ABSTRACT
Neoadjuvant cisplatin-based chemotherapy is standard of care for muscle-invasive bladder cancer (MIBC). Immune checkpoint inhibition (ICI) alone, and ICI in combination with chemotherapy, have demonstrated promising pathologic response (Subject(s)
Deoxycytidine
, Gemcitabine
, Immunotherapy
, Neoadjuvant Therapy
, Urinary Bladder Neoplasms
, Humans
, Urinary Bladder Neoplasms/drug therapy
, Urinary Bladder Neoplasms/immunology
, Urinary Bladder Neoplasms/therapy
, Urinary Bladder Neoplasms/pathology
, Neoadjuvant Therapy/methods
, Deoxycytidine/analogs & derivatives
, Deoxycytidine/therapeutic use
, Deoxycytidine/administration & dosage
, Immunotherapy/methods
, Male
, Cisplatin/therapeutic use
, Cisplatin/administration & dosage
, Female
, Antibodies, Monoclonal, Humanized/therapeutic use
, Antineoplastic Combined Chemotherapy Protocols/therapeutic use
, Immune Checkpoint Inhibitors/therapeutic use
, Aged
, Middle Aged
, Neoplasm Invasiveness
, Interleukin-9/metabolism
, B7-H1 Antigen/metabolism
, Biomarkers, Tumor/blood
, Treatment Outcome
ABSTRACT
BACKGROUND: Platinum-based neoadjuvant chemotherapy (NAC) is standard for patients with muscle-invasive bladder cancer (MIBC). Pathologic response (complete: ypT0N0 and partial: Subject(s)
Cisplatin
, Urinary Bladder Neoplasms
, Humans
, Neoadjuvant Therapy/methods
, Gemcitabine
, Nivolumab/therapeutic use
, Proteomics
, Tumor Microenvironment
, Urinary Bladder Neoplasms/drug therapy
, Urinary Bladder Neoplasms/pathology
, Biomarkers, Tumor
, Muscles/pathology
, Immunotherapy
, Neoplasm Invasiveness
, Cystectomy
ABSTRACT
MOTIVATION: Elimination of cancer cells by T cells is a critical mechanism of anti-tumor immunity and cancer immunotherapy response. T cells recognize cancer cells by engagement of T cell receptors with peptide epitopes presented by major histocompatibility complex molecules on the cancer cell surface. Peptide epitopes can be derived from antigen proteins coded for by multiple genomic sources. Bioinformatics tools used to identify tumor-specific epitopes via analysis of DNA and RNA-sequencing data have largely focused on epitopes derived from somatic variants, though a smaller number have evaluated potential antigens from other genomic sources. RESULTS: We report here an open-source workflow utilizing the Nextflow DSL2 workflow manager, Landscape of Effective Neoantigens Software (LENS), which predicts tumor-specific and tumor-associated antigens from single nucleotide variants, insertions and deletions, fusion events, splice variants, cancer-testis antigens, overexpressed self-antigens, viruses, and endogenous retroviruses. The primary advantage of LENS is that it expands the breadth of genomic sources of discoverable tumor antigens using genomics data. Other advantages include modularity, extensibility, ease of use, and harmonization of relative expression level and immunogenicity prediction across multiple genomic sources. We present an analysis of 115 acute myeloid leukemia samples to demonstrate the utility of LENS. We expect LENS will be a valuable platform and resource for T cell epitope discovery bioinformatics, especially in cancers with few somatic variants where tumor-specific epitopes from alternative genomic sources are an elevated priority. AVAILABILITY AND IMPLEMENTATION: More information about LENS, including code, workflow documentation, and instructions, can be found at (https://gitlab.com/landscape-of-effective-neoantigens-software).
Subject(s)
Neoplasms , Male , Humans , Antigens, Neoplasm/genetics , Epitopes, T-Lymphocyte/genetics , Peptides , SoftwareABSTRACT
The role of B cells in antitumor immunity is becoming increasingly appreciated, as B cell populations have been associated with response to immune checkpoint blockade (ICB) in patients with breast cancer and murine models of breast cancer. Deeper understanding of antibody responses to tumor antigens is needed to clarify the function of B cells in determining response to immunotherapy. We evaluated tumor antigen-specific antibody responses in patients with metastatic triple negative breast cancer treated with pembrolizumab following low-dose cyclophosphamide therapy using computational linear epitope prediction and custom peptide microarrays. We found that a minority of predicted linear epitopes were associated with antibody signal, and signal was associated with both neoepitopes and self-peptides. No association was observed between signal presence and subcellular localization or RNA expression of parent proteins. Patient-specific patterns of antibody signal boostability were observed that were independent of clinical response. Intriguingly, measures of cumulative antibody signal intensity relative to immunotherapy treatment showed that the one complete responder in the trial had the greatest increase in total antibody signal, which supports a potential association between ICB-dependent antibody boosting and clinical response. The antibody boost in the complete responder was largely driven by increased levels of IgG specific to a sequence of N-terminal residues in native Epidermal Growth Factor Receptor Pathway Substrate 8 (EPS8) protein, a known oncogene in several cancer types including breast cancer. Structural protein prediction showed that the targeted epitope of EPS8 was in a region of the protein with mixed linear/helical structure, and that this region was solvent-exposed and not predicted to bind to interacting macromolecules. This study highlights the potential importance of the humoral immune response targeting neoepitopes as well as self epitopes in shaping clinical response to immunotherapy.
Subject(s)
Triple Negative Breast Neoplasms , Humans , Animals , Mice , Triple Negative Breast Neoplasms/drug therapy , Antibody Formation , Antibodies, Monoclonal, Humanized/pharmacology , Antibodies, Monoclonal, Humanized/therapeutic use , Cyclophosphamide/pharmacology , Cyclophosphamide/therapeutic use , Epitopes , Immune Checkpoint Inhibitors , Adaptor Proteins, Signal TransducingABSTRACT
Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (NCT02643043), UC-GENOME, is a genomic analysis and biospecimen repository study in 218 patients with metastatic urothelial carcinoma. Here we report on the primary outcome of the UC-GENOME-the proportion of subjects who received next generation sequencing (NGS) with treatment options-and present the initial genomic analyses and clinical correlates. 69.3% of subjects had potential treatment options, however only 5.0% received therapy based on NGS. We found an increased frequency of TP53E285K mutations as compared to non-metastatic cohorts and identified features associated with benefit to chemotherapy and immune checkpoint inhibition, including: Ba/Sq and Stroma-rich subtypes, APOBEC mutational signature (SBS13), and inflamed tumor immune phenotype. Finally, we derive a computational model incorporating both genomic and clinical features predictive of immune checkpoint inhibitor response. Future work will utilize the biospecimens alongside these foundational analyses toward a better understanding of urothelial carcinoma biology.