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

Exp Mol Med. 2025 Jan 8. doi: 10.1038/s12276-024-01382-0. Online ahead of print.

ABSTRACT

Most cancer mutation profiling studies are laboratory-based and lack direct clinical application. For clinical use, it is necessary to focus on key genes and integrate them with relevant clinical variables. We aimed to evaluate the prognostic value of the dosage of the KRAS G12 mutation, a key pancreatic ductal adenocarcinoma (PDAC) variant and to investigate the biological mechanism of the prognosis associated with the dosage of the KRAS G12 mutation. In this retrospective cohort study, we analyzed 193 surgically treated patients with PDAC between 2009 and 2016. RNA, whole-exome, and KRAS-targeted sequencing data were used to estimate the dosage of the KRAS G12 mutant. Our prognostic scoring system included the mutation dosage from targeted sequencing ( > 0.195, 1 point), maximal tumor diameter at preoperative imaging ( > 20 mm, 1 point), and carbohydrate antigen 19-9 levels ( > 150 U/mL, 1 point). The KRAS mutation dosage exhibited comparable performance with clinical variables for survival prediction. High KRAS mutation dosages activated the cell cycle, leading to high mutation rates and poor prognosis. According to prognostic scoring systems that integrate mutation dosage with clinical factors, patients with 0 points had superior median overall survival of 97.0 months and 1-year, 3-year, and 5-year overall survival rates of 95.8%, 70.8%, and 66.4%, respectively. In contrast, patients with 3 points had worse median overall survival of only 16.0 months and 1-year, 3-year, and 5-year overall survival rates of 65.2%, 8.7%, and 8.7%, respectively. The incorporation of the KRAS G12 mutation dosage variable into prognostic scoring systems can improve clinical variable-based survival prediction, highlighting the feasibility of an integrated scoring system with clinical significance.

PMID:39779977 | DOI:10.1038/s12276-024-01382-0