Single-cell multi-omic analysis of fibrolamellar carcinoma reveals rewired cell-to-cell communication patterns and unique vulnerabilities.

Fibrolamellar carcinoma (FLC) is a rare malignancy disproportionately affecting adolescents and young adults with no standard of care. FLC is characterized by thick stroma, which has long suggested an important role of the tumor microenvironment. Over the past decade, several studies have revealed aberrant markers and pathways in FLC.

Improving real-world evaluation of patient- and physician-reported tolerability: niraparib for recurrent ovarian cancer (NiQoLe).

Background: Maintenance niraparib at an individualized starting dose (ISD) is established in platinum-sensitive recurrent ovarian cancer (PSROC). However, patients' perspectives on the burden of prolonged maintenance therapy have not been reported in prospective trials or routine practice.

Methods: In the real-life multicenter NiQoLe study, patients with PSROC received ISD maintenance niraparib.

Transcriptional reprogramming primes CD8+ T cells toward exhaustion in Myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME) is a severe, debilitating disease, with substantial evidence pointing to immune dysregulation as a key contributor to pathophysiology. To characterize the gene regulatory state underlying T cell dysregulation in ME, we performed multiomic analysis across T cell subsets by integrating single-cell RNA-seq, RNA-seq, and ATAC-seq and further analyzed CD8+ T cell subpopulations following symptom provocation. Specific subsets of CD8+ T cells, as well as certain innate T cells, displayed the most pronounced dysregulation in ME.

Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines.

Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computational framework incorporating a machine learning algorithm-MHCvalidator-to enhance mass spectrometry-based immunopeptidomics sensitivity.

Refining SARS-CoV-2 intra-host variation by leveraging large-scale sequencing data.

Understanding viral genome evolution during host infection is crucial for grasping viral diversity and evolution. Analyzing intra-host single nucleotide variants (iSNVs) offers insights into new lineage emergence, which is important for predicting and mitigating future viral threats. Despite next-generation sequencing's potential, challenges persist, notably sequencing artifacts leading to false iSNVs.