Combined Metabolomics with Transcriptomics Reveals Important Serum Biomarkers Correlated with Lung Cancer Proliferation through a Calcium Signaling Pathway

Metabolomics for early-stage lung adenocarcinoma: diagnostic biomarker screening

Objective

This study aimed to identify specific metabolic markers in the blood that can diagnose early-stage lung adenocarcinoma.

Methods

An untargeted metabolomics study was performed, and the participants were divided into four groups: early-stage lung adenocarcinoma group (E-LUAD; n = 21), healthy control group (HC, n = 17), non-cancerous lung disease group (NCC; n = 17), and advanced lung adenocarcinoma group (A-LUAD; n = 25). Plasma metabolite levels that differed in the E-LUAD group compared to the other three groups were identified via liquid chromatography-mass spectrometry (LC-MS). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed at metaX for statistical analysis. A Venn diagram was constructed to identify overlapping differential metabolites of the class comparisons. The data were randomly divided into a training set and a validation set. Based on the overlapping differential metabolites, the diagnostic model was constructed. The discrimination of the model was evaluated using the area under the curve (AUC).

Results

A total of 527 metabolites were tentatively identified in positive ion mode and 286 metabolites in negative ion mode. Compared with the HC group, 121 differential metabolites were identified. Compared with the NCC group, 67 differential metabolites were identified. Compared with the A-LUAD group, 54 differential metabolites were identified. The Venn diagram showed that 29 metabolites can distinguish E-LUAD from HC and NCC and that four metabolites can distinguish E-LUAD from HC, NCC, and A-LUAD. The feature metabolites were selected to establish the diagnostic model for E-LUAD. The AUC value of the training set was 0.918, and it was 0.983 in the validation set.

Conclusion

Blood metabolomics has potential diagnostic value for E-LUAD. More medical studies are needed to verify whether the metabolic markers identified in the current research can be applied in clinical practice.

Exploring manzamine a: a promising anti-lung cancer agent from marine sponge Haliclona sp

Manzamine A (MA), a bioactive compound derived from the marine sponge Haliclona sp., shows considerable therapeutic potential, particularly in the treatment of various cancer types. Extracted with acetone and purified through chromatography, MA exhibits a bioavailability of 20.6% when administered orally in rats, underscoring its feasibility for therapeutic use. This compound disrupts key cellular mechanisms essential for cancer progression, including microtubule dynamics and DNA replication enzymes, demonstrating strong anti-proliferative effects against multiple cancer cell lines while sparing normal cells. Additionally, network pharmacology and molecular docking studies reveal MA's interactions with important targets related to lung cancer progression, such as EGFR and SRC, bolstering its potential as a novel anti-lung cancer agent. Pathway analyses further indicate that MA influences critical signaling pathways involved in tumor growth and metastasis. Given the urgent need for effective treatments against drug-resistant cancers and the limited toxicity profile of MA, further exploration of its pharmacological benefits and mechanism could pave the way for new therapeutic strategies in lung cancer.

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Metabolomics and lipidomics in non-small cell lung cancer

Due to its insidious nature, lung cancer remains a leading cause of cancer-related deaths worldwide. Therefore, there is an urgent need to identify sensitive/specific biomarkers for early diagnosis and monitoring. The current study was designed to provide a current metabolic profile of non-small cell lung cancer (NSCLC) by systematically reviewing and summarizing various metabolomic/ lipidomic studies based on NSCLC blood samples, attempting to find biomarkers in human blood that can predict or diagnose NSCLC, and investigating the involvement of key metabolites in the pathogenesis of NSCLC. We searched all articles on lung cancer published in Elsevier, PubMed, Web of Science and the Cochrane Library between January 2012 and December 2022. After critical selection, a total of 31 studies (including 2768 NSCLC patients and 9873 healthy individuals) met the inclusion criteria, and 22 were classified as "high quality". Forty-six metabolites related to NSCLC were repeatedly identified, involving glucose metabolism, amino acid metabolism, lipid metabolism and nucleotide metabolism. Pyruvic acid, carnitine, phenylalanine, isoleucine, kynurenine and 3-hydroxybutyrate showed upward trends in all studies, citric acid, glycine, threonine, cystine, alanine, histidine, inosine, betaine and arachidic acid showed downward trends in all studies. This review summarizes the existing metabolomic/lipidomic studies related to the identification of blood biomarkers in NSCLC, examines the role of key metabolites in the pathogenesis of NSCLC, and provides an important reference for the clinical diagnosis and treatment of NSCLC. Due to the limited size and design heterogeneity of the existing studies, there is an urgent need for standardization of future studies, while validating existing findings with more studies.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

How do prolonged anchorage-free lifetimes strengthen non-small-cell lung cancer cells to evade anoikis? - A link with altered cellular metabolomics

BACKGROUND

Malignant cells adopt anoikis resistance to survive anchorage-free stresses and initiate cancer metastasis. It is still unknown how varying periods of anchorage loss contribute to anoikis resistance, cell migration, and metabolic reprogramming of cancerous cells.

RESULTS

Our study demonstrated that prolonging the anchorage-free lifetime of non-small-cell lung cancer NCI-H460 cells for 7 days strengthened anoikis resistance, as shown by higher half-life and capability to survive and grow without anchorage, compared to wild-type cells or those losing anchorage for 3 days. While the prolonged anchorage-free lifetime was responsible for the increased aggressive feature of survival cells to perform rapid 3-dimensional migration during the first 3 h of a transwell assay, no significant influence was observed with 2-dimensional surface migration detected at 12 and 24 h by a wound-healing method. Metabolomics analysis revealed significant alteration in the intracellular levels of six (oxalic acid, cholesterol, 1-ethylpyrrolidine, 1-(3-methylbutyl)-2,3,4,6-tetramethylbenzene, β-alanine, and putrescine) among all 37 identified metabolites during 7 days without anchorage. Based on significance values, enrichment ratios, and impact scores of all metabolites and their associated pathways, three principal metabolic activities (non-standard amino acid metabolism, cell membrane biosynthesis, and oxidative stress response) offered potential links with anoikis resistance.

CONCLUSIONS

These findings further our insights into the evolution of anoikis resistance in lung cancer cells and identify promising biomarkers for early lung cancer diagnosis.

2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo

2-hydroxybutyric acid (2HB) serves as an important regulatory factor in a variety of diseases. The circulating level of 2HB in serum is significantly higher in multiple diseases, such as cancer and type 2 diabetes (T2D). However, there is currently no systematic study on 2HB-producing bacteria that demonstrates whether gut bacteria contribute to the circulating 2HB pool. To address this question, we used BLASTP to reveal the taxonomic profiling of 2HB-producing bacteria in the human microbiome, which are mainly distributed in the phylum Proteobacteria and Firmicutes. In vitro experiments showed that most gut bacteria (21/32) have at least one path to produce 2HB, which includes Aspartic acid, methionine, threonine, and 2-aminobutyric acid. Particularly, Fusobacterium nucleatum has the strongest ability to synthesize 2HB, which is sufficient to alter colon 2HB concentration in mice. Nevertheless, neither antibiotic (ABX) nor Fusobacterium nucleatum gavage significantly affected mouse serum 2HB levels during the time course of this study. Taken together, our study presents the profiles of 2HB-producing bacteria and demonstrates that gut microbiota was a major contributor to 2HB concentration in the intestinal lumen but a relatively minor contributor to serum 2HB concentration.

Serum untargeted metabolomics reveal metabolic alteration of non-small cell lung cancer and refine disease detection

This study was performed to characterize the metabolic alteration of non-small-cell lung cancer (NSCLC) and discover blood-based metabolic biomarkers relevant to lung cancer detection. An untargeted metabolomics-based approach was applied in a case-control study with 193 NSCLC patients and 243 healthy controls. Serum metabolomics were determined by using an ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. We screened differential metabolites based on univariate and multivariate analysis, followed by identification of the metabolites and related pathways. For NSCLC detection, machine learning was employed to develop and validate the model based on the altered serum metabolite features. The serum metabolic pattern of NSCLC was definitely different from the healthy condition. In total, 278 altered features were found in the serum of NSCLC patients comparing with healthy people. About one-fifth of the abundant differential features were identified successfully. The altered metabolites were enriched in metabolic pathways such as phenylalanine metabolism, linoleic acid metabolism, and biosynthesis of bile acids. We demonstrated a panel of 10 metabolic biomarkers which representing excellent discriminating capability for NSCLC discrimination, with a combined area under the curve (AUC) in the validation set of 0.95 (95% CI: 0.91-0.98). Moreover, this model showed a desirable performance for the detection of NSCLC at an early stage (AUC = 0.95, 95% CI: 0.92-0.97). Our study offers a perspective on NSCLC metabolic alteration. The finding of the biomarkers might shed light on the clinical detection of lung cancer, especially for those cancers in an early stage in Chinese population.

Combined metabolomics with transcriptomics reveals potential plasma biomarkers correlated with non-small-cell lung cancer proliferation through the At pathway

BACKGROUND

Non-small-cell lung cancer (NSCLC) is one of the main types of lung cancer. Due to lack of effective biomarkers for early detection of NSCLC, the therapeutic effect is not ideal. This study aims to reveal potential biomarkers for clinical diagnosis.

METHODS

The plasma metabolic profiles of the patients were characterized by liquid chromatography-mass spectrometry (LC-MS). Differential metabolites were screened by p < 0.05 and VIP > 1. Multivariate statistical analysis was used to search for potential biomarkers. Receiver operating characteristic (ROC) curve was used to evaluate the predictors of potential biomarkers. Pathway enrichment analysis was performed on metabolomics data by Ingenuity Pathway Analysis (IPA) and transcriptomics data from GEO were used for validation.

RESULTS

A plasma metabolite biomarker panel including 13(S)-hydroxyoctadecadienoic acid (13(S)-HODE) and arachidonic acid was chose. The area under the ROC curve were 0.917, 0.900 and 0.867 for the panel in the different algorithm like Partial Least Squares Discrimination Analysis (PLS-DA), Support Vector Machine (SVM), Random Forest (RF). The candidate biomarkers were associated with the Akt pathway. Genes involved in the biological pathway had significant changes in the expression levels.

CONCLUSION

13(S)-HODE and arachidonic acid may be potential biomarkers of NSCLC. The Akt pathway was associated with this biomarker panel in NSCLC. Further studies are needed to clarify the mechanisms of disruption in this pathway.

Expression of cartilage oligomeric matrix protein (COMP) associates with capsular invasion in salivary gland pleomorphic adenoma

BACKGROUND

Accumulating evidence shows that pleomorphic adenoma (PA) exhibits a unique capsular invasion and with a crucial role in recurrence. This study was designed to explore RNA expression profiles in salivary gland PA in an attempt to further analyse genes associate with capsule invasion.

METHODS

We evaluated the expression profiles of 4 salivary gland PA patients by RNA-sequencing. The principal functions of the differentially expressed mRNAs (DEGs) were explored using GO and KEGG analysis. Then, RT-qPCR and correlation analyses were performed to verify the candidate DEGs in 59 PA patients, and immunohistochemical examinations were conducted to validate candidate DEGs. Finally, the COMP-related genes were screened using correlation and biological pathway enrichment analysis, and further validated by RT-qPCR.

RESULTS

A total of 974 DEGs were significantly upregulated and 1464 were downregulated (fold change ≥2.0; p < 0.05). Based on GO and KEGG analyses, extracellular matrix organization and the PI3K-Akt signaling pathway might play pivotal roles in the tumorigenesis of PA. 40 DEGs were screened and validated by RT-qPCR, 11 upregulated and 5 downregulated DEGs were consistent with the sequencing results. Cartilage oligomeric matrix protein (COMP) was identified to have a significant correlation with the capsular invasion of PA and expression of COMP in patients with invasive capsular PA was significantly stronger than PA. Finally, further results could reveal that 5 highest-scoring genes were screened as hub genes for COMP.

CONCLUSIONS

These findings suggested that COMP may be a prognostic target for PA and might contribute to its capsular invasion.

Metabolomic Fingerprinting for the Detection of Early-Stage Lung Cancer: From the Genome to the Metabolome

The five-year survival rate of lung cancer patients is very low, mainly because most newly diagnosed patients present with locally advanced or metastatic disease. Therefore, early diagnosis is key to the successful treatment and management of lung cancer. Unfortunately, early detection methods of lung cancer are not ideal. In this brief review, we described early detection methods such as chest X-rays followed by bronchoscopy, sputum analysis followed by cytological analysis, and low-dose computed tomography (LDCT). In addition, we discussed the potential of metabolomic fingerprinting, compared to that of other biomarkers, including molecular targets, as a low-cost, high-throughput blood-based test that is both feasible and affordable for early-stage lung cancer screening of at-risk populations. Accordingly, we proposed a paradigm shift to metabolomics as an alternative to molecular and proteomic-based markers in lung cancer screening, which will enable blood-based routine testing and be accessible to those patients at the highest risk for lung cancer.