Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer
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ABSTRACT: Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGE‑A3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer.
Project description:Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEâA3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer. Patients were participants in two Phase II studies of the recombinant MAGEâA3 antigen combined with immunological adjuvants. mRNA from tumor samples (biopsies) collected before MAGE-A3 immunotherapy was analyzed by microarray hybridization and by quantitative polymerase chain reaction (qRT-PCR). The melanoma microarray dataset was used to discover and crossvalidate a gene expression signature and classifier discriminative of Responders (R) versus Non-Responders (NR) patients; the gene signature and classifier were then applied to an adjuvant lung cancer study. Patients that were not included for analysis are denoted as NE (Non-evaluable). GSK Biologicals
Project description:Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGE‑A3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer. Patients were participants in two Phase II studies of the recombinant MAGE‑A3 antigen combined with immunological adjuvants. mRNA from tumor samples (biopsies) collected before MAGE-A3 immunotherapy was analyzed by microarray hybridization and by quantitative polymerase chain reaction (qRT-PCR). The melanoma microarray dataset was used to discover and crossvalidate a gene expression signature and classifier discriminative of Responders (R) versus Non-Responders (NR) patients; the gene signature and classifier were then applied to an adjuvant lung cancer study. Patients that were not included for analysis are denoted as NE (Non-evaluable). GSK Biologicals
Project description:The interaction of frameshift mutation-derived cancer neoantigens and cancer immunotherapy remains unknown. We found that live cell adjuvant or cDNA transfection in the muscle, which express MHC-class I and class II-restricted non-self-peptides, generated broad-spectrum anti-tumor immunity. Such chimeric peptides did not need to be tumor-neoantigens, but must be in a single chain (complete T cell antigen: CTA). Long product of frameshift mutation frequently contained CTA and the colon cancer patients with the long frameshift products (>120 amino acids) showed a good prognosis. Mechanistically, live cell adjuvant expressing CTA strengthened crosstalk between dendritic cells and CD8+ T cells in a CD4+ T cells-dependent manner. This cross talk suppressed CD8+ T cell exhaustion and produced stem-cell like progenitor CD8+ T cells in vivo. Combination of the live cell adjuvant conversed unresponsive tumors to responsive to PD-1 blockade therapy. Together, our findings provide a new broad-spectrum cancer immunotherapy, and clarify the type of frameshift neoantigens controlling the efficacy.