Project description:Clinical signs and radiographic findings of PDAC and pancreatitis are often indistinguishable, highlighting the need of a PDAC biomarker to be insensitive to pancreatitis. Therefore we validated a biomarker signature of 17-genes in this gene expression data containing PDAC, non-tumor pancreatic and pancreatitis of fresh-frozen and formalin-fixed paraffin-embedded tissues.
Project description:Diffuse large B-cell lymphoma (DLBCL) represents the most common subtype of malignant lymphoma and is heterogeneous with respect to morphology, biology, and clinical presentation.However, a robust prognostic factor based on cell biology of DLBCL has not yet been determined.To find the biomarker which may associate with clinical outcome in patients with DLBCL, microarray analysis was performed to screen a novel biomarker.
Project description:This SuperSeries is composed of the following subset Series: GSE27331: Gain of the oncostatin M receptor in cervical squamous cell carcinoma is associated with adverse clinical outcome [penn1Mb data] GSE27332: Gain of the oncostatin M receptor in cervical squamous cell carcinoma is associated with adverse clinical outcome [camb1Mb data] GSE27673: An integrated genomics approach for novel biomarker discovery in squamous cell cervical carcinoma Refer to individual Series
Project description:The validated use of biomarkers for clinical diagnostics and therapy necessitates the availability of a substantial number of high-quality samples, along with a complete set of clinical data. Establishing standards for sample collection, storage, and quality control is essential to reduce the variability of sample quality. This study evaluated the impact of a single freeze-and-thaw (FT) cycle on the quality of liquid nitrogen-stored clinical serum aliquots. This was achieved by data-independent acquisition mass spectrometry (DIA-MS) on a test cohort comprising 25 patients and 99 samples, and a validation cohort comprising 109 patients. Abundance differences of paired samples were assessed by employing biostatistics and bioinformatics approaches, including clustering analyses, linear mixed models, functional annotation, and machine learning. Following the library-free data analysis and implementation of strict data preprocessing, the relative abundance of 213 (pilot study) and 248 (validation study) human serum proteins were analyzed by comparing paired fresh (never frozen) and FT samples. The proteomic data demonstrated high quality and reproducibility. Of 30 target proteins observed in the pilot study, 11 proteins (36.6%) were successfully validated in the validation cohort. These targets exhibited significant changes (q-value <0.05) in measurable protein abundance after one FT cycle. A correlation analysis of the measured protein intensity and storage duration revealed no significant association between the two variables. Of the 11 validated FT-sensitive proteins, CP and IGHV6-1 were identified as potential biomarker candidates for discriminating between malignant and benign pancreatic disease patients. Distinct protein abundance patterns can be discerned between fresh serum samples and samples stored in liquid nitrogen. The findings of this study suggest that FT cycles are important pre-analytical impact factors and should be addressed during the translation of protein-based biomarkers into clinical use.
