E-MTAB-6214
Bulk RNA-seq validation experiments for "High dimensional single cell analysis predicts response to anti-PD-1 immunotherapy"
Immune checkpoint blockade has revolutionized cancer therapy. In particular, inhibition of programmed cell death protein 1 (PD-1) is effective for the treatment of metastatic melanoma and other cancers. Despite a dramatic increase in progression-free survival, a large proportion of patients do not show durable response. Therefore, predictive biomarkers of clinical response are urgently needed. Here, we employed high-dimensional single cell mass cytometry and a bioinformatics pipeline for the in-depth characterization of the immune cell subsets in the peripheral blood of  metastatic melanoma patients before and after anti-PD-1 immunotherapy. During therapy, we observed a clear treatment response to immunotherapy in the T cell compartment. However, prior to commending therapy a strong predictor of progression free and overall survival in response to anti-PD-1 immunotherapy was the frequency of CD14+CD16-HLA-DRhi monocytes. We could confirm this by conventional flow cytometry in an independent validation cohort and propose this as a novel predictive biomarker for therapy decisions in the clinic.  In order to determine whether there are cell intrinsic changes in the monocyte signature, we performed RNA sequencing on sorted CD14+CD16-HLA-DRhi cells from HD, NR and R at baseline.  Representative samples (n=4, each) of responders/non responders/ and healthy donors were selected from archival samples stored in the dermatology biobank according to the same clinical criteria used in the discovery and validation cohorts for CyTOF and FACS analysis. CD14+CD16-HLA-DRhiLin- (CD3, CD4, CD19, CD45RO) monocytes were sorted from frozen PBMC form blood samples from HD, R and NR at baseline.
Immune checkpoint blockade has revolutionized cancer therapy. In particular, inhibition of programmed cell death protein 1 (PD-1) is effective for the treatment of metastatic melanoma and other cancers. Despite a dramatic increase in progression-free survival, a large proportion of patients do not show durable response. Therefore, predictive biomarkers of clinical response are urgently needed. Here, we employed high-dimensional single cell mass cytometry and a bioinformatics pipeline for the in-depth characterization of the immune cell subsets in the peripheral blood of  metastatic melanoma patients before and after anti-PD-1 immunotherapy. During therapy, we observed a clear treatment response to immunotherapy in the T cell compartment. However, prior to commending therapy a strong predictor of progression free and overall survival in response to anti-PD-1 immunotherapy was the frequency of CD14+CD16-HLA-DRhi monocytes. We could confirm this by conventional flow cytometry in an independent validation cohort and propose this as a novel predictive biomarker for therapy decisions in the clinic.  In order to determine whether there are cell intrinsic changes in the monocyte signature, we performed RNA sequencing on sorted CD14+CD16-HLA-DRhi cells from HD, NR and R at baseline.  Representative samples (n=4, each) of responders/non responders/ and healthy donors were selected from archival samples stored in the dermatology biobank according to the same clinical criteria used in the discovery and validation cohorts for CyTOF and FACS analysis. CD14+CD16-HLA-DRhiLin- (CD3, CD4, CD19, CD45RO) monocytes were sorted from frozen PBMC form blood samples from HD, R and NR at baseline.