Michal Bassani‐Sternberg

The paper identifies a large class of non-canonical cancer-germline antigens (ncCGAs) from lncRNAs and mRNA untranslated regions, showing their potential as immunotherapeutic targets.

The paper identifies 25% of 7,264 non-canonical open reading frames (ncORFs) as producing translated gene products, supported by over 3,000 peptides from 3.8 billion mass spectra.

This study identifies two immune archetypes in HRD tumors—immune-inflamed and immune-evasive—linked to chromosomal instability and lineage, informing biomarker-driven therapies.

The paper identifies immune phenotypes and myeloid cell networks in recurrent ovarian cancer that influence prognosis and immune environment reinstatement.

The paper uses phage display and machine learning to discover TCRs specific to cancer antigens, identifying functional TCRs from large repertoires.

The paper assesses MS-based identifications of unannotated human microproteins, finding large variation in reported proteins and PSM quality across studies.

This study shows that SMG6-dependent NMD prevents dsRNA accumulation and immunogenicity in HCC by maintaining dsRNA homeostasis and suppressing MHC-I-presented peptides.

This paper discusses the current state of research on non-canonical open reading frames (ORFs) and proposes standards for their investigation and reporting using Ribo-seq and proteomics.

The paper reanalyzes the contribution of proteasomal spliced peptides to the HLA-I ligandome and finds that only 2-4% of the ligandome may be explained by such peptides.

The paper identifies HLA-I binding motifs from peptidomics data to improve neo-antigen predictions and reveals allosteric regulation of HLA specificity.