The Role of Lipid Metabolism in Gastric Cancer

Cui, Mengying; Yi, Xing; Zhu, Dan-Xia; Wu, Jun

doi:10.3389/fonc.2022.916661

Cited by 25 publications

(22 citation statements)

References 228 publications

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“…We speculated that ABCA1 may be involved in the invasion and metastasis of gastric cancer through the PI3K-Akt signaling pathway. Moreover, previous studies showed PI3K/Akt/mTOR signaling pathway as an important signaling pathway in lipid metabolism in gastric cancer ( 57 , 79 ). In addition, our study revealed that ABCA1 expression in STAD was closely associated with immune infiltration, MSI, TMB, and neoantigen loads.…”

Section: Discussionmentioning

confidence: 97%

“…At the same time, the increased level of mitochondrial fatty acid β-oxidation not only provides sufficient energy for the growth and metastasis of cancer cells, but also participates in the transduction of lipid rafts and lipid modified signaling molecules, which further promotes tumor progression. In addition, drug resistance in gastric cancer may also be related to lipid metabolism ( 57 , 58 ). However, no article has yet reported on the construction of risk models for genes related to lipid droplet metabolism in gastric cancer to predict survival prognosis and immunotherapy efficacy in patients with gastric cancer.…”

Section: Discussionmentioning

confidence: 99%

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Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer

et al. 2023

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BackgroundGastric cancer is one of the common malignant tumors of the digestive system worldwide, posing a serious threat to human health. A growing number of studies have demonstrated the important role that lipid droplets play in promoting cancer progression. However, few studies have systematically evaluated the role of lipid droplet metabolism-related genes (LDMRGs) in patients with gastric cancer.MethodsWe identified two distinct molecular subtypes in the TCGA-STAD cohort based on LDMRGs expression. We then constructed risk prediction scoring models in the TCGA-STAD cohort by lasso regression analysis and validated the model with the GSE15459 and GSE66229 cohorts. Moreover, we constructed a nomogram prediction model by cox regression analysis and evaluated the predictive efficacy of the model by various methods in STAD. Finally, we identified the key gene in LDMRGs, ABCA1, and performed a systematic multi-omics analysis in gastric cancer.ResultsTwo molecular subtypes were identified based on LDMRGs expression with different survival prognosis and immune infiltration levels. lasso regression models were effective in predicting overall survival (OS) of gastric cancer patients at 1, 3 and 5 years and were validated in the GEO database with consistent results. The nomogram prediction model incorporated additional clinical factors and prognostic molecules to improve the prognostic predictive value of the current TNM staging system. ABCA1 was identified as a key gene in LDMRGs and multi-omics analysis showed a strong correlation between ABCA1 and the prognosis and immune status of patients with gastric cancer.ConclusionThis study reveals the characteristics and possible underlying mechanisms of LDMRGs in gastric cancer, contributing to the identification of new prognostic biomarkers and providing a basis for future research.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer

et al. 2023

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“…By targeting Akt/b-catenin and Ras/MEK/ERK signaling pathways, phosphatidylcholine metabolism also contributes to addressing medication resistance [ 33 ]. Notably, lipid reprogramming changes intercellular lipid metabolism and immune cells' pharmaceutical resistance in the tumor microenvironment [ 2 ]. In present study, we interestingly discovered that GC patients with unfavorable plasma lipid metabolism profiles allowed by the 1 H-NMR platform had a significantly shorter OS under postoperative chemotherapy, further supporting the hypothesis that lipid metabolism may play an important role in antitumor drug resistance in GC.…”

Section: Discussionmentioning

confidence: 99%

“…Lipid metabolism dysregulation is a significant alteration in the development of cancer, involving proliferation, invasion, metastasis, and therapeutics in cancer due to cancer cells harnessing lipid metabolism to get the elements needed to make biological membranes, energy, as well as signaling molecules [1]. Current researches suggest that lipid metabolism changes in cancer are capable of mediating antitumor drug resistance by up-regulating lipogenesis and lipolytic enzyme expression [2]. In a mouse model, tumor tissues were reported to be able to increase the expression of proteins involved in lipid metabolism in gastric cancer (GC) [3,4].…”

Section: Introductionmentioning

confidence: 99%

Association of plasma lipid metabolism profiles with overall survival for patients with gastric cancer undergoing gastrectomy based on 1H-NMR spectroscopy

Qiu

Xie

et al. 2023

Nutr Metab (Lond)

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Background Lipid metabolism dysregulation is a prominent metabolic alteration in various cancers. The study aimed to explore the association of plasma lipid metabolism profiles with overall survival (OS) for gastric cancer (GC) patients who received gastrectomy. Methods GC patients who were treated with gastrectomy and measured with plasma lipid metabolism profiles using proton nuclear magnetic resonance (1H-NMR) spectroscopy in Nanfang Hospital between January 1, 2017, and October 31, 2018, were recruited. The Least Absolute Shrinkage and Selection Operator (LASSO) regression model was used to analyze variables selected by univariate analysis for OS. An index of plasma lipid metabolism profiles, named plasma lipid metabolism index (PLMI), was constructed by variables' coefficients in LASSO regression to explore its association with OS and its role in the prediction model. Results A total of 158 GC patients were included in this study. Four of the 110 lipid profiles, including LDL-5 Apo-B, LDL-4 Cholesterol, HDL-4 Apo-A2, and HDL-4 Free Cholesterol, were selected to construct the PLMI. The optimal cut-off value of PLMI for OS was used to classify the population into two subgroups, the high PLMI group (≥ − 0.163) and the low PLMI group (< − 0.163). The high PLMI group had a shorter OS (p = 0.0034) and was the independent risk factor for OS (Hazard Ratio = 2.13, 95% Confidence Interval (CI): 1.07–4.22, p = 0.031) after adjusting for perineural invasion and tumor stage. In subsets of the I–III stage and treating postoperative chemotherapy, high PLMI also had an unfavorable correlation with OS (p = 0.016 and p = 0.0086, respectively). The nomogram prediction models of both the training cohort and validation cohort showed good calibration and discrimination with the concordance indexes of 0.806 (95% CI, 0.732–0.880) in the training cohort and 0.794 (95% CI, 0.725–0.862) in the validation cohort. Conclusions This study found that the index derived from the LDL-5 Apo-B, LDL-4 Cholesterol, HDL-4 Apo-A2, and HDL-4 Free Cholesterol, was significantly associated with overall survival, suggesting that regulating lipid metabolisms might improve the prognosis for GC patients.

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“…Cancer cells dysregulate metabolic pathways by high rates of lipid synthesis to support rapid growth 29,30 . GC cells have been found to accelerate lipid synthesis and reduce lipid hydrolysis 31,32 , which leads to increased accumulation of excessive lipids in lipid droplets (LDs) 31,32 . More importantly, dysregulated lipid metabolism has been shown to promote cancer metastasis 33 , including PM 34 .…”

Section: Introductionmentioning

confidence: 99%

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

Chen

et al. 2023

Preprint

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Peritoneal metastasis (PM) is the most common form of distant metastasis and one of the leading causes of death in gastric cancer (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 we established the stimulated Raman cytology (SRC), a chemical microscopy-based intelligent cytology. By taking advantages of stimulated Raman scattering in label-free, high-speed, and high-resolution chemical imaging, we firstly imaged 53951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative), at the Raman bands corresponding to DNA, protein, and lipid, respectively. Then, we revealed 12 single cell features of morphology and composition that were significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, we developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix was crucial to identify the significant marker cell cluster, the divergence of which was finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, our SRC method assisted by machine learning classifiers could reach 81.5% sensitivity, 84.9% specificity, and the area under receiver operating characteristic curve of 0.85, within 20 minutes for each patient. Such remarkable improvement in detection accuracy is largely owing to incorporation of the single-cell composition features in SRC. Together, our SRC method shows great potential for accurate and rapid detection of PM from GC.

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The Role of Lipid Metabolism in Gastric Cancer

Cited by 25 publications

References 228 publications

Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer

Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer

Association of plasma lipid metabolism profiles with overall survival for patients with gastric cancer undergoing gastrectomy based on 1H-NMR spectroscopy

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

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