The impact of DNA methylation on the cancer proteome.

Aberrant DNA methylation disrupts normal gene expression in cancer and broadly contributes to oncogenesis. We previously developed MethylMix, a model-based algorithmic approach to identify epigenetically regulated driver genes. MethylMix identifies genes where methylation likely executes a functional role by using transcriptomic data to select only methylation events that can be linked to changes in gene expression.

GeM-Pro: a tool for genome functional mining and microbial profiling.

Gem-Pro is a new tool for gene mining and functional profiling of bacteria. It initially identifies homologous genes using BLAST and then applies three filtering steps to select orthologous gene pairs. The first one uses BLAST score values to identify trivial paralogs.

Randomized Controlled Trial Comparing White Light with Near-Infrared Autofluorescence for Parathyroid Gland Identification During Total Thyroidectomy.

Background: Parathyroid glands are difficult to identify during total thyroidectomies, and accidental resection can lead to problematic postoperative hypocalcemia. Our main goals were to evaluate the effectiveness of using near-infrared light (NIRL) autofluorescence intraoperatively for parathyroid gland identification and to measure its impact on postoperative hypocalcemia incidence.

Study Design: Total thyroidectomies were performed on 170 patients with different thyroid pathologies, block-randomized (1:1) into 2 equal groups.

MethylMix 2.0: an R package for identifying DNA methylation genes.

Summary: DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements.

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas.

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smoking and/or human papillomavirus (HPV). SCCs harbor 3q, 5p, and other recurrent chromosomal copy-number alterations (CNAs), DNA mutations, and/or aberrant methylation of genes and microRNAs, which are correlated with the expression of multi-gene programs linked to squamous cell stemness, epithelial-to-mesenchymal differentiation, growth, genomic integrity, oxidative damage, death, and inflammation. Low-CNA SCCs tended to be HPV(+) and display hypermethylation with repression of TET1 demethylase and FANCF, previously linked to predisposition to SCC, or harbor mutations affecting CASP8, RAS-MAPK pathways, chromatin modifiers, and immunoregulatory molecules.

NSD1 inactivation defines an immune cold, DNA hypomethylated subtype in squamous cell carcinoma.

Chromatin modifying enzymes are frequently mutated in cancer, resulting in widespread epigenetic deregulation. Recent reports indicate that inactivating mutations in the histone methyltransferase NSD1 define an intrinsic subtype of head and neck squamous cell carcinoma (HNSC) that features pronounced DNA hypomethylation. Here, we describe a similar hypomethylated subtype of lung squamous cell carcinoma (LUSC) that is enriched for both inactivating mutations and deletions in NSD1.

Increased identification of parathyroid glands using near infrared light during thyroid and parathyroid surgery.

Background: Parathyroid gland (PG) identification during thyroid and parathyroid surgery is challenging. Accidental parathyroidectomy increases the rate of postoperative hypocalcaemia. Recently, autofluorescence with near infrared light (NIRL) has been described for PG visualization.

[Use of a bayesian approach to rate estimation and projection].

Objective: Apply and assess a Bayesian approach to projecting cancer mortality rates by fitting age-period-cohort (APC) models.

Methods: The Bayesian estimation method was applied to bladder cancer mortality data in Argentina. A second-order autoregressive model was adopted for a priori specification of APC model coefficients.