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SERPINB7 Expression Predicts Poor Pancreatic Cancer Survival Upon Gemcitabine Treatment.

ABSTRACT: Stratification of patients with pancreatic ductal adenocarcinoma (PDAC) remains a key challenge in the field of clinical oncology. No predictive biomarkers have yet been found for any available treatment options. Previously, we identified SERPINB7 as a putative biomarker for PDAC and thus, herein, we aimed to validate our previous findings and assessed the predictive value of SERPINB7. Patients who underwent surgery and received gemcitabine (gem) or gemcitabine plus nab-paclitaxel (gem/nab) as adjuvant therapy, between 2011 and 2017, were included in this study (n?=?57). Expression level of SERPINB7 was assessed in tumor tissue by immunohistochemistry (IHC) and RNA in situ hybridization (RNA ISH). Its association with disease-free survival (DFS) and overall survival (OS) was investigated. While IHC did not show any correlation between survival and the protein level of SERPINB7, RNA ISH revealed that expression of SERPINB7 was associated with a poor DFS (P?=?.01) and OS (P?=?.002) in the gem group but not in the gem/nab. Adjusted Cox-regression analysis confirmed the independent predictive value of SERPINB7 on OS (P?=?.006, HR: 3.47; 95% CI: 1.49-8.09) in the gem group. In conclusion, SERPINB7 was identified as the first predictive RNA biomarker for PDAC. This study suggests that patients who expressed SERPINB7 might receive another treatment than gem alone.

SUBMITTER: Bianconi D

PROVIDER: S-EPMC6149193 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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SERPINB7 Expression Predicts Poor Pancreatic Cancer Survival Upon Gemcitabine Treatment.

Bianconi Daniela D Herac Merima M Spies Daniel D Kieler Markus M Brettner Robert R Unseld Matthias M Fürnkranz Katrin K Famler Barbara B Schmeidl Margit M Minichsdorfer Christoph C Zielinski Christoph C Heller Gerwin G Prager Gerald W GW

Translational oncology 20180920 1

Stratification of patients with pancreatic ductal adenocarcinoma (PDAC) remains a key challenge in the field of clinical oncology. No predictive biomarkers have yet been found for any available treatment options. Previously, we identified SERPINB7 as a putative biomarker for PDAC and thus, herein, we aimed to validate our previous findings and assessed the predictive value of SERPINB7. Patients who underwent surgery and received gemcitabine (gem) or gemcitabine plus nab-paclitaxel (gem/nab) as a ...[more]

PMID: 30245304

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Project description:Although gemcitabine monotherapy is the standard treatment for advanced pancreatic cancer, patient outcome varies significantly, and a considerable number do not benefit adequately. We therefore searched for new biomarkers predictive of overall patient survival. Using LC-MS, we compared the base-line plasma proteome between 29 representative patients with advanced pancreatic cancer who died within 100 days and 31 patients who survived for more than 400 days after receiving at least two cycles of the same gemcitabine monotherapy. Identified biomarker candidates were then challenged in a larger cohort of 304 patients treated with the same protocol using reverse-phase protein microarray. Among a total of 45,277 peptide peaks, we identified 637 peaks whose intensities differed significantly between the two groups (p < 0.001, Welch's t test). Two MS peaks with the highest statistical significance (p = 2.6 x 10(-4) and p = 5.0 x 10(-4)) were revealed to be derived from alpha(1)-antitrypsin and alpha(1)-antichymotrypsin, respectively. The levels of alpha(1)-antitrypsin (p = 8.9 x 10(-8)) and alpha(1)-antichymotrypsin (p = 0.001) were significantly correlated with the overall survival of the 304 patients. We selected alpha(1)-antitrypsin (p = 0.0001), leukocyte count (p = 0.066), alkaline phosphatase (p = 8.3 x 10(-8)), and performance status (p = 0.003) using multivariate Cox regression analysis and constructed a scoring system (nomogram) that was able to identify a group of high risk patients having a short median survival time of 150 days (95% confidence interval, 123-187 days; p = 2.0 x 10(-15), log rank test). The accuracy of this model for prognostication was internally validated and showed good calibration and discrimination with a bootstrap-corrected concordance index of 0.672. In conclusion, an increased level of alpha(1)-antitrypsin is a biomarker that predicts short overall survival of patients with advanced pancreatic cancer receiving gemcitabine monotherapy. Although an external validation study will be necessary, the current model may be useful for identifying patients unsuitable for the standardized therapy.

Project description:Background: Nucleolar and spindle-associated protein 1 (NUSAP1) was previously reported to be associated with poor prognosis in multiple cancers. In the present study, we comprehensively investigated the clinicopathological features and potential prognostic value of NUSAP1 in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Methods: The expression profiles of the genes were extracted from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Cancer Cell Line Encyclopedia (CCLE), Gene Expression Profiling Interactive Analysis (GEPIA), and The Human Protein Atlas databases. The association between clinicopathological characteristics and NUSAP1 was analyzed using logistic regression in TCGA patients and receiver operating characteristic (ROC) curve analysis for GSE7803, GSE9750, and GSE63514 datasets. The prognostic value of NUSAP1 in TCGA patients was evaluated using the Kaplan-Meier method and Cox regression. Gene set enrichment analysis (GSEA) was conducted using TCGA dataset. Results: A total of 68 differentially expressed genes (DEGs) were identified in CESC. ROC analysis of NUSAP1 suggested that the area under the ROC curve was 0.968. Kaplan-Meier survival analysis indicated that CESC with low expression of NUSAP1 has a worse prognosis than CESC with high NUSAP1 expression (P = 0.005). The logistic regression revealed that low NUSAP1 expression in CESC was related to advanced tumor stage in TCGA database. Moreover, Cox regression analysis showed that NUSAP1 expression correlated significantly with prognosis in the case of patients in TCGA database. GSEA demonstrated that CESC patients with high expression of NUSAP1 were enriched in the G2M checkpoint, MYC targets, and breast cancer ZNF217. Conclusion: The results suggest that identification of DEGs might enhance our understanding of the causes and molecular mechanisms underlying the development of CESC. Moreover, NUSAP1 may play an important role in CESC progression and prognosis and may serve as a valuable indicator of poor survival in CESC.

Dataset Information

SERPINB7 Expression Predicts Poor Pancreatic Cancer Survival Upon Gemcitabine Treatment.

Publications

SERPINB7 Expression Predicts Poor Pancreatic Cancer Survival Upon Gemcitabine Treatment.

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