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Research Paper

Identification of molecular subtypes and prognostic model to reveal immune infiltration and predict prognosis based on immunogenic cell death-related genes in lung adenocarcinoma

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Pages 2566-2583 | Received 13 Apr 2023, Accepted 25 Dec 2023, Published online: 02 Jan 2024
 

ABSTRACT

Immunogenic cell death (ICD) has been increasingly indicated to be related to caners. However, ICD’s role in Lung adenocarcinoma (LUAD) is still not well investigated. Clinical data along with associated mRNA expression profiles from LUAD cases were collected in TCGA and GEO databases. 13 ICD-related genes were identified. Relations of ICD-related genes expression with prognosis of patients, tumor immune microenvironment (TIME) was analyzed. Then, candidate genes were identified and the prognostic signature were constructed. Afterwards, one nomogram incorporating those chosen clinical data together with risk scores were built. Finally, the effect of HSP90AA1, one gene of the prognostic signature, on LUAD cell were analyzed. Two clusters were identified, which were designated as the ICD-high or -low subtype according to ICD-related genes levels. ICD-high subgroup showed good prognosis, high immune cell infiltration degrees, and enhanced immune response signaling activity compared with ICD-low subtype. Moreover, we established and verified the risk signature based on ICD-related genes. High risk group predicted poor prognosis of LUAD independently and presented negative association with immune score and immune status. Furthermore, nomogram contributed to the accurate prediction of LUAD prognostic outcome. Finally, HSP90AA1 levels were remarkably elevated within tumor cells in comparison with healthy pulmonary epithelial cells. HSP90α, HSP90AA1 protein product, promoted growth, migration, and invasion of LUAD cells. Molecular subtypes and prognostic model were identified by incorporating ICD-related genes, and it was related to TIME and might be adopted for the accurate prediction of LUAD prognosis.

Abbreviation

GAPDH=

Glyceraldehyde Phosphate Dehydrogenase

CCK-8=

Cell Counting Kit-8

RT-qPCR=

Real-Time Quantitative Polymerase Chain Reaction

HMGB1=

High Mobility Group Box 1

FASLG=

Factor Related Apoptosis Ligand

PDIA3=

Protein Disulfide Isomerase A3

ANXA1=

Annexin-A1

HSP90AA1=

Heat shock protein HSP 90α

IFNG=

Interferon γ

TLR4=

Toll-Like Receptor 4

CXCL10=

C-X-C Motif Chemokine Ligand 10

CASP8=

caspase 8

BAX=

Bcl2 Associated X Protein

P2RX7=

Purinergic Receptor P2X

LGIC7=

Ligand Gated Ion Channel 7

TNF=

Tumor Necrosing Factor

CCL2=

Chemokine Ligand 2

ATP=

Adenosine-Triphosphate

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

Yinying Dong and Haijun Lu contributed to study conception, manuscript reviewing, and supervising. Hao Song, Mingjin Xu, Jian Liu were responsible for collecting and analyzing data. Xiao Yu, Qingfeng Chen, Xiangyin Sun and Qiuxiao Wang were in charge of manuscript drafting, table and figure drawing. Bin Zheng, Xiaomeng Ji and Ruimei Ren performed experiments. The authors agreed the final version for publication.

Data availability statement

All data utilized in this work can be acquired from corresponding authors on request.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15384101.2023.2300591.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China, grant number 81803058; the Chinese Society of Clinical Oncology, grant numberY-QL2019-0337; Chinese Postdoctoral Science Foundation, grant number 2022M711316; Natural Science Foundation of Shandong Province in China, grant number ZR2023MH102; Mount Tai Scholar Project Special Fund, NO.tsqn202211363; Special Fund for Qilu Health Leading Talent Cultivation Project.

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