Dataset Information

Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue identifies distinct clinical subgroups.

ABSTRACT:

Introduction

Metabolic reprogramming is a hallmark feature of pancreatic ductal adenocarcinoma (PDAC). A pancreatic juice (PJ) metabolic signature has been reported to be prognostic of oncological outcome for PDAC. Integration of PJ profiling with transcriptomic and spatial characterization of the tumor microenvironment would help in identifying PDACs with peculiar vulnerabilities.

Methods

We performed a transcriptomic analysis of 26 PDAC samples grouped into 3 metabolic clusters (M_CL) according to their PJ metabolic profile. We analyzed molecular subtypes and transcriptional differences. Validation was performed by multidimensional imaging on tumor slides.

Results

Pancreatic juice metabolic profiling was associated with PDAC transcriptomic molecular subtypes (p=0.004). Tumors identified as M_CL1 exhibited a non-squamous molecular phenotype and demonstrated longer survival. Enrichment analysis revealed the upregulation of immune genes and pathways in M_CL1 samples compared to M_CL2, the group with worse prognosis, a difference confirmed by immunofluorescence on tissue slides. Enrichment analysis of 39 immune signatures by xCell confirmed decreased immune signatures in M_CL2 compared to M_CL1 and allowed a stratification of patients associated with longer survival.

Discussion

PJ metabolic fingerprints reflect PDAC molecular subtypes and the immune microenvironment, confirming PJ as a promising source of biomarkers for personalized therapy.

SUBMITTER: Pulvirenti A

PROVIDER: S-EPMC11234733 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Publications

Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue identifies distinct clinical subgroups.

Pulvirenti Alessandra A Barbagallo Marialuisa M Putignano Anna Rita AR Pea Antonio A Polidori Rebecca R Upstill-Goddard Rosie R Cortese Nina N Kunderfranco Paolo P Brunelli Laura L De Simone Giulia G Pastorelli Roberta R Spaggiari Paola P Nappo Gennaro G Jamieson Nigel B NB Zerbi Alessandro A Chang David K DK Capretti Giovanni G Marchesi Federica F

Frontiers in oncology 20240626

<h4>Introduction</h4>Metabolic reprogramming is a hallmark feature of pancreatic ductal adenocarcinoma (PDAC). A pancreatic juice (PJ) metabolic signature has been reported to be prognostic of oncological outcome for PDAC. Integration of PJ profiling with transcriptomic and spatial characterization of the tumor microenvironment would help in identifying PDACs with peculiar vulnerabilities.<h4>Methods</h4>We performed a transcriptomic analysis of 26 PDAC samples grouped into 3 metabolic clusters ...[more]

PMID: 38988711

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Project description:Hemangioblastomas (HBs) of the central nervous system are highly vascular neoplasms that occur sporadically or as a manifestation of von Hippel-Lindau (VHL) disease. Despite their benign nature, HBs are clinically heterogeneous and can be associated with significant morbidity due to mass effects of peritumoral cysts or tumor progression. Underlying molecular factors involved in HB tumor biology remain elusive. We investigated genome-wide DNA methylation profiles and clinical and histopathological features in a series of 47 HBs from 42 patients, including 28 individuals with VHL disease. Thirty tumors occurred in the cerebellum, 8 in the brainstem and 8 HBs were of spinal location, while 1 HB was located in the cerebrum. Histologically, 12 HBs (26%) belonged to the cellular subtype and exclusively occurred in the cerebellum, whereas 35 HBs were reticular (74%). Unsupervised clustering and dimensionality reduction of DNA methylation profiles revealed two distinct subgroups. Methylation cluster 1 comprised 30 HBs of mainly cerebellar location (29/30, 97%), whereas methylation cluster 2 contained 17 HBs predominantly located in non-cerebellar compartments (16/17, 94%). The sum of chromosomal regions being affected by copy-number alterations was significantly higher in methylation cluster 1 compared to cluster 2 (mean 262 vs. 109 Mb, p = 0.001). Of note, loss of chromosome 6 occurred in 9/30 tumors (30%) of methylation cluster 1 and was not observed in cluster 2 tumors (p = 0.01). No relevant methylation differences between sporadic and VHL-related HBs or cystic and non-cystic HBs could be detected. Deconvolution of the bulk DNA methylation profiles revealed four methylation components that were associated with the two methylation clusters suggesting cluster-specific cell-type compositions. In conclusion, methylation profiling of HBs reveals 2 distinct subgroups that mainly associate with anatomical location, cytogenetic profiles and differences in cell type composition, potentially reflecting different cells of origin.

Dataset Information

Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue identifies distinct clinical subgroups.

Introduction

Methods

Results

Discussion

Publications

Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue identifies distinct clinical subgroups.

Similar Datasets

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