Transcriptomic and Immunohistochemical Profiling of SLC6A14 in Pancreatic Ductal Adenocarcinoma.
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ABSTRACT:
SUBMITTER: Penheiter AR
PROVIDER: S-EPMC4461733 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Transcriptomic and Immunohistochemical Profiling of SLC6A14 in Pancreatic Ductal Adenocarcinoma.
Penheiter Alan R AR Erdogan Sibel S Murphy Stephen J SJ Hart Steven N SN Felipe Lima Joema J Rakhshan Rohakhtar Fariborz F O'Brien Daniel R DR Bamlet William R WR Wuertz Ryan E RE Smyrk Thomas C TC Couch Fergus J FJ Vasmatzis George G Bender Claire E CE Carlson Stephanie K SK
BioMed research international 20150527
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 im ...[more]
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Project description:Pancreatic cancer is one of the most fatal cancers and is associated with limited diagnostic and therapeutic modalities. Currently, gemcitabine is the only effective drug and represents the preferred first-line treatment for chemotherapy. However, a high level of intrinsic or acquired resistance of pancreatic cancer to gemcitabine can contribute to the failure of gemcitabine treatment. To investigate the underlying molecular mechanisms for gemcitabine resistance in pancreatic cancer, we performed label-free quantification of protein expression in intrinsic gemcitabine-resistant and - sensitive human pancreatic adenocarcinoma cell lines using our improved proteomic strategy, combined with filter-aided sample preparation, single-shot liquid chromatography-mass spectrometry, enhanced spectral counting, and a statistical method based on a power law global error model. We identified 1931 proteins and quantified 787 differentially expressed proteins in the BxPC3, PANC-1, and HPDE cell lines. Bioinformatics analysis identified 15 epithelial to mesenchymal transition (EMT) markers and 13 EMT-related proteins that were closely associated with drug resistance were differentially expressed. Interestingly, 8 of these proteins were involved in glutathione and cysteine/methionine metabolism. These results suggest that proteins related to the EMT and glutathione metabolism play important roles in the development of intrinsic gemcitabine resistance by pancreatic cancer cell lines.
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Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is highly associated with cachexia and weight loss, which is driven by the tumour's effect on the body. Data are lacking on differences in these metrics based on PDAC anatomic location. We hypothesize that the primary tumour's anatomic region influences the prevalence and severity of unintentional weight loss.MethodsTreatment naïve patients with PDAC who underwent pancreatectomy at a single institution between 2012 and 2020 were identified retrospectively. Patients with pancreatic head or distal tumours were matched by sex, age, N and T stage. Serologic and anthropometric variables were obtained at the time of diagnosis. Skeletal muscle index (SMI), muscle radiation attenuation (MRA) and adiposity were measured. The primary outcome was presence of significant weight loss [>5% body weight (BW) loss in past 6 months]. Signed rank tests, Cochran Mantel Haenszel tests and Kaplan-Meier survival analysis are presented. RNA-seq of tumours was performed to explore enriched pathways related to cachexia and weight loss.ResultsPancreatic head tumours (n = 24) were associated with higher prevalence (70.8% vs. 41.7%, P = 0.081) and degree of weight loss (7.9% vs. 2.5%, P = 0.014) compared to distal tumours (n = 24). BMI (P = 0.642), SMI (P = 0.738) and MRA (P = 0.478) were similar between groups. Combining BW loss, SMI and MRA into a composite score, patients with pancreatic head cancers met more criteria associated with poor prognosis (P = 0.142). Serum albumin (3.9 vs. 4.4 g/dL, P = 0.002) was lower and bilirubin (4.5 vs. 0.4 mg/dL, P < 0.001) were higher with pancreatic head tumours. Survival differed by tumour location (P = 0.014) with numerically higher median overall survival with distal tumours (11.1 vs. 21.8 months; P = 0.066). Transcriptomic analysis revealed inactivation of appetite stimulation, weight regulation and nutrient digestion/metabolism pathways in pancreatic head tumours.ConclusionsResectable pancreatic head PDAC is associated with higher prevalence of significant weight loss and more poor prognosis features. Pancreaticobiliary obstruction and hypoalbuminemia in patients with head tumours suggests compounding effects of nutrient malabsorption and systemic inflammation on molecular drivers of cachexia, possibly contributing to shorter survival. Therefore, PDAC-associated cachexia is a heterogenous syndrome, which may be influenced by the primary tumour location. Select patients with resectable pancreatic head tumours may benefit from nutritional rehabilitation to improve outcomes.
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Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.
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Project description:Comprehensive characterization of signaling in pancreatic ductal adenocarcinoma (PDAC) promises to enhance our understanding of the molecular aberrations driving this devastating disease, and may identify novel therapeutic targets as well as biomarkers that enable stratification of patients for optimal therapy. Here, we use immunoaffinity-coupled high-resolution mass spectrometry to characterize global tyrosine phosphorylation patterns across two large panels of human PDAC cell lines: the ATCC series (19 cell lines) and TKCC series (17 cell lines). This resulted in the identification and quantification of over 1800 class 1 tyrosine phosphorylation sites and the consistent segregation of both PDAC cell line series into three subtypes with distinct tyrosine phosphorylation profiles. Subtype-selective signaling networks were characterized by identification of subtype-enriched phosphosites together with pathway and network analyses. This revealed that the three subtypes characteristic of the ATCC series were associated with perturbations in signaling networks associated with cell-cell adhesion and epithelial-mesenchyme transition, mRNA metabolism, and receptor tyrosine kinase (RTK) signaling, respectively. Specifically, the third subtype exhibited enhanced tyrosine phosphorylation of multiple RTKs including the EGFR, ERBB3 and MET. Interestingly, a similar RTK-enriched subtype was identified in the TKCC series, and 'classifier' sites for each series identified using Random Forest models were able to predict the subtypes of the alternate series with high accuracy, highlighting the conservation of the three subtypes across the two series. Finally, RTK-enriched cell lines from both series exhibited enhanced sensitivity to the small molecule EGFR inhibitor erlotinib, indicating that their phosphosignature may provide a predictive biomarker for response to this targeted therapy. These studies highlight how resolution of subtype-selective signaling networks can provide a novel taxonomy for particular cancers, and provide insights into PDAC biology that can be exploited for improved patient management.
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