Lung cancer survivors are at high risk of developing a SPLC and the factors that contribute to this risk have not been established.
In a pilot case-control study, a team led by Dr. Summer Han with Stanford University School of Medicine in California examined the potential for using serum metabolomics to identify metabolite biomarkers that differ between SPLC and IPLC.
They applied an untargeted metabolomics approach based on ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) to serum samples of 82 SPLC cases and 82 IPLC controls enrolled in the Boston Lung Cancer Study.
They identified two metabolites that were significantly associated with SPLC: 5-methylthioadenosine (5-MTA; odds ratio, 2.04) and phenylacetylglutamine (OR, 2.65). Levels of each metabolite were roughly 1.5-fold higher in SPLC cases than IPLC controls.
The researchers developed a risk-prediction model integrating the metabolomics data with key clinical features.
In stratifying the study participants across quartiles of estimated SPLC risk, the risk-prediction model identified a significantly higher proportion of SPLC cases in the highest-risk quartile compared to the lowest-risk quartile (68% vs. 39%; P=0.044).
This suggests that a risk-prediction model based on the selected metabolites could potentially distinguish between SPLC cases and IPLC controls, the researchers say in the journal Lung Cancer.
They call for prospective validation studies to evaluate the potential for leveraging metabolomics in SPLC surveillance and screening. They also note that the mechanisms through which these candidate metabolomic biomarkers relate to SPLC are unknown.
This work had no commercial funding.
SOURCE: https://bit.ly/2OwPBPS Lung Cancer, online March 11, 2021.
By Reuters Staff
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