Brain differential gene expression and blood cross-validation of a molecular signature of patients with major depressive disorder.

Introduction: The agreement between clinicians diagnosing major depressive disorder (MDD) is poor. The objective of this study was to identify a reproducible and robust gene expression marker capable of differentiating MDD from healthy control (HC) subjects.

Materials And Methods: Brain and blood gene expression datasets were searched, which included subjects with MDD and HC.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies.

Identification and Temporal Characterization of Features Associated with the Conversion from Mild Cognitive Impairment to Alzheimer's Disease.

Background: Diagnosing Alzheimer's disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications.

Objectives: The goals of this study were to identify features from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion.

A robust biomarker of differential correlations improves the diagnosis of cytologically indeterminate thyroid cancers.

The fine-needle aspiration of thyroid nodules and subsequent cytological analysis is unable to determine the diagnosis in 15 to 30% of thyroid cancer cases; patients with indeterminate cytological results undergo diagnostic surgery which is potentially unnecessary. Current gene expression biomarkers based on well-determined cytology are complex and their accuracy is inconsistent across public datasets. In the present study, we identified a robust biomarker using the differences in gene expression values specifically from cytologically indeterminate thyroid tumors and a powerful multivariate search tool coupled with a nearest centroid classifier.

Integration and comparison of different genomic data for outcome prediction in cancer.

Background: In cancer, large-scale technologies such as next-generation sequencing and microarrays have produced a wide number of genomic features such as DNA copy number alterations (CNA), mRNA expression (EXPR), microRNA expression (MIRNA), and DNA somatic mutations (MUT), among others. Several analyses of a specific type of these genomic data have generated many prognostic biomarkers in cancer. However, it is uncertain which of these data is more powerful and whether the best data-type is cancer-type dependent.

SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis.

Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians.

Galectin labeling of cells from paraffinized tissues may serve as a diagnostic tool in the detection and classification of thyroid carcinomas.

This study seeks to determine whether the relative levels of attachment to galectins 1 and 3 of cells from thyroid tissues embedded in paraffin blocks can differentiate thyroid tumors from normal tissues. A total of 48 thyroid paraffin sample blocks from 4 groups of patients were analyzed: 12 samples served as controls, 12 samples were from patients with thyroid adenoma, 12 samples were from patients with thyroid follicular carcinoma, and 12 samples were from patients with thyroid papillary carcinoma. The relative attachment of cells to galectins 1 and 3 antigens was determined using the InnoCyte™ ECM Cell Adhesion kit at different cell sample concentrations.