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Transcriptomic profiling of highly- and lowly- metastasizing pancreatic ductal carcinoma cells

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE201177 | GEO | 2024/04/20

REPOSITORIES: GEO

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Transcriptomic profiling of highly- and lowly- metastasizing pancreatic ductal carcinoma cells [mRNAseq shNPTX1]

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Transcriptomic and Immunohistochemical Profiling of SLC6A14 in Pancreatic Ductal Adenocarcinoma.

Project description:We used a target-centric strategy to identify transporter proteins upregulated in pancreatic ductal adenocarcinoma (PDAC) as potential targets for a functional imaging probe to complement existing anatomical imaging approaches. We performed transcriptomic profiling (microarray and RNASeq) on histologically confirmed primary PDAC tumors and normal pancreas tissue from 33 patients, including five patients whose tumors were not visible on computed tomography. Target expression was confirmed with immunohistochemistry on tissue microarrays from 94 PDAC patients. The best imaging target identified was SLC6A14 (a neutral and basic amino acid transporter). SLC6A14 was overexpressed at the transcriptional level in all patients and expressed at the protein level in 95% of PDAC tumors. Very little is known about the role of SLC6A14 in PDAC and our results demonstrate that this target merits further investigation as a candidate transporter for functional imaging of PDAC.

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Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma.

Project description:BackgroundAccumulating evidence shows that the elevated expression of DCBLD2 (discoidin, CUB and LCCL domain-containing protein 2) is associated with unfavorable prognosis of various cancers. However, the correlation of DCBLD2 expression value with the diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated.MethodsUnivariate Cox regression analysis was used to screen robust survival-related genes. Expression pattern of selected genes was investigated in PDAC tissues and normal tissues from multiple cohorts. Kaplan-Meier (K-M) survival curves, ROC curves and calibration curves were employed to assess prognostic performance. The relationship between DCBLD2 expression and immune cell infiltrates was conducted by CIBERSORT software. Biological processes and KEGG pathway enrichment analyses were adopted to clarify the potential function of DCBLD2 in PDAC.ResultsUnivariate analysis, K-M survival curves and calibration curves indicated that DCBLD2 was a robust prognostic factor for PDAC with cross-cohort compatibility. Upregulation of DCBLD2 was observed in dissected PDAC tissues as well as extracellular vesicles from both plasma and serum samples of PDAC patients. Both DCBLD2 expression in tissue and extracellular vesicles had significant diagnostic value. Besides, DCBLD2 expression was correlated with infiltrating level of CD8+ T cells and macrophage M2 cells. Functional enrichment revealed that DCBLD2 might be involved in cell motility, angiogenesis, and cancer-associated pathways.ConclusionOur study systematically analyzed the potential diagnostic, prognostic and therapeutic value of DCBLD2 in PDAC. All the findings indicated that DCBLD2 might play a considerably oncogenic role in PDAC with diagnostic, prognostic and therapeutic potential. These preliminary results of bioinformatics analyses need to be further validated in more prospective studies.

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Project description:Dogs can be excellent models for spontaneous studies about breast cancers, presenting similarities in clinical behavior and molecular pathways of the disease. Thus, analyses of the canine transcriptome can identify deregulated genes and pathways, contributing to the identification of biomarkers and new therapeutic targets, benefiting humans and animals. In this context, this study aimed to determine the transcriptional profile of canine mammary ductal carcinoma and contribute to the clarification of the importance of deregulated molecules in the molecular pathways involved in the disease. Therefore, we used mammary ductal carcinoma tissue samples and non-tumor mammary tissue from the radical mastectomy of six female dogs. Sequencing was performed on the NextSeq-500 System platform. A comparison of carcinoma tissue and normal tissue revealed 633 downregulated and 573 upregulated genes, which were able to differentiate the groups by principal component analysis. Gene ontology analysis indicated that inflammatory, cell differentiation and adhesion, and extracellular matrix maintenance pathways were mainly deregulated in this series. The main differentially expressed genes observed in this research can indicate greater disease aggressiveness and worse prognosis. Finally, the study of the canine transcriptome indicates that it is an excellent model to generate information relevant to oncology in both species.

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EZH2-GATA6 axis in Pancreatic ductal adenocarcinoma

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-09-30 | GSE153538 | GEO

Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma.

Project description:ObjectiveWe performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC.Summary of background dataPretreatment risk stratification is essential for offering individualized treatments to patients with PDAC, but predicting recurrence following surgery remains clinically challenging.MethodsWe analyzed 210 plasma and serum specimens from 4 cohorts of PDAC patients. Using a discovery cohort (n = 25), we performed genome-wide sequencing to identify candidate exosomal miRNAs (exo-miRNAs). Subsequently, we trained and validated the predictive performance of the exo-miRNAs in two clinical cohorts (training cohort: n = 82, validation cohort: n = 57) without neoadjuvant therapy (NAT), followed by a post-NAT clinical cohort (n = 46) as additional validation.ResultsWe performed exo-miRNA expression profiling in plasma specimens obtained before any treatment in a discovery cohort. Subsequently we optimized and trained a 6-exo-miRNA risk-prediction model, which robustly discriminated patients with recurrence [area under the curve (AUC): 0.81, 95% confidence interval (CI): 0.70-0.89] and relapse-free survival (RFS, P < 0.01) in the training cohort. The identified exo-miRNA panel was successfully validated in an independent validation cohort (AUC: 0.78, 95% CI: 0.65- 0.88, RFS: P < 0.01), where it exhibited comparable performance in the post-NAT cohort (AUC: 0.72, 95% CI: 0.57-0.85, RFS: P < 0.01) and emerged as an independent predictor for RFS (hazard ratio: 2.84, 95% CI: 1.30-6.20).ConclusionsWe identified a novel, noninvasive exo-miRNA signature that robustly predicts recurrence following surgery in patients with PDAC; highlighting its potential clinical impact for optimized patient selection and improved individualized treatment strategies.

| S-EPMC8674379 | biostudies-literature

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