Research Paper Volume 15, Issue 20 pp 11588—11610
Immunobiological signatures and the emerging role of SPP1 in predicting tumor heterogeneity, malignancy, and clinical outcomes in stomach adenocarcinoma
- 1 Department of Gastroenterology, Rudong People’s Hospital, Rudong Hospital Affiliated to Nantong University, Nantong, China
- 2 Cancer Research Center Nantong, Nantong Tumor Hospital and Affiliated Tumor Hospital of Nantong University, Nantong, China
- 3 Department of Medical Imaging, Medical School of Nantong University, Nantong, China
- 4 Department of Engineering Training Center, Nantong University, Nantong, China
- 5 Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
Received: June 20, 2023 Accepted: October 2, 2023 Published: October 26, 2023
https://doi.org/10.18632/aging.205148How to Cite
Copyright: © 2023 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: Immunotherapy, as a form of immunobiological therapy, represents a promising approach for enhancing patients’ immune responses. This work aims to present innovative ideas and insights for prognostic assessment and clinical treatment of stomach adenocarcinoma (STAD) by leveraging immunobiological signatures.
Methods: We employed weighted gene co-expression network analysis (WGCNA) and unsupervised clustering analysis to identify hub genes. These hub genes were utilized to construct a prognostic risk model, and their impact on the tumor microenvironment (TME) and DNA variations was assessed using large-scale STAD patient cohorts. Additionally, we conducted transfection experiments with plasmids to investigate the influence of SPP1 on the malignancy of HGC27 and NCI-N87 cells.
Results: Unsupervised clustering of 12 immune-related genes (IRGs) revealed three distinct alteration patterns with unique molecular phenotypes, clinicopathological characteristics, prognosis, and TME features. Using LASSO and multivariate Cox regression analyses, we identified three hub genes (MMP12, SPP1, PLAU) from the IRGs to establish a risk signature. This IRG-related risk model significantly stratified the prognosis risk among STAD patients in the training (n = 522), testing (n = 521), and validation (n = 300) cohorts. Notably, there were discernible differences in therapy responses and TME characteristics, such as tumor purity and lymphocyte infiltration, between the risk model groups. Subsequently, a nomogram that incorporates the IRG signature and clinicopathological factors demonstrated superior sensitivity and specificity in predicting outcomes for STAD patients. Furthermore, down-regulation of SPP1, as observed after siRNA transfection, significantly inhibited the proliferation and migration abilities of HGC27 and NCI-N87 cells.
Conclusions: In summary, this study highlights the critical role of immune-related signatures in STAD and offers novel insights into prognosis indicators and immunotherapeutic targets for this condition. SPP1 emerges as an independent prognostic factor for STAD and appears to regulate STAD progression by influencing the immune microenvironment.
Abbreviations
GEO: Gene Expression Omnibus; TCGA: The Cancer Genome Atlas; STAD: stomach adenocarcinoma; GC: gastric cancer; MSCs: Mesenchymal stem cells; TPM: transcripts per kilobase million; WGCNA: weighted gene co-expression network analysis; IRGs: immune-related genes; OS: overall survival; GSVA: Gene Set Variation Analysis; DO: Disease Ontology; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; LASSO: least absolute shrinkage and selection operator; CAF: cell adhesion factor; TNM: tumor node metastasis; ROC: receiver operating characteristic; IPS: immunophenotype score; ICIs: immune checkpoint inhibitors; ICB: immune checkpoint blockade; TMB: tumor mutational burden; MSI: microsatellite instability; PCA: principal component analysis; TME: tumor microenvironment; PD-L1: programmed death ligand 1; CRC: colorectal cancer; MMR: tissue Repair system; PGs: pyroptosis-related genes; MMPs: Matrix metalloproteinases; ECM: the extracellular matrix; HNSCC: head and neck squamous cell carcinoma studies; EMT: epithelial stromal transformation.