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A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

ABSTRACT: Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options.Using publicly available mRNA abundance datasets, we performed a large retrospective meta-analysis on 466 PDAC patients to discover prognostic gene signatures. These signatures were trained on two clinical cohorts (n?=?70), and validated on four independent clinical cohorts (n?=?246). Further validation of the identified gene signature was performed using quantitative real-time RT-PCR.We identified 225 candidate prognostic genes. Using these, a 36-gene signature was discovered and validated on fully independent clinical cohorts (hazard ratio (HR)?=?2.06, 95% confidence interval (CI)?=?1.51 to 2.81, P?=?3.62?×?10(-6), n?=?246). This signature serves as a good alternative prognostic stratification marker compared to tumour grade (HR?=?2.05, 95% CI?=?1.45 to 2.88, P?=?3.18?×?10(-5)) and tumour node metastasis (TNM) stage (HR?=?1.13, 95% CI?=?0.66 to 1.94, P?=?0.67). Upon multivariate analysis with adjustment for TNM stage and tumour grade, the 36-gene signature remained an independent prognostic predictor of clinical outcome (HR?=?2.21, 95% CI?=?1.17 to 4.16, P?=?0.01). Univariate assessment revealed higher expression of ITGA5, SEMA3A, KIF4A, IL20RB, SLC20A1, CDC45, PXN, SSX3 and TMEM26 was correlated with shorter survival while B3GNT1, NOSTRIN and CADPS down-regulation was associated with poor outcome.Our 36-gene classifier is able to prognosticate PDAC independent of patient cohort and microarray platforms. Further work on the functional roles, downstream events and interactions of the signature genes is likely to reveal true molecular candidates for PDAC therapeutics.

SUBMITTER: Haider S

PROVIDER: S-EPMC4293116 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

Haider Syed S Wang Jun J Nagano Ai A Desai Ami A Arumugam Prabhu P Dumartin Laurent L Fitzgibbon Jude J Hagemann Thorsten T Marshall John F JF Kocher Hemant M HM Crnogorac-Jurcevic Tatjana T Scarpa Aldo A Lemoine Nicholas R NR Chelala Claude C

Genome medicine 20141203 12

<h4>Background</h4>Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options.<h4>Methods</h4>Using publicly available mRNA abundance datasets, we performed a large retrospective meta-analysis on 466 PDAC patients to discover prognostic gene signatures. These signatures were trained on two clinical cohorts (n = 70), and validated on four ...[more]

PMID: 25587357

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Project description:A six-gene signature predicts survival of patients with localized pancreatic ductal adenocarcinoma Pancreatic ductal adenocarcinoma (PDAC), comprising over 90% of all pancreatic cancers, remains a lethal disease with an estimated 232,000 new cases, 227,000 deaths per year worldwide, and a less than 5% five-year survival rate. Currently the standard of care for the 20% of patients with localized disease is surgery followed by chemotherapy, and in some cases radiation. Unfortunately despite the use of adjuvant therapy, median survival remains at best 23 months. It is important to note however, that up to 27% of patients with resected PDAC can survive for five years. However, in these studies examining actual long-term survivors, only two have found that adjuvant therapy was associated with improved survival. In addition, randomized controlled trials of gemcitabine-based chemotherapy demonstrate an improvement in median survival of at best 3 months. One possible conclusion from these studies is that tumor biology dictates outcome and that our current adjuvant therapy has only a modest impact on altering a patient's course.Hypothesizing that the dismal outcome of patients with localized disease is due to the presence of micrometastasic disease, current clinical investigation has focused on preoperative or neoadjuvant therapy. This approach, where patients who cannot tolerate the stress of therapy or develop metastatic disease during treatment are spared surgery, has demonstrated an overall survival of 34 months in this highly selected patient population. Therefore the ability to select patients who would most benefit from a neoadjuvant approach may be important. One way to do this is to define a prognostic gene signature that can identify patients with more aggressive tumor biology upfront. reference x sample The 30 Nebraska and UNC samples were not analyzed with clinical data so it is not provided. One of the PE samples is missing some clinical data.

Project description:Pancreatic ductal adenocarcinoma (PDA) is notorious for its poor prognosis. The current mainstay of treatment for PDA is surgical resection followed by adjuvant chemotherapy. However, it is difficult to predict the post-operative outcome because of the lack of reliable markers. The single-nucleotide polymorphism (SNP) of N-acetylgalactosaminyltransferase14 (GALNT14) has been proven to predict the progression-free survival (PFS), overall survival (OS) and response to chemotherapy in various types of gastrointestinal (GI) cancers. However, its role in PDA has not been studied. This study aims to investigate whether the GALNT14 SNP genotype can be a prognostic marker for PDA. A cohort of one hundred and three PDA patients having received surgical resection were retrospectively enrolled. GALNT14 genotypes and the clinicopathological parameters were correlated with postoperative prognosis. The genotype analysis revealed that 19.4%, 60.2% and 20.4% of patients had the GALNT14 "TT", "TG" and "GG" genotypes, respectively. The patients with the "GG" genotype had a mean OS time of 37.1 months (95% confidence interval [CI]: 18.2-56.1) and those with the "non-GG" genotype had a mean OS time of 16.1 months (95% CI: 13.1-19.2). Kaplan-Meier analysis showed that the "GG" genotype had a significantly better OS compared to the "non-GG" genotype (p = 0.005). However, there was no significant difference between the "GG" and "non-GG" genotypes in PFS (p = 0.172). The baseline characteristics between patients with the "GG" and "non-GG" genotypes were compared, and no significant difference was found. Univariate followed by multivariate Cox proportional hazard models demonstrated the GALNT14 "GG" genotype, negative resection margin, and locoregional disease as independent predictors for favorable OS (p = 0.003, p = 0.037, p = 0.021, respectively). Sensitivity analysis was performed in each subgroup to examine the relationship of GALNT14 with different clinicopathological variables and no heterogeneity was found. The GALNT14 "GG" genotype is associated with favorable survival outcome, especially OS, in patients with resected PDA and could serve as a prognostic marker.

Project description:Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with an extremely low 5-year survival rate. Accumulating evidence has unveiled that inflammatory response promotes tumor progression, enhances angiogenesis, and causes local immunosuppression. Herein, we aim to develop an inflammatory related prognostic signature, and found it could be used to predict gemcitabine response in PDAC. Methods: PDAC cohorts with mRNA expression profiles and clinical information were systematically collected from the four public databases. An inflammatory response related genes (IRRGs) prognostic signature was constructed by LASSO regression analysis. Kaplan-Meier survival analysis, receiver operating characteristic analysis, principal component analysis, and univariate and multivariate Cox analyses were carried out to evaluate effectiveness, and reliability of the signature. The correlation between gemcitabine response and risk score was evaluated in the TCGA-PAAD cohort. The GDSC database, pRRophetic algorithm, and connectivity map analysis were used to predict gemcitabine sensitivity and identify potential drugs for the treatment of PDAC. Finally, we analyzed differences in frequencies of gene mutations, infiltration of immune cells, as well as biological functions between different subgroups divided by the prognostic signature. Results: We established a seven IRRGs (ADM, DCBLD2, EREG, ITGA5, MIF, TREM1, and BTG2) signature which divided the PDAC patients into low- and high-risk groups. Prognostic value of the signature was validated in 11 PDAC cohorts consisting of 1337 PDAC patients from 6 countries. A nomogram that integrated the IRRGs signature and clinicopathologic factors of PDAC patients was constructed. The risk score showed positive correlation with gemcitabine resistance. Two drugs (BMS-536924 and dasatinib) might have potential therapeutic implications in high-risk PDAC patients. We found that the high-risk group had higher frequencies of KRAS, TP53, and CDKN2A mutations, increased infiltration of macrophages M0, neutrophils, and macrophages M2 cells, as well as upregulated hypoxia and glycolysis pathways, while the low-risk group had increased infiltration of CD8+ T, naïve B, and plasma and macrophages M1 cells. Conclusion: We constructed and validated an IRRGs signature that could be used to predict the prognosis and gemcitabine response of patients with PDAC, as well as two drugs (BMS-536924 and dasatinib) may contribute to PDAC treatment.

Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is characterized by an important heterogeneity, reflected by different clinical outcomes and chemoresistance. During carcinogenesis, tumor cells display aberrant glycosylated structures, synthetized by deregulated glycosyltransferases, supporting the tumor progression. In this study, we aimed to determine whether PDAC could be stratified through their glycosyltransferase expression profiles better than the current binary classification (basal-like and classical) in order to improve detection of patients with poor prognosis.MethodsBioinformatic analysis of 169 glycosyltransferase RNA sequencing data were performed for 74 patient-derived xenografts (PDX) of resected and unresectable tumors. The Australian cohort of International Cancer Genome Consortium and the microarray dataset from Puleo patient's cohort were used as independent validation datasets.FindingsNew PDAC stratification based on glycosyltransferase expression profile allowed to distinguish different groups of patients with distinct clinical outcome (p-value = 0.007). A combination of 19 glycosyltransferases differentially expressed in PDX defined a glyco-signature, whose prognostic value was validated on datasets including resected whole tumor tissues. The glyco-signature was able to discriminate three clusters of PDAC patients on the validation cohorts, two clusters displaying a short overall survival compared to one cluster having a better prognosis. Both poor prognostic clusters having different glyco-profiles in Puleo patient's cohort were correlated with stroma activated or desmoplastic subtypes corresponding to distinct microenvironment features (p-value < 0.0001). Besides, differential expression and enrichment analyses revealed deregulated functional pathways specific to different clusters.InterpretationThis study identifies a glyco-signature relevant for a prognostic use, potentially applicable to resected and unresectable PDAC. Furthermore, it provides new potential therapeutic targets.FundingThis work was supported by INCa (Grants number 2018-078 and 2018-079), Fondation ARC (Grant number ARCPJA32020070002326), Cancéropôle PACA, DGOS (labelization SIRIC, Grant number 6038), Amidex Foundation and Ligue Nationale Contre le Cancer and by institutional fundings from INSERM and the Aix-Marseille Université.

Dataset Information

A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

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A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

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