaneous injections of MICAL2 knockdown cells led to no tumor growth; injections of MRTF-A knockdown cells again led to comparable tumor growth as control (3.02 gm vs. 1.72 gm, p = 0.24). GSEA (Gene Set Enrichment Analysis) of RNAseq data demonstrated a correlation between MICAL2 knockdown and downregulation of Hallmark EMT pathways. Intrasplenic injection studies in syngeneic mice revealed grossly decreased liver metastases after intrasplenic injection of shMRTF-A cells, with total abrogation of metastases after injection of shMICAL2 cells. Conclusions: MICAL2 promotes pancreatic cancer cell growth and metastasis. While MICAL2’s effect on metastasis appears largely dependent on SRF/MRTF-A, tumor growth appears to be MRTF-A independent, suggesting putative novel functions of MICAL2. Given its potentially targetable enzymatic domain and important role in promoting cell growth in vitro and tumor progression and metastasis in vivo, MICAL2 holds promise as a novel tractable therapeutic target in pancreatic cancer. Citation Format: Sohini Khan, Shweta Sharma, Divya Sood, Bharti Garg, Dawn Jaquish, Evangeline Mose, Edgar Esparza, Herve Tiriac, Andrew M. Lowy. MICAL2 promotes pancreatic cancer growth and metastasis independent of MRTF-A signaling [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B017.

Identification of a novel target of SETD1A histone methyltransferase and the clinical significance in pancreaticcancer.

Although histone H3K4 methyltransferase SETD1A is overexpressed in various cancer types, the molecular mechanism underlying its overexpression and its target genes in pancreatic ductal adenocarcinoma (PDAC) remain unclarified. We conducted immunohistochemical staining for SETD1A in 105 human PDAC specimens to assess the relationship between SETD1A overexpression and clinicopathological features. The function and target genes of SETD1A were investigated using human pancreatic cancer cell lines. SETD1A expression was upregulated in 51.4% of patients with PDAC and was an independent prognostic factor associated with shorter disease-free survival after resection (p< 0.05). Knockdown and overexpression of SETD1A showed that SETD1A plays a crucial role in increasing the proliferation and motility of PDAC cells. SETD1A overexpression increased tumorigenicity. RNA sequencing of SETD1A-knockdown cells revealed downregulation of RUVBL1, an oncogenic protein ATP-dependent DNA helicase gene. ChIP analysis revealed that SETD1A binds to the RUVBL1 promoter region, resulting in increased H3K4me3 levels. Knockdown of RUVBL1 showed inhibition of cell proliferation, migration, and invasion of PDAC cells, which are similar biological effects to SETD1A knockdown. High expression of both SETD1A and RUVBL1 was an independent prognostic factor not only for disease-free survival but also for overall survival (p< 0.05). In conclusion, we identified RUVBL1 as a novel downstream target gene of the SETD1A-H3K4me3 pathway. Co-expression of SETD1A and RUVBL1 is an important factor for predicting the prognosis of patients with PDAC.

Wild‑type KRAS inhibits the migration and invasion of pancreatic cancer through the Wnt/β‑catenin pathway

Kirsten rat sarcoma virus (KRAS) mutation is considered to be the event that leads to the initiation of pancreatic ductal adenocarcinoma (PDAC), the mutation frequency of the KRAS gene in PDAC is 90‑95%. Studies have shown that wild‑type KRAS (KRASWT) has a survival advantage in PDAC and can antagonize the effect of mutated KRAS G12D (KRASG12D), leading to a low cell transformation efficiency. The present study focused on the differences in biological behavior between KRASWT and KRASG12D and explored the mechanism in pancreatic cancer. Overexpressed KRASWT and KRASG12D was transfected into cells through lentiviral transfection. The differences and mechanisms were explored using cell counting kit‑8 (CCK‑8), clone formation, wound healing and Transwell assays, as well as western blotting, immunohistochemistry and tumor formation in nude mice. Invitro, the proliferation of KRASWT group was reduced compared with PANC‑1 group, while the proliferation of KRASG12D group was not significantly changed. Invivo, the proliferation of KRASWT group was reduced and that of KRASG12D group was enhanced compared with that in the PANC‑1 group. The invasion and migration of KRASWT group were decreased, while the invasion and migration of KRASG12D group were increased. Western blotting showed that the expression of E‑cadherin, α‑E‑catenin, MMP‑3, MMP‑9, STAT3 and phosphorylated STAT3 in KRASWT group was increased, while no significant difference was observed in KRASG12D group. The results of immunohistochemistry were consistent with those of western blotting. KRASWT group can inhibit the proliferation of pancreatic cancer invitro and invivo, while KRASG12D group can significantly promote proliferation invivo, but not significantly invitro. Wild‑type KRAS may inhibit the invasion and migration of pancreatic cancer through the Wnt/β‑catenin pathway.

A novel refined pyroptosis and inflammasome-related genes signature for predicting prognosis and immune microenvironment in pancreatic ductal adenocarcinoma

Pyroptosis is an inflammatory form of cell death, which plays a key role in the development of auto-inflammation and cancer. This study aimed to construct a pyroptosis and inflammasome-related genes for predicting prognosis of the pancreatic ductal adenocarcinoma (PDAC). This study was based primarily on the one-way analysis of variance, univariate Cox regression analysis, Least absolute shrinkage and selection operator (LASSO) Cox regression, a risk-prognostic signature, gene set variation analysis (GSVA), and immune microenvironment analysis, using PDAC data from The Cancer Genome Atlas and International Cancer Genome Consortium databases for the analysis of the role of 676 pyroptosis and inflammasome-related genes in PDAC retrieved from the Reactome and GeneCards databases. Lastly, we collected six paired PDAC and matched normal adjacent tissue samples to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR). We identified 18 candidate pyroptosis and inflammasome-related genes that differed significantly between pathologic grades (stages) of PDAC patients. The univariate Cox and LASSO analyses pointed to six genes as the best variables for constructing a prognostic signature, including ACTA2, C1QTNF9, DNAH8, GATM, LBP, and NGF. The results of the risk prognostic model indicated that the AUCs at 1, 3, and 5 years were greater than 0.62. GSVA revealed that ‘GLYCOLYSIS’, ‘P53 PATHWAY’, ‘KRAS SIGNALING UP’, and ‘INFLAMMATORY RESPONSE’ hallmark gene sets were associated with the risk score. The high-risk group was associated with poor prognosis and was characterized by a lower infiltration of cells involved in anti-tumor immunity; whereas the low-risk group with higher T cells, NK cells, and macrophages showed relatively better survival and significantly higher upregulation of cytolytic scores and inflammation scores. Additionally, crucial pyroptosis and inflammasome-related genes were further validated by qRT-PCR. Our study revealed the prognostic role of the pyroptosis and inflammasome-related genes in PDAC for the first time. Simultaneously, the biological and prognostic heterogeneity of PDAC had been demonstrated, deepening our molecular understanding of this tumor.

KDM6A Loss Recruits Tumor-Associated Neutrophils and Promotes Neutrophil Extracellular Trap Formation in Pancreatic Cancer.

KDM6A loss in pancreatic cancer cells alters the immune microenvironment by increasing CXCL1 secretion and neutrophil recruitment, providing a rationale for targeting the CXCL1-CXCR2 signaling axis in tumors with low KDM6A.

Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer.

Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles.

Integrated analysis of senescence-associated genes in pancreatic ductal adenocarcinoma.

Background: Cellular senescence plays a critical role in the occurrence and development, and immune modulation of cancer. This research primarily investigated the role of senescence-associated genes (SAGs) in the survival and tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC). Methods: From the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, the gene expression profiles and clinical data of PDAC samples were downloaded. SAGs in the TCGA cohort were used to build a novel prognostic model and validated in the ICGC cohort. The relationship of signature with the immune landscape, tumor mutational burden (TMB), as well as the sensitivity of different therapies, was explored. Moreover, a nomogram was developed to predict the overall survival of PDAC patients. Results: A prognostic signature was constructed on basis of three SAGs, and patients in the low-risk score group had a longer survival time. The accuracy of the signature to distinguish different score groups was confirmed through principal component analysis (PCA) and the Receiver operator curves curve. The mRNA expression of the three signature genes was also verified in normal pancreatic and PDAC cell lines by RT-qPCR. The signature could independently predict the prognosis of PDAC patients and had broad applicability. Meanwhile, the nomogram predicted that 1- and 3-years survival rates were in good agreement with the observed overall survival rates. Low-risk patients had lower tumor mutational burden, and low-TMB patients had a better prognosis. Low- and high-risk patients exhibit distinct immune cell infiltration and immune checkpoint changes. By further analyzing the risk score, patients in the low-risk group were more responsive to immunotherapy and a variety of commonly used chemotherapeutic drugs. Conclusion: The prognostic signature can well predict the prognosis and assess the possibility of immunotherapy in personalized PDAC treatment.

Abstract 6142: Gain-of-function p53R172H mutation drives accumulation of neutrophils in the pancreatic tumor microenvironment promoting resistance to immunotherapy

Abstract The immune microenvironment plays a critical role in cancer development, progression and resistance to therapy. Specific tumor genotypes can profoundly influence the composition of the immune microenvironment. After oncogenic KRAS, TP53 is the most frequently mutated gene in pancreatic ductal adenocarcinoma (PDAC). KRASG12D mutations in tumor cells are known to modify the immune landscape of PDAC, however the immune effects of neomorphic TP53 mutations have not been defined. Focusing on the most common neomorphic TP53 mutation in human PDAC, we sought to evaluate the non-cell-autonomous role of gain-of-function mutant Trp53R172H in modulating the immune microenvironment of pancreatic tumors by using KrasG12D-mutated mouse pancreatic ductal epithelial cells (PDEC) genetically engineered to express the Trp53R172H gain-of-function. Orthotopically implanted tumors derived from CRISPR-generated KrasG12D/+;Trp53R172H/+ PDEC had a distinct immune profile in comparison to KrasG12D/+;Trp53+/+ tumors, characterized by an influx of intratumoral CD11b+Ly6G+ neutrophils and concomitant decreases in CD3+ T cells, CD8+ T cells, and CD4+ T helper 1 (Th1) cells. Analysis of publicly available human PDAC cohorts revealed enrichment of genes in neutrophil-related pathways in TP53-mutated tumors. Knockdown of CXCL2, a neutrophil chemoattractant, in the tumor epithelial compartment of CRISPR KrasG12D/+;Trp53R172H/+ PDEC tumors reversed the neutrophil phenotype. Depleting neutrophils in mice bearing CRISPR KrasG12D/+;Trp53R172H/+ PDEC tumors augmented sensitivity to combined CD40 immunotherapy and chemotherapy. Collectively, these data link gain-of-function mutant Trp53R172H to the presence of intratumoral neutrophils in pancreatic cancer and suggests that tumor genotypes could inform patient selection for immunotherapy. Citation Format: Despina Siolas, Emily Vucic, Emma Kurz, Cristina Hajdu, Dafna Bar-Sagi. Gain-of-function p53R172H mutation drives accumulation of neutrophils in the pancreatic tumor microenvironment promoting resistance to immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6142.

Abstract 2522: Pathway and immune profile analysis of cyst-derived versus PanIN-derived pancreatic ductal adenocarcinomas

Abstract Introduction: Pancreatic cystic lesions (PCL) are common and a subset of mucinous cysts will transform into pancreatic ductal adenocarcinoma (PDAC). However, predicting which of these mucinous PCL may progress to PDAC and warrant surgery remains a clinical challenge. Moreover, identifying those clinically emergent mucinous PCL for which a surveillance approach is best is a dire clinical need. Therefore, we aimed to identify molecular signatures that distinguished between PDAC with and without clinical evidence of a PCL to identify novel biomarkers. Methods: We leveraged data from the Oncology Research Information Exchange Network (ORIEN) multi-institute sequencing project and analyzed 66 PDAC cases recruited to ORIEN from The Ohio State University Wexner Medical Center and Moffitt Cancer Center for which tumor whole transcriptome sequencing datasets were generated. We separated the cases based on whether a tumor had originated from a cystic lesion (n=16) or presumably through the pancreatic intraepithelial neoplasia (PanIN) pathway (n=50). We then performed differential expression and pathway analysis using both Gene-Set Enrichment Analysis (GSEA) and Pathway Analysis with Down-weighted Genes (PADOG) algorithms. Based on the emerging importance of the immune landscape in PDAC development, we also analyzed immune profiles using a novel tool, Tumor-immune Microenvironment Deconvolution Web-portal for Bulk Transcriptomics (TIMEx). Results: When grouped by tumor origin, cyst-derived PDAC gene expression sets are enriched in immune signaling pathways, specifically NOTCH signaling (p=0.04), and demonstrate significant downregulation in amino acid metabolism, mitochondrial import and Gsα signaling pathways. Furthermore, GSEA based on TIMEx signatures indicated that multiple immune cell-specific profiles had significant enrichment scores in either the cyst-derived (for example, plasma cell: normalized enrichment score=-1.53; p=0.007) or non-cyst-derived (for example, neutrophil: normalized enrichment score=2.24; p=0.0001) PDAC cohorts. Conclusions: Our data suggest that cyst-derived and non-cyst-derived PDACs differ by immune profile, enhanced NOTCH pathway usage and in the metabolic processing of multiple amino acids. These initial findings support future studies to assess the accuracy of risk stratifying PCLs based on their amino acid, metabolic, or immune profiles, and exploration into mechanisms to explain these findings. Citation Format: Margaret A. Park, Somashekar G. Krishna, Maria C. Genilo-Delgado, Kristyn Gumpper-Fedus, Darwin L. Conwell, Phil A. Hart, Mary E. Dillhoff, Maria F. Gomez, Toni L. Basinski, Aamir N. Dam, Jason B. Klapman, Jason B. Fleming, Mokenge Malafa, Amir Mohammadi, Barbara A. Centeno, Kun Jiang, Daniel Jeong, Dung-Tsa Chen, Mengyu Xie, Aik Choon Tan, Brooke L. Fridley, Jamie K. Teer, Zobeida Cruz-Monserrate, Jennifer B. Permuth. Pathway and immune profile analysis of cyst-derived versus PanIN-derived pancreatic ductal adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2522.

The identification of liver metastasis- and prognosis-associated genes in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is an often fatal malignancy with an extremely low survival rate. Liver metastasis, which causes high mortality, is the most common recurring metastasis for PDAC. However, the mechanisms underlying this liver metastasis and associated candidate biomarkers are unknown.MethodsWe performed mRNA profiling comparisons in 8 primary tumors (T) and 12 liver metastases (M) samples using the Gene Expression Omnibus (GEO) database. After determining differentially expressed genes (DEG), gene ontology (GO), pathway enrichment and protein–protein interaction (PPI) network analyses were performed to determine DEG functions. Then, Cytoscape was used to screen out significant hub genes, after which their clinical relevance was investigated using The Cancer Genome Atlas (TCGA) resources. Furthermore, prognosis-associated gene expression was validated using Oncomine and TCGA database. Lastly, associations between prognosis-associated genes, immune cells and immunological checkpoint genes were evaluated using the Tumor Immune Estimation Resource (TIMER).ResultsIn total, 102 genes were related to liver metastasis and predominantly involved in cell migration, motility, and adhesion. Using Cytoscape, this number was narrowed down to 16 hub genes. Elevated mRNA expression levels for two of these genes, SPARC (P = 0.019) and TPM1 (P = 0.037) were significantly correlated with poor disease prognosis. For the remaining 14, expression was not related to overall patient survival. SPARC had higher expression in patients with metastatic PDAC than those with non-metastatic PDAC in TCGA dataset. SPARC and TPM1 levels were also positively correlated with the immune infiltration of specific cell types. Additionally, both genes exhibited strong co-expression associations with immune checkpoint genes.ConclusionsCombined, we suggest SPARC has high potential as biomarker to predict liver metastasis during PDAC. Additionally, both SPARC and TPM1 appeared to recruit and regulate immune-infiltrating cells during these pathophysiological processes.

ADAMTS12 promotes migration and epithelial-mesenchymal transition and predicts poor prognosis for pancreatic cancer

BackgroundADAMTS (a disintegrin and metalloproteinase with thrombospondin-like motifs) family, a group of extracellular multifunctional enzymes, has been proven to play a pivotal role in the tumor. In pancreatic cancer, the role and mechanism of this family remain unclear. The present study aimed to figure out the hub gene of ADAMTSs and explore the exact roles in the prognosis and biological functions in pancreatic ductal adenocarcinoma (PDAC). MethodsWe used several databases to analyze the ADAMTS family and then screen out the hub genes. The expression of ADAMTS12 in 106 pairs of PDAC tumors and adjacent normal tissues was examined by immunohistochemistry, and its correlations with clinical parameters were further analyzed. The impacts of ADAMTS12 on the migration of PDAC cells were predicted by gene set enrichment analysis and confirmed by transwell assays. The potential impacts of ADAMTS12 on the epithelial-mesenchymal transition (EMT) were identified by database analysis and experimental proof of real-time quantitative polymerase chain reaction (qPCR) and Western blotting. ResultsOur study found that ADAMTS12 was a crucial gene in PDAC, and it was highly expressed in tumor tissues when compared to that in the adjacent tissues. ADATMS12 had predictive value of a poor prognosis for PDAC. The elevation of ADAMTS12 was parallel to the progression of PDAC. Inhibition of ADAMTS12 suppressed the migration of PDAC cells and interfered with the process of EMT. ConclusionsADAMTS12 is a crucial member of ADAMTSs in PDAC and a predictor of poor prognosis. Additionally, based on its impacts on migration and metastasis in PDAC and the relationship with EMT, ADAMTS12 plays a role of an oncogene in PDAC and may be a promising target for treatment.

RELA-induced MiR-21 Exerts Oncogenic Effects on PDAC via Targeting of ARHGAP24.

Inflammation is one of the inducing factors of pancreatic ductal adenocarcinoma (PDAC), and microRNAs have been confirmed to be involved in the occurrence and development of PDAC. However, whether RELA, an inflammatory regulator, is involved in the regulation of PDAC by miRNA remains to be further studied. In the present study miR-21 was characterized and its upstream regulatory mechanism was investigated, as well as its functional effects and target genes in pancreatic ductal adenocarcinoma (PDAC). In situ hybridization analysis confirmed increased miR-21 expression levels in PDAC tissues. The results of the chromatin immunoprecipitation and dual-luciferase reporter assays demonstrated that transcription factor RELA modulated miR-21 transcription in the PDAC, PANC-1 and MIA PaCa-2 cell lines. Subsequently, a cell viability assay, EdU staining assay and flow cytometry analysis, demonstrated that miR-21 promoted cell proliferation and cell cycle progression, but inhibited cell apoptosis in vitro. Furthermore, a xenograft assay demonstrated that miR-21 accelerated tumor growth in vivo. Mechanistically, miR-21 directly regulated the expression of Rho GTPase activating protein 24 (ARHGAP24), which was indicated to be a tumor suppressor gene. Moreover, both miR-21 and ARHGAP24 were strongly associated with clinical features and may therefore serve as valuable biomarkers in PDAC prognosis.

Comprehensive analysis reveals an arachidonic acid metabolism-related gene signature in patients with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is highly heterogeneous, making its prognosis prediction difficult. The arachidonic acid (AA) cascade is involved in carcinogenesis. Therefore, the metabolic enzymes of the AA cascade consist of lipoxygenases (LOXs), phospholipase A2s (PLA2s), and cyclooxygenases (COXs) along with their metabolic products, including leukotrienes. Nevertheless, the prognostic potential of AA metabolism-associated PDAC has not been explored. Herein, the mRNA expression patterns and the matching clinical information of individuals with PDAC were abstracted from online data resources. We employed the LASSO Cox regression model to develop a multigene clinical signature in the TCGA queue. The GEO queue and the ICGC queue were employed as the validation queue. There was differential expression of a significant number of AA metabolism-associated genes (56.8%) between PDAC and neighboring nonmalignant tissues in the TCGA queue. Univariate Cox regression demonstrated that 13 of the differentially expressed genes (DEGs) were linked to overall survival (OS) (p < 0.05). A 6-gene clinical signature was developed for stratifying the PDAC patients into two risk groups, with the high-risk group patients exhibiting remarkably lower OS than the low-risk group patients (p < 0.001 in the TCGA data set and the ICGC queue, and p = 0.001 in the GEO data set). The multivariate Cox data revealed the risk score as an independent OS predictor (HR > 1, p < 0.01). The receiver operating characteristic (ROC) curve verified the predictive potential of our signature. The expression and alteration of the six genes in PDAC were also validated using online databases. Functional analyses demonstrated that immune-linked cascades were enriched, and the immune status was remarkably different between the high- and low-risk groups. In summary, an AA metabolism-associated clinical gene signature can be applied for prognostic estimation in PDAC.

Loss of Rnf43 Accelerates Kras-Mediated Neoplasia and Remodels the Tumor Immune Microenvironment in Pancreatic Adenocarcinoma

RNF43 is an E3 ubiquitin ligase that is recurrently mutated in pancreatic ductal adenocarcinoma (PDAC) and precursor cystic neoplasms of the pancreas. The impact of RNF43 mutations on PDAC is poorly understood and autochthonous models have not been characterized sufficiently. In this study, we describe a genetically engineered mouse model (GEMM) of PDAC with conditional expression of oncogenic Kras and deletion of the catalytic domain of Rnf43 in exocrine cells. We generated Ptf1a-Cre;LSL-KrasG12D;Rnf43flox/flox (KRC) and Ptf1a-Cre; LSL-KrasG12D (KC) mice and animal survival was assessed. KRC mice were sacrificed at 2 months, 4 months, and at moribund status followed by analysis of pancreata by single-cell RNA sequencing. Comparative analyses between moribund KRC and a moribund Kras/Tp53-driven PDAC GEMM (KPC) was performed. Cell lines were isolated from KRC and KC tumors and interrogated by cytokine array analyses, ATAC sequencing, and invitro drug assays. KRC GEMMs were also treated with an anti-CTLA4 neutralizing antibody with treatment response measured by magnetic response imaging. We demonstrate that KRC mice display a marked increase in incidence of high-grade cystic lesions of the pancreas and PDAC compared with KC. Importantly, KRC mice have a significantly decreased survival compared with KC mice. Using single-cell RNA sequencing, we demonstrated that KRC tumor progression is accompanied by a decrease in macrophages, as well as an increase in T and B lymphocytes, with evidence of increased immune checkpoint molecule expression and affinity maturation, respectively. This was in stark contrast to the tumor immune microenvironment observed in the KPC PDAC GEMM. Furthermore, expression of the chemokine CXCL5 was found to be specifically decreased in KRC cancer cells by means of epigenetic regulation and emerged as a putative candidate for mediating the unique KRC immune landscape. The KRC GEMM establishes RNF43 as a bona fide tumor suppressor gene in PDAC. This GEMM features a markedly different immune microenvironment compared with previously reported PDAC GEMMs and puts forth a rationale for an immunotherapy approach in this subset of PDAC cases.

Metabolic syndrome related gene signature predicts the prognosis of patients with pancreatic ductal carcinoma. A novel link between metabolic dysregulation and pancreatic ductal carcinoma

BackgroundPancreatic cancer is one of the most common malignancies worldwide. In recent years, specific metabolic activities, which involves the development of tumor, caused wide public concern. In this study, we wish to explore the correlation between metabolism and progression of tumor.MethodsA retrospective analysis including 95 patients with pancreatic ductal adenocarcinoma (PDAC) and PDAC patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and The Gene Expression Omnibus (GEO) database were involved in our study. Multivariate Cox regression analysis was used to construct the prognosis model. The potential connection between metabolism and immunity of PDAC was investigated through a weighted gene co-expression network analysis (WGCNA). 22 types of Tumor-infiltrating immune cells (TIICs) between high-risk and low-risk groups were estimated through CIBERSORT. Moreover, the potential immune-related signaling pathways between high-risk and low-risk groups were explored through the gene set enrichment analysis (GSEA). The role of key gene GMPS in developing pancreatic tumor was further investigated through CCK-8, colony-information, and Transwell.ResultsThe prognostic value of the MetS factors was analyzed using the Cox regression model, and a clinical MetS-based nomogram was established. Then, we established a metabolism-related signature to predict the prognosis of PDAC patients based on the TCGA databases and was validated in the ICGC database and the GEO database to find the distinct molecular mechanism of MetS genes in PDAC. The result of WGCNA showed that the blue module was associated with risk score, and genes in the blue module were found to be enriched in the immune-related signaling pathway. Furthermore, the result of CIBERSORT demonstrated that proportions of T cells CD8, T cells Regulatory, Tregs NK cells Activated, Dendritic cells Activated, and Mast cells Resting were different between high-risk and low-risk groups. These differences are potential causes of different prognoses of PDAC patients. GSEA and the protein–protein interaction network (PPI) further revealed that our metabolism-related signature was significantly enriched in immune‐related biological processes. Moreover, knockdown of GMPS in PDAC cells suppressed proliferation, migration, and invasion of tumor cells, whereas overexpression of GMPS performed oppositely.ConclusionThe results shine light on fundamental mechanisms of metabolic genes on PDAC and establish a reliable and referable signature to evaluate the prognosis of PDAC. GMPS was identified as a potential candidate oncogene with in PDAC, which can be a novel biomarker and therapeutic target for PDAC treatment.

Identification of Hub Genes in Pancreatic Ductal Adenocarcinoma Using Bioinformatics Analysis.

Background:To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis.Methods:The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation, Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by Cyto-Hubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA.Results:Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1.Conclusion:we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection.