Proteomic profiles of thyroid tumors by mass spectrometry-imaging on tissue microarrays.

The current study proposes the successful use of a mass spectrometry-imaging technology that explores the composition of biomolecules and their spatial distribution directly on-tissue to differentially classify benign and malignant cases, as well as different histotypes. To identify new specific markers, we investigated with this technology a wide histological Tissue Microarray (TMA)-based thyroid lesion series. Results showed specific protein signatures for malignant and benign specimens and allowed to build clusters comprising several proteins with discriminant capabilities.

A Support Vector Machine Classification of Thyroid Bioptic Specimens Using MALDI-MSI Data.

Biomarkers able to characterise and predict multifactorial diseases are still one of the most important targets for all the "omics" investigations. In this context, Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has gained considerable attention in recent years, but it also led to a huge amount of complex data to be elaborated and interpreted. For this reason, computational and machine learning procedures for biomarker discovery are important tools to consider, both to reduce data dimension and to provide predictive markers for specific diseases.

Proteomics in thyroid cytopathology: Relevance of MALDI-imaging in distinguishing malignant from benign lesions.

Several proteomic strategies are used extensively for the purpose of biomarker discovery and in order to obtain insights into the molecular aspects of cancers, using either body fluids or tissue as samples. Among them, MALDI-imaging can be applied to cytological thyroid specimens to investigate the molecular signatures of different pathological conditions and highlight differences in the proteome that are of relevance for diagnostic and pathogenetic research. In this study, 26 ex-vivo fine needle aspirations from benign thyroid nodules (n = 13) and papillary thyroid carcinomas (n = 13) were analyzed by MALDI-imaging.

α-1-Antitrypsin detected by MALDI imaging in the study of glomerulonephritis: Its relevance in chronic kidney disease progression.

Idiopathic glomerulonephritis (GN), such as membranous glomerulonephritis, focal segmental glomerulosclerosis (FSGS), and IgA nephropathy (IgAN), represent the most frequent primary glomerular kidney diseases (GKDs) worldwide. Although the renal biopsy currently remains the gold standard for the routine diagnosis of idiopathic GN, the invasiveness and diagnostic difficulty related with this procedure highlight the strong need for new diagnostic and prognostic biomarkers to be translated into less invasive diagnostic tools. MALDI-MS imaging MALDI-MSI was applied to fresh-frozen bioptic renal tissue from patients with a histological diagnosis of FSGS (n = 6), IgAN, (n = 6) and membranous glomerulonephritis (n = 7), and from controls (n = 4) in order to detect specific molecular signatures of primary glomerulonephritis.

Tumor size, stage and grade alterations of urinary peptidome in RCC.

Background: Several promising biomarkers have been found for RCC, but none of them has been used in clinical practice for predicting tumour progression. The most widely used features for predicting tumour aggressiveness still remain the cancer stage, size and grade. Therefore, the aim of our study is to investigate the urinary peptidome to search and identify peptides whose concentrations in urine are linked to tumour growth measure and clinical data.