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Flow Cytometry-based Assay for the Monitoring of NK Cell Functions
Published on: October 30, 2016
Prediction of Prognosis and Immunotherapy Response with a Novel Natural Killer Cell Marker Genes Signature in
Qinwen Li1, Xiaoyan Huang2, Youfang Zhao2
1Department of Orthopedics, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China.
Abstract:
Natural killer (NK) cells are characterized by their antitumor efficacy without previous sensitization, which have attracted attention in tumor immunotherapy. The heterogeneity of osteosarcoma (OS) has hindered therapeutic application of NK cell-based immunotherapy. The authors aimed to construct a novel NK cell-based signature to identify certain OS patients more responsive to immunotherapy. A total of eight publicly available datasets derived from patients with OS were enrolled in this study. Single-cell RNA sequencing data obtained from the Gene Expression Omnibus (GEO) database were analyzed to screen NK cell marker genes. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was used to construct an NK cell-based prognostic signature in the TARGET-OS dataset. The differences in immune cell infiltration, immune system-related metagenes, and immunotherapy response were evaluated among risk subgroups. Furthermore, this prognostic signature was experimentally validated by reverse transcription-quantitative real-time PCR (RT-qPCR). With differentially expressed NK cell marker genes screened out, a five-gene NK cell-based prognostic signature was constructed. The prognostic predictive accuracy of the signature was validated through internal clinical subgroups and external GEO datasets. Low-risk OS patients contained higher abundances of infiltrated immune cells, especially CD8 T cells and naive CD4 T cells, indicating that T cell exhaustion states were present in the high-risk OS patients. As indicated from correlation analysis, immune system-related metagenes displayed a negative correlation with risk scores, suggesting the existence of immunosuppressive microenvironment in OS. In addition, based on responses to immune checkpoint inhibitor therapy in two immunotherapy datasets, the signature helped predict the response of OS patients to anti-programmed cell death protein 1 (PD-1) or anti-programmed cell death ligand 1 (PD-L1) therapy. RT-qPCR results demonstrated the roughly consistent relationship of these five gene expressions with predicting outcomes. The NK cell-based signature is likely to be available for the survival prediction and the evaluation of immunotherapy response of OS patients, which may shed light on subsequent immunotherapy choices for OS patients. In addition, the authors revealed a potential link between immunosuppressive microenvironment and OS.
Insights
A new five-gene natural killer (NK) cell signature predicts osteosarcoma (OS) patient survival and response to immunotherapy. This signature may guide treatment decisions for OS patients by identifying those likely to benefit from immune checkpoint inhibitors.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Natural killer (NK) cells show promise in tumor immunotherapy due to their inherent antitumor activity.
- Osteosarcoma (OS) heterogeneity complicates NK cell-based immunotherapy efficacy.
- Developing predictive biomarkers is crucial for optimizing OS treatment strategies.
Purpose of the Study:
- To construct and validate a novel NK cell-based prognostic signature for osteosarcoma (OS).
- To assess the signature's ability to predict patient survival and response to immunotherapy.
- To explore the relationship between the NK cell signature, immune microenvironment, and OS progression.
Main Methods:
- Analysis of single-cell RNA sequencing data from eight public OS datasets (GEO database).
- Construction of a prognostic signature using LASSO Cox regression on the TARGET-OS dataset.
- Evaluation of immune cell infiltration, metagenes, and immunotherapy response across risk subgroups.
- Experimental validation using reverse transcription-quantitative real-time PCR (RT-qPCR).
Main Results:
- A five-gene NK cell-based prognostic signature was developed and validated.
- Low-risk patients exhibited higher immune cell infiltration (e.g., CD8 T cells), while high-risk patients showed signs of T cell exhaustion.
- The signature correlated negatively with immune metagenes, suggesting an immunosuppressive OS microenvironment.
- The signature effectively predicted patient response to anti-PD-1/PD-L1 immunotherapy.
Conclusions:
- The NK cell-based signature serves as a valuable tool for predicting OS patient survival and immunotherapy response.
- This signature may inform clinical decisions regarding immunotherapy choices for osteosarcoma.
- A potential link between an immunosuppressive microenvironment and osteosarcoma was identified.
