Signaling state and abundance of circulating immune cell subpopulations determine cancer response to immunotherapy
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE130157 | GEO | 2020/06/09
REPOSITORIES: GEO
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Project description: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.
2017-12-20 | E-MTAB-6214 | biostudies-arrayexpress
Project description:<p>Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10<sup>-5</sup>) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10<sup>-6</sup>) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.</p>
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Project description:Systemic sclerosis is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects African Americans (AA). Additionally, monocytes show heightened activation in SSc, and in AA relative to European ancestry (EA) individuals. Monocytes are thus a good target tissue for elucidating disease mechanisms. In this study, we sought to identify differentially expressed genes in classical monocytes from AA SSc patients relative to unaffected AA controls. We performed RNAseq to profile the transcriptome on FACS-isolated classical monocytes (CD14++CD16-) from 16 female AA SSc cases and 18 female AA controls. We observed modest gene expression differences between cases and controls. The genes harboring the top differentially methylated cytosines are enriched for metabolic processes. The relatively modest differences in gene expression observed between patients and controls is consistent with prior evidence of stronger inflammatory signatures in AA.
2022-02-07 | GSE196070 | GEO
Project description:Cancer immunotherapy trials have produced encouraging results, but resistance remains a problem necessitating strategies to identify patients that benefit from immunotherapy alone or who require additional combinations like chemotherapy or radiotherapy. Here we employ single-cell transcriptomics and spatial proteomics to profile triple negative breast cancer biopsies taken before and after one cycle of pembrolizumab and after a second cycle of pembrolizumab given with radiotherapy. Non-responders lack immune infiltrate before and after therapy and exhibit minimal therapy-induced immune changes. Responding tumors form two groups that are distinguishable by a classifier prior to therapy, with one showing high MHC expression, evidence of tertiary lymphoid structures and displaying anti-tumor immunity before treatment. The other responder group resembles non-responders at baseline and mounts a maximal immune response after the combination therapy, which is characterized by cytotoxic T cell and antigen presenting myeloid cell interactions and is mirrored in murine breast tumors only after radiation.
2024-01-01 | GSE246613 | GEO
Project description:Systemic sclerosis is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects African Americans (AA). Additionally, monocytes show heightened activation in SSc, and in AA relative to European ancestry (EA) individuals. Monocytes are thus a good target tissue for elucidating disease mechanisms. In this study, we sought to investigate differentially methylated loci in classical monocytes from AA SSc patients and unaffected AA controls. We used Illumina’s MethylationEPIC BeadChip to profile DNA methylation patterns on FACS-isolated classical monocytes (CD14++CD16-) from 12 female AA SSc cases and 12 female AA controls. We observed modest DNA methylation differences between cases and controls. The genes harboring the top differentially methylated cytosines are enriched for immune pathways and metabolic processes. The relatively modest differences in DNA methylation observed between patients and controls is consistent with prior evidence of stronger inflammatory signatures in AA.
2022-02-07 | GSE196007 | GEO
Project description:Objectives: To predict response prior to anti-TNF treatment and comprehensively understand the mechanism how patients respond differently to anti-TNF treatment in rheumatoid arthritis (RA). Methods: Gene expression and/or DNA methylation profiling on PBMC, monocytes, and CD4+ T cells, from 80 RA patients before initiating either adalimumab (ADA) or etanercept (ETN) therapy was studied. After 6-month treatment response was evaluated according to the EULAR criteria of disease response. Differential expression and methylation analyses were performed to identify the response-associated transcriptional and epigenetic signatures. Machine learning models were built using these signatures by random forest algorithm to predict response prior to anti-TNF treatment and were further validated by a follow-up study. Results: Transcriptional signatures in ADA and ETN responders are divergent in PBMCs, and this phenomenon was reproduced in monocytes and CD4+ T cells. The genes upregulated in CD4+ T cells of ADA responders were enriched in the TNF signaling pathway, while very few pathways were differential in monocytes. Differential methylation positions (DMPs) of responders to ETN but not to ADA are majorly hypermethylated. The machine learning models to predict the response to ADA and ETN using differential genes reached overall accuracy of 85.9% and 79%, respectively. The models using DMPs reached overall accuracy of 84.7% and 88% for ADA and ETN, respectively. A follow-up study validated the high performance of these models. Conclusions: Machine learning models based on these molecular signatures could accurately predict response before ADA and ETN treatment, paving the path towards personalized anti-TNF treatment.
2020-08-24 | GSE138746 | GEO
Project description:Objectives: To predict response prior to anti-TNF treatment and comprehensively understand the mechanism how patients respond differently to anti-TNF treatment in rheumatoid arthritis (RA). Methods: Gene expression and/or DNA methylation profiling on PBMC, monocytes, and CD4+ T cells, from 80 RA patients before initiating either adalimumab (ADA) or etanercept (ETN) therapy was studied. After 6-month treatment response was evaluated according to the EULAR criteria of disease response. Differential expression and methylation analyses were performed to identify the response-associated transcriptional and epigenetic signatures. Machine learning models were built using these signatures by random forest algorithm to predict response prior to anti-TNF treatment and were further validated by a follow-up study. Results: Transcriptional signatures in ADA and ETN responders are divergent in PBMCs, and this phenomenon was reproduced in monocytes and CD4+ T cells. The genes upregulated in CD4+ T cells of ADA responders were enriched in the TNF signaling pathway, while very few pathways were differential in monocytes. Differential methylation positions (DMPs) of responders to ETN but not to ADA are majorly hypermethylated. The machine learning models to predict the response to ADA and ETN using differential genes reached overall accuracy of 85.9% and 79%, respectively. The models using DMPs reached overall accuracy of 84.7% and 88% for ADA and ETN, respectively. A follow-up study validated the high performance of these models. Conclusions: Machine learning models based on these molecular signatures could accurately predict response before ADA and ETN treatment, paving the path towards personalized anti-TNF treatment.
2020-08-24 | GSE138653 | GEO
Project description:Treatment of multiple sclerosis (MS) patients with sphingosine-1-phosphate receptor agonist fingolimod (FTY) increases for unknown reasons the risk for symptomatic reactivation of alpha-herpesviruses, in particular of varicella zoster virus (VZV), but not of other co-infecting herpesviruses (e.g. human cytomegalovirus (HCMV). To elucidate this specific signal in adverse events, we systematically assessed changes in global and herpesvirus-specific immune responses and signatures in MS patients before and during FTY therapy. In addition to phenotypical and functional changes, we thought to identify FTY-induced modifications on the gene expression level, which might add to perturbations in antiviral immune responses. Therefore, gene expression of CD4+ EM T cells and CD14+ monocytes were analyzed. These two subsets, CD4+ EM T cells and CD14+ monocytes, were isolated from PBMC of six female RRMS patients collected before (V0) and after 9 months of FTY therapy (V9) for RNA sequencing (RNASeq). Comparison of gene expression profiles of monocytes between V0 and V9 revealed 226 down- and 38 upregulated genes. Gene ontology categories and pathway analysis detected most significant alterations for genes involved in immune response, defense against viruses as well as type-1 interferon signaling pathways. Next, we compared gene expression profiles of CD4+ EM T cells collected at V0 and V9 of FTY therapy and found 314 down- and 219 upregulated genes. The most significantly modified pathways were involved in immune responses, including NK cell chemotaxis, cytotoxicity and antiviral responses. In summary, gene expression analysis of monocytes suggests that HCMV might be more susceptible to reactivation during FTY treatment because of FTY-induced modifications of immune control pathways important for HCMV latency. However, increased cytolytic potential of CD4+ EM T cells and expansion of HCMV-specific CD4+ T cells might counteract synthesis or release of viral particles and prevent viremia.
2023-12-21 | GSE120375 | GEO
Project description:Many studies have shown association of tumor infiltrating B-cells and presence of tertiary lymphoid structure with improved clinical responses to immune checkpoint inhibitors therapy. We hypothesized that their presence could also have an impact on TIL therapy response. To address this, we performed RNA-seq of FFPE samples from a cohort of patients that received TIL therapy. Melanoma tumors collected prior to TIL infusion were evaluated for immune content in 9 responders and 11 non-responders to TIL therapy. Our data demonstrate an increase in class-switched memory B-cells in responders compared with non-responders to TIL therapy. In the myeloid compartment, increased presence of dendritic cell populations (pDC, aDC, and iDC) and basophils was observed in responders to TIL therapy, as well as higher content of γδ T cells and effector memory CD8+ T cells (CD8+ Tem) in the T-cell compartment. Next, we assessed the TLS presence in the same cohort by a gene expression signature of 12 chemokines using principal component analysis. The responders showed a higher TLS score compared with the non-responder patients, suggesting that patients responding to TIL therapy had more TLS in their tumors than the non-responder patients. These observations indicate that, same as in the immune checkpoint inhibitors therapy response, presence of B-cells and TLS might have a positive impact in the clinical outcome to TIL therapy.
2024-06-30 | GSE217387 | GEO
Project description:Objective: Glucocorticoids (GC) have been a cornerstone of Rheumatoid arthritis (RA)-therapy for the last decades. However, about a third of RA-patients do not respond adequately. As monocytes and T-cells play an important role in RA-pathogenesis, the differential gene expression of these cells before pulse therapy with methylprednisolone was evaluated in order to find predictors for clinical response to GC. Methods: CD14-positive and CD4-positive cells were isolated by MACS sorting from five GC-Responders meeting the European League against Rheumatism (EULAR) response criteria and five Non-Responders. The clinical response was measured by disease activity score (DAS28) at the end of pulse therapy (3x 1000mg Methylprednisolone) at day 5. Cellular RNA was hybridized to Agilent 4x44K microarray chips and differentially expressed genes were calculated by MAANOVA. False discovery rate (FDR) was used as multiple testing correction. Selected genes were verified by quantitative real-time PCR (qPCR). Results: Eight genes were differentially regulated in CD14-cells and 4 genes in CD4-T-cells of GC-Responders compared to Non-Responders. Up-regulation of ERAP2 in monocytes and CD4-cells and LST1 and FAM26F in CD4-Tcells of GC-Responders was verified by qPCR and correlated with DAS28 at day 5 and (for LST1 and FAM26F) with smoking. Conclusion: As ERAP2 and LST1 are implicated in autoimmune disease, their increased expression in GC-Responders before GC-therapy may constitute not only a new tool for prediction of the clinical response to GC in RA, but also warrants further investigation to elucidate their role in the inflammatory process of RA.
2017-11-11 | GSE48823 | GEO