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KAT2B is an immune infiltration-associated biomarker predicting prognosis and response to immunotherapy in non‐small cell lung cancer

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Summary

Background. Over the past few years, dramatic breakthroughs in the field of tumor immunotherapy with immune checkpoint inhibitors (ICIs) have made a therapeutic revolution for non-small cell lung cancer (NSCLC). While only some patients present a favorable response to this treatment. It is urgent to explore the potential molecular mechanisms underlying the regulation of tumor immune microenvironment in the process of immunotherapy. Lysine acetyltransferase 2B (KAT2B) plays a crucial role in the regulation of gene expression at the post-transcriptional level by acetylation, and is associated with many types of cancer. Methods. RNA-sequencing data, genetic mutation data, and corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, then subjected to immune characteristics, gene expression, survival, genetic alteration, enrichment analyses. Results. KAT2B expression correlated positively with infiltrating levels of multiple immune cells and mRNA expression levels of immune checkpoint genes in NSCLC. Furthermore, KAT2B expression was downregulated in tumor tissues, and low KAT2B expression was associated with unsatisfactory efficacy of immune checkpoint blockade (ICB) and poor prognosis of patients with lung adenocarcinoma. Moreover, there were higher somatic genes mutation frequency in patients with low expression of KAT2B. Finally, functional enrichment analysis suggested that KAT2B was mainly linked to the regulation of immune cells and interferon − gamma (IFN-γ) mediated signaling pathways, response to IFN-γ, antigen processing and presentation. Conclusion. This is the first comprehensive study to disclose that KAT2B is correlated with immune infiltrates and may serve as a novel biomarker predicting prognosis and response to immunotherapy in NSCLC.

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Data availability

All data is available under reasonable request.

Abbreviations

CNA:

Copy number alteration

DEGs:

Differentially expressed genes

GEO:

Gene expression omnibus

GEPIA:

Gene expression profiling interactive analysis

GO:

Gene Ontology

GTEx:

Genotype-tissue expression

HAT:

Histone acetyltransferase

HDAC:

Histone deacetylases

ICIs:

Immune checkpoint inhibitors

IFN-γ:

Interferon − gamma

KAT2B:

Lysine acetyltransferase 2B

LUAD:

Lung adenocarcinoma

LUSC:

Lung squamous cell carcinoma

NSCLC:

Non-small cell lung cancer

OS:

Overall survival

DSS:

Disease specific survival

PCAF:

P300/CBP associating factor

PD-1:

Programmed death receptor 1

PD-L1:

Programmed death receptor ligand 1

PPI:

Protein–protein interaction

SCLC:

Small cell lung cancer

TCGA:

The cancer genome atlas

TIMER 2.0:

Tumor immune estimation resource, version 2

TME:

Tumor microenvironment

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Acknowledgements

We acknowledge the Oncomine, TCGA, GEO, GTEx, TIMER, TISIDB, GEPIA, and STRING databases for free use.

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Authors and Affiliations

  1. Haihe Clinical College of Tianjin Medical University, Tianjin, 300350, China

    Xue Zhou & Qi Wu

  2. Department of Nephrology, Tianjin Haihe Hospital, Tianjin, 300350, China

    Xue Zhou & Yuefeng Zhang

  3. Tianjin Third Central Hospital, Tianjin, 300170, China

    Ning Wang

  4. Department of Respiratory Medicine, Tianjin Haihe Hospital, Tianjin, 300350, China

    Hongzhi Yu

  5. Tianjin Institute of Respiratory Diseases, Tianjin, 300350, China

    Qi Wu

  6. Department of Respiratory Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China

    Qi Wu

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  1. Xue Zhou
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  2. Ning Wang
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  3. Yuefeng Zhang
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  4. Hongzhi Yu
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Contributions

Xue Zhou and Qi Wu contributed to the study conception, design, and data analysis. Ning Wang, Yuefeng Zhang, and Hongzhi Yu contributed to collection and integration of data, visualization and figure generation. Xue Zhou and Ning Wang wrote the manuscript.

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Correspondence to Qi Wu.

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Zhou, X., Wang, N., Zhang, Y. et al. KAT2B is an immune infiltration-associated biomarker predicting prognosis and response to immunotherapy in non‐small cell lung cancer. Invest New Drugs 40, 43–57 (2022). https://doi.org/10.1007/s10637-021-01159-6

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  • DOI: https://doi.org/10.1007/s10637-021-01159-6

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