Lung metastases occur in up to 54% of patients with metastatic tumours. Contributing factors to this high frequency include the physical properties of the pulmonary system and a less oxidative environment that may favour the survival of cancer cells. Moreover, secreted factors from primary tumours alter immune cells and the extracellular matrix of the lung, creating a permissive pre-metastatic environment primed for the arriving cancer cells.
View Article and Find Full Text PDFBackground: Venous thromboembolism (VTE) is a frequent complication of childhood acute lymphoblastic leukemia (ALL).
Objectives: We aimed to identify molecular markers and signatures of leukemia microenvironment associated with VTE in childhood ALL, by dual-omics approach of gene expression (GEP) and DNA-methylation profiling.
Patients/methods: Eligible children were aged 1-21 years old with newly diagnosed ALL enrolled on the Dana Farber Cancer Institute 16-001 trial with available RNA sequencing data from bone marrow at diagnosis.
In targeted proteomics utilizing Selected Reaction Monitoring (SRM), the precise detection of specific peptides within complex mixtures remains a significant challenge, particularly due to noise and interference in chromatograms. Existing methodologies, such as isotopic labeling and scoring algorithms, offer partial solutions but are constrained by high run times and elevated false discovery rates. To address these limitations, we have developed ProPickML a machine learning-based tool designed to accurately identify peptide peaks across diverse data sets, independent of the assumed presence of the peptide.
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