Advances in methylation analysis of liquid biopsy in early cancer detection of colorectal and lung cancer.

Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I-IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I-IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I-IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis.Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.

Fungal kinases and transcription factors regulating brain infection in Cryptococcus neoformans.

Cryptococcus neoformans causes fatal fungal meningoencephalitis. Here, we study the roles played by fungal kinases and transcription factors (TFs) in blood-brain barrier (BBB) crossing and brain infection in mice. We use a brain infectivity assay to screen signature-tagged mutagenesis (STM)-based libraries of mutants defective in kinases and TFs, generated in the C. neoformans H99 strain. We also monitor in vivo transcription profiles of kinases and TFs during host infection using NanoString technology. These analyses identify signalling components involved in BBB adhesion and crossing, or survival in the brain parenchyma. The TFs Pdr802, Hob1, and Sre1 are required for infection under all the conditions tested here. Hob1 controls the expression of several factors involved in brain infection, including inositol transporters, a metalloprotease, PDR802, and SRE1. However, Hob1 is dispensable for most cellular functions in Cryptococcus deuterogattii R265, a strain that does not target the brain during infection. Our results indicate that Hob1 is a master regulator of brain infectivity in C. neoformans.