Abstract
BackgroundAlthough pemetrexed plus cis/carboplatin has become the most effective chemotherapy regimen for patients with advanced lung adenocarcinoma, predictive biomarkers are not yet available, and new tools to identify chemosensitive patients who would likely benefit from this treatment are desperately needed. In this study, we constructed and validated predictive peptide models using the serum peptidome profiles of two datasets.MethodsOne hundred eighty-three patients treated with first-line platinum-based pemetrexed treatment for advanced lung adenocarcinoma were retrospectively enrolled and randomized into the training (n = 92) or validation (n = 91) set, and pre-treatment serum samples were analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinProTools software. Serum peptidome profiles from the training set were used to identify potential predictive peptide biomarkers and construct a predictive peptide model for accurate group discrimination; which was then used to classify validation samples into “good” and “poor” outcome groups. The clinical outcomes of objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were analyzed based on the classification result.ResultsEight potential peptide biomarkers were identified. A predictive peptide model based on four distinct m/z features (2,142.12, 3,316.19, 4,281.94, and 6,624.02 Da) was developed based on the clinical outcomes of training set patients after first-line pemetrexed plus platinum treatment. In the validation set, the good group had significantly higher ORR (49.1% vs. 8.3%, P <0.001) and DCR (96.4% vs. 47.2%, P <0.001), and longer PFS (7.3 months vs. 2.7 months, P <0.001) vs. the poor group. However, the model did not predict OS (13.6 months vs. 12.7 months, P = 0.0675).ConclusionOur predictive peptide model could predict pemetrexed plus platinum treatment outcomes in patients with advanced lung adenocarcinoma and might thus facilitate appropriate patient selection. Further studies are needed to confirm these findings.
Highlights
Adenocarcinoma is the most common histological subtype of lung cancer, the leading cause of cancer-related deaths worldwide [1]
A predictive peptide model based on four distinct m/z features (2,142.12, 3,316.19, 4,281.94, and 6,624.02 Da) was developed based on the clinical outcomes of training set patients after first-line pemetrexed plus platinum treatment
A total of 183 patients with advanced lung adenocarcinoma who were treated with first-line pemetrexed plus platinum at the Affiliated Hospital of Academy of Military Medical Sciences from December 2012 to November 2014 were enrolled in this retrospective study
Summary
Adenocarcinoma is the most common histological subtype of lung cancer, the leading cause of cancer-related deaths worldwide [1]. The American Society of Clinical Oncology suggests that patients with advanced non-squamous nonsmall cell lung cancer (NSCLC) patients who are not suitable for targeted therapy or immunotherapy should receive a platinum-based combination of two cytotoxic drugs [2]. In this context, pemetrexed is one of the most effective agents when combined with cisplatin or carboplatin [3,4]. Pemetrexed plus cis/carboplatin has become the most effective chemotherapy regimen for patients with advanced lung adenocarcinoma, predictive biomarkers are not yet available, and new tools to identify chemosensitive patients who would likely benefit from this treatment are desperately needed. We constructed and validated predictive peptide models using the serum peptidome profiles of two datasets
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