Microarray Analysis of Peripheral Blood Mononuclear Cells (PBMC) in Renal Cell Carcinoma (RCC) Patients Undergoing Immunotherapy - Exploring the Secret to Successful Immunotherapy

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Background:
Successful immunotherapy is directly dependent on the function of immune effector cells. RCC is known to have impact on immune effector cells function. We analyzed gene expression profiles of immune effector cells in patients with metastatic RCC treated in a Phase II autologous dendritic cell vaccine trial.
Methods: Patients were divided into responders (R; complete and partial, n=6) and non-responders (NR; stable and progressive disease, n=5) and compared with healthy age-matched donors (HD, n=5). Patients underwent leukapheresis prior to vaccine preparation and lymphocytes were isolated by elutriation. Lymphocyte RNA was isolated using the Qiagen kit and hybridized to 25-mer, whole genome Human Gene 1.0 ST Array (Affymetrix). After normalization, statistical analysis was performed using fold change and t-test. Genes of interest were further analyzed using Ingenuity Pathway Analysis.
Results: When compared to healthy donors (HD), RCC patients were found to have 2078 genes with p<0.001, fold change>1.6 differentially expressed. These were mostly upregulated. Among these were 18 genes associated with PDGF signaling (CSNK2B, EIF2AK2, GRB2, etc.), 34 genes assiciated with immunological disease (APOD, GBP1, IFI44, IFI6, Ifn gamma, IL10RA, IL10RB, IL27RA, IL2RA, IRF1, LY6E, etc.) and 34 genes associated with posttranslational modification and tumor developement (ANXA4, AP1GBP1, CTBS, DDX18, EIF3D, ERAP1, FAM129A, SQRDL (includes EG:58472), SSBP2, TADA2L, TIMM23, TRIP12, VDAC2, etc.). When treatment effect was evaluated in samples prior to treatment compared to post-treatment, 114 genes were up- or down regulated upon treatment (p<0.001, FC>2). Genes of interest were 14 molecules associated with the immune system and the hematological system (BCL11A, BCL6, BLK, CCL1, CCL3, FCER2, IGH-3, IGH@, IGHA1, IGHM, IGK-V28, IGK@, IGKC, IGL@, IGLL1, IL2RA, etc.). When responders were compared to non-responders at baseline prior to treatment, only few genes were expressed differentially. Genes associated with antigen presentation were upregulated (p<0.01, FC>1.3) in responding patients compared with non-responders (HLA-A, HLA-DPB1). In non-responding patients, genes for tumor development and growth inhibitory deficiency were up-regulated in comparison to non-responders (HMGB1, STX2, etc.). Post-treatment, 42 genes were differentially regulated between R and NR (p<0.001, FC > 2). These included genes associated with cancer genesis and immune response (Ap1, HBA1, HBB (includes EG:3043), IL17B, IL17C, IL1B, IRG1, KLF7, LY6E, MHC CLASS I D2D ANTIGEN, etc.). In addition, genes associated with NK-cell signaling (KIR2DS2, KIR2DS4) were up-regulated in R. Genes for inflammatory diseases (CRLF2, MS4A1, HLA-DQA1, etc.), immune response (KIR3DL1, AIM2, MS4A1, etc.) and among those for B cell receptor signaling (CD19, JUN, CD22, NFATC2, etc.), and IL-4 signaling (HLA-DQB1, NFATC2, etc.) were strongly up-regulated in R.
Conclusions:
In conclusion, this study represents the most comprehensive analysis of gene expression in immune effector cells of kidney cancer patients. The analysis of this vast amount of data is challenging, yet early results demonstrate a distinct difference in the genetic profile of these cells between healthy donors and RCC patients, as well as between responders and non-responders. Finally, genetic changes in the effector cells throughout immunotherapy were evident.

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