Tumor DNA Methylation Profiles Enable Diagnosis, Prognosis Prediction, and Screening for Cervical Cancer.

Background: DNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.

Methods: The methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program.

Combined Identification of Novel Markers for Diagnosis and Prognostic of Classic Hodgkin Lymphoma.

Background: An effective diagnostic and prognostic marker based on the gene expression profile of classic Hodgkin lymphoma (cHL) has not yet been developed. The aim of the present study was to investigate potential markers for the diagnosis and prediction of cHL prognosis.

Methods: The gene expression profiles with all available clinical features were downloaded from the Gene Expression Omnibus (GEO) database.

Comprehensive Characterization of Cachexia-Inducing Factors in Diffuse Large B-Cell Lymphoma Reveals a Molecular Subtype and a Prognosis-Related Signature.

Background: Cachexia is defined as an involuntary decrease in body weight, which can increase the risk of death in cancer patients and reduce the quality of life. Cachexia-inducing factors (CIFs) have been reported in colorectal cancer and pancreatic adenocarcinoma, but their value in diffuse large B-cell lymphoma (DLBCL) requires further genetic research.

Methods: We used gene expression data from Gene Expression Omnibus to evaluate the expression landscape of 25 known CIFs in DLBCL patients and compared them with normal lymphoma tissues from two cohorts [GSE56315 ( = 88) and GSE12195 ( = 136)].

Prognostic and predictive value of a mRNA signature in peripheral T-cell lymphomas: A mRNA expression analysis.

Current international prognostic index is widely questioned on the risk stratification of peripheral T-cell lymphoma and does not accurately predict the outcome for patients. We postulated that multiple mRNAs could combine into a model to improve risk stratification and helping clinicians make treatment decisions. In this study, the gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database.

Prognostic Significance of β-Catenin Expression in Osteosarcoma: A Meta-Analysis.

β-catenin plays a crucial role in the progression of osteosarcoma. However, the clinical significance of β-catenin over-expression in osteosarcoma still remains unclear. Thus, we performed a meta-analysis of studies that evaluated the impact of β-catenin on metastasis and overall survival (OS) in osteosarcoma.

Platelet-lymphocyte ratio as a potential prognostic factor in gynecologic cancers: a meta-analysis.

Purpose: Cancer-related inflammation plays an important role in tumor development and progression. Platelet-lymphocyte ratio (PLR) has been studied as a biomarker for prognosis in gynecologic cancers. But, the results of previous studies were controversial, so we performed this meta-analysis.

Identification of key genes and pathways associated with classical Hodgkin lymphoma by bioinformatics analysis.

The current study aimed to explore the mechanisms associated with classic Hodgkin lymphoma (cHL) to identify novel diagnostic and therapeutic targets. The GES12453 microarray dataset was downloaded from the Gene Expression Omnibus database; the differentially expressed genes (DEGs) between cHL samples and normal B cell samples by were identified using the limma package. Gene ontology (GO) and pathway enrichment analysis of DEGs gene were performed.