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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http://dx.doi.org/10.1097/MD.0000000000021287 | DOI Listing |
Clin Transl Oncol
April 2024
Department of Breast Surgery, Beijing Tuberculosis and Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China.
Background: Diffuse large B-cell lymphoma (DLBCL) exhibits remarkable heterogeneity but still remains undiagnosed in identifying the subpopulation of DLBCL to predict the prognosis and guide clinical treatment.
Methods: Molecular subgroups were identified in gene expression data from GSE10846 by a consensus clustering algorithm. And gene set enrichment analysis, immune infiltration, and the proposed cell cycle algorithm were applied to explore the biological functions of different subtypes.
Breast Cancer Res Treat
June 2022
Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Road, Shanghai, 200032, People's Republic of China.
Am J Cancer Res
February 2021
Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Gene expression features that are valuable for pancreatic ductal adenocarcinoma (PDAC) prognosis are still largely unknown. We aimed to explore pivotal molecular signatures for PDAC progression and establish an efficient survival score to predict PDAC prognosis. Overall, 163 overlapping genes were identified from three statistical methods, including differentially expressed genes (DEGs), coexpression network analysis (WGCNA), and target genes for miRNAs that were significantly related to PDAC patients' overall survival (OS).
View Article and Find Full Text PDFTransl Cancer Res
November 2020
Department of Ultrasound, China-Japan Union Hospital of Jilin University, Changchun, China.
Background: The aim of the present study was to establish a prognostic model for the survival of children with osteosarcoma (OS).
Methods: The mRNA expression and clinical characteristics of pediatric patients with OS were extracted from the Therapeutically Available Research to Generate Effective Treatments (TARGET) database. After genes with differential mRNA expression were identified, univariate and multivariate Cox analyses were performed, and a prognostic model of pediatric OS was established.
Front Endocrinol (Lausanne)
May 2021
Department of Otorhinolaryngology, Head & Neck Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Though many patients with thyroid cancer may be indolent, there are still about 50% lymph node metastases and 20% the recurrence rates. There is still no ideal method to predict its relapse. In this study, we analyzed the gene transcriptome profiles of eight Gene Expression Omnibus (GEO), and next screened 77 commonly differential expressed genes.
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