The mediation effect of serum metabolites on the relationship between long-term smoking exposure and esophageal squamous cell carcinoma

Long-term outcomes of smoker and drinker with oesophageal squamous cell carcinoma after oesophagectomy: a large-scale propensity score matching analysis

BACKGROUND

Oesophageal squamous cell carcinoma (OSCC) poses a considerable health burden, particularly in regions such as East Asia. This study aims to investigate the long-term outcomes of OSCC patients who are smokers and drinkers.

MATERIALS AND METHODS

In this retrospective analysis, data from Sichuan Cancer Hospital and Institute Esophageal Cancer Case Management Database between January 2010 and December 2017 were examined. Patients were categorised into different groups based on their smoking and alcohol consumption history: None, Smoker, Non-Smoker, Smoke-Only, Drinker, Non-Drinker, Drinker-Only, and Both. Survival outcomes were compared between the groups using Kaplan-Meier analysis and propensity score matching (PSM). The primary outcome was overall survival (OS), measured from surgery to death or last follow-up in April 2022.

RESULTS

The OS median was 45.4 months for all patients after oesophagectomy. Smokers had a significantly lower median OS of 36.6 months compared with Non-Smokers with 66.2 months (p<0.001). Similarly, Drinkers had a lower median OS of 34.4 months compared with Non-Drinkers with 52.0 months (p<0.001). PSM analysis confirmed the significant differences in OS between Smokers and Non-Smokers (p=0.002) and between Drinkers and Non-Drinkers (p=0.002). Subgroup analyses showed no significant differences in OS between Group Another and Group Both, Group Smoker-Only and Group Drinker-Only, and Group Drinker-Only and Group Both. (figure 4) CONCLUSION: Smoking and drinking were associated with significantly reduced OS in patients. However, no significant differences were found between the subgroups of patients who only smoked, only drank, or engaged in both habits.

Metabolomic landscape of overall and common cancers in the UK Biobank: A prospective cohort study

Information about the NMR metabolomics landscape of overall, and common cancers is still limited. Based on a cohort of 83,290 participants from the UK Biobank, we used multivariate Cox regression to assess the associations between each of the 168 metabolites with the risks of overall cancer and 20 specific types of cancer. Then, we applied LASSO to identify important metabolites for overall cancer risk and obtained their associations using multivariate cox regression. We further conducted mediation analysis to evaluate the mediated role of metabolites in the effects of traditional factors on overall cancer risk. Finally, we included the 13 identified metabolites as predictors in prediction models, and compared the accuracies of our traditional models. We found that there were commonalities among the metabolic profiles of overall and specific types of cancer: the top 20 frequently identified metabolites for 20 specific types of cancer were all associated with overall cancer; most of the specific types of cancer had common identified metabolites. Meanwhile, the associations between the same metabolite with different types of cancer can vary based on the site of origin. We identified 13 metabolic biomarkers associated with overall cancer, and found that they mediated the effects of traditional factors. The accuracies of prediction models improved when we added 13 identified metabolites in models. This study is helpful to understand the metabolic mechanisms of overall and a wide range of cancers, and our results also indicate that NMR metabolites are potential biomarkers in cancer diagnosis and prevention.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility

BACKGROUND

Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance.

METHODS

In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI).

FINDINGS

The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92).

INTERPRETATION

The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review

An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021. A total of 2,048 articles were screened, of which 314 full texts were further assessed resulting in 77 included articles. The most well-studied cancers were colorectal (19.5%), prostate (19.5%), and breast (19.5%). Most studies used a nested case-control design to estimate associations between individual metabolites and cancer risk and a liquid chromatography-tandem mass spectrometry untargeted or semi-targeted approach to measure metabolites in blood. Studies were geographically diverse, including countries in Asia, Europe, and North America; 27.3% of studies reported on participant race, the majority reporting White participants. Most studies (70.2%) included fewer than 300 cancer cases in their main analysis. This scoping review identified key areas for improvement, including needs for standardized race and ethnicity reporting, more diverse study populations, and larger studies.

Spatial distribution of tumor-infiltrating T cells indicated immune response status under chemoradiotherapy plus PD-1 blockade in esophageal cancer

Background

The spatial distribution of tumor-infiltrating T cells and its dynamics during chemoradiotherapy combined with PD-1 blockade is little known in esophageal squamous cell carcinoma (ESCC).

Methods

We applied the multiplex immunofluorescence method to identify T cells (CD4⁺, CD8⁺ T cells, and their PD-1^- or PD-1⁺ subsets) and myeloid-derived cells (CD11c⁺ dendritic cells, CD68⁺ macrophages, and their PD-L1⁺ subpopulations) in paired tumor biopsies (n = 36) collected at baseline and during combination (40 Gy of radiation) from a phase Ib trial (NCT03671265) of ESCC patients treated with first-line chemoradiotherapy plus anti-PD-1 antibody camrelizumab. We used the FoundationOne CDx assay to evaluate tumor mutational burden (TMB) in baseline tumor biopsies (n = 14). We dynamically assessed the nearest distance and proximity of T-cell subsets to tumor cells under combination and estimated the association between T-cell spatial distribution and combination outcome, myeloid-derived subsets, TMB, and patient baseline characteristics.

Findings

We found that the tumor compartment had lower T-cell subsets than the stromal compartment but maintained a comparable level under combination. Both before and under combination, PD-1^- T cells were located closer than PD-1⁺ T cells to tumor cells; T cells, dendritic cells, and macrophages showed the highest accumulation in the 5-10-μm distance. Higher CD4⁺ T cells in the tumor compartment and a shorter nearest distance of T-cell subsets at baseline predicted poor OS. Higher baseline CD4⁺ T cells, dendritic cells, and macrophages were associated with worse OS in less than 10-μm distance to tumor cells, but related with better OS in the farther distance. Higher on-treatment PD-1-positive-expressed CD4⁺ and CD8⁺ T cells within the 100-μm distance to tumor cells predicted longer OS. T cells, dendritic cells, and macrophages showed a positive spatial correlation. Both high TMB and smoking history were associated with a closer location of T cells to tumor cells at baseline.

Conclusions

We firstly illustrated the T-cell spatial distribution in ESCC. Combining chemoradiotherapy with PD-1 blockade could improve the antitumor immune microenvironment, which benefits the treatment outcome. Further understanding the precision spatiality of tumor-infiltrating T cells would provide new evidence for the tumor immune microenvironment and for the combination treatment with immunotherapy.

Clinical significance of atherosclerotic risk factors differs in early and advanced stages of plaque formation: A longitudinal study in the general population

BACKGROUND

Carotid plaque is a well-known prognostic factor for cardiovascular diseases. It is unclear which risk factors are associated with the transformation of carotid plaque over time. In this longitudinal study, we examined the risk factors related to carotid plaque progression.

METHODS

We enrolled 738 men without medication (mean age: 55 ± 10 years) who underwent the first and second health examinations. We measured carotid plaque thickness (PT) at three points of the right and left carotid artery. Plaque score (PS) was calculated by summing all the PTs. We divided the PS into three groups: None-group (PS <1.1), Early-group (1.1 ≤ PS <5.1), and Advanced-group (PS ≥5.1). We analyzed the relationship between PS progression and parameters such as age, body mass index, systolic blood pressure (SBP), fasting blood sugar, low-density lipoprotein cholesterol (LDL-C), and smoking and exercise habits.

RESULTS

In multivariable logistic regression analysis, age and SBP were independent factors for PS progression from none to early stages (age, OR 1.07, p = 0.002; SBP, 10 mmHg, OR 1.27, p = 0.041). Age, follow-up period and LDL-C were independently associated factors for PS progression from early to advanced stages (age, OR 1.08,p < 0.001; follow-up period OR1.19, p = 0.041; LDL-C, 10 mg/dL, OR 1.10, p = 0.049).

CONCLUSIONS

SBP was independently associated with the progress of early atherosclerosis, while LDL-C was independently associated with the progression of advanced atherosclerosis in the general population. Further studies are needed to assess whether early control of SBP and LDL-C levels can reduce the occurrence of future cardiovascular events.