Immune Signature Could Help Tailor Treatment Choices in NSCLC

A new analysis of immune-related genes in non–small cell lung cancer (NSCLC) has resulted in the identification of an immune signature that investigators say could help clinicians better understand an individual patient’s prognosis.

The report, published in Frontiers in Oncology, could also help guide clinical care, the authors said.

NSCLC is the most common type of lung cancer, and lung adenocarcinoma (LUAD) has become the most common subtype of NSCLC. Patients with NSCLC have a 5-year survival rate of just 18%, wrote the study authors.

One of the biggest developments in the treatment of NSCLC has been the development of immune checkpoint inhibitors, which target immune checkpoints such as programmed cell death protein 1 (PD-1) andprogrammed death-ligand 1 (PD-L1), among others. However, the investigators noted that only about 1 in 5 people with NSCLC respond to anti–PD-1/PD-L1 therapy, a problem that may be caused by the heterogeneity of the cancer type and its tumor microenvironment.

“Thus, regarding their prognostic potential in LUAD, the molecular events of tumor cell immunocyte interactions in LUAD microenvironments need to be further summarized, and the expression level of immune related genes (IRGs) in LUAD needs to be comprehensively explored,” they wrote.

They set out to do just that. First, they extracted the profiles of immune-related genes for patients with NSCLC from 3 databases. Next, they constructed coexpression modules and identified the hub genes of the modules that had the highest correlations with tumor samples. They then analyzed those results to see which hub genes seemed to play a role with tumor progression and cancer-associated immunology. Finally, they used Cox and Lasso regression analyses to screen prognostic signatures and develop a risk model, they said.

“Functional analysis showed that immune-related hub genes were involved in the migration, activation, response, and cytokine-cytokine receptor interaction of immune cells,” they wrote.

Most of the hub genes had high frequencies of amplifications, with MASP1 and SEMA5A having the highest rates, they said. M2 macrophages and naive B cells had a significantly negative correlation, they said, while CD8-positive T cells and activated CD4-positive memory T cells, naive B cells, and plasma cells had a positive correlation, they noted.

In terms of patient outcomes and overall survival (OS), the authors found several insights.

“Our results indicated that a high level of resting mast cell infiltration was associated with better prognosis, whereas a high level of activated mast cells was significantly related to worse OS,” they said.

The authors were able to develop and verify a prognostic immune signature. They said unsupervised hub gene clustering was used to create 2 NSCLC subgroups, and those 2 subgroups had distinct differences in tumor immune dysfunction and exclusion scores and in their sensitivity to several common cancer therapies.

They said their model would need to be validated using a larger number of clinical samples, but that the subgroups identified in their study may help clinicians choose the most appropriate therapeutic strategy.

“These findings suggested that our immune-related genes can provide clinical guidance for the diagnosis and prognosis of different immunophenotypes and facilitate the management of immunotherapy in NSCLC,” they concluded.

Reference

Han S, Jiang D, Zhang F, et al. A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer. Front Oncol. Published online January 30, 2023. doi:10.3389/fonc.2023.1095313