Impact of glycemic traits, type 2 diabetes and metformin use on breast and prostate cancer risk: a Mendelian randomization study

Implications of obesity and insulin resistance for the treatment of oestrogen receptor-positive breast cancer

Breast cancer is the most common cancer in women, and incidence rates are rising, it is thought in part, due to increasing levels of obesity. Endocrine therapy (ET) remains the cornerstone of systemic therapy for early and advanced oestrogen receptor-positive (ER + ) breast cancer, but despite treatment advances, it is becoming more evident that obesity and insulin resistance are associated with worse outcomes. Here, we describe the current understanding of the relationship between both obesity and diabetes and the prevalence and outcomes for ER+ breast cancer. We also discuss the mechanisms associated with resistance to ET and the relationship to treatment toxicity.

The effect of SGLT2 inhibition on prostate cancer: Mendelian randomization and observational analysis using electronic healthcare and cohort data

We evaluated the effect of sodium-glucose cotransporter 2 (SGLT2) inhibition on prostate cancer by evidence triangulation. Using Mendelian randomization, we found that genetically proxied SGLT2 inhibition reduced the risk of overall (odds ratio = 0.56, 95% confidence interval [CI] = 0.38 to 0.82; 79,148 prostate cancer cases and 61,106 controls), advanced, and early-onset prostate cancer. Using electronic healthcare data (nSGLT2i = 24,155; nDPP4i = 24,155), we found that the use of SGLT2 inhibitors was associated with a 23% reduced risk of prostate cancer (hazard ratio = 0.77, 95% CI = 0.61 to 0.99) in men with diabetes. Using data from two prospective cohorts (n4C = 57,779; nUK_Biobank = 165,430), we found little evidence to support the association of HbA1c with prostate cancer, implying a non-glycemic effect of SGLT2 inhibition on prostate cancer. In summary, this study provides multiple layers of evidence to support the beneficial effect of SGLT2 inhibition on reducing prostate cancer risk. Future trials are warranted to investigate whether SGLT2 inhibitors can be recommended for prostate cancer prevention.

APOB and CCL17 as mediators in the protective effect of SGLT2 inhibition against myocardial infarction: Insights from proteome-wide mendelian randomization

AIMS

Sodium-glucose cotransporter 2 (SGLT2) inhibitors offer a novel therapeutic avenue for myocardial infarction (MI). However, the exact nature of this relationship and the underlying mechanisms are not fully understood.

METHODS

Utilizing a two-sample Mendelian Randomization (MR) analysis, we elucidated the causal effects stemming from the inhibition of SGLT2 on MI. Then, The pool of 4907 circulating proteins within the plasma proteome were utilized to explore the mediators of SGLT2 inhibitors on MI. Protein-protein network and enrichment analysis were conducted to clarify the potential mechanism. Finally, employing MR analysis and meta-analysis techniques, we systematically assessed the causal associations between SGLT2 inhibition and coronary heart diseases (CHD).

RESULTS

SGLT2 inhibition (per 1 SD decrement in HbA1c) was associated with reduced risk of MI (odds ratio [OR] = 0.462, [95% CI 0.222, 0.958], P = 0.038). Among 4907 circulating proteins, we identified APOB and CCL17 which were related to both SGLT2 inhibition and MI. Mediation analysis showed evidence of the indirect effect of SGLT2 inhibition on MI through APOB (β = -0.557, 95%CI [-1.098, -0.155]) with a mediated proportion of 72%, and CCL17 (β = -0.176, 95%CI [-0.332, -0.056]) with a mediated proportion of 17%. The meta-analysis result showed that SGLT2 inhibition was associated with a lower risk of CHD.

CONCLUSION

Based on proteome-wide mendelian randomization, APOB and CCL17 were seen as mediators in the protective effect of SGLT2 inhibition against myocardial infarction.

Association between the metabolic score for insulin resistance and prostate cancer: a cross-sectional study in Xinjiang

Background

Insulin resistance is associated with the development and progression of various cancers. However, the epidemiological evidence for the association between insulin resistance and prostate cancer is still limited.

Objectives

To investigate the associations between insulin resistance and prostate cancer prevalence.

Methods

A total of 451 patients who were pathologically diagnosed with prostate cancer in the First Affiliated Hospital of Xinjiang Medical University were selected as the case population; 1,863 participants who conducted physical examinations during the same period were selected as the control population. The metabolic score for insulin resistance (METS-IR) was calculated as a substitute indicator for evaluating insulin resistance. The Chi-square test and Mann-Whitney U test were performed to compare the basic information of the case population and control population. Univariate and multivariate logistic regression analyses to define factors that may influence prostate cancer prevalence. The generalized additive model (GAM) was applied to fit the relationship between METS-IR and prostate cancer. Interaction tests based on generalized additive model (GAM) and contour plots were also carried out to analyze the interaction effect of each factor with METS-IR on prostate cancer.

Results

METS-IR as both a continuous and categorical variable suggested that METS-IR was negatively associated with prostate cancer prevalence. Smoothed curves fitted by generalized additive model (GAM) displayed a nonlinear correlation between METS-IR and prostate cancer prevalence (P < 0.001), and presented that METS-IR was negatively associated with the odds ratio (OR) of prostate cancer. The interaction based on the generalized additive model (GAM) revealed that METS-IR interacted with low-density lipoprotein cholesterol (LDL-c) to influence the prostate cancer prevalence (P = 0.004). Contour plots showed that the highest prevalence probability of prostate cancer was achieved when METS-IR was minimal and low-density lipoprotein cholesterol (LDL-c) or total cholesterol (TC) was maximal.

Conclusions

METS-IR is nonlinearly and negatively associated with the prevalence of prostate cancer. The interaction between METS-IR and low-density lipoprotein cholesterol (LDL-c) has an impact on the prevalence of prostate cancer. The study suggests that the causal relationship between insulin resistance and prostate cancer still needs more research to confirm.

Does metformin really reduce prostate cancer risk: an up-to-date comprehensive genome-wide analysis

BACKGROUND

The relationship between metformin use and prostate cancer (PCa) risk has yet to be clear despite more than a decade of debate on this topic. Hence, we aimed to investigate the causal role of metformin in reducing PCa risk through an up-to-date comprehensive genome-wide analysis.

METHODS

We employed validated instrument variables of metformin use derived from a prior high-quality study, including five potential targets (AMPK, GCG, GDF15, MCI and MG3). Mendelian randomization (MR) analysis was performed to harmonize genetically predicted metformin use and PCa phenotypes. PCa phenotypes were from two large genome-wide association studies (GWAS), the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) and the FinnGen cohort. Seven methods were applied to generate MR results: the inverse variance weighted (IVW), IVW with multiplicative random effects, MR-Egger, MR-Egger (bootstrap), weighted median, simple mode and weighted mode. Strict sensitivity analysis was conducted to satisfy core assumptions of MR design.

RESULTS

We enrolled 32 significant single nucleotide polymorphisms (SNPs) that involved with metformin use. Nearly all targets yielded insignificant primary results (IVW with multiplicative random effects), except that AMPK target posed a positive effect on PCa risk from FinnGen cohort [odds ratio (OR): 6.09, 95% confidence interval (CI): 1.10-33.53, P value: 0.038]. The general effect of metformin use, comprising all 5 targets, also yielded negative results (random-effect meta-analysis with OR: 1.09, 95% CI: 0.76-1.58, P value: 0.637 for PRACTICAL; OR: 2.55, 95% CI: 0.58-11.16, P value: 0.215 for FinnGen). None of the sensitivity analyses provided support for a causal association between metformin use and PCa risk.

CONCLUSION

This up-to-date study did not support the protective role of metformin in reducing PCa risk, considering each target, overall effect, and sensitivity analysis. It is imperative to reflect on the presumed "almighty medicine" and ongoing phase III trials are anticipated to assess the anti-neoplasm effect of metformin.

SGLT2 inhibition, circulating proteins, and insomnia: A mendelian randomization study

BACKGROUND

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) initially emerged as oral antidiabetic medication but were subsequently discovered to exhibit pleiotropic actions. Insomnia is a prevalent and debilitating sleep disorder. To date, the causality between SGLT2 inhibitors and insomnia remains unclear. This study aims to evaluate the causality between SGLT2 inhibitors and insomnia and identify potential plasma protein mediators.

METHODS

Using a two-sample Mendelian Randomization (MR) analysis, we estimated the causality of SGLT2 inhibition on insomnia and sleep duration. Additionally, employing a two-step and proteome-wide MR analysis, we evaluated the causal link of SGLT2 inhibition on 4907 circulating proteins and the causality of SGLT2 inhibition-driven plasma proteins on insomnia. We applied a false discovery rate (FDR) correction for multiple comparisons. Furthermore, mediation analyses were used to identify plasma proteins that mediate the effects of SGLT2 inhibition on insomnia.

RESULTS

SGLT2 inhibition was negatively correlated with insomnia (odds ratio [OR] = 0.791, 95 % confidence interval [CI] [0.715, 0.876], P = 5.579*10^-6) and positively correlated with sleep duration (β = 0.186, 95 % CI [0.059, 0.314], P = 0.004). Among the 4907 circulating proteins, diadenosine tetraphosphatase (Ap4A) was identified as being linked to both SGLT2 inhibition and insomnia. Mediation analysis indicated that the effect of SGLT2 inhibition on insomnia partially operates through Ap4A (β = -0.018, 95 % CI [-0.036, -0.005], P = 0.023), with a mediation proportion of 7.7 %.

CONCLUSION

The study indicated a causality between SGLT2 inhibition and insomnia, with plasma Ap4A potentially serving as a mediator.

Causal relationship between genetically determined plasma metabolites and skin cancer: a two-sample Mendelian randomization study

We aimed to unveil the underlying pathogenic mechanisms of skin cancer in relation to metabolic factors and pathway mechanisms. This study utilized the TwoSample Mendelian randomization (MR) method to investigate the causal relationship between 1400 plasma metabolites and skin cancer. The primary method employed was the inverse variance weighting (IVW). Through IVW analysis, we found 105 plasma metabolites associated with Basal Cell Carcinoma (BCC), with the highest association observed for Prolylglycine levels (OR [95% CI]: 1.1902 [1.0274, 1.3788]). For Malignant Melanoma of Skin (MSS), 68 plasma metabolites were linked, with the highest causal relationship seen for 3-Hydroxybutyrate levels (OR [95% CI]: 1.0030 [1.0013, 1.0048]). Regarding actinic keratosis (AK), and the highest association observed for Hexadecadienoate (16:2n6) levels (OR [95% CI]: 1.3302 [1.0333, 1.7125]). Glycerol to palmitoylcarnitine (16: n6) levels (OR [95% CI]: 1.3302 [1.0333, 1.125]) were found to be significant for BCC and AK. Palmitoylcarnitine (C16) had the most positive causal effect for BCC (OR [95% CI]: 1.1777 [1.0493, 1.3218]), while 5-hydroxy-2-methylpyridine sulfate levels had the highest effect for AK (OR [95% CI]: 1.1788 [1.0295, 1.3498]). And 4-guanidinobutanoate levels had the largest positive causal effect (OR [95% CI]: 1.0857 [1.0417, 1.1317]) for BCC, and X-11880 levels for MSS (OR [95% CI]: 1.0013 [1.0000, 1.0025]). The study revealed a positive association between hereditary Glycerol to palmitoylcarnitine (C16) and 5-hydroxy-2-methylpyridine sulfate levels with the risk of developing BCC and AK. Additionally, 4-guanidinobutanoate levels and X 11880 levels were found to be positively associated with the risk of BCC and MMS.

Drug-target Mendelian randomization revealed a significant association of genetically proxied metformin effects with increased prostate cancer risk

The association between metformin use and risk of prostate cancer remains controversial, while data from randomized trials is lacking. We aim to evaluate the association of genetically proxied metformin effects with prostate cancer risk using a drug-target Mendelian randomization (MR) approach. Summary statistics for prostate cancer were obtained from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium (79,148 cases and 61,106 controls). Cis-expression quantitative trait loci (cis-eQTL) variants in the gene targets of metformin were identified in the GTEx project and eQTLGen consortium. We also obtained male-specific genome-wide association study data for type 2 diabetes, body mass index (BMI), total testosterone, bioavailable testosterone, estradiol, and sex hormone binding globulin for mediation analysis. Inverse-variance weighted (IVW) regression, weighted median, MR-Egger regression, and MR-PRESSO were performed in the main MR analysis. Multivariable MR was used to identify potential mediators and genetic colocalization analysis was performed to assess any shared genetic basis between two traits of interest. We found that genetically proxied metformin effects (1-SD HbA1c reduction, equivalent to 6.75 mmol/mol) were associated with higher risk of prostate cancer (odds ratioIVW [ORIVW]: 1.55, 95% confidence interval, CI: 1.23-1.96, p = 3.0 × 10-3). Two metformin targets, mitochondrial complex I (ORIVW: 1.48, 95% CI: 1.07-2.03, p = 0.016) and gamma-secretase complex (ORIVW: 2.58, 95%CI :1.47-4.55, p = 0.001), showed robust associations with prostate cancer risk, and their effects were partly mediated through BMI (16.4%) and total testosterone levels (34.3%), respectively. These results were further supported by colocalization analysis that expressions of NDUFA13 and BMI, APH1A, and total testosterone may be influenced by shared genetic factors, respectively. In summary, our study indicated that genetically proxied metformin effects may be associated with an increased risk of prostate cancer. Repurposing metformin for prostate cancer prevention in general populations is not supported by our findings.

The causality between Type 2 diabetes and breast cancer: a bidirectional two-sample Mendelian randomization study

Objective: Observational studies showed that Type 2 diabetes increased the risk of breast cancer, and vice versa. However, it is uncertain whether the link is causal or just due to confounding factors. Using bidirectional Mendelian randomization analysis, we assessed the bidirectional causal relationship from a genetic level. Methods: Large genome-wide association studies yielded summary-level data for Type 2 diabetes and breast cancer. Results: Genetically predicted Type 2 diabetes presented no statistically significant association with overall breast cancer or its subtypes. Similarly, genetically predicted overall breast cancer or its subtypes had no causal effect on Type 2 diabetes. Sensitivity analyses yielded similar results. Conclusion: Our bidirectional Mendelian randomization studies revealed no causal links between Type 2 diabetes and breast cancer.

Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses

BACKGROUND

The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses.

METHODS AND FINDINGS

We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices.

CONCLUSIONS

In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.

Genetic effect of metformin use on risk of cancers: evidence from Mendelian randomization analysis

BACKGROUND

Increasing number of studies reported the positive effect of metformin on the prevention and treatment of cancers. However, the genetic causal effect of metformin utilization on the risk of common cancers was not completely demonstrated.

METHODS

Two-sample Mendelian Randomization (two-sample MR) analysis was conducted to uncover the genetically predicted causal association between metformin use and 26 kinds of cancers. Besides, two-step Mendelian Randomization (two-step MR) assessment was applied to clarify the mediators which mediated the causal effect of metformin on certain cancer. We utilized five robust analytical methods, in which the inverse variance weighting (IVW) method served as the major one. Sensitivity, pleiotropy, and heterogeneity were assessed. The genetic statistics of exposure, outcomes, and mediators were downloaded from publicly available datasets, including the Open Genome-Wide Association Study (GWAS), FinnGen consortium (FinnGen), and UK Biobank (UKB).

RESULTS

Among 26 kinds of common cancers, HER-positive breast cancer was presented with a significant causal relationship with metformin use [Beta: - 4.0982; OR: 0.0166 (95% CI: 0.0008, 0.3376); P value: 0.0077], which indicated metformin could prevent people from HER-positive breast cancer. Other cancers only showed modest associations with metformin use. Potential mediators were included in two-step MR, among which total testosterone levels (mediating effect: 24.52%) displayed significant mediating roles. Leave-one-out, MR-Egger, and MR-PRESSO analyses produced consistent outcomes.

CONCLUSION

Metformin use exhibited a genetically protective effect on HER-positive breast cancer, which was partially mediated by total testosterone levels.

Evaluation of the Effect of Sodium-Glucose Cotransporter 2 Inhibition on Fracture Risk: Evidence From Mendelian Randomization and Genetic Association Study

This study aims to evaluate the causal effect of sodium-glucose cotransporter 2 (SGLT2) inhibition on bone mineral density (BMD), osteoporosis, and fracture risk using genetics. Two-sample Mendelian randomization (MR) analyses were performed utilizing two sets of genetic variants as instruments (six and two single-nucleotide polymorphisms [SNPs]) associated with SLC5A2 gene expression and glycated hemoglobin A1c levels. Summary statistics of BMD from the Genetic Factors for Osteoporosis consortium (BMD for total body, n = 66,628; femoral neck, n = 32,735; lumbar spine, n = 28,498; forearm, n = 8143) and osteoporosis (6303 cases, 325,717 controls) and 13 types of fracture (≤17,690 cases, ≤328,382 controls) data from the FinnGen study were obtained. One-sample MR and genetic association analyses were conducted in UK Biobank using the individual-level data of heel BMD (n = 256,286) and incident osteoporosis (13,677 cases, 430,262 controls) and fracture (25,806 cases, 407,081 controls). Using six SNPs as the instrument, genetically proxied SGLT2 inhibition showed little evidence of association with BMD of total body, femoral neck, lumbar spine, and forearm (all p ≥ 0.077). Similar results were observed using two SNPs as instruments. Little evidence was found for the SGLT2 inhibition effect on osteoporosis (all p ≥ 0.112) or any 11 major types of fracture (all p ≥ 0.094), except for a nominal significance for fracture of lower leg (p = 0.049) and shoulder and upper arm (p = 0.029). One-sample MR and genetic association analysis showed that both the weighted genetic risk scores constructed from the six and two SNPs were not causally associated with heel BMD, osteoporosis, and fracture (all p ≥ 0.387). Therefore, this study does not support an effect of genetically proxied SGLT2 inhibition on fracture risk. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Dietary glycemic index, glycemic load and all-cause and cause-specific mortality: A meta-analysis of prospective cohort studies

BACKGROUND & AIMS

The findings of previous studies investigating the association between dietary glycemic index, glycemic load, and the risk of mortality have been inconsistent. We performed a meta-analysis to evaluate this association.

METHODS

A systematic search in PubMed and Web of Science databases was conducted to identify prospective cohort studies on dietary glycemic index and load with risk of mortality through January 2023. Study-specific relative risks (RR) were combined by using random effects models.

RESULTS

Fifteen prospective cohort studies with a total of 527,650 participants and 48,598 all-cause and cause-specific deaths were included in the current meta-analysis. Pooled analyses indicated a higher risk of all-cause mortality (RR = 1.10, 95% CI: 1.00-1.20) and stroke mortality (RR = 1.30, 95% CI: 1.04-1.62) for the highest versus lowest levels of glycemic index. A significant non-linear association was found between glycemic index and mortality of all-causes (P for non-linearity = 0.02) and CVD (P for non-linearity <0.001), indicating increased risk at high levels of glycemic index (≥63.1 for all-cause mortality; ≥72.8 for CVD mortality). Glycemic load was positively associated with risk of CVD mortality (RR = 1.18, 95% CI: 1.09-1.27) and stroke mortality (RR = 1.30, 95% CI: 1.05-1.60) in the highest versus lowest meta-analysis. For cancer mortality, there was no significant association with glycemic index, but the association with glycemic load differed by sex.

CONCLUSIONS

Our results indicated that high glycemic index and glycemic load was associated with an increased risk of mortality from CVD and stroke. Further large prospective studies are warranted to provide definitive evidence in subgroups.

Elevated Glycated Haemoglobin (HbA1c) Is Associated with an Increased Risk of Pancreatic Ductal Adenocarcinoma: A UK Biobank Cohort Study

BACKGROUND

The role of dysglycaemia as a risk marker for Pancreatic Ductal Adenocarcinoma (PDAC) is uncertain. We investigated the relationship between glycated haemoglobin (HbA1c) and incident PDAC using a retrospective cohort study within the UK Biobank.

METHODS

A study involving 499,804 participants from the UK Biobank study was undertaken. Participants were stratified by diabetes mellitus (DM) status, and then by HbA1c values < 42 mmol/mol, 42-47 mmol/mol, or ≥48 mmol/mol. Cox proportional hazard models were used to describe the association between HbA1c category (with time-varying interactions) and incident PDAC.

RESULTS

PDAC occurred in 1157 participants during 11.6 (10.9-12.3) years follow up [(median (interquartile range)]. In subjects without known DM at baseline, 12 months after recruitment, the adjusted hazard ratios (aHR, 95% CI) for incident PDAC for HbA1c 42-47 mmol/mol compared to HbA1c < 42 mmol/mol (reference group) was 2.10 (1.31-3.37, p = 0.002); and was 8.55 (4.58-15.99, p < 0.001) for HbA1c ≥ 48 mmol/mol. The association between baseline HbA1c and incident PDAC attenuated with increasing duration of time of follow-up to PDAC diagnosis.

CONCLUSIONS

Dysglycaemia detected by elevated HbA1c is associated with an increased risk of PDAC. The strength of the association between elevated HbA1c and incident PDAC is inversely proportional to the time from detecting dysglycaemia but remains significant for at least 60 months following HbA1c testing.

A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach

In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.

Prognostic value of metformin in cancers: An updated meta-analysis based on 80 cohort studies

BACKGROUND

Experiments have shown that metformin can inhibit cancer cell growth, but clinical observations have been inconsistent, so we pooled the currently available data to evaluate the impact of metformin on cancer survival and progression.

METHODS

PubMed, web of science, Embase, and Cochrane databases were searched. Pooled hazard ratios (HRs) were identified using a random-effects model to estimate the strength of the association between metformin and survival and progression in cancer patients.

RESULTS

We incorporated 80 articles published from all databases which satisfied the inclusion criterion. It showed that metformin was associated with better overall survival (hazard ratio [HR] = 0. 81; 95% confidence interval [CI]: [0.77-0.85]) and cancer-specific survival (HR = 0.79; 95% CI: [0.73-0.86]), and metformin was associated with progression-free survival (HR = 0.76; 95% CI: [0.66-0.87]). In patients with diabetes mellitus, the HR of overall survival was 0.79(95% CI: [0.75-0.83]), progression-free survival was 0.72(95% CI: [0.60-0.85]), and the cancer-specific survival was 0.76(95% CI: [0.68-0.86]). It was proposed that metformin can improve the prognosis of cancer patients with diabetes mellitus.

CONCLUSION

Based on cohort studies, metformin therapy has potential survival benefits for patients with malignancy, especially with the greatest benefits seen in breast cancer on overall survival, progression-free survival, and cancer-specific survival. And metformin also showed potential benefits in cancer-specific survival in colorectal and prostate cancer.

Linking Physical Activity to Breast Cancer Risk via the Insulin/Insulin-like Growth Factor Signaling System, Part 2: The Effect of Insulin/Insulin-like Growth Factor Signaling on Breast Cancer Risk

Perturbation of the insulin/insulin-like growth factor (IGF) signaling system is often cited as a mechanism driving breast cancer risk. A systematic review identified prospective cohort studies and Mendelian randomization studies that examined the effects of insulin/IGF signaling (IGF, their binding proteins (IGFBP), and markers of insulin resistance] on breast cancer risk. Meta-analyses generated effect estimates; risk of bias was assessed and the Grading of Recommendations Assessment, Development and Evaluation system applied to evaluate the overall quality of the evidence. Four Mendelian randomization and 19 prospective cohort studies met our inclusion criteria. Meta-analysis of cohort studies confirmed that higher IGF-1 increased risk of breast cancer; this finding was supported by the Mendelian randomization studies. IGFBP-3 did not affect breast cancer. Meta analyses for connecting-peptide and fasting insulin showed small risk increases, but confidence intervals were wide and crossed the null. The quality of evidence obtained ranged from 'very low' to 'moderate'. There were insufficient studies to examine other markers of insulin/IGF signaling. These findings do not strongly support the biological plausibility of the second part of the physical activity-insulin/IGF signaling system-breast cancer pathway. Robust conclusions cannot be drawn due to the dearth of high quality studies. See related article by Swain et al., p. 2106.

KCNK3 inhibits proliferation and glucose metabolism of lung adenocarcinoma via activation of AMPK-TXNIP pathway

Non-small cell lung cancer (NSCLC) is a primary histological subtype of lung cancer with increased morbidity and mortality. K⁺ channels have been revealed to be involved in carcinogenesis in various malignant tumors. However, TWIK-related acid-sensitive potassium channel 1 (TASK-1, also called KCNK3), a genetic member of K2P channels, remains an enigma in lung adenocarcinoma (LUAD). Herein, we investigated the pathological process of KCNK3 in proliferation and glucose metabolism of LUAD. The expressions of KCNK3 in LUAD tissues and corresponding adjacent tissues were identified by RNA sequencing, quantitative real-time polymerase chain reaction, western blot, and immunohistochemistry. Gain and loss-of-function assays were performed to estimate the role of KCNK3 in proliferation and glucose metabolism of LUAD. Additionally, energy metabolites of LUAD cells were identified by targeted metabolomics analysis. The expressions of metabolic molecules and active biomarkers associated with AMPK-TXNIP signaling pathway were detected via western blot and immunofluorescence. KCNK3 was significantly downregulated in LUAD tissues and correlated with patients' poor prognosis. Overexpression of KCNK3 largely regulated the process of oncogenesis and glycometabolism in LUAD in vitro and in vivo. Mechanistic studies found that KCNK3-mediated differential metabolites were mainly enriched in AMPK signaling pathway. Furthermore, rescue experiments demonstrated that KCNK3 suppressed proliferation and glucose metabolism via activation of the AMPK-TXNIP pathway in LUAD cells. In summary, our research highlighted an emerging role of KCNK3 in the proliferative activity and glycometabolism of LUAD, suggesting that KCNK3 may be an optimal predictor for prognosis and a potential therapeutic target of LUAD.

Role of single nucleotide polymorphisms of the HSD3B1 gene (rs6203 and rs33937873) in the prediction of prostate cancer risk

3-β-hydroxysteroid dehydrogenase 1 (HSD3B1) is shown to affect dihydrotestosterone level in prostatic tissue which is a risk factor for prostate cancer (PC). The present study aimed to determine whether rs33937873 (G313A) and rs6203 (C338T) single nucleotide polymorphisms (SNP) in HSD3B1 gene was a potential risk factor for PC susceptibility and can predict the recurrence of PC in Egyptian patients. A total of 186 Egyptian patients were selected with incident primary PC and compared with 180 age healthy controls. The frequencies and the main effect of rs33937873 and rs6203 in HSD3B1 were compared and investigated between the patients and control using genotyping technique and statistical analysis. The mutant GA genotype of G313A in rs33937873 SNP was considered as an independent risk for PC in the multivariate regression analysis [odds ratio (OR)=2.7, 95% confidence intervals (CI): 1.2-5.5, P=0.01] together with positive history of hypertension (HTN) (OR=6.2, 95% CI: 3.2-12.1, P=0.0001) and begin prostatic hyperplasia (BPH; OR=8.9, 95% CI: 4.5-17.5, P=0.0001). Conversely, in rs6203 (C338T), C allele is considered as major risk allele in the development of PC (OR=1.8, 95% CI: 1.3-2.4, P=0.0003). The univariate logistic regression analyses indicated that CC genotype of rs6203 was a PC risk factor (OR=1.9, 95% CI: 1.3-2.9, P=0.002). In addition, the frequency of the A-C haplotype established by rs33937873-rs6203 was also significantly higher for PC (P=0.013). The predication of PC recurrence was associated only with positive family history (OR=7.7, 95% CI: 2.3-25.9, P=0.001) and not for The G313A and C338T SNPs. These results suggested that the two HSD3B1 polymorphisms rs33937873 and rs6203 may modify the risk of PC, particularly among patients with HTN and history of BPH, suggesting them as prominent future markers for prediction of PC risk.

The Impact of Metabolic Syndrome and Type 2 Diabetes Mellitus on Prostate Cancer

Prostate cancer (PCa) remains the second most common type of cancer in men worldwide in 2020. Despite its low death rate, the need for new therapies or prevention strategies is critical. The prostate carcinogenesis process is complex and multifactorial. PCa is caused by a variety of mutations and carcinogenic events that constitutes the disease's multifactorial focus, capable of not only remodeling cellular activity, but also modeling metabolic pathways to allow adaptation to the nutritional requirements of the tumor, creating a propitious microenvironment. Some risk factors have been linked to the development of PCa, including Metabolic Syndrome (MetS) and Type 2 Diabetes Mellitus (T2DM). MetS is intrinsically related to PCa carcinogenic development, increasing its aggressiveness. On the other hand, T2DM has the opposite impact, although in other carcinomas its effect is similar to the MetS. Although these two metabolic disorders may share some developmental processes, such as obesity, insulin resistance, and dyslipidemia, their influence on PCa prognosis appears to have an inverse effect, which makes this a paradox. Understanding the phenomena behind this paradoxical behavior may lead to new concepts into the comprehension of the diseases, as well as to evaluate new therapeutical targets. Thus, this review aimed to evaluate the impact of metabolic disorders in PCa's aggressiveness state and metabolism.

Systematic review of Mendelian randomization studies on risk of cancer

BACKGROUND

We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence.

METHODS

We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded.

RESULTS

We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer.

CONCLUSIONS

Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.

Metformin Downregulates PD-L1 Expression in Esophageal Squamous Cell Catrcinoma by Inhibiting IL-6 Signaling Pathway

Purpose

To characterize the mechanism by which metformin inhibits PD-L1 expression in esophageal squamous cell carcinoma (ESCC) and to evaluate the effect of metformin on the antitumor immune response.

Methods

The Cancer Genome Atlas (TCGA) database was used to analyze the correlations between IL-6 and prognosis and between IL-6 and PD-L1 gene expression in esophageal cancer. Reverse transcription-quantitative polymerase chain reaction (RT-PCR), Western blotting and immunofluorescence were used to study the mechanism by which metformin affects PD-L1 expression. Additionally, T cell function was assessed in a coculture system containing ESCC cells and peripheral blood mononuclear cells (PBMCs) treated with metformin or IL-6. In an in vivo assay, we used a model established with NPIdKO™ mice, which have a reconstituted immune system generated by transplanting PBMCs through intravenous injection, to evaluate the effect of metformin on tumors.

Results

The TCGA esophageal cancer data showed that IL-6 expression was positively correlated with PD-L1 expression and that patients with high IL-6 expression had a significantly lower overall survival rate than patients with low IL-6 expression. PD-L1 expression in ESCC cell lines was significantly inhibited by metformin via the IL-6/JAK2/STAT3 signaling pathway but was not correlated with the canonical AMPK pathway. In the coculture system, the metformin pretreatment group showed higher T cell activation and better T cell killing function than the control group. Animal experiments confirmed that metformin downregulated PD-L1 expression and that combination treatment with metformin and PD-1 inhibitors synergistically enhanced the antitumor response.

Conclusions

Metformin downregulated PD-L1 expression by blocking the IL-6/JAK2/STAT3 signaling pathway in ESCC, which enhanced the antitumor immune response.

Identifying causality, genetic correlation, priority and pathways of large-scale complex exposures of breast and ovarian cancers

BACKGROUND

Genetic correlations, causalities and pathways between large-scale complex exposures and ovarian and breast cancers need systematic exploration.

METHODS

Mendelian randomisation (MR) and genetic correlation (GC) were used to identify causal biomarkers from 95 cancer-related exposures for risk of breast cancer [BC: oestrogen receptor-positive (ER + BC) and oestrogen receptor-negative (ER - BC) subtypes] and ovarian cancer [OC: high-grade serous (HGSOC), low-grade serous, invasive mucinous (IMOC), endometrioid (EOC) and clear cell (CCOC) subtypes].

RESULTS

Of 31 identified robust risk factors, 16 were new causal biomarkers for BC and OC. Body mass index (BMI), body fat mass (BFM), comparative body size at age 10 (CBS-10), waist circumference (WC) and education attainment were shared risk factors for overall BC and OC. Childhood obesity, BMI, CBS-10, WC, schizophrenia and age at menopause were significantly associated with ER + BC and ER - BC. Omega-6:omega-3 fatty acids, body fat-free mass and basal metabolic rate were positively associated with CCOC and EOC; BFM, linoleic acid, omega-6 fatty acids, CBS-10 and birth weight were significantly associated with IMOC; and body fat percentage, BFM and adiponectin were significantly associated with HGSOC. Both GC and MR identified 13 shared factors. Factors were stratified into five priority levels, and visual causal networks were constructed for future interventions.

CONCLUSIONS

With analysis of large-scale exposures for breast and ovarian cancers, causalities, genetic correlations, shared or specific factors, risk factor priority and causal pathways and networks were identified.

Observation of Efficacy of Internet-Based Chronic Disease Management Model Combined with Modified Therapy of Bushenyiliu Decoction in Treating Patients with Type 2 Diabetes Mellitus and Prostate Cancer and Its Effect on Disease Control Rate

Objective

To explore the efficacy of Internet-based chronic disease management model combined with the modified therapy of Bushenyiliu decoction in treating patients with type 2 diabetes mellitus (T2DM) and prostate cancer and its effect on disease control rate (DCR).

Methods

120 patients with T2DM and prostate cancer admitted to the Affiliated Hospital of Yangzhou University, Yangzhou First People's Hospital, from February 2019 to February 2020, were retrospectively analyzed and equally divided into the experimental group and the control group according to their admission order. Conventional treatment combined with the modified therapy of Bushenyiliu decoction was performed on all patients for 3 months, and the Internet-based chronic disease management model was adopted for patients in the experimental group additionally, so as to compare their short-term effect, survival time, disease progression, blood glucose indicators, immune function indicators, and type 2 Diabetes Self-Care Scale (2-DSCS) scores.

Results

Compared with the control group, the experimental group obtained significantly higher DCR and objective remission rate (ORR) (P < 0.05), higher survival time and disease progression (P < 0.001), better blood glucose indicators and immune function indicators (P < 0.001), and higher 2-DSCS scores (P < 0.001) after treatment.

Conclusion

Combining the Internet-based chronic disease management model with the modified therapy of Bushenyiliu decoction can effectively enhance the self-care ability of patients with T2DM and prostate cancer, improve their blood glucose level, promote their body immunity, and comprehensively optimize the cancer control effect, which should be promoted in practice.

Glycaemic index, glycaemic load and cancer risk: results from the prospective NutriNet-Santé cohort

BACKGROUND

Evidence is accumulating that high dietary glycaemic index (GI) and glycaemic load (GL) are potential risk factors for several metabolic disorders (e.g. type-2 diabetes, cardiovascular diseases), but remains limited concerning cancer risk. Although, mechanistic data suggest that consuming high-GI foods may contribute to carcinogenesis through elevated blood glucose levels, insulin resistance or obesity-related mechanisms. Our objective was to study the associations between dietary GI/GL and cancer.

METHODS

In total, 103 020 French adults (median age = 40.2 years) from the NutriNet-Santé cohort (2009-2020) with no cancer or diabetes at baseline were included (705 137 person-years, median follow-up time = 7.7 years). Repeated 24-h dietary records linked with a detailed food-composition table (>3500 food/beverage items). We computed the average dietary GI and GL at the individual level. Associations between GI, GL, contribution of low- and medium/high-GI foods to energy and carbohydrate intake and cancer risk (overall, breast, prostate and colorectal) were assessed using multivariable Cox proportional-hazard models.

RESULTS

Higher dietary GL was associated with higher overall cancer risk [n = 3131 cases, hazard ratios (HRs) for sex-specific quintile 5 vs 1 = 1.25, 95% confidence interval (CI) = 1.03-1.52; Ptrend = 0.008] and specifically postmenopausal breast cancer (n = 924, HRQ5vs.Q1 = 1.64, 95% CI = 1.06-2.55; Ptrend = 0.03). A higher contribution of low-GI food/beverages to energy intake was associated with lower cancer risk whereas a higher contribution of medium/high-GI items to energy intake was positively associated with higher risk of overall, breast and postmenopausal breast cancers (Ptrend ≤ 0.02).

CONCLUSIONS

These results support a possible impact of GI/GL on cancer risk. If confirmed in other populations and settings, dietary GI/GL could be considered as modifiable risk factors for primary cancer prevention.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT03335644.

Metformin mitigates PLCε gene expression and modulates the Notch1/Hes and androgen receptor signaling pathways in castration-resistant prostate cancer xenograft models

The present study aimed to establish a mouse model of patient-derived castration-resistant prostate cancer (CRPC) xenograft tumors, and to evaluate the effects of various doses of metformin on phospholipase Cε (PLCε) expression and the neurogenic locus notch homolog protein 1 (Notch1)/hairy and enhancer of split 1 and androgen receptor (AR) signaling pathways via western blotting and reverse transcription-quantitative PCR. Additionally, phorbol 12-myristate 13-acetate was used to activate PLC, and Jagged1 was used as a Notch activator to verify whether metformin could suppress CRPC development via the PLCε/Notch1/AR pathways. The results confirmed that metformin may serve critical roles in CRPC by significantly inhibiting the occurrence, growth and proliferation of CRPC tumors by decreasing PLCε/Notch1 expression and AR nucleation.

Instrumental Heterogeneity in Sex-Specific Two-Sample Mendelian Randomization: Empirical Results From the Relationship Between Anthropometric Traits and Breast/Prostate Cancer

Background

In two-sample Mendelian randomization (MR) studies, sex instrumental heterogeneity is an important problem needed to address carefully, which however is often overlooked and may lead to misleading causal inference.

Methods

We first employed cross-trait linkage disequilibrium score regression (LDSC), Pearson's correlation analysis, and the Cochran's Q test to examine sex genetic similarity and heterogeneity in instrumental variables (IVs) of exposures. Simulation was further performed to explore the influence of sex instrumental heterogeneity on causal effect estimation in sex-specific two-sample MR analyses. Furthermore, we chose breast/prostate cancer as outcome and four anthropometric traits as exposures as an illustrative example to illustrate the importance of taking sex heterogeneity of instruments into account in MR studies.

Results

The simulation definitively demonstrated that sex-combined IVs can lead to biased causal effect estimates in sex-specific two-sample MR studies. In our real applications, both LDSC and Pearson's correlation analyses showed high genetic correlation between sex-combined and sex-specific IVs of the four anthropometric traits, while nearly all the correlation coefficients were larger than zero but less than one. The Cochran's Q test also displayed sex heterogeneity for some instruments. When applying sex-specific instruments, significant discrepancies in the magnitude of estimated causal effects were detected for body mass index (BMI) on breast cancer (P = 1.63E-6), for hip circumference (HIP) on breast cancer (P = 1.25E-20), and for waist circumference (WC) on prostate cancer (P = 0.007) compared with those generated with sex-combined instruments.

Conclusion

Our study reveals that the sex instrumental heterogeneity has non-ignorable impact on sex-specific two-sample MR studies and the causal effects of anthropometric traits on breast/prostate cancer would be biased if sex-combined IVs are incorrectly employed.

Type 2 Diabetes and Cancer: An Umbrella Review of Observational and Mendelian Randomization Studies

BACKGROUND

Type 2 diabetes mellitus (T2DM) has been associated with an increased risk of developing several common cancers, but it is unclear whether this association is causal. We aimed to summarize the evidence on T2DM and cancer and evaluate the validity of associations from both observational and Mendelian randomization (MR) studies.

METHODS

We performed an umbrella review of the evidence across meta-analyses of observational studies that examined associations of T2DM with risk of developing or dying from site-specific cancers, and MR studies that explored the potential causal association of T2DM and associated biomarkers with cancer risk.

RESULTS

We identified eligible observational meta-analyses that assessed associations between T2DM and cancer incidence for 18 cancer sites, cancer mortality for seven sites, and cancer incidence or mortality for four sites. Positive associations between T2DM and six cancers reached strong or highly suggestive evidence. We found eight MR studies assessing the association of genetically predicted T2DM and seven and eight studies assessing the association of genetically predicted fasting insulin or fasting glucose concentrations, respectively, upon site-specific cancers. Positive associations were found between genetically predicted T2DM and fasting insulin and risk of six cancers. There was no association between genetically predicted fasting plasma glucose and cancer except for squamous cell lung carcinoma.

CONCLUSIONS

We found robust observational evidence for the association between T2DM and colorectal, hepatocellular, gallbladder, breast, endometrial, and pancreatic cancers.

IMPACT

Potential causal associations were identified for genetically predicted T2DM and fasting insulin concentrations and risk of endometrial, pancreas, kidney, breast, lung, and cervical cancers.

Prevalent diabetes and risk of total, colorectal, prostate and breast cancers in an ageing population: meta-analysis of individual participant data from cohorts of the CHANCES consortium

BACKGROUND

We investigated whether associations between prevalent diabetes and cancer risk are pertinent to older adults and whether associations differ across subgroups of age, body weight status or levels of physical activity.

METHODS

We harmonised data from seven prospective cohort studies of older individuals in Europe and the United States participating in the CHANCES consortium. Cox proportional hazard regression was used to estimate the associations of prevalent diabetes with cancer risk (all cancers combined, and for colorectum, prostate and breast). We calculated summary risk estimates across cohorts using pooled analysis and random-effects meta-analysis.

RESULTS

A total of 667,916 individuals were included with an overall median (P25-P75) age at recruitment of 62.3 (57-67) years. During a median follow-up time of 10.5 years, 114,404 total cancer cases were ascertained. Diabetes was not associated with the risk of all cancers combined (hazard ratio (HR) = 0.94; 95% confidence interval (CI): 0.86-1.04; I2 = 63.3%). Diabetes was positively associated with colorectal cancer risk in men (HR = 1.17; 95% CI: 1.08-1.26; I2 = 0%) and a similar HR in women (1.13; 95% CI: 0.82-1.56; I2 = 46%), but with a confidence interval including the null. Diabetes was inversely associated with prostate cancer risk (HR = 0.81; 95% CI: 0.77-0.85; I2 = 0%), but not with postmenopausal breast cancer (HR = 0.96; 95% CI: 0.89-1.03; I2 = 0%). In exploratory subgroup analyses, diabetes was inversely associated with prostate cancer risk only in men with overweight or obesity.

CONCLUSIONS

Prevalent diabetes was positively associated with colorectal cancer risk and inversely associated with prostate cancer risk in older Europeans and Americans.

The Influence of Anti-Diabetic Drugs on Prostate Cancer

The incidences of prostate cancer (PC) and diabetes are increasing, with a sustained trend. The occurrence of PC and type 2 diabetes mellitus (T2DM) is growing with aging. The correlation between PC occurrence and diabetes is noteworthy, as T2DM is correlated with a reduced risk of incidence of prostate cancer. Despite this reduction, diabetes mellitus increases the mortality in many cancer types, including prostate cancer. The treatment of T2DM is based on lifestyle changes and pharmacological management. Current available drugs, except insulin, are aimed at increasing insulin secretion (sulfonylureas, incretin drugs), improving insulin sensitivity (biguanides, thiazolidinediones), or increasing urinary glucose excretion (gliflozin). Comorbidities should be taken into consideration during the treatment of T2DM. This review describes currently known information about the mechanism and impact of commonly used antidiabetic drugs on the incidence and progression of PC. Outcomes of pre-clinical studies are briefly presented and their correlations with available clinical trials have also been observed. Available reports and meta-analyses demonstrate that most anti-diabetic drugs do not increase the risk during the treatment of patients with PC. However, some reports show a potential advantage of treatment of T2DM with specific drugs. Based on clinical reports, use of metformin should be considered as a therapeutic option. Moreover, anticancer properties of metformin were augmented while combined with GLP-1 analogs.

Obesity, Type 2 Diabetes, and Cancer Risk

Obesity and type 2 diabetes have both been associated with increased cancer risk and are becoming increasingly prevalent. Metabolic abnormalities such as insulin resistance and dyslipidemia are associated with both obesity and type 2 diabetes and have been implicated in the obesity-cancer relationship. Multiple mechanisms have been proposed to link obesity and diabetes with cancer progression, including an increase in insulin/IGF-1 signaling, lipid and glucose uptake and metabolism, alterations in the profile of cytokines, chemokines, and adipokines, as well as changes in the adipose tissue directly adjacent to the cancer sites. This review aims to summarize and provide an update on the epidemiological and mechanistic evidence linking obesity and type 2 diabetes with cancer, focusing on the roles of insulin, lipids, and adipose tissue.

Evaluating the impact of AMPK activation, a target of metformin, on risk of cardiovascular diseases and cancer in the UK Biobank: a Mendelian randomisation study

AIMS/HYPOTHESIS

Whether metformin reduces cardiovascular or cancer risk is unclear owing to concerns over immortal time bias and confounding in observational studies. This study evaluated the effect of AMP-activated protein kinase (AMPK), the target of metformin, on risk of cardiovascular disease and cancer.

METHODS

This is a Mendelian randomisation design, using AMPK, the pharmacological target of metformin, to infer the AMPK pathway-dependent effects of metformin on risk of cardiovascular disease and cancer in participants of white British ancestry in the UK Biobank.

RESULTS

A total of 391,199 participants were included (mean age 56.9 years; 54.1% women), including 26,690 cases of type 2 diabetes, 38,098 cases of coronary artery disease and 80,941 cases of overall cancer. Genetically predicted reduction in HbA_1c (%) instrumented by AMPK variants was associated with a 61% reduction in risk of type 2 diabetes (OR 0.39; 95% CI 0.20, 0.78; p = 7.69 × 10^-3), a 53% decrease in the risk of coronary artery disease (OR 0.47; 95% CI 0.26, 0.84; p = 0.01) and a 44% decrease in the risk of overall cancer (OR 0.56; 95% CI 0.36, 0.85; p = 7.23 × 10^-3). Results were similar using median or quartiles of AMPK score, with dose-response effects (p for trend = 4.18 × 10^-3 for type 2 diabetes, 4.37 × 10^-3 for coronary artery disease and 4.04 × 10^-3 for overall cancer).

CONCLUSIONS/INTERPRETATION

This study provides some genetic evidence that AMPK activation by metformin may protect against cardiovascular disease and cancer, which needs to be confirmed by randomised controlled trials.

Novel combination of celecoxib and metformin improves the antitumor effect by inhibiting the growth of Hepatocellular Carcinoma

Objective: To explore the effect of COX-2 inhibitor celecoxib in combination with metformin on the prevention of Hepatocellular carcinoma (HCC) and the mechanisms involved.

Methods: HCC cell lines and an HCC rat model were treated with celecoxib, metformin or a combination of both. Cell viability and tumor formation were measured.

Results:In vitro and in vivo studies showed that treatment with a combination of celecoxib and metformin inhibited proliferation of HCC to a greater extent than either treatment alone, by reducing the phosphorylation of MTOR.

Conclusion: The study suggested that celecoxib combined with metformin would be more effective for the preventing occurrence of HCC than either treatment alone and this combination of therapy is worthy of further study.

Using genetics to decipher the link between type 2 diabetes and cancer: shared aetiology or downstream consequence?

Recent developments in the field of genetics have accelerated our understanding of the aetiology of complex diseases. Type 2 diabetes mellitus and cancer are no exception, with large-scale genome-wide association studies (GWAS) facilitating exploration of the underlying pathology. Here, we discuss how genetics studies can be used to investigate the relationship between these complex diseases. Observational epidemiological studies consistently report that people with type 2 diabetes have a higher risk of several types of cancer. Indeed, type 2 diabetes and cancer share many common risk factors, such as obesity, ageing, poor diet and low levels of physical activity. However, questions remain regarding the biological mechanisms that link these two diseases. Large-scale GWAS of type 2 diabetes and cancer allow us to consider the evidence for shared genetic architecture. Several shared susceptibility genes have been identified, yet tissue specificity and direction of effect must be taken into account when considering common genetic aetiology. We also consider how GWAS, and associated techniques such as Mendelian randomisation, allow us to dissect the link between the two diseases and address questions such as 'Does type 2 diabetes cause cancer or is the increased risk observed driven by higher adiposity or another associated metabolic feature?' Graphical abstract.

Metformin protects against diabetes-induced heart injury and dunning prostate cancer model

In this study, both diabetes and Dunning prostate cancer were induced for the first time in Copenhagen rats in vivo. Thus, the effects of metformin against heart tissue damage of these rats were investigated by biochemical methods. Dunning prostate cancer was induced in Copenhagen rats using high metastatic MAT-LyLu cells. The rats were divided as follows: Control group: only injected with 0.9% NaCl for 14 days; Diabetic group: only injected single dose of streptozotocin (STZ) (65 mg/kg); Cancer group: subcutaneously (s.c) inoculated with 2 x 10⁴ MAT-LyLu cells only; Diabetic + cancer (DC) group: inoculated with 2 x 10⁴ MAT-LyLu cells and STZ injection, Cancer + metformin (CM) group: injected with metformin for 14 days after Mat-LyLu cells application; Diabetic + cancer + metformin (DCM) group: metformin administered for 14 days together with STZ and Mat-LyLu cells. At the end of the experimental period, heart tissues were taken. Reduced glutathione and total antioxidant status levels in heart tissues were decreased, whereas lipid peroxidation, advanced oxidized protein products, nitric oxide, homocysteine, and reactive oxygen species levels, total oxidant status and catalase, superoxide dismutase, glutathione peroxidase, glutathione reductase, glutathione-S-transferase, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase and xanthine oxidase activities increased in the diabetic, cancer and DC groups. Treatment with metformin reversed these effects. In conclusion, the present study shows that metformin has a protective effect against heart tissue damage in STZ-induced diabetic rats with Dunning prostate cancer.

Is Type 2 Diabetes Causally Associated With Cancer Risk? Evidence From a Two-Sample Mendelian Randomization Study

We conducted a two-sample Mendelian randomization study to investigate the causal associations of type 2 diabetes mellitus (T2DM) with risk of overall cancer and 22 site-specific cancers. Summary-level data for cancer were extracted from the Breast Cancer Association Consortium and UK Biobank. Genetic predisposition to T2DM was associated with higher odds of pancreatic, kidney, uterine, and cervical cancer and lower odds of esophageal cancer and melanoma but not associated with 16 other site-specific cancers or overall cancer. The odds ratios (ORs) were 1.13 (95% CI 1.04, 1.22), 1.08 (1.00, 1.17), 1.08 (1.01, 1.15), 1.07 (1.01, 1.15), 0.89 (0.81, 0.98), and 0.93 (0.89, 0.97) for pancreatic, kidney, uterine, cervical, and esophageal cancer and melanoma, respectively. The association between T2DM and pancreatic cancer was also observed in a meta-analysis of this and a previous Mendelian randomization study (OR 1.08; 95% CI 1.02, 1.14; P = 0.009). There was limited evidence supporting causal associations between fasting glucose and cancer. Genetically predicted fasting insulin levels were positively associated with cancers of the uterus, kidney, pancreas, and lung. The current study found causal detrimental effects of T2DM on several cancers. We suggest reinforcing the cancer screening in T2DM patients to enable the early detection of cancer.

The effect of metformin on esophageal cancer risk in patients with type 2 diabetes mellitus: a systematic review and meta‑analysis

OBJECTIVE

Recently, numerous studies have yielded inconsistent results regarding the effect of metformin on esophageal cancer risk in type 2 diabetes mellitus patients. The purpose of this study is to systematically assess this effect using meta-analysis.

METHODS

We searched clinical studies on metformin and esophageal cancer risk in PubMed, Embase, and the Cochrane Library. After literature screening, a series of meta-analyses were conducted using RevMan 5.3 software. The pooled hazard ratio (HR) and the corresponding 95% confidence interval (CI) were used as the effect size.

RESULTS

Five eligible studies (four cohort studies and one case-control study) were included for our meta-analysis using a random-effect model. The analysis showed that metformin could not reduce esophageal cancer risk in type 2 diabetes mellitus patients (HR 0.88, 95% CI 0.60-1.28, P > 0.05). Subgroup analyses by geographic location showed that metformin significantly reduced esophageal cancer risk in Asian patients with type 2 diabetes mellitus (HR 0.59, 95% CI 0.39-0.91, P = 0.02), without heterogeneity between studies (P = 0.80 and I² = 0%).

CONCLUSIONS

Overall, our systematic review and meta-analysis demonstrate that metformin does not reduce esophageal cancer risk in type 2 diabetes mellitus patients. However, a significant reduction in esophageal cancer risk in Asian populations remains to be clarified.