Identification and characterization of a SARS-CoV-2 specific CD8+ T cell response with immunodominant features

The COVID-19 pandemic caused by SARS-CoV-2 is a continuous challenge worldwide, and there is an urgent need to map the landscape of immunogenic and immunodominant epitopes recognized by CD8+ T cells. Here, we analyze samples from 31 patients with COVID-19 for CD8+ T cell recognition of 500 peptide-HLA class I complexes, restricted by 10 common HLA alleles. We identify 18 CD8+ T cell recognized SARS-CoV-2 epitopes, including an epitope with immunodominant features derived from ORF1ab and restricted by HLA-A*01:01. In-depth characterization of SARS-CoV-2-specific CD8+ T cell responses of patients with acute critical and severe disease reveals high expression of NKG2A, lack of cytokine production and a gene expression profile inhibiting T cell re-activation and migration while sustaining survival. SARS-CoV-2-specific CD8+ T cell responses are detectable up to 5 months after recovery from critical and severe disease, and these responses convert from dysfunctional effector to functional memory CD8+ T cells during convalescence

Comprehensive analysis of cutaneous and uveal melanoma liver metastases

Background The profound disparity in response to immune checkpoint blockade (ICB) by cutaneous melanoma (CM) and uveal melanoma (UM) patients is not well understood. Therefore, we characterized metastases of CM and UM from the same metastatic site (liver), in order to dissect the potential underlying mechanism in differential response on ICB.Methods Tumor liver samples from CM (n=38) and UM (n=28) patients were analyzed at the genomic (whole exome sequencing), transcriptional (RNA sequencing) and protein (immunohistochemistry and GeoMx Digital Spatial Profiling) level.Results Comparison of CM and UM metastases from the same metastatic site revealed that, although originating from the same melanocyte lineage, CM and UM differed in somatic mutation profile, copy number profile, tumor mutational burden (TMB) and consequently predicted neoantigens. A higher melanin content and higher expression of the melanoma differentiation antigen MelanA was observed in liver metastases of UM patients. No difference in B2M and human leukocyte antigen-DR (HLA-DR) expression was observed. A higher expression of programmed cell death ligand 1 (PD-L1) was found in CM compared with UM liver metastases, although the majority of CM and UM liver metastases lacked PD-L1 expression. There was no difference in the extent of immune infiltration observed between CM and UM metastases, with the exception of a higher expression of CD163 (p<0.0001) in CM liver samples. While the extent of immune infiltration was similar for CM and UM metastases, the ratio of exhausted CD8 T cells to cytotoxic T cells, to total CD8 T cells and to Th1 cells, was significantly higher in UM metastases.Conclusions While TMB was different between CM and UM metastases, tumor immune infiltration was similar. The greater dependency on PD-L1 as an immune checkpoint in CM and the identification of higher exhaustion ratios in UM may both serve as explanations for the difference in response to ICB. Consequently, in order to improve current treatment for metastatic UM, reversal of T cell exhaustion beyond programmed cell death 1 blockade should be considered

Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial

The efficacy of programmed cell death protein 1 (PD-1) blockade in metastatic triple-negative breast cancer (TNBC) is low 1–5 , highlighting a need for strategies that render the tumor microenvironment more sensitive to PD-1 blockade. Preclinical research has suggested immunomodulatory properties for chemotherapy and irradiation 6–13 . In the first stage of this adaptive, non-comparative phase 2 trial, 67 patients with metastatic TNBC were randomized to nivolumab (1) without induction or with 2-week low-dose induction, or with (2) irradiation (3 × 8 Gy), (3) cyclophosphamide, (4) cisplatin or (5) doxorubicin, all followed by nivolumab. In the overall cohort, the objective response rate (ORR; iRECIST 14 ) was 20%. The majority of responses were observed in the cisplatin (ORR 23%) and doxorubicin (ORR 35%) cohorts. After doxorubicin and cisplatin induction, we detected an upregulation of immune-related genes involved in PD-1–PD-L1 (programmed death ligand 1) and T cell cytotoxicity pathways. This was further supported by enrichment among upregulated genes related to inflammation, JAK–STAT and TNF-α signaling after doxorubicin. Together, the clinical and translational data of this study indicate that short-term doxorubicin and cisplatin may induce a more favorable tumor microenvironment and increase the likelihood of response to PD-1 blockade in TNBC. These data warrant confirmation in TNBC and exploration of induction treatments prior to PD-1 blockade in other cancer types

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community