Tumorigenesis and development lead to metabolic remodelling to adapt to nutritional/metabolic stress in vivo, promoting malignant cell transformation and tumour evolution. Monitoring metabolite levels is important for tumour diagnosis and treatment. In this study, we identified 57 differential serum metabolites between the early-stage NSCLC group and the control group. We screened the significant differentially abundant metabolites according to the Brouta model, performed ROC analysis, and ultimately confirmed three differentially abundant metabolites, isoleucine, 5Z-dodecenoic acid and 9E-tetradecenoic acid. The ROC-AUCs of this panel in the discovery and validation cohorts were 0.95 and 0.88, respectively.
Fifty-seven different metabolites were involved in the FA and amino acid metabolic pathways and were especially enriched in the fatty acid synthesis pathway and branched-chain amino acid (BCAA) metabolism pathway. FAs are the major components of several lipids, including phospholipids, sphingolipids, and triglycerides, which play important roles in energy storage, membrane biosynthesis, signalling, and regulation of gene transcription17–19. In tumour cells, a high rate of de novo synthesis leading to the production of large amounts of monounsaturated fatty acids (MUFAs) is considered to be the 3rd most common typical tumour feature after alterations in glucose and glutamine metabolism19. Through scRNA-seq, Yin et al. reconfirmed that aberrant lipid metabolism is common in nontumorigenic cells, including fatty acid biosynthesis and unsaturated fatty acid biosynthesis, and further identified nine lipids as the most important features for early cancer detection through plasma untargeted lipidomics20. In the present study, 5Z-dodecenoic acid and 9E-tedecenoic acid were shown to be associated with the development of NSCLC, which, to our knowledge, has not been reported previously.
Amino acids, especially BCAAs (valine, leucine and isoleucine), play important roles in tumour development. Recent evidence suggests that altered gene expression related to BCAA metabolism is observed in various cancer types and is correlated with tumour aggressiveness and treatment resistance21,22. The TCGA database analysis showed that BCAA catabolic enzymes have prognostic value in NSCLC23. Studies have shown that changes in BCAA metabolism specifically affect the status of tumour cells and the systemic metabolism of individuals with malignant tumours. BCAAs cannot be synthesized in the human body; they can be catabolized and metabolized by the highly reversible branched-chain amino acid aminotransferase 1/2 (BCAT1/2) to provide energy for tumour cells, or they can be reversed and converted to leucine by BCKA to activate the mTOR signalling pathway, which results in metabolic abnormalities between different cells or tissues and organs in the body and promotes tumour growth24.
A study from foreign scholars included five types of cancer patients, namely, lung cancer, gastric cancer, colorectal cancer, breast cancer and prostate cancer patients, to determine the plasma free amino acid profiles of the patients and its application in early diagnosis. By comparing the changes in amino acid profiles in the blood of patients with the above five types of cancer, it was found that the AUCs for the discrimination of patients based on amino acid concentrations and ratios was 0.802 and 0.802 for lung cancer, respectively. The levels of valine and leucine change significantly in tumour patients, and the use of amino acid profiles can effectively assist in improving cancer screening and diagnosis25. Another study enrolled 22 patients with COPD and 77 lung cancer patients (stage I-IV), and a collection of NMR metabolic fingerprints was modelled using OPLS-DA. The model successfully distinguished between COPD and NSCLC (AUC = 0.993), suggesting that isoleucine may be able to distinguish between COPD and lung cancer patients26. Decreased concentrations of arginine, alanine, isoleucine, tyrosine and tryptophan are helpful for diagnosing breast cancer and predicting tumour progression27. Elevated plasma levels of circulating metabolites of BCAAs can more than triple the risk of pancreatic cancer development28.
The tumour microenvironment (TME) is a highly structured ecosystem that contains cancer cells and different types of nonmalignant cells, such as rich and diverse immune cells, cancer-associated fibroblasts (CAFs), endothelial cells (ECs), peripheral cells, various cell types and a vascularized extracellular matrix 29. The various types of cells in the TME, as well as their secretion of cytokines, play key roles in the pathogenesis of cancer. IL-17 is a universal cytokine in the TME that can induce the production of multiple factors, play a multifactorial role in tumour immunity, exert antitumour effects and promote tumour progression30,31. Abnormally elevated levels of IL-17 promote tumour progression by increasing cell proliferation and mutation rates and increasing immune tolerance in transformed cells32. Reppert et al. performed qPCR on tissue samples from 25 NSCLC patients and reported that the expression of IL-17A was 10-fold greater in these patients than in healthy controls33. Xiao-Tang Yang et al. also reported that the level of IL-17A was greater in NSCLC patients than in healthy controls and was also significantly greater in stage III and IV patients than in stage I or II patients34. IL-2 can induce the depletion of CD8 + T cells, thereby inhibiting the antitumour immune response35. Our results demonstrated a significantly high level of IL-17A expression and downregulation of IL-2 in the peripheral serum of early-stage NSCLC patients, which was similar to the results of previous studies35,36.
In recent years, there have been several studies on cfDNA methylation and fragmentation omics for early detection and localization of multiple cancers37–39. However, due to the low content of cfDNA, there is a need for high sequencing depth, library construction and whole-genome bisulfite sequencing in combination with machine learning. Integrative profiling of the cfDNA methylome and fragmentome has been technologically challenging, and a unified standard has not been established, which limits clinical applications. In this study, we established an early-stage NSCLC diagnostic model through metabolomics detection of serum, which is simple, noninvasive and easily reproducible. It is easier to realize clinical translation, and this approach is conducive to clinical practice.
This study has several limitations. First, the sample in this study was small, but because all the patients had early-stage NSCLC, the sample was representative. Second, these markers found in the case‒control study are relatively innovative but need to be further confirmed in prospective cohort studies. Finally, at the same time, we need to explore the relevant mechanisms in animal experiments. However, whether cytokine and metabolomics detection can be combined for the early diagnosis of NSCLC and the relationship between the two need further study.