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

Diabetes and Cancer: A Twisted Bond

This paper presents an overview of the interconnection between various factors related to both cancer and type 2 diabetes mellitus (T2DM). Hyperglycemia, hyperinsulinemia, chronic inflammation, and obesity are involved in the development and progression of both diseases but, strong evidence for a direct causal relationship between diabetes and cancer, is lacking. Several studies described a relationship between hyperglycemia and cancer at the cellular, tissular and organismic levels but at the same time recent Mendelian randomization studies proved a significant causal relationship only between hyperglycemia and breast cancer. On the other hand, the association between both hyperinsulinemia and obesity and several cancer types appears to be robust as demonstrated by Mendelian randomized studies. Metabolic alterations, including the Warburg effect and excessive glucose consumption by tumors, are discussed, highlighting the potential impact of dietary restrictions, such as fasting and low-carb diets, on tumor growth and inflammation. Recent data indicates that circulating branched-chain amino acids levels, may represent novel biomarkers that may contribute to both better diabetes control and early pancreatic cancer detection. Understanding the underlying mechanisms and shared risk factors between cancer and T2DM can provide valuable insights for cancer prevention, early detection, and management strategies.

Genetic markers of cardiac autonomic neuropathy in the Kazakh population

BACKGROUND

Cardiac autonomic neuropathy (CAN) is a complication of diabetes mellitus (DM) that increases the risk of morbidity and mortality by disrupting cardiac innervation. Recent evidence suggests that CAN may manifest even before the onset of DM, with prediabetes and metabolic syndrome potentially serving as precursors. This study aims to identify genetic markers associated with CAN development in the Kazakh population by investigating the SNPs of specific genes.

MATERIALS AND METHODS

A case-control study involved 82 patients with CAN (cases) and 100 patients without CAN (controls). A total of 182 individuals of Kazakh nationality were enrolled from a hospital affiliated with the RSE "Medical Center Hospital of the President's Affairs Administration of the Republic of Kazakhstan". 7 SNPs of genes FTO, PPARG, SNCA, XRCC1, FLACC1/CASP8 were studied. Statistical analysis was performed using Chi-square methods, calculation of odds ratios (OR) with 95% confidence intervals (CI), and logistic regression in SPSS 26.0.

RESULTS

Among the SNCA gene polymorphisms, rs2737029 was significantly associated with CAN, almost doubling the risk of CAN (OR 2.03(1.09-3.77), p = 0.03). However, no statistically significant association with CAN was detected with the rs2736990 of the SNCA gene (OR 1.00 CI (0.63-1.59), p = 0.99). rs12149832 of the FTO gene increased the risk of CAN threefold (OR 3.22(1.04-9.95), p = 0.04), while rs1801282 of the PPARG gene and rs13016963 of the FLACC1 gene increased the risk twofold (OR 2.56(1.19-5.49), p = 0.02) and (OR 2.34(1.00-5.46), p = 0.05) respectively. rs1108775 and rs1799782 of the XRCC1 gene were associated with reduced chances of developing CAN both before and after adjustment (OR 0.24, CI (0.09-0.68), p = 0.007, and OR 0.43, CI (0.22-0.84), p = 0.02, respectively).

CONCLUSION

The study suggests that rs2737029 (SNCA gene), rs12149832 (FTO gene), rs1801282 (PPARG gene), and rs13016963 (FLACC1 gene) may be predisposing factors for CAN development. Additionally, SNPs rs1108775 and rs1799782 (XRCC1 gene) may confer resistance to CAN. Only one polymorphism rs2736990 of the SNCA gene was not associated with CAN.

Correlation between High Incidence of Colorectal Neoplastic Polyps and High-risk Adenomas in Patients with Diabetes Mellitus: A Retrospective Study

BACKGROUND

Early detection and resection of colorectal polyps by routine colonoscopy screening can be effective in reducing the risk of colorectal cancer (CRC).

OBJECTIVE

This study aimed to determine the association between diabetes mellitus (DM) and different types of colorectal polyps in the Chinese population.

METHODS

A retrospective analysis was performed on inpatients admitted to the Gastroenterology Department of our hospital from January to December 2019. Clinical data, and colonoscopy and pathology findings of the subjects were collected. Bivariate analysis was used to assess factors associated with colorectal polyps. Significant variables from the bivariate evaluation were included in a stepwise multivariate logistic regression analysis to recognize independent predictors of neoplastic polyps and high-risk adenomas.

RESULTS

The proportion of patients with DM was significantly higher in patients with neoplastic polyps and high-risk adenomas than in patients without polyps. Age ≥ 50 years, male gender, and a first-degree relative with a history of CRC were independent risk factors for neoplastic polyps and high-risk adenomas, even in non-smokers. An independent risk factor analysis that did not include a family history of CRC showed that age, gender, and alcohol consumption were independent risk factors for neoplastic polyps and high-risk adenomas. DM was an independent risk factor for high-risk adenomas (OR = 2.902, 95% CI = 1.221-6.899; p = 0.016) after adjusting for age, gender, alcohol consumption, and body mass index. Thus, a history of DM significantly increases the risk of high-risk adenomas.

CONCLUSION

This study demonstrated that patients with DM, age ≥ 50 years, male gender, alcohol consumption, and a first-degree relative with a history of CRC should undergo regular endoscopic screening and colonic polypectomy.

Linkage disequilibrium block single-nucleotide polymorphisms in FTO alpha ketoglutarate dependent dioxygenase gene inference with breast cancer and Type II diabetes in Pakistani female population

Breast Cancer and Diabetes Mellitus are top ranked non-communicable life threatening diseases concerned in South Asia. The growing scientific clues witness the involvement of genetic variations which readily serve as risk factors for the disease onset. Comprehending the association of genetic predictors and risk factors in the conserved genome regions can help reveal underlying disease genetics and identify the sustained druggable targets. The present study aims to identify discrete inference of FTO alpha-ketoglutarate dependent dioxygenase gene linkage disequilibrium block SNPs rs9940128 and rs9939609 as prognostic genetic elements in defining the disease course either as BrC or NIDDM in Pakistani population. Clinically abreast female Breast Cancer and Type II (Non-Insulin Dependent) Diabetes Mellitus cases with the healthy controls participated in the study. The genomic study was established on the DNA of cases and controls through Tetra primers ARMS PCR and PCR-RFLP; data were analyzed statistically to reach comprehensive scientific annotation. Breast Cancer incidence was high in post menopause women. Fretful cholesterol, triglycerides, hypertension, sugar profiles and high incidence in females was evident in Type II (Non-Insulin Dependent) Diabetes Mellitus. BMI and family history were meager factor for either of the diseases. FTO gene alpha-ketoglutarate dependent dioxygenase linkage disequilibrium block Single-Nucleotide Polymorphism rs9939609 and rs9940128 threating inference was significant in the cancer and diabetes subjects correspondingly. The conclusion indicates serious clinical derailments in breast cancer and Type II (Non-Insulin Dependent) Diabetes Mellitus auxiliary to disease complication in genetically risk bearing FTO alpha-ketoglutarate dependent dioxygenase gene haplotype/linkage disequilibrium block SNPs prevailing in the affected Pakistani population. These clinical and genetic indicators could decisively be adopted in health care practice to intervene the sky rising disease incidence.

Computational screening and analysis of deleterious nsSNPs in human p14ARF (CDKN2A gene) protein using molecular dynamic simulation approach

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments.Communicated by Ramaswamy H. Sarma.

A post-transcriptional regulatory landscape of aging in the female mouse hippocampus

Aging is associated with substantial physiological changes and constitutes a major risk factor for neurological disorders including dementia. Alterations in gene expression upon aging have been extensively studied; however, an in-depth characterization of post-transcriptional regulatory events remains elusive. Here, we profiled the age-related changes of the transcriptome and translatome in the female mouse hippocampus by RNA sequencing of total RNA and polysome preparations at four ages (3-, 6-, 12-, 20-month-old); and we implemented a variety of bioinformatics approaches to unravel alterations in transcript abundance, alternative splicing, and polyadenylation site selection. We observed mostly well-coordinated transcriptome and translatome expression signatures across age including upregulation of transcripts related to immune system processes and neuroinflammation, though transcripts encoding ribonucleoproteins or associated with mitochondrial functions, calcium signaling and the cell-cycle displayed substantial discordant profiles, suggesting translational control associated with age-related deficits in hippocampal-dependent behavior. By contrast, alternative splicing was less preserved, increased with age and was associated with distinct functionally-related transcripts encoding proteins acting at synapses/dendrites, RNA-binding proteins; thereby predicting regulatory roles for RBM3 and CIRBP. Only minor changes in polyadenylation site selection were identified, indicating pivotal 3'-end selection in young adults compared to older groups. Overall, our study provides a comprehensive resource of age-associated post-transcriptional regulatory events in the mouse hippocampus, enabling further examination of the molecular features underlying age-associated neurological diseases.

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.

Sorafenib decreases glycemia by impairing hepatic glucose metabolism

PURPOSE

Sorafenib has been reported to reduce blood glucose levels in diabetic and non-diabetic patients in previous retrospective studies. However, the mechanism of which the hypoglycemic effects of sorafenib is not clearly explored. In this study, we investigated the effect of sorafenib on blood glucose levels in diabetic and normal mice and explored the possible mechanism.

METHODS

We established a mouse model of type 2 diabetes by a high-fat diet combined with a low-dose of streptozotocin (STZ), to identify the hypoglycemic effect of sorafenib in different mice. Glucose tolerance, insulin tolerance and pyruvate tolerance tests were done after daily gavage with sorafenib to diabetic and control mice. To explore the molecular mechanism by which sorafenib regulates blood glucose levels, hepatic glucose metabolism signaling was studied by a series of in vivo and in vitro experiments.

RESULTS

Sorafenib reduced blood glucose levels in both control and diabetic mice, particularly in the latter. The diabetic mice exhibited improved glucose and insulin tolerance after sorafenib treatment. Further studies showed that the expressions of gluconeogenesis-related enzymes, such as PCK1, G6PC and PCB, were significantly decreased upon sorafenib treatment. Mechanistically, sorafenib downregulates the expression of c-MYC downstream targets PCK1, G6PC and PCB through blocking the ERK/c-MYC signaling pathway, thereby playing its hypoglycemic effect by impairing hepatic glucose metabolism.

CONCLUSION

Sorafenib reduces blood glucose levels through downregulating gluconeogenic genes, especially in diabetic mice, suggesting the patients with T2DM when treated with sorafenib need more emphasis in monitoring blood glucose to avoid unnecessary hypoglycemia.

Advancing a causal role of type 2 diabetes and its components in developing macro- and microvascular complications via genetic studies

The role of diabetes in developing microvascular and macrovascular complications has been subject to extensive research. Despite multiple observational and genetic studies, the causal inference of diabetes (and associated risk factors) on those complications remains incomplete. In this review, we focused on type 2 diabetes, as the major form of diabetes, and investigated the evidence of causality provided by observational and genetic studies. We found that genetic studies based on Mendelian randomization provided consistent evidence of causal inference of type 2 diabetes on macrovascular complications; however, the evidence for causal inference on microvascular complications has been somewhat limited. We also noted high BMI could be causal for several diabetes complications, notable given high BMI is commonly upstream of type 2 diabetes and the recent calls to target weight loss more aggressively. We emphasize the need for further studies to identify type 2 diabetes components that mostly drive the risk of those complications. Even so, the genetic evidence summarized broadly concurs with the need for a multifactorial risk reduction approach in type 2 diabetes, including addressing excess adiposity.

LncRNA-Associated Genetic Etiologies Are Shared between Type 2 Diabetes and Cancers in the UAE Population

Numerous epidemiological studies place patients with T2D at a higher risk for cancer. Many risk factors, such as obesity, ageing, poor diet and low physical activity, are shared between T2D and cancer; however, the biological mechanisms linking the two diseases remain largely unknown. The advent of genome wide association studies (GWAS) revealed large numbers of genetic variants associated with both T2D and cancer. Most significant disease-associated variants reside in non-coding regions of the genome. Several studies show that single nucleotide polymorphisms (SNPs) at or near long non-coding RNA (lncRNA) genes may impact the susceptibility to T2D and cancer. Therefore, the identification of genetic variants predisposing individuals to both T2D and cancer may help explain the increased risk of cancer in T2D patients. We aim to investigate whether lncRNA genetic variants with significant diabetes and cancer associations overlap in the UAE population. We first performed an annotation-based analysis of UAE T2D GWAS, confirming the high prevalence of variants at or near non-coding RNA genes. We then explored whether these T2D SNPs in lncRNAs were relevant to cancer. We highlighted six non-coding genetic variants, jointly reaching statistical significance in T2D and cancer, implicating a shared genetic architecture between the two diseases in the UAE population.

Disease consequences of higher adiposity uncoupled from its adverse metabolic effects using Mendelian randomisation

Background

Some individuals living with obesity may be relatively metabolically healthy, whilst others suffer from multiple conditions that may be linked to adverse metabolic effects or other factors. The extent to which the adverse metabolic component of obesity contributes to disease compared to the non-metabolic components is often uncertain. We aimed to use Mendelian randomisation (MR) and specific genetic variants to separately test the causal roles of higher adiposity with and without its adverse metabolic effects on diseases.

Methods

We selected 37 chronic diseases associated with obesity and genetic variants associated with different aspects of excess weight. These genetic variants included those associated with metabolically 'favourable adiposity' (FA) and 'unfavourable adiposity' (UFA) that are both associated with higher adiposity but with opposite effects on metabolic risk. We used these variants and two sample MR to test the effects on the chronic diseases.

Results

MR identified two sets of diseases. First, 11 conditions where the metabolic effect of higher adiposity is the likely primary cause of the disease. Here, MR with the FA and UFA genetics showed opposing effects on risk of disease: coronary artery disease, peripheral artery disease, hypertension, stroke, type 2 diabetes, polycystic ovary syndrome, heart failure, atrial fibrillation, chronic kidney disease, renal cancer, and gout. Second, 9 conditions where the non-metabolic effects of excess weight (e.g. mechanical effect) are likely a cause. Here, MR with the FA genetics, despite leading to lower metabolic risk, and MR with the UFA genetics, both indicated higher disease risk: osteoarthritis, rheumatoid arthritis, osteoporosis, gastro-oesophageal reflux disease, gallstones, adult-onset asthma, psoriasis, deep vein thrombosis, and venous thromboembolism.

Conclusions

Our results assist in understanding the consequences of higher adiposity uncoupled from its adverse metabolic effects, including the risks to individuals with high body mass index who may be relatively metabolically healthy.

Funding

Diabetes UK, UK Medical Research Council, World Cancer Research Fund, National Cancer Institute.

The pro-proliferative effect of insulin in human breast epithelial DMBA-transformed and non-transformed cell lines is PI3K-, mTOR- and GLUT1-dependent

Type 2 diabetes mellitus (T2DM) is linked to an increased risk of breast cancer. We aimed to investigate how T2DM-associated characteristics (high levels of glucose, insulin, leptin, inflammatory mediators and oxidative stress) influence breast cancer carcinogenesis, in DMBA-treated (MCF-12A_DMBA ) and non-treated breast epithelial (MCF-12A) cell lines. Insulin (50 nM) promotes cell proliferation, ³ H-DG uptake and lactic acid production in both cell lines. The stimulatory effects of insulin upon cell proliferation and ³ H-DG uptake were hampered by rapamycin, LY294001 and BAY-876, in both cell lines. In conclusion, hyperinsulinemia, one important characteristic of T2DM, contributes to the initiation of breast cancer by a PI3K- and mTOR-dependent mechanism involving increased GLUT1-mediated glucose uptake. SIGNIFICANCE: The pro-proliferative effect of insulin in human breast epithelial DMBA-transformed and non-transformed cell lines is PI3K-, mTOR- and GLUT1-dependent.

MTNR1B polymorphisms with CDKN2A and MGMT methylation status are associated with poor prognosis of colorectal cancer in Taiwan

BACKGROUND

Identifying novel colorectal cancer (CRC) prognostic biomarkers is crucial to helping clinicians make appropriate therapy decisions. Melatonin plays a major role in managing the circadian rhythm and exerts oncostatic effects on different kinds of tumours.

AIM

To explore the relationship between MTNR1B single-nucleotide polymorphism (SNPs) combined with gene hypermethylation and CRC prognosis.

METHODS

A total of 94 CRC tumour tissues were investigated. Genotyping for the four MTNR1B SNPs (rs1387153, rs2166706, rs10830963, and rs1447352) was performed using multiplex polymerase chain reaction. The relationships between the MTNR1B SNPs and CRC 5-year overall survival (OS) was assessed by calculating hazard ratios with 95%CIs.

RESULTS

All SNPs (rs1387153, rs2166706, rs10830963, and rs1447352) were correlated with decreased 5-year OS. In stratified analysis, rs1387153, rs10830963, and rs1447352 risk genotype combined with CDKN2A and MGMT methylation status were associated with 5-year OS. A strong cumulative effect of the four polymorphisms on CRC prognosis was observed. Four haplotypes of MTNR1B SNPs were also associated with the 5-year OS. MTNR1B SNPs combined with CDKN2A and MGMT gene methylation status could be used to predict shorter CRC survival.

CONCLUSION

The novel genetic biomarkers combined with epigenetic biomarkers may be predictive tool for CRC prognosis and thus could be used to individualise treatment for patients with CRC.

Epidemiological link between obesity, type 2 diabetes mellitus and cancer

There exists a complex interaction between obesity, type 2 diabetes mellitus (T2DM) and cancer, and an increase in the incidence of cancer is expected with the growing obesity-diabetes pandemic. The association of cancer with diabetes mellitus and obesity appears to be site-specific, the highest risk being for post-menopausal breast cancer, endometrial cancer, and colorectal cancer. Moreover, there is worsening of hyperglycaemia with the onset of cancer, evidencing a bi-directional link between cancer and diabetes mellitus and the need for monitoring for diabetes in cancer survivors. In this review, we look at the epidemiological evidence from observational studies and Mendelian randomization studies linking obesity, diabetes, and cancer, as well as the complex pathophysiological mechanisms involved, including insulin resistance with associated hyperinsulinaemia, the effect of chronic low-grade inflammation, and the effect of various adipokines that are associated with obesity and T2DM. Additionally, we describe the novel therapeutic strategies, based on their role on the discrete pathophysiological mechanisms involved in the tumourigenesis.

Diabetes, Antidiabetic Medications and Cancer Risk in Type 2 Diabetes: Focus on SGLT-2 Inhibitors

In the last decade, cancer became the leading cause of death in the population under 65 in the European Union. Diabetes is also considered as a factor increasing risk of cancer incidence and mortality. Type 2 diabetes is frequently associated with being overweight and obese, which also plays a role in malignancy. Among biological mechanisms linking diabetes and obesity with cancer hyperglycemia, hyperinsulinemia, insulin resistance, increased levels of growth factors, steroid and peptide hormones, oxidative stress and increased activity of pro-inflammatory cytokines are listed. Antidiabetic medications can modulate cancer risk through directly impacting metabolism of cancer cells as well as indirectly through impact on risk factors of malignancy. Some of them are considered beneficial (metformin and thiazolidinedions—with the exception of bladder cancer); on the other hand, excess of exogenous insulin may be potentially harmful, while other medications seem to have neutral impact on cancer risk. Inhibitors of the sodium-glucose cotransporter-2 (SGLT-2) are increasingly used in the treatment of type 2 diabetes. However, their association with cancer risk is unclear. The aim of this review was to analyze the anticancer potential of this class of drugs, as well as risks of site-specific malignancies associated with their use.

Metabolite Sensing GPCRs: Promising Therapeutic Targets for Cancer Treatment?

G-protein-coupled receptors constitute the most diverse and largest receptor family in the human genome, with approximately 800 different members identified. Given the well-known metabolic alterations in cancer development, we will focus specifically in the 19 G-protein-coupled receptors (GPCRs), which can be selectively activated by metabolites. These metabolite sensing GPCRs control crucial processes, such as cell proliferation, differentiation, migration, and survival after their activation. In the present review, we will describe the main functions of these metabolite sensing GPCRs and shed light on the benefits of their potential use as possible pharmacological targets for cancer treatment.

Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population

The epidemic of type 2 diabetes mellitus (T2DM) is an important global health concern. Our earlier epidemiological investigation in Pakistan prompted us to conduct a molecular investigation to decipher the differential genetic pathways of this health condition in relation to non-diabetic controls. Our microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their canonical pathways. High-throughput qRT-PCR TaqMan Low Density Array (TLDA) was performed to validate the selected differentially expressed genes of our interest, viz., ARNT, LEPR, MYC, RRAD, CYP2D6, TP53, APOC1, APOC2, CYP1B1, SLC2A13, and SLC33A1 using a small population validation sample (n = 15 cases and their corresponding matched controls). Overall, our small pilot study revealed a discrete gene expression profile in cases compared to controls. The disease pathways included: Insulin Receptor Signaling, Type II Diabetes Mellitus Signaling, Apoptosis Signaling, Aryl Hydrocarbon Receptor Signaling, p53 Signaling, Mitochondrial Dysfunction, Chronic Myeloid Leukemia Signaling, Parkinson's Signaling, Molecular Mechanism of Cancer, and Cell Cycle G1/S Checkpoint Regulation, GABA Receptor Signaling, Neuroinflammation Signaling Pathway, Dopamine Receptor Signaling, Sirtuin Signaling Pathway, Oxidative Phosphorylation, LXR/RXR Activation, and Mitochondrial Dysfunction, strongly consistent with the evidence from epidemiological studies. These gene fingerprints could lead to the development of biomarkers for the identification of subgroups at high risk for future disease well ahead of time, before the actual disease becomes visible.