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Tumor immunological phenotype signature-based high-throughput screening for the discovery of combination immunotherapy compounds

ABSTRACT: Tumor immunological phenotype signature-based high-throughput screening for the discovery of combination immunotherapy compounds

PROVIDER: PRJNA671726 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR12893300_1.fastq.gz	Fastqsanger.gz
	SRR12893300_2.fastq.gz	Fastqsanger.gz
	SRR12893301_1.fastq.gz	Fastqsanger.gz
	SRR12893301_2.fastq.gz	Fastqsanger.gz
	SRR12893302_1.fastq.gz	Fastqsanger.gz

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Tumor immunological phenotype signature-based high-throughput screening for the discovery of combination immunotherapy compounds

Project description:Immune checkpoint blockade (ICB) therapy intends to only benefit a fraction of cancer patients, and combination immunotherapy with a compound is a promising treatment to overcome this limitation. Here, a tumor immunological phenotype (TIP) gene signature and high throughput sequencing-based high throughput screening (HTS2) were combined to identify combination immunotherapy compounds. We firstly defined a TIP gene signature, which expression pattern distinguishes “cold” tumors from “hot” tumors, and predicts ICB response in cancer patients. Then, after screening thousands of compounds, we identified that aurora kinase inhibitors, including ENMD-2076 and TAK-901, could reprogram the expression pattern of TIP genes from “cold” tumor to “hot” tumor in triple negative breast cancer (TNBC) cells. The treatment of aurora kinase inhibitors on TNBC cells dramatically up-regulates expression of Th1 type chemokine genes CXCL10 and CXCL11, which promotes effective T cells infiltrating into tumor microenvironment and significantly improves anti-PD-1 efficacy in inhibiting the tumor growth of TNBC in preclinical models. Mechanistically, these aurora kinase inhibitors are mainly through inhibiting AURKA-STAT3 signaling pathway to stimulate the expression of CXCL10 and CXCL11. Our study established a high throughput strategy to discover candidate compounds for combination immunotherapy, and suggested the therapeutic potential of combining aurora kinase inhibitors with checkpoint blockade immunotherapy for the treatment of TNBC.

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Project description:Single-agent immunotherapy, such as immune checkpoint inhibition, has shown remarkable efficacy in selected cancer entities and individual patients. However, most patients fail to respond. This is likely due to diverse immunosuppressive mechanisms acting in a concerted way to suppress the host anti-tumor immune response reducing the efficacy of single-agent immunotherapy. Combination immunotherapy approaches that are effective in such poorly immunogenic tumors mostly rely on precise knowledge of immunological targets on tumor cells by vaccinations or antibodies engineered to directly target those. Thus, creating a target-agnostic combination immunotherapy that is effective in poorly immunogenic tumors for which an immunological target is not known is a major challenge. We show that combined adoptive cellular therapy (ACT) with lymphokine-activated killer cells (LAKs), cytokine-induced killer cells (CIKs), Vγ9Vδ2-T-cells (γδ-T-cells) and adaptive, tumor-specific T-cells (CTLs) display synergistic anti-tumor treatment effects, which is further enhanced by co-treatment with anti-PD1 antibodies. Most strikingly, combination of this ACT with anti-PD1 antibodies, local immunotherapy of agonists against Toll-like receptor 3, 7 and 9 and pre-ACT lymphodepletion, a protocol we named TRI-IT, eradicates established, poorly immunogenic tumors and induces durable anti-tumor immunity in a variety of poorly immunogenic syngeneic, autochthonous, as well as autologous humanized patient-derived models. Mechanistically, we show that TRI-IT co-activates adaptive cellular and humoral, as well as innate anti-tumor immune responses to mediate its anti-tumor effect without inducing off-target toxicity. Our data demonstrate the efficacy of a target-agnostic combination immunotherapy that eradicates and potentially cures established poorly immunogenic tumors.

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Project description:Genetically defined syngeneic mouse models of ovarian cancer as tools for the discovery of combination immunotherapy (Exome)

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