Abstract
Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.
Highlights
Despite extensive research over the past decade to improve lung cancer (LuCa) detection and treatment, LuCa presents persistent clinical challenges
Inspired by the achievements in genomics, proteomics, and transcriptomics, cancer metabolomics, which reflect the functional read-outs of these upstream biological processes, can yield measures of global metabolite profiles associated with various metabolic pathways influenced by oncological developments
These analyses were carried out with the special technique of high resolution magic angle spinning magnetic resonance spectroscopy (HRMAS MRS), which we developed for metabolomic analysis of intact biological tissue[22,23] and complex fluids
Summary
Despite extensive research over the past decade to improve lung cancer (LuCa) detection and treatment, LuCa presents persistent clinical challenges. LuCa is usually diagnosed at late stages, with >70% of patients dying from the disease; the ratios for breast and prostate cancer are about 16% and 17%, respectively[1]. This reality is largely attributable to the lack of a widespread, early screening test for LuCa. In its absence, the vast majority of patients seeking medical advice for symptoms of LuCa harbour locally advanced or metastatic disease. While LDCT enables detection of small lung nodules, its implementation as a screening tool for the general population is not feasible. Inspired by the achievements in genomics, proteomics, and transcriptomics, cancer metabolomics, which reflect the functional read-outs of these upstream biological processes, can yield measures of global metabolite profiles associated with various metabolic pathways influenced by oncological developments
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