Transl Lung Cancer Res. 2025 Sep 30;14(9):4112-4130. doi: 10.21037/tlcr-2025-350. Epub 2025 Sep 18.

ABSTRACT

Lung squamous cell carcinoma (LUSC), a predominant type of lung cancer, is marked by an unfavorable prognosis and limited therapeutic options. Unlike lung adenocarcinoma (LUAD), LUSC exhibits few driver mutations, resulting in minimal benefits from targeted therapies for these patients. Despite the transformative effects of immunotherapy on patient outcomes, only a subset of patients achieving durable responses. This heterogeneity in treatment outcomes is increasingly attributed to the complex feature of the tumor immune microenvironment (TIME) in LUSC. The TIME of LUSC is a highly dynamic ecosystem composed of diverse immune cell populations and stromal components that collectively foster an immune-evasive niche. Recent breakthroughs in multi-omics technologies, particularly single-cell RNA sequencing (scRNA-seq) and spatial omics, have provided unprecedented resolution in dissecting the cellular and molecular architecture of the TIME in LUSC. These technologies have enabled the identification of distinct immune cells and their spatial interactions with the tumor, shedding light on the mechanisms underlying immune evasion and resistance to immunotherapy. Building on these advancements, this review establishes a new classification of the TIME which may guide patient stratification and personalized immunotherapy. And we comprehensively offer a detailed examination of the principal characteristics and regulatory mechanisms of the TIME, highlighting potential immunotherapeutic strategies tailored to this distinct immunological context.

PMID:41133013 | PMC:PMC12541881 | DOI:10.21037/tlcr-2025-350

Transl Lung Cancer Res. 2025 Sep 30;14(9):3645-3658. doi: 10.21037/tlcr-2025-603. Epub 2025 Sep 25.

ABSTRACT

BACKGROUND: Lung cancer poses a major public health challenge, accounting for the highest cancer-related mortality worldwide. This study aimed to identify non-invasive biomarkers for the early detection of non-small cell lung cancer (NSCLC) risk.

METHODS: We randomly selected 150 incident NSCLC cases during follow-up from the Korean Cancer Prevention Study-II. Controls (n=150) were matched to cases by age, gender, and the time of blood collection. Non-targeted metabolite screening by ultra-high-performance liquid chromatography (UHPLC)/mass spectrometry (MS) was conducted on the pre-diagnostic biological samples. The 11 reported lung cancer-associated single-nucleotide polymorphisms (SNPs) in Koreans were extracted from DNA genotyping data of the study population. Metabolite markers related to NSCLC risk were identified through clustering using hierarchical density-based spatial clustering of applications with noise. The associations between smoking, dietary factors, and NSCLC were also examined.

RESULTS: Six discriminative serum metabolites were identified as having an association with NSCLC incidence. Notably, the relationship between specific metabolite levels and NSCLC risk differed by rs7086803 genotype. Smoking status and occupational exposures appear to influence specific metabolite profiles, while dietary vegetable intake may modulate the risk of NSCLC among smokers.

CONCLUSIONS: The meaningful biomarkers revealed in the current research could be used to enhance the predictive ability for NSCLC risk. Furthermore, we suggest that the protective role of dietary vegetables against NSCLC may be attenuated or absent in smokers.

PMID:41133005 | PMC:PMC12541849 | DOI:10.21037/tlcr-2025-603