Association between blood lipid levels and risk of gastric cancer: A systematic review and meta-analysis

Correlation between dyslipidaemia and gastric cancer: pathogenesis to prevention and treatment strategies

As the sixth most common cancer in the world, the development of gastric cancer (GC) is influenced by many factors. Recent studies have revealed a strong association between dyslipidaemia and GC. In this paper, the relationships between dyslipidaemia and GC are discussed in depth. We review the development of GC through the mechanisms of the inflammatory response, signalling pathways, and apolipoprotein function, and the intersecting targets of atherosclerosis and GC are explored. The synergistic effects of Helicobacter pylori infection and dyslipidaemia on the development of GC are also analysed, and the potential value of statins in the prevention and treatment of GC is discussed. In this review, we systematically investigated the relationship between dyslipidaemia and GC to provide new ideas for GC prevention and treatment.

The multifaceted role of agents counteracting metabolic syndrome: A new hope for gastrointestinal cancer therapy

Metabolic syndrome (MetS) is defined by the presence of at least three of five clinical parameters including abdominal obesity, insulin resistance, elevated triglycerides, reduced high-density lipoprotein (HDL) and hypertension. Major features describing MetS have been recognized risk factors for cancer onset, with an alarming impact on gastrointestinal (GI) tumors. Intriguingly, therapeutic administration of drugs to improve glycemic control and dyslipidemia (including metformin, statins) has been shown to have a preventive role in the development and in prognosis improvement of several cancer types. Overall, these observations highlight the key role of altered metabolism prevalently in cancer risk development and unveil anti-MetS agent repurposing potential beyond their conventional pharmacological action. The objective of this review is to summarize the current knowledge about the antitumor activity of anti-diabetic and anti-lipemic agents in GI cancer onset and progression. Here, pre-clinical evidence of their therapeutic potential and of their integration in novel compelling therapeutic strategies will be discussed. Possible clinical outcomes of these novel therapeutic combined protocols specifically dedicated to GI cancer patients will be put under the spotlight. In the future, these novel therapeutic options should be considered to improve conventional chemotherapy response and prognosis of this group of patients.

Roles of plasma proteins in mediating the causal effect of the lipid species on gastric cancer: Insights from proteomic and two-step Mendelian randomization

The change of plasma lipid species has close contacts with gastric cancer (GC). However, the specific mechanism still needs to be explored further. We aim to utilize plasma proteins to decipher the association between lipid species and GC, and seek possible drug targets for GC. We performed a two-step Mendelian randomization (MR) analysis to investigate causal relationships among 179 lipid species, 4907 plasma proteins, and GC. Using summary-data-based MR and colocalization, we first examined protein-GC associations in discovery (N = 35,559) and validation (N = 54,219) cohorts. Subsequent MR analyses assessed lipid-GC and lipid-protein relationships, followed by mediation analysis using error propagation methods. Finally, macromolecular docking of prioritized proteins identified potential therapeutic ligands. Our MR analysis revealed causal relationships between 12 lipid species and GC, as well as 3 plasma proteins and GC. Importantly, mediation analysis demonstrated that CCDC80 protein mediates 2.90% (95% CI: 0.30-5.5%) of the protective effect of diacylglycerol (16:1_18:1) against GC. Based on these findings, we identified valproic acid as a promising therapeutic candidate targeting CCDC80 for GC treatment. Our study demonstrates that reduced CCDC80 expression mediates the tumor-promoting effects of diacylglycerol (16:1_18:1) in GC pathogenesis. Molecular docking confirms valproic acid binds stably to CCDC80, suggesting its therapeutic potential. These findings advance GC etiology understanding and provide a new drug development direction.

Development of a nomogram for predicting the risk of carcinoma in chronic atrophic gastritis

OBJECTIVE

To construct a machine learning (ML) model to predict the progression of chronic atrophic gastritis (CAG) to gastric cancer (GC), given its precancerous significance.

METHODS

Using medical records from the Affiliated Hospital of Qingdao University, common laboratory indicators were extracted. LASSO regression identified 10 core risk factors, which were further analyzed using binary logistic regression to develop a nomogram model in R. The model's performance was evaluated using receiver operating characteristic (ROC) curves, the concordance index (C-index), calibration curves, and decision curve analysis (DCA).

RESULTS

The model showed excellent performance, with a C-index of 0.887. The key factors included sex, coagulation, blood cell indexes, and blood lipid levels. The ROC areas were 0.892 (quantitative) and 0.853 (qualitative), confirming model reliability.

CONCLUSION

A new nomogram model for assessing GC risk in CAG patients was successfully developed. However, due to data collection and time limitations, future studies should expand the sample size, perfect the validation process, and optimize the model to achieve more accurate risk prediction.

Lipid Metabolism in Gastrointestinal Malignancies: Exploring Dysregulation, Biomarkers, and Treatment Strategies

BACKGROUND

Gastrointestinal malignancies are a major public health concern worldwide, characterized by high incidence and mortality rates. Despite continuous advancements in existing treatment methods, overall survival rates remain low. Lipid metabolism plays a crucial role in the occurrence, progression, and treatment of gastrointestinal malignancies. Its involvement in the metabolic reprogramming of tumor cells, regulation of the tumor microenvironment, and drug response has become a research hotspot.

MATERIALS & METHODS

This review summarizes current research related to lipid metabolism mechanisms, biomarkers, and therapies in GI cancers, with emphasis on its interaction with the tumor microenvironment.

Platelet-to-high-density lipoprotein ratio (PHR) as a predictive biomarker for gastrointestinal cancers: evidence from NHANES

BACKGROUND

Gastrointestinal (GI) cancers, including gastric, colorectal, and esophageal cancers, pose a significant global health burden. Despite advancements in diagnostic tools, early detection remains challenging, particularly in low-resource settings. Emerging evidence highlights the platelet-to-high-density lipoprotein ratio (PHR) as a novel biomarker integrating systemic inflammation and lipid metabolism. However, its association with GI cancer risk remains underexplored.

METHODS

This study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2010 to 2018, comprising 19,388 participants, including 230 with GI cancers. PHR was calculated as the ratio of platelet count to high-density lipoprotein cholesterol levels and categorized into quartiles. Weighted logistic regression models, restricted cubic spline analysis, and subgroup analyses were employed to evaluate the association between PHR and GI cancer risk, adjusting for demographic, socioeconomic, lifestyle, and clinical factors.

RESULTS

Elevated PHR was independently associated with an increased risk of GI cancers. Participants in the highest PHR quartile exhibited a significantly higher risk (adjusted OR = 3.09; 95% CI: 2.16-4.43) compared to the lowest quartile. A dose-response relationship was observed, with two critical inflection points at PHR values of 3.2 and 4.5. Subgroup analyses revealed stronger associations among older adults, males, and obese individuals. The findings suggest that PHR may reflect the dynamic balance of systemic inflammation and lipid metabolism, contributing to tumorigenesis.

CONCLUSION

This study identifies PHR as a promising, cost-effective biomarker for early detection and risk stratification of GI cancers. Its integration into screening programs could improve precision medicine strategies by identifying high-risk individuals for early intervention. Further longitudinal and mechanistic studies are warranted to confirm these findings and explore the underlying biological mechanisms.

Exploring the mediating role of blood metabolites in the relationship between gut microbiota and gastric cancer risk: a Mendelian randomization study

Background

Prior studies have established correlations between gut microbiota (GM) dysbiosis, circulating metabolite alterations, and gastric cancer (GC) risk. However, the causal nature of these associations remains uncertain.

Methods

We utilized summary data from genome-wide association studies (GWAS) on GM (European, n=8,956), blood metabolites (European, n=120,241; East Asian, n=4,435), and GC (European, n=476,116; East Asian, n=167,122) to perform a bidirectional Mendelian randomization (MR) analysis, investigating the causal effects of GM and metabolites on GC risk. Additionally, we conducted mediation analysis (two-step MR) to identify potential metabolite mediators in the GM-GC relationship.

Results

We identified twelve negative and seven positive associations between specific GM taxa and GC risk. For blood metabolites, seven traits were found to be significantly associated with reduced GC risk in the European population, with these findings subsequently validated in the East Asian cohort. Three GM taxa showed potential causal associations with five metabolic traits: the Bacteroidia class and Bacteroidales order were positively correlated with five metabolites (all P < 0.013), while Bacteroides OTU97_27 exhibited a negative correlation with one metabolite (P = 0.007). Two-step MR analysis indicated that total lipids in intermediate-density lipoprotein (IDL), IDL particle concentration, phospholipids in medium low-density lipoprotein (LDL), phospholipids in small LDL, and free cholesterol in small LDL indirectly influenced the association between Bacteroidia class/Bacteroidales order and GC, with mediation proportions of 1.71% (P = 0.048), 1.69% (P = 0.048), 2.05% (P = 0.045), 1.85% (P = 0.048), and 1.99% (P = 0.045), respectively.

Conclusion

The present study provides suggestive evidence of a causal relationship between specific GM, blood metabolites, and GC risk, potentially offering new insights into GC etiology.

Gastric cancer: Nursing care and impact

ABSTRACT

Patients with gastric cancer experience symptoms that impact adequate nutritional intake. Delayed diagnosis may result in advanced disease. Surgery, chemotherapy, biologic therapy, and radiotherapy comprise interventions. This article discusses gastric cancer incidence and risks, treatment approaches, and nursing management of patients with gastric cancer, including advanced care planning for patients with terminal diagnoses.

Establishment and validation of a nomogram model for early diagnosis of gastric cancer: a large-scale cohort study

Purpose

Identifying high-risk populations and diagnosing gastric cancer (GC) early remains challenging. This study aimed to establish and verify a nomogram model for the early diagnosis of GC based on conventional laboratory indicators.

Methods

We performed a retrospective analysis of the clinical data of 2,770 individuals with first diagnosis of GC and 1,513 patients with benign gastric disease from January 2018 to December 2022. The cases were divided into the training set and validation set randomly, with a ratio of 7:3. Variable screening was performed by least absolute shrinkage and selection operator (LASSO) and logistic regression analysis. A nomogram was constructed in the training set to assist in the early diagnosis of GC.

Results

There were 4283 patients included in the study, with 2998 patients assigned in the training set and 1285 patients in the validation set. Through LASSO regression and logistic regression analysis, independent variables associated with GC were identified, including CEA, CA199, LYM, HGB, MCH, MCHC, PLT, ALB, TG, HDL, and AFR. The nomogram model was constructed using the above 11 independent indicators. The AUC was 0.803 for the training set and 0.797 for the validation set, indicating that the model showed high clinical diagnostic efficacy. The calibration curves and decision curve analysis (DCA) of the nomogram presented good calibration and clinical application ability.

Conclusion

Based on the analysis of large sample size, we constructed a nomogram model with 11 routine laboratory indicators, which showed good discrimination ability and calibration.

Blood lipid profiles associated with metastatic sites in advanced gastric cancer

BACKGROUND

This study explored the correlation between peripheral blood lipid levels and clinicopathological parameters in patients with advanced gastric cancer (GC), focusing on changes in lipid levels during disease progression.

METHODS

Pathological features and serum lipid profiles of 179 patients with stage III-IV gastric adenocarcinoma were analyzed. Lipid parameters examined included total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), apolipoprotein AI (Apo AI), apolipoprotein B (Apo B), lipoprotein(a) (Lp(a)), among others. The total cholesterol-lymphocyte score (TL score) and BMI were also calculated. The association between lipid parameters and clinicopathological characteristics such as age, gender, family history, and metastasis sites was assessed.

RESULTS

In GC patients, females had higher TG levels than males. Patients with peritoneal metastasis had significantly lower levels of TC, LDL-C, Apo B, and B/A ratio. Those with lung metastasis exhibited higher LDL-C levels and lower levels of VLDL-C. No significant associations were found between lipid levels and metastasis to distant lymph nodes, liver, or bone. Female patients with ovarian metastasis had significantly lower VLDL-C levels. Multivariate analysis revealed low TC as an independent risk factor for peritoneal metastasis, high LDL-C and low VLDL-C levels for lung metastasis, and younger age and low VLDL-C for ovarian metastasis.

CONCLUSION

Specific blood lipid levels are significantly associated with metastatic sites in advanced gastric cancer. Lipid profiles could serve as potential biomarkers for predicting metastatic sites in GC patients.

Association between serum total cholesterol and the development of gastric cancer: A two-way two-sample Mendelian randomization study

Previous epidemiologic studies have suggested a potential negative correlation between total cholesterol (TC) and Gastric cancer (GC); however, several observational studies have shown conflicting results and have failed to provide definitive evidence for a causal relationship between TC and GC. Therefore, we conducted a 2-sample bidirectional Mendelian randomization (MR) study to explore the genetic correlation and potential causal relationship between the 2 variables. We screened for single nucleotide polymorphisms (SNPs) associated with TC and GC utilizing a large-scale genome-wide association study (GWAS) public database. The causal relationship was analyzed using 5 MR analysis methods: inverse variance weighting (IVW), weighted median, MR-Egger regression, weighted mode, and simple mode. Additionally, reverse MR analysis was performed to evaluate the possibility of reverse causality. Sensitivity analyses were conducted, including heterogeneity tests, horizontal multiple validity tests, and leave-one-out tests. After meticulous screening, 79 SNPs were identified as instrumental variables (IVs). The IVW method revealed a causal relationship between TC and GC (OR = 0.844; 95% CI: 0.741-0.961; P = .01). Sensitivity analyses did not detect significant horizontal pleiotropy. Though heterogeneity was observed in the forward MR analysis (IVW, Qp = 0.0006), the results remained reliable as we utilized the IVW random-effects model as the primary analytical method. Furthermore, inverse MR analysis found no evidence of reverse causality between TC and GC, effectively ruling out the influence of GC on the reverse causality of TC. Our MR study provided evidence of a causal association between TC and GC, suggesting that TC acts as a protective factor against GC due to its negative association with the disease.

Association between blood lipid levels and the risk of liver cancer: a systematic review and meta-analysis

PURPOSE

The association between blood lipid levels and the risk of developing liver cancer remains a subject of ongoing debate. To elucidate this association, we conducted a meta-analysis by systematically incorporating data from all relevant prospective cohort studies.

METHODS

We conducted a systematic search of the PubMed, Embase, Web of Science, and Cochrane Library databases covering studies published from database inception through July 2023. This study included prospective cohort studies related to lipid profiles (e.g., total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels) that reported hazard ratios (HRs) or relative risks (RRs) with corresponding 95% confidence intervals (95% CIs) to investigate their association with the risk of liver cancer. During the analysis process, we used fixed-effects or random-effects models based on the level of heterogeneity among the studies and obtained pooled risk ratios using these models. To ensure the robustness and reliability of the study findings, we also conducted sensitivity analyses and publication bias analyses.

RESULTS

After conducting a systematic search, 12 studies were identified from a total of 11,904 articles and were included in the meta-analysis. These studies included a combined population of 10,765,221 participants, among whom 31,055 cases of liver cancer were reported. The analysis revealed that the pooled HR for the serum TC concentration (highest versus lowest) was 0.45 (95% CI = 0.35-0.58, I2 = 78%). For TGs, the HR was 0.67 (95% CI = 0.46-0.96, I2 = 86%), while for HDL-C, the HR was 0.72 (95% CI = 0.58-0.90, I2 = 65%). The HR for LDL-C was 0.51 (95% CI = 0.23-1.13, I2 = 93%).

CONCLUSION

The findings of this study indicate that serum TC, TG, and HDL-C levels are negatively associated with liver cancer risk, suggesting that higher concentrations of these lipids are associated with a reduced risk of liver cancer. However, no significant association has been found between LDL-C levels and liver cancer risk.

Biomarkers of lipid metabolism in gastric cancer: a case control study

BACKGROUND

The aim of this study was to explore the correlation between biomarkers of lipid metabolism and gastric cancer.

METHODS

1120 gastric cancer patients and 1134 health examiners enrolled in this study. The clinic data and serum lipid level, including Total cholesterol (TC), Triglyceride (TG), Low-density lipoprotein cholesterol (LDL-C) and High-density lipoprotein cholesterol (HDL-C), were collected.

RESULTS

Serum TG and LDL-C levels in patients with gastric cancer were higher than those in the control group. HDL-C levels were lower than the control group (P < 0.05). HDL-C and LDL-C were significantly correlated with the risk of gastric cancer. Concentrating on clinicopathological features, increased TG was more frequently in male patients with distal gastric cancer, N0 stage and early TNM stage. Increased TC was more frequently in early T, N and TNM stage. Decreased HDL-C was more common in distal location and low-undifferentiated gastric cancer. LDL-C elevation was more common in distal gastric cancer and early T stage.

CONCLUSIONS

The serum lipid level of gastric cancer patients was higher than healthy controls. HDL-C and LDL-C abnormal correlated with gastric cancer risk. However, as the progresses of gastric cancer, poor patient intake, increased tumor consumption, and continuous declining in nutritional status, the levels of TC and TG gradually decreased in advanced gastric cancer.

Metabolic underpinnings of cancer-related fatigue

Cancer-related fatigue (CRF) is one of the most prevalent and detrimental complications of cancer. Emerging evidence suggests that obesity and insulin resistance are associated with CRF occurrence and severity in cancer patients and survivors. In this narrative review, we analyzed recent studies including both preclinical and clinical research on the relationship between obesity and/or insulin resistance and CRF. We also describe potential mechanisms for these relationships, though with the caveat that because the mechanisms underlying CRF are incompletely understood, the mechanisms mediating the association between obesity/insulin resistance and CRF are similarly incompletely delineated. The data suggest that, in addition to their effects to worsen CRF by directly promoting tumor growth and metastasis, obesity and insulin resistance may also contribute to CRF by inducing chronic inflammation, neuroendocrinological disturbance, and metabolic alterations. Furthermore, studies suggest that patients with obesity and insulin resistance experience more cancer-induced pain and are at more risk of emotional and behavioral disruptions correlated with CRF. However, other studies implied a potentially paradoxical impact of obesity and insulin resistance to reduce CRF symptoms. Despite the need for further investigation utilizing interventions to directly elucidate the mechanisms of cancer-related fatigue, current evidence demonstrates a correlation between obesity and/or insulin resistance and CRF, and suggests potential therapeutics for CRF by targeting obesity and/or obesity-related mediators.