Integrative Serum Metabolic Fingerprints Based Multi‐Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification

Abstract

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.

A nomogram based on metabolic profiling to discriminate lung cancer among patients with lung nodules

“… 26 Metabolic reprogramming is considered one of the hallmarks of cancer. 7 In recent years, metabolic fingerprints have been used as early diagnostic markers of tumors, including for lung adenocarcinoma, 27 colorectal cancer, 28 breast cancer, 29 and early-stage gastric cancer. 30 The emergence of advanced tools such as metal-organic framework hybrids, 28 mass spectrometry, 29 plasmonic alloys, 30 and bionanoparticles 31 have greatly accelerated the use of metabolic fingerprints.…”

“…Various models for cancer management that use metabolic fingerprinting have also shown excellent diagnostic efficacy. [26][27][28][29][30][31] It is believed that the advancement of analytical techniques will also increase screening for early-stage cancers.…”

Targeting neddylation as a novel approach to lung cancer treatment (Review)

“…DCNL5 is overexpressed in LUSC and LUAD (74). This suggests that NEDD8 may be used as a serum metabolic fingerprint (SMF) for the diagnosis and treatment of lung cancer, and there are numerous platforms and methods based on SMF for the early detection of lung cancer (75,76).…”

Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicentre study

“…However, traditional MS analysis of biosamples usually calls for liquid/gas phase chromatography for enrichment and purification of metabolites to enhanced specificity and sensibility, affecting the analytical speed and capacity 24 25. In this regard, nanoparticle-enhanced laser desorption/ionisation-MS (NPELDI-MS) relies on nanoparticles of defined structures for selective recognition and trapping of metabolites in solid phase, as a promising alternative to liquid/gas phase chromatography 26–28…”