A robust CD8+ T cell-related classifier for predicting the prognosis and efficacy of immunotherapy in stage III lung adenocarcinoma

Abstract

Patients with stage III lung adenocarcinoma (LUAD) have significant survival heterogeneity, meanwhile, CD8+ T cell has a remarkable function in immunotherapy. Therefore, developing novel biomarkers based on CD8+ T cell can help evaluate the prognosis and guide the strategy of immunotherapy for patients with stage III LUAD. Thus, we abstracted twelve datasets from multiple online databases and grouped the stage III LUAD patients into training and validation sets. We then used WGCNA and CIBERSORT, while univariate Cox analysis, LASSO analysis, and multivariate Cox analysis were performed. Subsequently, a novel CD8+ T cell-related classifier including HDFRP3, ARIH1, SMAD2, and UPB1 was developed, which could divide stage III LUAD patients into high- and low-risk groups with distinct survival probability in multiple cohorts (all P < 0.05). Moreover, a robust nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its powerful predictive capacity. Besides, we detected the difference in immune cell subpopulations and evaluated the potential benefits of immunotherapy between the two risk subsets. Finally, we verified the correlation between the gene expression and CD8+ T cells included in the model by immunohistochemistry and validated the validity of the model in a real-world cohort. Overall, we constructed a robust CD8+ T cell-related risk model originally which could predict the survival rates in stage III LUAD. What’s more, this model suggested that patients in the high-risk group could benefit from immunotherapy, which has significant implications for accurately predicting the effect of immunotherapy and evaluating the prognosis for patients with stage III LUAD.

Immunotherapy efficacy predictive tool for lung adenocarcinoma based on neural network

“…Meanwhile, other researchers were dedicated to the information on the tumor microenvironment. Jinteng Feng et al constructed a nomogram associated with CD8 + T cells to predict survival rates and immunotherapy benefits of stage III LUAD patients (30). A moderate performance showed in an online database that their prediction model had approximately 0.649-0.709 AUC, but a survival difference between the two groups (highand low-risk groups) was not observed (30).…”

“…Jinteng Feng et al constructed a nomogram associated with CD8 + T cells to predict survival rates and immunotherapy benefits of stage III LUAD patients (30). A moderate performance showed in an online database that their prediction model had approximately 0.649-0.709 AUC, but a survival difference between the two groups (highand low-risk groups) was not observed (30). A similar study used the next-generation sequencing method mainly; these predictive models might be limited to being widely applied for lack of gene sequencing data, which might be too expensive for most patients.…”

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing

“…Many of these are neoantigens that induce tumor-specific immune responses. 32 – 34 Activated CD8+ T cells are responsible for tumor cell recognition and lysis, the mechanisms of which have been described in detail, involving the release of cytotoxic particles. Interestingly, in most tumors, invasive cytotoxic T cells express inhibitory receptors (e.g.…”

“…programed death-1 (PD-1), Tim-3, and Lag-3) whose function in physiological situations is to suppress the immune response when bound to their ligands. 32 – 34 In fact, many tumor cells can take advantage of this inhibitory mechanism and express multiple ligands (e.g. PD-L1, PD-L2) to help them escape T-cell attacks.…”

Low UPB1 Level Correlates With Poor Prognosis in Lung Adenocarcinoma

“…A previous report demonstrated the clinical relevance of UPB1 variants as an indicator of fluoropyrimidine-related toxicity in East Asians. Recent studies have shown that UPB1 plays a key role in various cancers, such as LUAD, 14 hepatocellular carcinoma (HCC), 15,16 and clear cell renal cell carcinoma. 13,17 A study revealed that UPB1 may be a protective factor in LUAD and that UPB1 expression is associated with CD8+ T cells.…”