Towards designing improved cancer immunotherapy targets with a peptide-MHC-I presentation model, HLApollo.

Based on the success of cancer immunotherapy, personalized cancer vaccines have emerged as a leading oncology treatment. Antigen presentation on MHC class I (MHC-I) is crucial for the adaptive immune response to cancer cells, necessitating highly predictive computational methods to model this phenomenon. Here, we introduce HLApollo, a transformer-based model for peptide-MHC-I (pMHC-I) presentation prediction, leveraging the language of peptides, MHC, and source proteins.

Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity.

Antigen presentation on MHC class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce the efficacy of large-molecule drugs by triggering an anti-drug response. Significant progress has been made in pMHCII presentation modeling due to the collection of large-scale pMHC mass spectrometry datasets (ligandomes) and advances in machine learning.

Origins and Timing of Emerging Lesions in Advanced Renal Cell Carcinoma.

Unlabelled: Renal cell carcinoma (RCC) with venous tumor thrombus (VTT) arising from the primary tumor occurs in approximately 10% of cases and is thought to represent more advanced disease. The intravascular nature of VTT suggests that it may serve as a source for hematogenous metastases. RCC with VTT and distant metastasis provides unique opportunities to examine the origins and emergence timing of these distinct tumor lesions, and to identify molecular correlates with disease state.

Indication-specific tumor evolution and its impact on neoantigen targeting and biomarkers for individualized cancer immunotherapies.

Background: Individualized neoantigen-specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. It is assumed that clonal neoantigens are preferred targets for immunotherapy, but the distributions of clonal neoantigens are not well characterized across cancer types.

Methods: We combined multiregion sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients in order to characterize their globally clonal neoantigen content and factors that would impact neoantigen targeting.

SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays.

Hit selection from high-throughput assays remains a critical bottleneck in realizing the potential of omic-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs. The specific limitations of these individual approaches and the lack of a systematic way by which to integrate their rankings have contributed to limited overlap in the reported results from comparable genome-wide studies and costly inefficiencies in secondary validation efforts.

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues.

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly with many downstream assays such as next generation sequencing. Automated tissue dissection is a new methodology that automates and improves tumor enrichment in these common, low tumor content tissues by decreasing the user-dependent imprecision of traditional macro-dissection and time, cost, and expertise limitations of laser capture microdissection by using digital image annotation overlay onto unstained slides. Here, digital hematoxylin and eosin (H&E) annotations are used to target small tumor areas using a blade that is 250 µm in diameter in unstained formalin fixed paraffin embedded (FFPE) or fresh frozen sections up to 20 µm in thickness for automated tumor enrichment prior to nucleic acid extraction and whole exome sequencing (WES).

A small sustained increase in NOD1 abundance promotes ligand-independent inflammatory and oncogene transcriptional responses.

Small, genetically determined differences in transcription [expression quantitative trait loci (eQTLs)] are implicated in complex diseases through unknown molecular mechanisms. Here, we showed that a small, persistent increase in the abundance of the innate pathogen sensor NOD1 precipitated large changes in the transcriptional state of monocytes. A ~1.

Mutation position is an important determinant for predicting cancer neoantigens.

Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic.

Dual Roles for Ikaros in Regulation of Macrophage Chromatin State and Inflammatory Gene Expression.

Macrophage activation by bacterial LPS leads to induction of a complex inflammatory gene program dependent on numerous transcription factor families. The transcription factor Ikaros has been shown to play a critical role in lymphoid cell development and differentiation; however, its function in myeloid cells and innate immune responses is less appreciated. Using comprehensive genomic analysis of Ikaros-dependent transcription, DNA binding, and chromatin accessibility, we describe unexpected dual repressor and activator functions for Ikaros in the LPS response of murine macrophages.