Plasma Metabolomics as a Tool to Distinguish PET-positive Malignant From PET-positive Benign Nodules

Lung Cancer, Solitary Pulmonary Nodules

Pulmonary nodules, Lung cancer, Plasma metabolomics, 1H-NMR, HPLC

Positron emission tomography-computed tomography (PET-CT) is an important technique in lung cancer staging, where almost no lung lesion goes undetected. However, PET-CT often fails to discriminate between malignant and non-malignant PET-positive solitary pulmonary nodules (SPNs) with a specificity of only 23%. 40-50% of those patients are advised to repeat their CT after three to six months to follow up on their lesions' progression, delaying a clear and correct cancer diagnosis and subsequent therapy. In more than 10% of the patients with an SPN on the PET-CT scan, an uncertain lung cancer diagnosis based on the PET-positive lesion leads to surgery that appears to be unnecessary. This project aims to use the plasma glutamate concentration as a biomarker to complement PET-CT in the discrimination between malignant and non-malignant PET-positive SPNs. The investigators will validate a plasma glutamate determination by high- performance liquid chromatography (HPLC) since this test needs to be rapid, cheap, minimally invasive, and available in every hospital. In addition to the analysis of plasma glutamate, other plasma metabolites will be screened to check for other potential biomarkers to discriminate between malignant and non-malignant PET-positive SPNs. Together with the PET-CTs' basic parameters, a quick measurement of fasted plasma glutamate and potentially other biomarker levels right before undergoing a PET-CT scan will support a more rapid lung cancer diagnosis and treatment, resulting in less risk for disease progression. In conclusion, our approach will improve the accuracy of lung cancer diagnosis, and avoid unnecessary surgery.

PET-CT is an indispensable technique in lung cancer staging, where almost no lung lesion goes undetected since its sensitivity reaches 96%. However, PET-CT often fails to discriminate between malignant and non-malignant PET-positive SPNs with a specificity of only 23%. 40-50% of those patients are advised to repeat their CT after three to six months to follow up on their lesions' progression, delaying a clear and correct cancer diagnosis and subsequent therapy. More than 10% of the patients with a non-metastasized SPN on the PET-CT scan receive an unnecessary surgery due to this diagnostic uncertainty. Due to these current challenges, the investigators will be searching for metabolite biomarkers that allow discrimination between benign and malignant SPNs. Biomarkers are defined as characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathological processes, or pharmacological responses to therapeutic interventions. This research will focus on metabolomics-based/metabolite biomarkers, as metabolic reprogramming is one of the hallmarks of cancer cells. As soon as the disease arises, cancer cells will reprogram their metabolism in order to meet the increased proliferation rate and energy consumption. Changes in metabolism result in changes in the concentration of metabolic end-products, metabolites, both intra- and extracellular. This principle allows for the detection of malignant SPNs by measuring metabolite concentrations in plasma. The clinical applicability of metabolite biomarkers became clear from previously published work. Using proton nuclear magnetic resonance (1H-NMR) based metabolomics, a prior study of our research group demonstrated that a single plasma glutamate analysis could increase the PET-CT scans' discriminative specificity from 23% to 81% in a PET-positive patient population. However, further development and optimization are still needed to reach a clinical phase. This prospective study will not only study plasma glutamate levels, but also the plasma levels of 61 additional metabolites. These 61 additional metabolites were identified in plasma in a previous study performed by our research group using 1H-NMR. Several of these metabolites, including lactate, acetate, cysteine, and asparagine, have already been shown to significantly contribute to malignant processes. Besides including more metabolites compared to the previously performed glutamate study, a technique other than 1H-NMR will be used. Even though 1H-NMR is characterized by its non-destructive and fast sample preparation and quantitative nature, it is a very costly technique that is usually unavailable in most hospitals. As this study aims to find plasma metabolites that can serve as clinical biomarkers for the distinction between benign and malignant SPNs, a more widely available technique will be used, called high-performance liquid chromatography (HPLC). As the 61 metabolites of interest can be categorized into multiple chemical classes, such as amino acids and organic acids, different HPLC methods will be required. After the development of a suitable method for metabolite identification and quantification, plasma samples will be measured and metabolites will be quantified. By comparing metabolite concentrations in plasma samples derived from patients with a benign SPN and a malignant SPN, the investigators aim to find significant differences in metabolite concentrations between these two groups. Significantly altered metabolites could then potentially serve as plasma biomarkers for the distinction of benign and malignant SPNs, thereby improving diagnostic accuracy.

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