MDM2 inhibition enhances immune checkpoint inhibitor therapy in melanoma
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PROVIDER: PRJNA764915 | ENA |
REPOSITORIES: ENA
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Project description:Immune checkpoint therapy has improved outcome of patients with advanced melanoma, however the tumor becomes refractory in a large number of patients. Therefore, novel combination therapies that enhance anti-melanoma immunity are highly desirable. We studied the impact of MDM2 (mouse double minute 2) inhibition, leading to p53 activation, on response to anti-PD-1 immunotherapy in melanoma. MDM2 treatment caused upregulation of MHC II and IL-15 in melanoma cells in a p53 dependent manner. Survival of melanoma bearing mice improved upon combining anti-PD1 and MDM2 inhibition in vivo. Lack of IL-15Rα in T cells abrogated the beneficial effect of the combined treatment. This gene expression study was performed to determine potential effects of MDM2 inhibition on genes in the melanoma microenvironment.
2024-08-22 | GSE184524 | GEO
Project description:We performed single-cell RNA-sequencing of tumor immune infiltrates and matched peripheral blood mononuclear cells of checkpoint inhibitor (CPI)-naive stage III-IV metastatic melanoma patients. After sample collection, the same patients received CPI-treatment and their response was assessed.
2024-04-08 | E-MTAB-13770 | biostudies-arrayexpress
Project description:Immune checkpoint inhibitors (ICIs) have transformed the treatment of melanoma. However, the majority of patients have primary or acquired resistance to ICIs, limiting durable responses and patient survival. Interferon-gamma (IFNg) signaling and the expression of IFNg-stimulated genes correlate with either response or resistance to ICIs, in a context-dependent manner. While IFNg-inducible immunostimulatory genes are required for response to ICIs, chronic IFNg signaling induces the expression of immunosuppressive genes, promoting resistance to these therapies. Here, we show that high levels of ULK1 correlate with poor survival in melanoma patients and overexpression of ULK1 in melanoma cells enhances IFNg-induced expression of immunosuppressive genes, with minimal effects on the expression of immunostimulatory genes. In contrast, genetic or pharmacological inhibition of ULK1 reduces expression of IFNg-induced immunosuppressive genes. ULK1 binds IRF1 in the nuclear compartment of melanoma cells, controlling its binding to the PD-L1 promoter region. Additionally, pharmacological inhibition of ULK1 in combination with anti-PD-1 therapy further reduces melanoma tumor growth and enhances anti-tumor immune responses in vivo. Our data suggest that targeting ULK1 represses IFNg-dependent immunosuppression. These findings support the combination of ULK1 drug-targeted inhibition with ICIs for the treatment of melanoma patients to improve response rates and patient outcomes.
2023-02-02 | PXD035347 | Pride
Project description:Chemohormonal Therapy Remodels Prostate Cancer Immune Microenvironment and Enhances Checkpoint Inhibitor-based immunotherapy
| PRJNA798366 | ENA
Project description:Immune checkpoint blockade (ICB) therapy provides remarkable clinical gains, where melanoma is at the forefront of its success. However, only a subset of patients with advanced tumors currently benefit from these therapies, which at times incur considerable side-effects and costs. Constructing such predictors of patient’s response has remained a serious challenge due to the complexity of the immune response and the shortage of large ICB-treated patient cohorts including both omics and response data. Here we build IMPRES, a predictor of ICB-response in melanoma which encompasses 15 pairwise transcriptomics relations between immune checkpoint genes. It is based on two key conjectures: (a) immune mechanisms underlining spontaneous regression in neuroblastoma can predict ICB response in melanoma, and (b) key immune interactions can be captured via specific pairwise relations of immune checkpoint genes’ expression. IMPRES is validated on 9 published datasets1–6 and on a newly generated dataset of 31 tumor samples treated with anti-PD-1 and 10 tumor samples treated with anti-CTLA-4 (some of these are treated with both antibodies), spanning 297 samples in total. It achieves an overall accuracy of AUC=0.83, outperforming existing predictors, capturing almost all true responders while misclassifying less than half of the non-responders. Future studies are warranted to determine the value of the approach presented here in other cancer types.
2018-08-20 | GSE115821 | GEO
Project description:The clinical success of immune-checkpoint inhibitors (ICI) in both resected and metastatic melanoma has confirmed the validity of therapeutic strategies that boost the immune system to counteract cancer. However, half of patients with metastatic disease treated with even the most aggressive regimen do not derive durable clinical benefit. Thus, there is a critical need for predictive biomarkers that can identify individuals who are unlikely to benefit with high accuracy, so that these patients may be spared the toxicity of treatment without the likely benefit of response. Ideally, such an assay would have a fast turnaround time and minimal invasiveness. Here, we utilize a novel platform that combines mass spectrometry with an artificial intelligence-based data processing engine to interrogate the blood glycoproteome in melanoma patients before receiving ICI therapy. We identify 143 biomarkers that demonstrate a difference in expression between the patients who died within six months of starting ICI treatment and those who remained progression-free for three years. We then develop a glycoproteomic classifier that predicts benefit of immunotherapy (HR=2.7; p=0.026) and achieves a significant separation of patients in an independent cohort (HR=5.6; p=0.027). To understand how circulating glycoproteins may affect efficacy of treatment, we analyze the differences in glycosylation structure and discover a fucosylation signature in patients with shorter overall survival (OS). We then develop a fucosylation-based model that effectively stratifies patients (HR=3.5; p=0.0066). Together, our data demonstrate the utility of plasma glycoproteomics for biomarker discovery and prediction of ICI benefit in patients with metastatic melanoma and suggest that protein fucosylation may be a determinant of anti-tumor immunity.
2023-05-31 | MSV000092069 | MassIVE
Project description:Purpose: The clinical use of MEK inhibitors in uveal melanoma is limited by the rapid acquisition of resistance. The current study has used multi-omics approaches and drug screens to identify the pan-HDAC inhibitor panobinostat as an effective strategy to limit MEK inhibitor resistance. Experimental Design: Mass spectrometry-based proteomics and RNA-Seq was used to identify the signaling pathways involved in the escape of uveal melanoma cells from MEK inhibitor therapy. Mechanistic studies were performed to evaluate the escape pathways identified and the efficacy of the MEK-HDAC inhibitor combination was demonstrated in multiple in vivo xenograft models of uveal melanoma. Results: We identified a number of putative escape pathways that were upregulated following MEK inhibition including the PI3K/AKT pathway, ROR1/2 and IGF1R signaling. MEK inhibition was also associated with a widespread increase in GPCR expression, particularly the Endothelin B receptor and that this contributed to therapeutic escape through YAP signaling. A screen of 289 clinical grade compounds identified HDAC inhibitors as potential candidates that suppressed the adaptive YAP and AKT signaling that followed MEK inhibition. In vivo xenograft studies revealed the MEK-HDAC inhibitor combination to outperform either agent alone, leading to a long-term decrease of tumor growth and the suppression of adaptive PI3K/AKT and YAP signaling. Conclusions Together our studies have identified GPCR-mediated YAP activation and RTK-driven AKT signaling as key pathways involved in the escape of uveal melanoma cells from MEK inhibition. We further demonstrate that HDAC inhibition is a promising combination partner for MEK inhibitors in uveal melanoma.
2020-05-26 | PXD013988 | Pride
Project description:Checkpoint blockade immunotherapy is a promising strategy in cancer treatment, depending on a favorable preexisting tumor immune microenvironment. However, prostate cancer is usually considered as an immune “cold” tumor with the poor immunogenic response and low density of tumor-infiltrating immune cells. This research uses samples from prostate cancer patients showing that docetaxel-based chemohormonal therapy reprograms the immune microenvironment and increases tumor-infiltrating T cells. Mechanistically, docetaxel treatment activates the cGAS/STING pathway and induces the type I interferon signaling, which may boost T cell-mediated immune response. In a murine prostate cancer model, chemohormonal therapy sensitizes tumor-bearing mice to PD1-blockade therapy. These findings demonstrate that docetaxel-based chemohormonal therapy activates prostate cancer immunogenicity and acts cooperatively with anti-PD-1 checkpoint blockade, providing a combination immunotherapy strategy that would lead to better therapeutic benefit for prostate cancer.
2022-08-01 | GSE193898 | GEO
Project description:Defects in DNA damage responses may underlie genetic instability and malignant progression in melanoma. Cultures of normal human melanocytes (NHMs) and melanoma lines were analyzed to determine whether global patterns of gene expression could predict the efficacy of DNA damage cell cycle checkpoints that arrest growth and suppress genetic instability. NHMs displayed effective G1 and G2 checkpoint responses to ionizing radiation-induced DNA damage. A majority of melanoma cell lines (11/16) displayed significant quantitative defects in one or both checkpoints. Melanomas with B-RAF mutations as a class displayed a significant defect in DNA damage G2 checkpoint function. In contrast the epithelial-like subtype of melanomas with wildtype N-RAS and B-RAF alleles displayed an effective G2 checkpoint but a significant defect in G1 checkpoint function. RNA expression profiling revealed that melanoma lines with defects in the DNA damage G1 checkpoint displayed reduced expression of p53 transcriptional targets, such as CDKN1A and DDB2, and enhanced expression of proliferation-associated genes, such as CDC7 and GEMININ. A Bayesian analysis tool was more accurate than significance analysis of microarrays for predicting checkpoint function using a leave-one-out method. The results suggest that defects in DNA damage checkpoints may be recognized in melanomas through analysis of gene expression. Experiment Overall Design: Normal human melanocyte and melanoma cell lines w/wo mutations in B-raf or N-ras were treated with 1.5 Gy IR irridiartion for G1 and G2 checkpoint determination. RNA was isolated from exponentially growing cultures and applied for microarray hybridizaton with Agilent 44 K (G4112A) array.
2008-06-15 | E-GEOD-7469 | biostudies-arrayexpress
Project description:HDAC inhibition enhances the in vivo efficacy of MEK inhibitor therapy in uveal melanoma
| PRJNA525852 | ENA