Discovering Biomarkers in Peritoneal Metastasis of Gastric Cancer by Metabolomics

Metabolomic profiling of upper GI malignancies in blood and tissue: a systematic review and meta-analysis

OBJECTIVE

To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue.

BACKGROUND

Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC.

METHODS

Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC.

RESULTS

A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group.

CONCLUSION

Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.

Sulfatide imaging identifies tumor cells in colorectal cancer peritoneal metastases

Even with systemic chemotherapy, cytoreductive surgery (CRS), and hyperthermic intraperitoneal chemotherapy (HIPEC), peritoneal metastases (PM) remain a common site of disease progression for colorectal cancer (CRC) and are frequently associated with a poor prognosis. The mass spectrometry (MS) method known as Matrix-Assisted Laser Desorption/Ionization - Time of Flight (MALDI-TOF) is frequently used in medicine to identify structural compounds and biomarkers. It has been demonstrated that lipids are crucial in mediating the aggressive growth of tumors. In order to investigate the lipid profiles, particularly with regard to histological distribution, we used MALDI-TOF MS (MALDI-MS) and MALDI-TOF imaging MS (MALDI-IMS) on patient-derived tumor organoids (PDOs) and PM clinical samples. According to the MALDI-IMS research shown here, the predominant lipid signature of PDOs in PM tissues, glycosphingolipid (GSL) sulfates or sulfatides, or STs, is unique to the areas containing tumor cells and absent from the surrounding stromal compartments. Bioactive lipids are derived from arachidonic acid (AA), and AA-containing phosphatidylinositol (PI), or PI (18:0-20:4), is shown to be highly expressed in the stromal components. On the other hand, the tumor components contained a higher abundance of PI species with shorter and more saturated acyl chains (C34 and C36 carbons). The cellular subversion of PI and ST species may alter in ways that promote the growth, aggressiveness, and metastasis of tumor cells. Together, these findings suggest that the GSL/ST metabolic programming of PM may contain novel therapeutic targets to impede or halt PM progression.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of "big data" and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

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.

Abnormal arginine synthesis confers worse prognosis in patients with middle third gastric cancer

BACKGROUND

Gastric cancer at different locations has distinct prognoses and biological behaviors, but the specific mechanism is unclear.

METHODS

Non-targeted metabolomics was performed to examine the differential metabolite phenotypes that may be associated with the effects of tumor location on the prognosis of gastric cancer. And silencing of the rate-limiting enzyme to evaluate the effect of abnormal changes in metabolic pathway on the functional biological assays of gastric cancer cells HGC-27 and MKN28.

RESULTS

In a retrospective study of 94 gastric cancer patients, the average survival time of patients with gastric cancer in the middle third of the stomach was significantly lower than that of patients with gastric cancer in other locations (p < 0.05). The middle third location was also found to be an independent risk factor for poor prognosis (HR = 2.723, 95%CI 1.334-5.520), which was closely associated with larger tumors in this location. Non-targeted metabolomic analysis showed that the differential metabolites affected 16 signaling pathways including arginine synthesis, retrograde endocannabinoid signaling, arginine biosynthesis, and alanine and aspartate and glutamate metabolism between gastric cancer and normal tissue, as well as between tumors located in the middle third of the stomach and other locations. Argininosuccinate synthetase 1 (ASS1), the rate-limiting enzyme of the arginine biosynthesis pathway, catalyzes the production of argininosuccinic acid. Here, knockdown of ASS1 significantly inhibited the proliferation, colony formation, and migration/invasion of gastric cancer cells, and promoted apoptosis.

CONCLUSIONS

Our study suggests that abnormal arginine synthesis may lead to larger tumor size and worse prognosis in gastric cancer located in the middle third position of the stomach. These findings may provide the basis for the stratification and targeted treatment of gastric cancer in different locations.

Utilizing serum metabolomics for assessing postoperative efficacy and monitoring recurrence in gastric cancer patients

OBJECTIVE

(1) This study aims to identify distinct serum metabolites in gastric cancer patients compared to healthy individuals, providing valuable insights into postoperative efficacy evaluation and monitoring of gastric cancer recurrence; (2) Methods: Serum samples were collected from 15 healthy individuals, 16 gastric cancer patients before surgery, 3 months after surgery, 6 months after surgery, and 15 gastric cancer recurrence patients. T-test and analysis of variance (ANOVA) were performed to screen 489 differential metabolites between the preoperative group and the healthy control group. Based on the level of the above metabolites in the recurrence, preoperative, three-month postoperative, and six-month postoperative groups, we further selected 18 significant differential metabolites by ANOVA and partial least squares discriminant analysis (PLS-DA). The result of hierarchical clustering analysis about the above metabolites showed that the samples were regrouped into the tumor-bearing group (comprising the original recurrence and preoperative groups) and the tumor-free group (comprising the original three-month postoperative and six-month postoperative groups). Based on the results of PLS-DA, 7 differential metabolites (VIP > 1.0) were further selected to distinguish the tumor-bearing group and the tumor-free group. Finally, the results of hierarchical clustering analysis showed that these 7 metabolites could well identify gastric cancer recurrence; (3) Results: Lysophosphatidic acids, triglycerides, lysine, and sphingosine-1-phosphate were significantly elevated in the three-month postoperative, six-month postoperative, and healthy control groups, compared to the preoperative and recurrence groups. Conversely, phosphatidylcholine, oxidized ceramide, and phosphatidylglycerol were significantly reduced in the three-month postoperative, six-month postoperative, and healthy control groups compared to the preoperative and recurrence groups. However, these substances did not show significant differences between the preoperative and recurrence groups, nor between the three-month postoperative, six-month postoperative, and healthy control groups; (4) Conclusions: Our findings demonstrate the presence of distinct metabolites in the serum of gastric cancer patients compared to healthy individuals. Lysophosphatidic acid, triglycerides, lysine, sphingosine-1-phosphate, phosphatidylcholine, oxidized ceramide, and phosphatidylglycerol hold potential as biomarkers for evaluating postoperative efficacy and monitoring recurrence in gastric cancer patients. These metabolites exhibit varying concentrations across different sample categories.

Role of Metabolomics in Pathogenesis and Prompt Diagnosis of Gastric Cancer Metastasis-A Systematic Review

INTRODUCTION

Gastric cancer is the fourth most frequently diagnosed form of cancer and the third leading cause of cancer-related mortality worldwide. The aim of this review is to identify individual metabolic biomarkers and their association with accurate diagnostic values, which can predict gastric cancer metastasis.

MATERIALS AND METHODS

After searching the keywords, 83 articles were found over a period of 13 years. One was eliminated because it was not written in English, and two were published outside the selected period. Seven scientific papers were qualified for this investigation after eliminating duplicates, non-related articles, systematic reviews, and restricted access studies.

RESULTS

New metabolic biomarkers with predictive value for gastric cancer metastasis and for elucidating metabolic pathways of the metastatic process have been found. The pathogenic processes can be outlined as follows: pro-oxidant capacity, T-cell inactivation, cell cycle arrest, energy production and mitochondrial enzyme impairment, cell viability and pro-apoptotic effect, enhanced degradation of collagen extracellular matrix, migration, invasion, structural protein synthesis, and tumoral angiogenesis.

CONCLUSION

Metabolic biomarkers have been recognized as independent risk factors in the molecular process of gastric cancer metastasis, with good diagnostic and prognostic value.

A Novel Assessment of Metabolic Pathways in Peritoneal Metastases from Low-Grade Appendiceal Mucinous Neoplasms

BACKGROUND

There is a paucity of targeted therapies for patients with pseudomyxoma peritonei (PMP) secondary to low-grade appendiceal mucinous neoplasms (LAMNs). Dysregulated metabolism has emerged as a hallmark of cancer, and the relationship of metabolomics and cancer is an area of active scientific exploration. We sought to characterize phenotypic differences found in peritoneal metastases (PM) derived from LAMN versus adenocarcinoma.

METHODS

Tumors were washed with phosphate-buffered saline (PBS), microdissected, then dissociated in ice-cold methanol dried and reconstituted in pyridine. Samples were derivatized in tert-butyldimethylsilyl (TBDMS) and subjected to gas chromatography-coupled mass spectrometry. Metabolites were assessed based on a standard library. RNA sequencing was performed, with pathway and network analyses on differentially expressed genes.

RESULTS

Eight peritoneal tumor samples were obtained and analyzed: LAMNs (4), and moderate to poorly differentiated adenocarcinoma (colon [1], appendix [3]). Decreases in pyroglutamate, fumarate, and cysteine in PM from LAMNs were found compared with adenocarcinoma. Analyses showed the differential gene expression was dominated by the prevalence of metabolic pathways, particularly lipid metabolism. The gene retinol saturase (RETSAT), downregulated by LAMN, was involved in the multiple metabolic pathways that involve lipids. Using network mapping, we found IL1B signaling to be a potential top-level modulation candidate.

CONCLUSIONS

Distinct metabolic signatures may exist for PM from LAMN versus adenocarcinoma. A multitude of genes are differentially regulated, many of which are involved in metabolic pathways. Additional research is needed to identify the significance and applicability of targeting metabolic pathways in the potential development of novel therapeutics for these challenging tumors.

Targeting Oncometabolites in Peritoneal Cancers: Preclinical Insights and Therapeutic Strategies

Peritoneal cancers present significant clinical challenges with poor prognosis. Understanding the role of cancer cell metabolism and cancer-promoting metabolites in peritoneal cancers can provide new insights into the mechanisms that drive tumor progression and can identify novel therapeutic targets and biomarkers for early detection, prognosis, and treatment response. Cancer cells dynamically reprogram their metabolism to facilitate tumor growth and overcome metabolic stress, with cancer-promoting metabolites such as kynurenines, lactate, and sphingosine-1-phosphate promoting cell proliferation, angiogenesis, and immune evasion. Targeting cancer-promoting metabolites could also lead to the development of effective combinatorial and adjuvant therapies involving metabolic inhibitors for the treatment of peritoneal cancers. With the observed metabolomic heterogeneity in cancer patients, defining peritoneal cancer metabolome and cancer-promoting metabolites holds great promise for improving outcomes for patients with peritoneal tumors and advancing the field of precision cancer medicine. This review provides an overview of the metabolic signatures of peritoneal cancer cells, explores the role of cancer-promoting metabolites as potential therapeutic targets, and discusses the implications for advancing precision cancer medicine in peritoneal cancers.

Accurate and Rapid Detection of Peritoneal Metastasis from Gastric Cancer by AI-Assisted Stimulated Raman Molecular Cytology

Peritoneal metastasis (PM) is the mostcommon form of distant metastasis and one of the leading causes of death in gastriccancer (GC). For locally advanced GC, clinical guidelines recommend peritoneal lavage cytology for intraoperative PM detection. Unfortunately, current peritoneal lavage cytology is limited by low sensitivity (<60%). Here the authors established the stimulated Raman molecular cytology (SRMC), a chemical microscopy-based intelligent cytology. The authors firstly imaged 53 951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative). Then, the authors revealed 12 single cell features of morphology and composition that are significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, the authors developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix is crucial to identify the significant marker cell cluster, the divergence of which is finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, their SRMC method could reach 81.5% sensitivity, 84.9% specificity, and the AUC of 0.85, within 20 minutes for each patient. Together, their SRMC method shows great potential for accurate and rapid detection of PM from GC.

Single-cell sequencing of ascites fluid illustrates heterogeneity and therapy-induced evolution during gastric cancer peritoneal metastasis

Peritoneal metastasis is the leading cause of death for gastrointestinal cancers. The native and therapy-induced ascites ecosystems are not fully understood. Here, we characterize single-cell transcriptomes of 191,987 ascites cancer/immune cells from 35 patients with/without gastric cancer peritoneal metastasis (GCPM). During GCPM progression, an increase is seen of monocyte-like dendritic cells (DCs) that are pro-angiogenic with reduced antigen-presenting capacity and correlate with poor gastric cancer (GC) prognosis. We also describe the evolution of monocyte-like DCs and regulatory and proliferative T cells following therapy. Moreover, we track GC evolution, identifying high-plasticity GC clusters that exhibit a propensity to shift to a high-proliferative phenotype. Transitions occur via the recently described, autophagy-dependent plasticity program, paligenosis. Two autophagy-related genes (MARCKS and TXNIP) mark high-plasticity GC with poorer prognosis, and autophagy inhibitors induce apoptosis in patient-derived organoids. Our findings provide insights into the developmental trajectories of cancer/immune cells underlying GCPM progression and therapy resistance.

Microbiota and metabolites alterations in proximal and distal gastric cancer patients

Background

Globally, gastric cancer is the third most common cancer and the third leading cause of cancer death. Proximal and distal gastric cancers have distinct clinical and biological behaviors. The microbial composition and metabolic differences in proximal and distal gastric cancers have not been fully studied and discussed.

Methods

In this study, the gastric microbiome of 13 proximal gastric cancer tissues, 16 distal gastric cancer tissues, and their matched non-tumor tissues were characterized using 16S rRNA amplicon sequencing. Additionally, 10 proximal gastric cancer tissues, 11 distal gastric cancer tissues, and their matched non-tumor tissues were assessed by untargeted metabolomics.

Results

There was no significant difference in microbial diversity and richness between the proximal and distal gastric cancer tissues. At the genus level, the abundance of Rikenellaceae_RC9_gut_group, Porphyromonas, Catonella, Proteus, Oribacterium, and Moraxella were significantly increased in Proximal T, whereas that of Methylobacterium_Methylorubrum was significantly increased in Distal T. The untargeted metabolomics analysis revealed 30 discriminative metabolites between Distal T and Distal N. In contrast, there were only 4 discriminative metabolites between Proximal T and Proximal N. In distal gastric cancer, different metabolites were scattered through multiple pathway, including the sphingolipid signaling pathway, arginine biosynthesis, protein digestion and absorption, alanine, aspartate and, glutamate metabolism, etc.In proximal gastric cancer, differential microbial metabolites were mainly related to hormone metabolism.

Conclusion

Methylobacterium-Methylorubrum was significantly increased in Distal T, positively correlated with cancer-promoting metabolites, and negatively correlated with cancer-inhibiting metabolites. Rikenellaceae_RC_gut_group was significantly increased in Proximal T and positively correlated with cancer-promoting metabolites. Further studies regarding the functions of the above-mentioned microorganisms and metabolites were warranted as the results may reveal the different mechanisms underlying the occurrence and development of proximal and distal gastric cancers and provide a basis for future treatments.

Importance

First, the differences in microbial composition and metabolites between the proximal and distal gastric cancers were described; then, the correlation between microbiota and metabolites was preliminarily discussed. These microbes and metabolites deserve further investigations as they may reveal the different mechanisms involved in the occurrence and development of proximal and distal gastric cancers and provide a basis for future treatments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03650-x.

High serum levels of L-carnitine and citric acid negatively correlated with alkaline phosphatase are detectable in Koreans before gastric cancer onset

INTRODUCTION

Monitoring metabolic biomarkers could be utilized as an effective tool for the early detection of gastric cancer (GC) risk.

OBJECTIVE

We aimed to discover predictive serum biomarkers for GC and investigate biomarker-related metabolism.

METHODS

Subjects were randomly selected from the Korean Cancer Prevention Study-II cohort and matched by age and sex. We analyzed baseline serum samples of 160 subjects (discovery set; control and GC occurrence group, 80 each) via nontargeted screening. Identified putative biomarkers were validated in baseline serum samples of 140 subjects (validation set; control and GC occurrence group, 70 each) using targeted metabolites analysis.

RESULTS

The final analysis was conducted on the discovery set (control, n = 52 vs. GC occurrence, n = 50) and the validation set (control, n = 43 vs. GC occurrence, n = 44) applying exclusion conditions. Eighteen putative metabolite sets differed between two groups found on nontargeted metabolic screening. We focused on fatty acid-related energy metabolism. In targeted analysis, levels of decanoyl-L-carnitine (p = 0.019), L-carnitine (p = 0.033), and citric acid (p = 0.025) were significantly lower in the GC occurrence group, even after adjusting for age, sex, and smoking status. Additionally, L-carnitine and citric acid were confirmed to have an independently significant relationship to GC development. Notably, alkaline phosphatase showed a significant correlation with these two biomarkers.

CONCLUSION

Changes in serum L-carnitine and citric acid levels that may result from alterations of fatty-acid-related energy metabolism are expected to be valuable biomarkers for the early diagnosis of GC risk.

UHPLC-ESI-MS/MS Quantification of Relevant Substrates and Metabolites of the Kynurenine Pathway Present in Serum and Peritoneal Fluid from Gastric Cancer Patients-Method Development and Validation

Metabolites and enzymes involved in the kynurenine pathway (KP) are highly promising targets for cancer treatment, including gastrointestinal tract diseases. Thus, accurate quantification of these compounds in body fluids becomes increasingly important. The aim of this study was the development and validation of the UHPLC-ESI-MS/MS methods for targeted quantification of biologically important KP substrates (tryptophan and nicotinamide) and metabolites(kynurenines) in samples of serum and peritoneal fluid from gastric cancer patients. The serum samples were simply pretreated with trichloroacetic acid to precipitate proteins. The peritoneal fluid was purified by solid-phase extraction before analysis. Validation was carried out for both matrices independently. Analysis of the samples from gastric cancer patients showed different accumulations of tryptophan and its metabolites in different biofluids of the same patient. The protocols will be used for the evaluation of tryptophan and kynurenines in blood and peritoneal fluid to determine correlation with the clinicopathological status of gastric cancer or the disease's prognosis.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.