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Prediction of response and adverse drug reaction of pemetrexed plus platinum-based chemotherapy in lung adenocarcinoma by serum metabolomic profiling. | LitMetric

Background: Pemetrexed plus platinum doublet chemotherapy regimen remains to be the standard first-line treatment for lung adenocarcinoma patients. However, few biomarkers can be used to identify potential beneficiaries with maximal efficacy and minimal toxicity. This study aimed to explore potential biomarker models predictive of efficacy and toxicity after pemetrexed plus platinum chemotherapy based on metabolomics profiling.

Methods: A total of 144 patients who received at least two cycles of pemetrexed plus platinum chemotherapy were enroled in the study. Serum samples were collected before initial treatment to perform metabolomics profiling analysis. Logistic regression analysis was performed to establish prediction models.

Results: 157 metabolites were found to be differentially expressed between the response group and the nonresponse group. A panel of Phosphatidylserine 20:4/20:1, Sphingomyelin d18:1/18:0, and Phosphatidic Acid 18:1/20:0 could predict pemetrexed and platinum chemotherapy response with an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.7968. 76 metabolites were associated with hematological toxicity of pemetrexed plus platinum chemotherapy. A panel incorporating triglyceride 14:0/22:3/22:5, 3-(3-Hydroxyphenyl) Propionate Acid, and Carnitine C18:0 was the best predictive ability of hematological toxicity with an AUROC of 0.7954. 54 differential expressed metabolites were found to be associated with hepatotoxicity of pemetrexed plus platinum chemotherapy. A model incorporating stearidonic acid, Thromboxane B3, l-Homocitrulline, and phosphoinositide 20:3/18:0 showed the best predictive ability of hepatotoxicity with an AUROC of 0.8186.

Conclusions: This study established effective and convenient models that can predict the efficacy and toxicity of pemetrexed plus platinum chemotherapy in lung adenocarcinoma patients before treatment delivery.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918859PMC
http://dx.doi.org/10.1016/j.tranon.2022.101393DOI Listing

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