Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features.
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ABSTRACT:
SUBMITTER: Raffenne J
PROVIDER: S-EPMC7999057 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To bridge the translational gap between recent discoveries of distinct molecular phenotypes of pancreatic cancer and tangible improvements in patient outcome, there is an urgent need to develop strategies and tools informing and improving the clinical decision process. Radiomics and machine learning approaches can offer non-invasive whole tumor analytics for clinical imaging data-based classification. The retrospective study assessed baseline computed tomography (CT) from 207 patients with proven pancreatic ductal adenocarcinoma (PDAC). Following expert level manual annotation, Pyradiomics was used for the extraction of 1474 radiomic features. The molecular tumor subtype was defined by immunohistochemical staining for KRT81 and HNF1a as quasi-mesenchymal (QM) vs. non-quasi-mesenchymal (non-QM). A Random Forest machine learning algorithm was developed to predict the molecular subtype from the radiomic features. The algorithm was then applied to an independent cohort of histopathologically unclassifiable tumors with distinct clinical outcomes. The classification algorithm achieved a sensitivity, specificity and ROC-AUC (area under the receiver operating characteristic curve) of 0.84 ± 0.05, 0.92 ± 0.01 and 0.93 ± 0.01, respectively. The median overall survival for predicted QM and non-QM tumors was 16.1 and 20.9 months, respectively, log-rank-test p = 0.02, harzard ratio (HR) 1.59. The application of the algorithm to histopathologically unclassifiable tumors revealed two groups with significantly different survival (8.9 and 39.8 months, log-rank-test p < 0.001, HR 4.33). The machine learning-based analysis of preoperative (CT) imaging allows the prediction of molecular PDAC subtypes highly relevant for patient survival, allowing advanced pre-operative patient stratification for precision medicine applications.
| S-EPMC7141256 | biostudies-literature
Project description:Pancreatic ductal adenocarcinoma (PDAC) is a malignancy characterized by a poor prognosis and high mortality rate. Genetic mutations and altered molecular pathways serve as targets in precise therapy. Using next-generation sequencing (NGS), these aberrant alterations can be identified and used to develop strategies that will selectively kill cancerous cells in patients with PDAC. The realization of targeted therapies in patients with PDAC may be summarized by three approaches. First, because oncogenes play a pivotal role in tumorigenesis, inhibition of dysregulated oncogenes is a promising method (Table 3). Numerous researchers are developing strategies to target oncogenes, such as KRAS, NRG1, and NTRK and related molecules, although most of the results are unsatisfactory. Accordingly, emerging strategies are being developed to target these oncogenes, including simultaneously inhibiting multiple molecules or pathways, modification of mutant residues by small molecules, and RNA interference. Second, researchers have attempted to reactivate inactivated tumour suppressors or modulate related molecules. TP53, CDKN2A and SMAD4 are three major tumour suppressors involved in PDAC. Advances have been achieved in clinical and preclinical trials of therapies targeting these three genes, and further investigations are warranted. The TGF-β-SMAD4 signalling pathway plays a dual role in PDAC tumorigenesis and participates in mediating tumour-stroma crosstalk and modulating the tumour microenvironment (TME); thus, molecular subtyping of pancreatic cancer according to the SMAD4 mutation status may be a promising precision oncology technique. Finally, genes such as KDM6A and BRCA have vital roles in maintaining the structural stability and physiological functions of normal chromosomes and are deficient in some patients with PDAC, thus serving as potential targets for correcting these deficiencies and precisely killing these aberrant tumour cells. Recent clinical trials, such as the POLO (Pancreas Cancer Olaparib Ongoing) trial, have reported encouraging outcomes. In addition to genetic event-guided treatment, immunotherapies such as chimeric antigen receptor T cells (CAR-T), antibody-drug conjugates, and immune checkpoint inhibitors also exhibit the potential to target tumours precisely, although the clinical value of immunotherapies as treatments for PDAC is still limited. In this review, we focus on recent preclinical and clinical advances in therapies targeting aberrant genes and pathways and predict the future trend of precision oncology for PDAC.
| S-EPMC7532113 | biostudies-literature
Project description:Pancreatic ductal adenocarcinoma
| PRJNA432344 | ENA
Project description:Pancreatic ductal adenocarcinoma (PDAC) is the most lethal malignancy known, with an extremely poor prognosis due to the lack of an efficient diagnostic scheme and no radical treatment option, except surgery. Therefore, understanding the pathophysiology of, and finding a novel biomarker to detect, PDAC should be prioritized. We observed an increase in mRNA expression of the cysteine protease inhibitor cystatin A (CSTA) in CD4+ T cells in peripheral blood cells of nine patients with PDAC, compared with the expression in seven healthy volunteers. Moreover, we confirmed significantly higher CSTA mRNA expression in a larger cohort of 41 patients with PDAC compared with that in 20 healthy volunteers. Correspondingly, the serum CSTA concentrations in 36 patients with PDAC were higher than those in 37 healthy volunteers, and this increase was correlated with PDAC clinical stage. Furthermore, the expression of CSTA and cathepsin B, which is a lysosomal cysteine protease inhibited by CSTA, was observed in tumor tissues and tumor-infiltrating immune cells in 20 surgically resected PDAC tissues by immunohistochemical staining. Expression of CSTA was detected in some tumor tissues and many tumor-infiltrating immune cells. Cathepsin B expression was also observed in most tumor tissues and tumor-infiltrating immune cells. In conclusion, CSTA and its substrate cathepsin B are involved in PDAC-related inflammation. The increment of CSTA expression in peripheral blood of patients with PDAC may have a potential role as a PDAC immunopathologic biomarker.
| S-EPMC5666027 | biostudies-literature
Project description:BACKGROUND We aimed to identify pivotal genes and pathways involved in pancreatic ductal adenocarcinoma (PDAC), and explore possible molecular markers for the early diagnosis of the disease. MATERIAL AND METHODS The array data of GSE74629, including 34 PDAC samples and 16 healthy samples, was downloaded from GEO (Gene Expression Omnibus) database. Then, the DEGs (differentially expressed genes) in PDAC samples were compared with healthy samples using limma (linear models for microarray). Gene functional interaction networks were analyzed with Cytoscape and ReactomeFIViz. PPI networks were constructed with Cytoscape software. In addition, PPI (protein-protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS A total of 630 upregulated and 1,002 downregulated DEGs were identified in PDAC samples compared with healthy samples. Some ribosomal protein genes with higher average correlation in module 0 were enriched in the ribosome pathway. NUP107 (nucleoporin 107 kDa) and NUP160 (nucleoporin 160 kDa) were enriched in module 3. HNRNPU (heterogeneous nuclear ribonucleoprotein U) with higher average correlation in module 8 was enriched in the spliceosome pathway. The ribosome pathway and the spliceosome pathway were significantly enriched in cluster 1 and cluster 2, respectively. CONCLUSIONS Ribosomal protein genes Nup170, Nup160, and HNRNPU, and the ribosome pathway as well as the spliceosome pathway may play important roles in PDAC progression. In addition, ribosomal protein genes Nup170, Nup160, and HNRNPU may be used as possible molecular markers for the early diagnosis of the disease.
| S-EPMC5928849 | biostudies-literature
Project description:Background:Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid tumors. The rapid progression of PDAC results in an advanced stage of patients when diagnosed. However, the dynamic molecular mechanism underlying PDAC progression remains far from clear. Methods:The microarray GSE62165 containing PDAC staging samples was obtained from Gene Expression Omnibus and the differentially expressed genes (DEGs) between normal tissue and PDAC of different stages were profiled using R software, respectively. The software program Short Time-series Expression Miner was applied to cluster, compare, and visualize gene expression differences between PDAC stages. Then, function annotation and pathway enrichment of DEGs were conducted by Database for Annotation Visualization and Integrated Discovery. Further, the Cytoscape plugin DyNetViewer was applied to construct the dynamic protein-protein interaction networks and to analyze different topological variation of nodes and clusters over time. The phosphosite markers of stage-specific protein kinases were predicted by PhosphoSitePlus database. Moreover, survival analysis of candidate genes and pathways was performed by Kaplan-Meier plotter. Finally, candidate genes were validated by immunohistochemistry in PDAC tissues. Results:Compared with normal tissues, the total DEGs number for each PDAC stage were 994 (stage I), 967 (stage IIa), 965 (stage IIb), 1027 (stage III), 925 (stage IV), respectively. The stage-course gene expression analysis showed that 30 distinct expressional models were clustered. Kyoto Encyclopedia of Genes and Genomes analysis indicated that the up-regulated DEGs were commonly enriched in five fundamental pathways throughout five stages, including pathways in cancer, small cell lung cancer, ECM-receptor interaction, amoebiasis, focal adhesion. Except for amoebiasis, these pathways were associated with poor PDAC overall survival. Meanwhile, LAMA3, LAMB3, LAMC2, COL4A1 and FN1 were commonly shared by these five pathways and were unfavorable factors for prognosis. Furthermore, by constructing the stage-course dynamic protein interaction network, 45 functional molecular modules and 19 nodes were identified as featured regulators for all PDAC stages, among which the collagen family and integrins were considered as two main regulators for facilitating aggressive progression. Additionally, the clinical relevance analysis suggested that the stage IV featured nodes MLF1IP and ITGB4 were significantly correlated with shorter overall survival. Moreover, 15 stage-specific protein kinases were identified from the dynamic network and CHEK1 was particularly activated at stage IV. Experimental validation showed that MLF1IP, LAMA3 and LAMB3 were progressively increased from tumor initiation to progression. Conclusions:Our study provided a view for a better understanding of the dynamic landscape of molecular interaction networks during PDAC progression and offered potential targets for therapeutic intervention.
| S-EPMC6303882 | biostudies-literature
Project description:BackgroundLung cancer in young patients is rare and has unique clinicopathological features. However, the molecular features of lung cancer in these patients are unclear. In this study, we aimed to describe the molecular features and outcomes of lung adenocarcinoma in patients aged ?35?years.MethodsA total of 89 patients aged ?35?years with pathologically diagnosed lung adenocarcinoma were retrospectively evaluated. Mutations in 59 cancer-associated genes and fusions of ALK and ROS1 were analyzed to understand the molecular features of young patients with lung adenocarcinoma. The clinicopathological characteristics and prognosis of each patient were reviewed.ResultsOf the 89 young patients, 25 (28.1%) were male, 9 (10.1%) were smokers, and the median age was 32?years (range, 18-35?years). The authors analyzed 59 genes and a total of 6 mutations and 2 fusion genes were detected. These genes were distributed among 60 patients, 12 of which had two or more mutations. ERBB2 mutations were most common (24.7%), followed by EGFR mutation (21.3%), ALK fusion (16.9%), TP53 mutation (9.0%), BRAF mutation (3.4%), PIK3CA mutation (1.1%), CTNNB1 mutation (1.1%), and ROS1 fusion (1.1%). EGFR, ERBB2, and TP53 mutations, gene abnormalities, and ALK fusions all had significant correlations with histopathological differentiation (P?<?0.01). ALK fusions and EGFR mutations conferred a significantly worse prognosis than did ERBB2 mutations and tumors that contained no mutations or fusions (P?<?0.01).ConclusionsThe molecular features of lung adenocarcinoma in young patients are different from those of common adenocarcinoma, and the main driver genes are closely correlated with tumor differentiation and prognosis.
| S-EPMC6685166 | biostudies-literature
Project description:PURPOSE:Pancreatic ductal adenocarcinoma (PDA) is associated with an immunosuppressive microenvironment that supports the growth of the malignancy as well as immune system evasion. Here we examine markers of immunosuppression in PDA within the context of the glycolytic tumor microenvironment, their interrelationship with tumor biology and association with overall survival. EXPERIMENTAL DESIGN:We utilized tissue microarrays consisting of 223 PDA patients annotated for clinical stage, tumor size, lymph node involvement, and survival. Expression of CD163, FoxP3, PD-L1, and MCT4 was assessed by IHC and statistical associations were evaluated by univariate and multivariate analysis. Multimarker subtypes were defined by random forest analysis. Mechanistic interactions were evaluated using PDA cell lines and models for myeloid differentiation. RESULTS:PDA exhibits discrete expression of CD163, FoxP3, and PD-L1 with modest individual significance. However, combined low expression of these markers was associated with improved prognosis (P = 0.02). PDA tumor cells altered macrophage phenotype and function, which supported enhanced invasiveness in cell-based models. Lactate efflux mediated by MCT4 was associated with, and required for, the selective conversion of myeloid cells. Correspondingly, MCT4 expression correlated with immune markers in PDA cases, and increased the significance of prognostic subtypes (P = 0.002). CONCLUSIONS:There exists a complex interplay between PDA tumor cells and the host immune system wherein immunosuppression is associated with negative outcome. MCT4 expression, representative of the glycolytic state of PDA, contributes to the phenotypic conversion of myeloid cells. Thus, metabolic status of PDA tumors is an important determinant of the immunosuppressive environment. Clin Cancer Res; 22(14); 3606-17. ©2016 AACR.
| S-EPMC4947442 | biostudies-literature
Project description:Monocytes and macrophages make up part of the innate immune system and provide one of the first defenses against variety of treats. Macrophages can also modulate the adaptive immune system. Efficient sensing and response to tissue environmental cues highlights the complexity and dynamic nature of macrophages and their plasticity. Macrophages may have divergent roles depending on their polarity and stimulus received. Accumulating evidence demonstrates the critical role played by macrophages in tumor initiation, development, and progression. In this review, we discuss the characteristics of tumor-associated macrophages (TAMs) and their role in pancreatic adenocarcinoma. In addition, we give an overview on recent advances related to the therapeutic implication associated with targeting TAMs in pancreas cancer.
| S-EPMC4912945 | biostudies-literature
Project description:Pancreatic Ductal Adenocarcinoma (PDAC) is a fatal disease with poor prognosis because patients rarely express symptoms in initial stages, which prevents early detection and diagnosis. Syndecans, a subfamily of proteoglycans, are involved in many physiological processes including cell proliferation, adhesion, and migration. Syndecans are physiologically found in many cell types and their interactions with other macromolecules enhance many pathways. In particular, extracellular matrix components, growth factors, and integrins collect the majority of syndecans associations acting as biochemical, physical, and mechanical transducers. Syndecans are transmembrane glycoproteins, but occasionally their extracellular domain can be released from the cell surface by the action of matrix metalloproteinases, converting them into soluble molecules that are capable of binding distant molecules such as extracellular matrix (ECM) components, growth factor receptors, and integrins from other cells. In this review, we explore the role of syndecans in tumorigenesis as well as their potential as therapeutic targets. Finally, this work reviews the contribution of syndecan-1 and syndecan-2 in PDAC progression and illustrates its potential to be targeted in future treatments for this devastating disease.
| S-EPMC7996579 | biostudies-literature