Cancer Immunotherapy and Biomarkers

The paper identifies RNA editing signatures that predict immunotherapy response in melanoma patients with high accuracy.

This paper identifies that immuno-positive neoantigens cluster in 3D genome regions and are enriched in active chromosomal compartments, suggesting 3D genome information can improve neoantigen prioritization.

The paper quantifies tumor immunogenicity using dN/dS ratios in the immunopeptidome and shows it predicts immunotherapy response by distinguishing adaptation from escape mechanisms.

The paper identifies cancer-specific driver gene mutations associated with immunotherapy outcomes in a multi-cancer cohort of 1,525 patients.

The paper shows that polygenic risk scores for skin autoimmunity affect the response to immune checkpoint blockade in bladder cancer, with higher vitiligo and psoriasis scores linked to better outcomes.

This paper critiques a previous study that claimed no neoantigen depletion signal in untreated cancer genomes, arguing that the study's methodology is flawed due to misalignment between defined HLA-binding regions and actual immunogenic neoantigens.

The paper develops a network-based approach to identify predictive biomarkers and therapeutic combinations for anti-PD-1 immunotherapy, finding genes and pathways associated with response and validating them through CRISPR and drug target data.

The paper analyzes gene correlations between metabolism and immunity in tumor and normal tissues, finding reduced correlations in tumors and identifying key gene pairs with potential therapeutic implications.

The paper identifies germline genetic features associated with immune infiltration in solid tumors using TCGA data and develops a framework for studying inherited factors influencing immune microenvironment.

neoANT-HILL improves neoantigen detection from NGS data by integrating immunogenomic analyses and was tested on melanoma TCGA somatic mutations.

The paper introduces the CSiN score to predict immunotherapy outcomes by assessing tumor neoantigen quality through clonality and immunogenicity, showing improved performance over existing methods.

This study identifies recurrent neoantigens in breast cancer by analyzing somatic mutations and their immunogenic potential through HLA recognition.

This study finds that 5% of breast cancers have high tumor mutation burden, more common in metastatic tumors, with APOBEC activity as the most common mutational process and potential benefit from PD-1 inhibitors.

The paper shows that genetic antigen loss in melanoma cells is selected for under T-cell therapy due to subclone fitness differences and stochastic events.

The paper quantifies immune-based counterselection of somatic mutations by analyzing their depletion in MHC class I-displayed peptides and shows that MHC alleles are incompletely dominant.

This paper evaluates TMB assessment methods in NSCLC using WES and FoundationOne CDx, finding high correlation between methods and parameter variations affecting results.

The paper develops a PMBT system to classify lung adenocarcinoma into four subtypes based on immune and stromal features, showing distinct molecular, cellular, and prognostic characteristics.

NeoPredPipe predicts and assesses neoantigen recognition potential from tumor variants in single and multi-region samples, providing insights into neoantigen burden and tumor heterogeneity.

The paper analyzes immuno-genomic data across 31 cancer types to identify immune escape mechanisms and immuno-editing histories.

The paper quantifies neoantigen depletion in cancer genomes and finds negligible depletion signals, suggesting weak or absent immunogenic negative selection.

This paper introduces a single-cell computational method to predict cancer immunotherapy response by analyzing CD8+ T cell exhaustion profiles.

The paper identifies cancer-associated T cells using TCR repertoire and gene expression data, revealing novel regulators and antigens with potential for immune monitoring and immunotherapy.

The paper identifies recurrent PD-L1 structural rearrangements and JAK3 mutations in NKTL patients achieving CR with PD-1 blockade therapy, suggesting genomic screening may improve patient selection.

The paper identifies common matrisome variations linked to tumor genotypes and immunophenotypes across cancers using a unified data resource.

This study identifies genomic and transcriptomic traits associated with immune-phenotypes in 9,403 solid tumors across 29 cancers, revealing patterns linked to immune evasion and tumor progression.

This study shows that neutral evolution dominates tumor shaping in a mouse CRC model, and PD-1/PD-L1 blockade enhances immunoediting and tumor homogeneity.

This paper reviews informatics techniques used in cancer immunotherapy, focusing on data analysis of tumors, immune microenvironment, and therapy development.

The paper introduces neoantigeR, a pipeline for identifying tumor-specific peptide epitopes (neoantigens) from sequencing data to aid in cancer immunotherapy.

This study explores factors influencing response and resistance to atezolizumab in urothelial cancer using multi-omic data, finding associations between TCR clonality and clinical outcomes.

Immunogenomic profiling of 8243 TCGA samples across 20 solid cancers yields an immune atlas and a random-forest-derived immunophenoscore stratifying melanoma responders to checkpoint blockade.