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Arif T, Nazir F, Aurangzeb RF, Hussain M, Aurangzeb RI, Rehman A, Kumar K, Islam R, Islam H, Khalid Q, Arrey Agbor DB, Munir K, Bokhari SFH, Shehryar A, Ibrahim M. The Potential of Fecal and Urinary Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review. Cureus 2024; 16:e59248. [PMID: 38813271 PMCID: PMC11134185 DOI: 10.7759/cureus.59248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2024] [Indexed: 05/31/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer often diagnosed at advanced stages, highlighting the urgent need for early detection strategies. This systematic review explores the potential of fecal and urinary biomarkers for early PDAC detection. A comprehensive search identified eight relevant studies investigating various biomarkers, including proteins, metabolites, microbial profiles, DNA mutations, and non-coding RNAs. Promising findings suggest that urinary biomarkers related to metabolic alterations, inflammatory processes, fecal microbiome profiles, and fecal miRNAs hold diagnostic potential even at early stages of PDAC. Combining biomarkers into panels may enhance diagnostic accuracy. Challenges such as validation in larger cohorts, standardization of protocols, and regulatory approval must be addressed for clinical translation. Despite these hurdles, non-invasive urinary and fecal biomarkers represent a promising avenue for improving PDAC outcomes through early detection.
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Affiliation(s)
- Talha Arif
- Accident and Emergency, Imran Idrees Teaching Hospital, Sialkot, PAK
| | - Faran Nazir
- Internal Medicine, Faisalabad Medical University, Deer Park, USA
| | | | | | | | | | - Kabeer Kumar
- Internal Medicine, Chandka Medical College, Larkana, PAK
| | - Rabia Islam
- Research, Faisalabad Medical University, Faisalabad, PAK
| | - Hamza Islam
- Internal Medicine, Punjab Medical College, Faisalabad, PAK
| | - Qais Khalid
- Internal Medicine, Khyber Medical University, Peshawar, PAK
| | | | - Kashaf Munir
- Medicine, Shalamar Medical and Dental College, Lahore, PAK
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Chen X, Yang J, Lu Z, Ding Y. A 70‑RNA model based on SVR and RFE for predicting the pancreatic cancer clinical prognosis. Methods 2022; 204:278-285. [PMID: 35248692 DOI: 10.1016/j.ymeth.2022.02.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/09/2022] [Accepted: 02/27/2022] [Indexed: 12/12/2022] Open
Abstract
Researches on the prognosis of pancreatic cancer is of great significance to improve the patient treatment effect and survival. Current researches mainly focus on the prediction of the survival status and the determination of prognostic markers. Each patient has its own characteristics, there is no report about the prediction of survival time. However, accurate prediction of survival time is critical for personalized medicine. In this paper, a hybrid algorithm of Support Vector Regression (SVR) and Recursive Feature Elimination (RFE) was used to construct a quantitative prediction model of Overall Survival (OS) for pancreatic cancer patients, 70 RNAs related to OS were determined, including 33 mRNAs, 28 lncRNAs, and 9 miRNAs. The results of 10-fold cross-validation (R2 is 0.9693) and the generalization ability (R2 is 0.9666) showed that the model has reliable predictive performance and these 70 RNAs are important factors influencing the OS of pancreatic cancer patients. To further study the relationship between RNA-RNA interaction and the survival, competitive endogenous RNA (ceRNA) regulation network was constructed. Degree centrality, betweenness centrality and closeness centrality of nodes in the ceRNA network showed that hsa-mir-570, hsa-mir-944, hsa-mir-6506, hsa-mir-3136, MMP16, PLGLB2, HPGD, FUT1, MFSD2A, SULT1E1, SLC13A5, ZNF488, F2RL2, TNFRSF8, TNFSF11, FHDC1, ISLR2 and THSD7B are hub nodes, which are key RNAs closely determining the OS of pancreatic cancer patients.
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Affiliation(s)
- Xu Chen
- School of Science, Jiangnan University, Wuxi, Jiangsu 214122, PR China; Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi, Jiangsu 214122, PR China
| | - Jing Yang
- School of Science, Jiangnan University, Wuxi, Jiangsu 214122, PR China; Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi, Jiangsu 214122, PR China
| | - Zhengshu Lu
- School of Science, Jiangnan University, Wuxi, Jiangsu 214122, PR China; Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi, Jiangsu 214122, PR China
| | - Yanrui Ding
- School of Science, Jiangnan University, Wuxi, Jiangsu 214122, PR China; Key Laboratory of Industrial Biotechnology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China.
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He QL, Jiang HX, Zhang XL, Qin SY. Relationship between a 7-mRNA signature of the pancreatic adenocarcinoma microenvironment and patient prognosis (a STROBE-compliant article). Medicine (Baltimore) 2020; 99:e21287. [PMID: 32702921 PMCID: PMC7373597 DOI: 10.1097/md.0000000000021287] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 04/16/2020] [Accepted: 06/15/2020] [Indexed: 12/23/2022] Open
Abstract
The potential association between the prognosis of the pancreatic adenocarcinoma (PAAD) and its microenvironment is unclear. This study aims to construct a prognostic index (PI) model of the PAAD microenvironment to predict PAAD patient survival outcomes.The mRNA sequencing and the clinical parameters data were obtained from The Cancer Genome Atlas. Immune and stromal scores were computed using the expression data algorithm to capture infiltration of immune and stromal cells in the PAAD tissue, where patients were categorized as high and low score groups according to these scores. Differentially expressed genes were identified using the R package LIMMA. Univariate and multivariate Cox regression analysis were conducted to select candidate survival-correlated gene signatures from the tumor microenvironment for constructing a model. The Kaplan-Meier method was used to access overall survival of the primary and validation cohorts. The immunological features of the PI model was explored using the Tumor Immune Estimation Resource (TIMER) database. Bioinformatic analyses were conducted based on the DAVID database.A total of 1266 overlapping differentially expressed genes and 49 prognosis-associated genes were identified. A 7-mRNA signature (GBP5, BICC1, SLC7A14, CYSLTR1, P2RY6, VENTX, and RAB39B) was screened for the construction of a PI model (area under the curve = 0.791). In both the primary and validation cohorts, Kaplan Meier analysis revealed that the overall survival of the high-risk group was significantly worse compared to the low-risk group (P < .0001, P = .0028 respectively). The TIMER database described that the 7 signature genes were correlated with immune infiltrating cells and tumor purity. Bioinformatic analyses revealed that these prognosis-associated genes were significantly enriched during inflammation, the defense response, would response, calcium ion transport, and plasma membrane part.A list of the prognosis-correlated genes was generated based on the PAAD microenvironment. A 7-mRNA PI model may be used for predicting the prognosis of PAAD patients.
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Liao X, Huang K, Huang R, Liu X, Han C, Yu L, Yu T, Yang C, Wang X, Peng T. Genome-scale analysis to identify prognostic markers in patients with early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy. Onco Targets Ther 2017; 10:4493-4506. [PMID: 28979141 PMCID: PMC5602474 DOI: 10.2147/ott.s142557] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Molecular analysis is a promising source of clinically useful prognostic biomarkers. The aim of this investigation was to identify prognostic biomarkers for patients with early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy. METHODS An RNA sequencing dataset of PDAC was obtained from The Cancer Genome Atlas. Survival analysis and weighted gene co-expression network analysis were used to investigate the prognostic markers of early-stage PDAC after pancreaticoduodenectomy. RESULTS Using whole genome expression level screening, we identified 1,238 markers that were related to the prognosis of PDAC after pancreaticoduodenectomy, and identified 9 hub genes (ARHGAP30, HCLS1, CD96, FAM78A, ARHGAP15, SLA2, CD247, GVINP1, and IL16) using the weighted gene co-expression network analysis approach. We also constructed a signature comprising the 9 hub genes and weighted by the regression coefficient derived from a multivariate Cox proportional hazards regression model to divide patients into a high-risk group, with increased risk of death, and a low-risk group, with significantly improved overall survival (adjusted P=0.026, adjusted HR =0.513, 95% CI =0.285-0.924). The prognostic signature of the 9 genes demonstrated good performance for predicting 1-year overall survival (area under the respective receiver operating characteristic curves =0.641). CONCLUSION Our results have provided a new prospect for prognostic biomarkers of PDAC after pancreaticoduodenectomy, and may have a value in clinical application.
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Affiliation(s)
- Xiwen Liao
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
| | - Ketuan Huang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
| | - Rui Huang
- Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Xiaoguang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University.,Department of Hepatobiliary Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang
| | - Chuangye Han
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
| | - Long Yu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University.,Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Tingdong Yu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
| | - Chengkun Yang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
| | - Xiangkun Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
| | - Tao Peng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University
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Chang ZY, Sun R, Ma YS, Fu D, Lai XL, Li YS, Wang XH, Zhang XP, Lv ZW, Cong XL, Li WP. Differential gene expression of the key signalling pathway in para-carcinoma, carcinoma and relapse human pancreatic cancer. Cell Biochem Funct 2014; 32:258-67. [PMID: 24122964 DOI: 10.1002/cbf.3009] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2013] [Revised: 09/01/2013] [Accepted: 09/16/2013] [Indexed: 01/21/2023]
Abstract
Pancreatic cancer (PC) has a high rate of mortality and a poorly understood mechanism of progression. Investigation of the molecular mechanism of PC and exploration of the specific markers for early diagnosis and specific targets of therapy are key points to prevent and treat PC effectively and to improve their prognosis. In our study, expression profiles experiment of para-carcinoma, carcinoma and relapse human PC was performed using Agilent human whole genomic oligonucleotide microarrays with 45 000 probes. Differentially expressed genes related with PC were screened and analysed further by Gene Ontology term analysis and Kyoto encyclopaedia of genes and genomes pathway analysis. Our results showed that there were 3853 differentially expressed genes associated with pancreatic carcinogenesis and relapse. In addition, our study found that PC was related to the Jak-STAT signalling pathway, PPAR signalling pathway and Calcium signalling pathway, indicating their potential roles in pancreatic carcinogenesis and progress.
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Affiliation(s)
- Zheng-Yan Chang
- Veterinary Faculty, College of Veterinary Medicine, Hunan Agricultural University, Changsha, China
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